What is Automation?


Chapter 1

1.1 Introduction

What is Automation?

Automation in general, can be explained as the use of computers or microcontrollers to control industrial machinery and processes thereby fully replacing human operators. Automation is a kind of transition from mechanization. In mechanization, human operators are provided with machinery to assist their operations, where as automation fully replaces the human operators with computers.

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The advantages of automation are

  1. Increased productivity and higher production rates.
  2. Better product quality and efficient use of resources.
  3. Greater control and consistency of products.
  4. Improved safety and reduced factory lead times.

Home Automation

Home automation is the field specializing in the general and specific automation requirements of homes and apartments for their better safety, security and comfort of its residents. It is also called Domotics. Home automation can be as simple as controlling a few lights in the house or as complicated as to monitor and to record the activities of each resident. Automation requirements depend on person to person. Some may be interested in the home security while others will be more into comfort requirements. Basically, home automation is anything that gives automatic control of things in your house.

Some of the commonly used features in home automation are

  • Control of lighting.
  • Climate control of rooms.
  • Security and surveillance systems.
  • Control of home entertainment systems.
  • House plant watering system.
  • Overhead tank water level controllers.

Intelligent Sensors

Complex large-scale systems consist of a large number of interconnected components. Mastering the dynamic behavior of such systems, calls for distributed control architectures. This can be achieved by implementing control and estimation algorithms in several controllers. Some algorithms manipulate only local variables (which are available in the local interface) but in most cases, algorithms implemented in some given computing device will use variables which are available in this device’s local interface, and also variables which are input to the control system via remote interfaces, thus rising the need for communication networks, whose architecture and complexity depend on the amount of data to be exchanged, and on the associated time constraints. Associating computing (and communication) devices with sensing or actuating functions, has given rise to intelligent sensors. These sensors have gained a huge success in the past ten years, especially with the development of neural networks, fuzzy logic, and soft computing algorithms.

The modern definition of smart or intelligent sensors can be formulated now as: ‘Smart sensor is an electronic device, including sensing element, interfacing, signal processing and having several intelligence functions as self-testing, self-identification, self-validation or self-adaptation’. The keyword in this definition is ‘intelligence’. The self-adaptation is a relatively new function of smart sensors and sensor systems. Self-adaptation smart sensors and systems are based on so-called adaptive algorithms and directly connected with precision measurements of frequency-time parameters of electrical signals.

The later chapters will give an elaborate view on why we should use intelligent sensors, intelligent sensor structure, characteristics and network standards.

Chapter 2

2.1 Conventional Sensors

Before talking more on intelligent sensors, first we need to examine regular sensors in order to obtain a solid foundation on which we can develop our understanding on intelligent sensors. Most of the conventional sensors have shortcomings, both technically and economically. For a sensor to work effectively, it must be calibrated. That is, its output must be made to match some predetermined standard so that its reported values correctly reflect the parameter being measured. In the case of a bulb thermometer, the graduations next to the mercury column must be positioned so that they accurately correspond to the level of mercury for a given temperature. If the sensor is not calibrated, the information that it reports won’t be accurate, which can be a big problem for the systems that use the reported information.

The second concern one has when dealing with sensors is that their properties usually change over time, a phenomenon knows as drift. For instance, suppose we are measuring a DC current in a particular part of a circuit by monitoring the voltage across a resistor in that circuit. In this case, the sensor is the resistor and the physical property that we are measuring the voltage across it. As the resistor ages, its chemical properties will change, thus altering its resistance. As with the issue of calibration, some situations require much stricter drift tolerances than others; the point is that sensor properties will change with time unless we compensate for the drift in some fashion, and these changes are usually undesirable.

The third problem is that not only do sensors themselves change with time, but so, too, does the environment in which they operate. An excellent example of that would be the electronic ignition for an internal combustion engine. Immediately after a tune-up, all the belts are tight, the spark plugs are new, the fuel injectors are clean, and the air filter is pristine. From that moment on, things go downhill; the belts loosen, deposits build up on the spark plugs and fuel injectors, and the air filter becomes clogged with ever-increasing amounts of dirt and dust. Unless the electronic ignition can measure how things are changing and make adjustments, the settings and timing sequence that it uses to fire the spark plugs will become progressively mismatched for the engine conditions, resulting in poorer performance and reduced fuel efficiency. The ability to compensate for often extreme changes in the operating environment makes a huge difference in a sensor’s value to a particular application.

Yet a fourth problem is that most sensors require some sort of specialized hardware called signal-conditioning circuitry in order to be of use in monitoring or control applications. The signal-conditioning circuitry is what transforms the physical sensor property that we’re monitoring (often an analog electrical voltage that varies in some systematic way with the parameter being measured) into a measurement that can be used by the rest of the system. Depending upon the application, the signal conditioning may be as simple as a basic amplifier that boosts the sensor signal to a usable level or it may entail complex circuitry that cleans up the sensor signal and compensates for environmental conditions, too. Frequently, the conditioning circuitry itself has to be tuned for the specific sensor being used, and for analog signals that often means physically adjusting a potentiometer or other such trimming device. In addition, the configuration of the signal-conditioning circuitry tends to be unique to both the specific type of sensor and to the application itself, which means that different types of sensors or different applications frequently need customized circuitry.

Finally, standard sensors usually need to be physically close to the control and monitoring systems that receive their measurements. In general, the farther a sensor is from the system using its measurements, the less useful the measurements are. This is due primarily to the fact that sensor signals that are run long distances are susceptible to electronic noise, thus degrading the quality of the readings at the receiving end. In many cases, sensors are connected to the monitoring and control systems using specialized (and expensive) cabling; the longer this cabling is, the more costly the installation, which is never popular with end users. A related problem is that sharing sensor outputs among multiple systems becomes very difficult, particularly if those systems are physically separated. This inability to share outputs may not seem important, but it severely limits the ability to scale systems to large installations, resulting in much higher costs to install and support multiple redundant sensors.

What we really need to do is to develop some technique by which we can solve or at least greatly alleviate these problems of calibration, drift, and signal conditioning.

2.2 Making Sensors Intelligent

Control systems are becoming increasingly complicated and generate increasingly complex control information. Control must nevertheless be exercised, even under such circumstances. Even considering just the detection of abnormal conditions or the problems of giving a suitable warning, devices are required that can substitute for or assist human sensation, by detecting and recognizing multi-dimensional information, and conversion of non visual information into visual form. In systems possessing a high degree of functionality, efficiency must be maximized by division of the information processing function into central processing and processing dispersed to local sites. With increased progress in automation, it has become widely recognized that the bottleneck in such systems lies with the sensors.

Such demands are difficult to deal with by simply improvising the sensor devices themselves. Structural reinforcement, such as using array of sensors, or combinations of different types of sensors, and reinforcement from the data processing aspect by a signal processing unit such as a computer, are indispensible. In particular, the data processing and sensing aspects of the various stages involved in multi-dimensional measurement, image construction, characteristic extraction and pattern recognition, which were conventionally performed exclusively by human beings, have been tremendously enhanced by advances in micro-electronics. As a result, in many cases sensor systems have been implemented that substitute for some or all of the intellectual actions of human beings, i.e. intelligent sensor systems.

Sensors which are made intelligent in this way are called ‘intelligent sensors’ or ‘smart sensors’. According to Breckenridge and Husson, the smart sensor itself has a data processing function and automatic calibration/automatic compensation function, in which the sensor itself detects and eliminates abnormal values or exceptional values. It incorporates an algorithm, which is capable of being altered, and has a certain degree of memory function. Further desirable characteristics are that the sensor is coupled to other sensors, adapts to changes in environmental conditions, and has a discriminant function.

Scientific measuring instruments that are employed for observation and measurement of physical world are indispensible extensions of our senses and perceptions in the scientific examination of nature. In recognizing nature, we mobilize all the resources of information obtained from the five senses of sight, hearing, touch, taste and smell etc. and combine these sensory data in such a way as to avoid contradiction. Thus more reliable, higher order data is obtained by combining data of different types. That is, there is a data processing mechanism that combines and processes a number of sensory data. The concept of combining sensors to implement such a data processing mechanism is called ‘sensor fusion’

2.2.1 Digitizing the Sensor Signal

The discipline of digital signal processing or DSP, in which signals are manipulated mathematically rather than with electronic circuitry, is well established and widely practiced. Standard transformations, such as filtering to remove unwanted noise or frequency mappings to identify particular signal components, are easily handled using DSP. Furthermore, using DSP principles we can perform operations that would be impossible using even the most advanced electronic circuitry.

For that very reason, today’s designers also include a stage in the signal-conditioning circuitry in which the analog electrical signal is converted into a digitized numeric value. This step, called analog-to-digital conversion, A/D conversion, or ADC, is vitally important, because as soon as we can transform the sensor signal into a numeric value, we can manipulate it using software running on a microprocessor. Analog-to-digital converters, or ADCs as they’re referred to, are usually single-chip semiconductor devices that can be made to be highly accurate and highly stable under varying environmental conditions. The required signal-conditioning circuitry can often be significantly reduced, since much of the environmental compensation circuitry can be made a part of the ADC and filtering can be performed in software.

2.2.2 Adding Intelligence

Once the sensor signal has been digitized, there are two primary options in how we handle those numeric values and the algorithms that manipulate them. We can either choose to implement custom digital hardware that essentially “hard-wires” our processing algorithm, or we can use a microprocessor to provide the necessary computational power. In general, custom hardware can run faster than microprocessor-driven systems, but usually at the price of increased production costs and limited flexibility. Microprocessors, while not necessarily as fast as a custom hardware solution, offer the great advantage of design flexibility and tend to be lower-priced since they can be applied to a variety of situations rather than a single application.

Once we have on-board intelligence, we’re able to solve several of the problems that we noted earlier. Calibration can be automated, component drift can be virtually eliminated through the use of purely mathematical processing algorithms, and we can compensate for environmental changes by monitoring conditions on a periodic basis and making the appropriate adjustments automatically. Adding a brain makes the designer’s life much easier.

2.2.3 Communication Interface

The sharing of measurements with other components within the system or with other systems adds to the value of these measurements. To do this, we need to equip our intelligent sensor with a standardized means to communicate its information to other elements. By using standardized methods of communication, we ensure that the sensor’s information can be shared as broadly, as easily, and as reliably as possible, thus maximizing the usefulness of the sensor and the information it produces.

Thus these three factors consider being mandatory for an intelligent sensor:

  • A sensing element that measures one or more physical parameters (essentially the traditional sensor we’ve been discussing),
  • A computational element that analyzes the measurements made by the sensing element, and
  • A communication interface to the outside world that allows the device to exchange information with other components in a larger system.

It’s the last two elements that really distinguish intelligent sensors from their more common standard sensor relatives because they provide the abilities to turn data directly into information, to use that information locally, and to communicate it to other elements in the system.

2.3 Types of Intelligent Sensors

Intelligent sensors are chosen depending on the object, application, precision system, environment of use and cost etc. In such cases consideration must be given as to what is an appropriate evaluation standard. This question involves a multi-dimensional criterion and is usually very difficult. The evaluation standard directly reflects the sense of value itself applied in the design and manufacture of the target system. This must therefore be firmly settled at the system design stage.

In sensor selection, the first matter to be considered is determination of the subject of measurement. The second matter to be decided on is the required precision and dynamic range. The third is ease of use, cost, delivery time etc., and ease of maintenance in actual use and compatibility with other sensors in the system. The type of sensor should be matched to such requirements at the design stage. Sensors are usually classified by the subject of measurement and the principle of sensing action.

2.3.1 Classification Based on Type of Input

In this, the sensor is classified in accordance with the physical phenomenon that is needed to be detected and the subject of measurement. Some of the examples include voltage, current, displacement and pressure. A list of sensors and their categories are mentioned in the following table.



Dynamic Quantity

Flow rate, Pressure, force, tension

Speed, acceleration

Sound, vibration

Distortion, direction proximity

Optical Quantities

Light (infra red, visible light or radiation)

Electromagnetic Quantities

Current, voltage, frequency, phase, vibration, magnetism

Quantity of Energy or Heat

Temperature, humidity, dew point

Chemical Quantities

Analytic sensors, gas, odour, concentration, pH, ions

Sensory Quantities or Biological Quantities

Touch, vision, smell

Table 2.3.1: Sensed items Classified in accordance with subject of measurement.

2.3.2 Classification Based on Type of Output

In an intelligent sensor, it is often necessary to process in an integrated manner the information from several sensors or from a single sensor over a given time range. A computer of appropriate level is employed for such purposes in practically y all cases. For coupling to the computer when constructing an intelligent sensor system, a method with a large degree of freedom is therefore appropriate. It is also necessary to pay careful attention to the type of physical quantity carrying the output information to the sensor, and to the information description format of this physical quantity or dynamic quantity, and for the description format an analog, digital or encoded method etc., might be used.

Although any physical quantities could be used as output signal, electrical quantities such as voltage are more convenient for data input to a computer. The format of the output signal can be analog or digital. For convenience in data input to the computer, it is preferable if the output signal of the sensor itself is in the form of a digital electrical signal. In such cases, a suitable means of signal conversion must be provided to input the data from the sensor to the computer

2.3.3 Classification Based on Accuracy

When a sensor system is constructed, the accuracy of the sensors employed is a critical factor. Usually sensor accuracy is expressed as the minimum detectable quantity. This is determined by the sensitivity of the sensor and the internally generated noise of the sensor itself. Higher sensitivity and lower internal noise level imply greater accuracy.

Generally for commercially available sensors the cost of the sensor is determined by the accuracy which it is required to have. If no commercial sensor can be found with the necessary accuracy, a custom product must be used, which will increase the costs. For ordinary applications an accuracy of about 0.1% is sufficient. Such sensors can easily be selected from commercially available models. Dynamic range (full scale deflection/minimum detectable quantity) has practically the same meaning as accuracy, and is expressed in decibel units. For example a dynamic range of 60dB indicates that the full scale deflection is 103 times the minimum detectable quantity. That is, a dynamic range of 60dB is equivalent to 0.1% accuracy.

In conventional sensors, linearity of output was regarded as quite important. However, in intelligent sensor technology the final stage is normally data processing by computer, so output linearity is not a particular problem. Any sensor providing a reproducible relationship of input and output signal can be used in an intelligent sensor system.

Chapter 3

3.1 Sensor selection

The function of a sensor is to receive some action from a single phenomenon of the subject of measurement and to convert this to another physical phenomenon that can be more easily handled. The phenomenon constituting the subject of measurement is called the input signal, and the phenomenon after conversion is called the output signal. The ratio of the output signal to the input signal is called the transmittance or gain. Since the first function of a sensor is to convert changes in the subject of measurement to a physical phenomenon that can be more easily handled, i.e. its function consists in primary conversion, its conversion efficiency, or the degree of difficulty in delivering the output signal to the transducer constituting the next stage is of secondary importance

The first point to which attention must be paid in sensor selection is to preserve as far as possible the information of the input signal. This is equivalent to preventing lowering of the signal-to-noise ratio (SNR). For example, if the SNR of the input signal is 60 dB, a sensor of dynamic range less than 60 dB should not be used. In order to detect changes in the quantity being measured as faithfully as possible, a sensor is required to have the following properties.

  • Non-interference. This means that its output should not be changed by factors other than changes in the subject of measurement. Conversion satisfying this condition is called direct measurement. Conversion wherein the measurement quantity is found by calculation from output signals determined under the influence of several input signals is called indirect measurement.
  • High sensitivity. The amount of change of the output signal that is produced by a change of unit amount of the input quantity being measured, i.e. the gain, should be as large as possible.
  • Small measurement pressure. This means that the sensor should not disturb the physical conditions of the subject of measurement. From this point of view, modulation conversion offers more freedom than direct-acting conversion.
  • High speed. The sensor should have sufficiently high speed of reaction to track the maximum anticipated rate of variation of the measured quantity.
  • Low noise. The noise generated by the sensor itself should be as little as possible.
  • Robustness. The output signal must be at least more robust than the quantity being measured, and be easier to handle. ‘Robustness’ means resistance to environmental changes and/or noise. In general, phenomena of large energy are more resistant to external disturbance such as noise than are phenomena of smaller energy, they are easier to handle, and so have better robustness.

If a sensor can be obtained that satisfies all these conditions, there is no problem. However, in practice, one can scarcely expect to obtain a sensor satisfying all these conditions. In such cases, it is necessary to combine the sensor with a suitable compensation mechanism, or to compensate the transducer of the secondary converter.

Progress in IC manufacturing technology has made it possible to integrate various sensor functions. With the progressive shift from mainframes to minicomputers and hence to microcomputers, control systems have changed from centralized processing systems to distributed processing systems. Sensor technology has also benefited from such progress in IC manufacturing technology, with the result that systems whereby information from several sensors is combined and processed have changed from centralized systems to dispersed systems. Specifically, attempts are being made to use silicon-integrated sensors in a role combining primary data processing and input in systems that measure and process two-dimensional information such as picture information. This is a natural application of silicon precision working technology and digital circuit technology, which have been greatly advanced by introduction of VLSI manufacturing technology. Three-dimensional integrated circuits for recognizing letter patterns and odour sensors, etc., are examples of this. Such sensor systems can be called perfectly intelligent sensors in that they themselves have a certain data processing capability. It is characteristic of such sensors to combine several sensor inputs and to include a microprocessor that performs data processing. Their output signal is not a simple conversion of the input signal, but rather an abstract quantity obtained by some reorganization and combination of input signals from several sensors.

This type of signal conversion is now often performed by a distributed processing mechanism, in which microprocessors are used to carry out the data processing that was previously performed by a centralized computer system having a large number of interfaces to individual sensors. However, the miniaturization obtained by application of integrated circuit techniques brings about an increase in the flexibility of coupling between elements. This has a substantial effect. Sensors of this type constitute a new technology that is at present being researched and developed. Although further progress can be expected, the overall picture cannot be predicted at the present time. Technically, practically free combinations of sensors can be implemented with the object of so-called indirect measurement, in which the signals from several individual sensors that were conventionally present are collected and used as the basis for a new output signal. In many aspects, new ideas are required concerning determination of the object of measurement, i.e. which measured quantities are to be selected, determination of the individual functions to achieve this, and the construction of the framework to organize these as a system.

3.2 Structure of an Intelligent Sensor

The rapidity of development in microelectronics has had a profound effect on the whole of instrumentation science, and it has blurred some of the conceptual boundaries which once seemed so firm. In the present context the boundary between sensors and instruments is particularly uncertain. Processes which were once confined to a large electronic instrument are now available within the housing of a compact sensor, and it is some of these processes which we discuss later in this chapter. An instrument in our context is a system which is designed primarily to act as a free standing device for performing a particular set of measurements; the provision of communications facilities is of secondary importance. A sensor is a system which is designed primarily to serve a host system and without its communication channel it cannot serve its purpose. Nevertheless, the structures and processes used within either device, be they hardware or software, are similar.

The range of disciplines which arc brought together in intelligent sensor system design is considerable, and the designer of such systems has to become something of a polymath. This was one of the problems in the early days of computer-aided measurement and there was some resistance from the backwoodsmen who practiced the ‘art’ of measurement.

3.2.1 Elements of Intelligent Sensors

The intelligent sensor is an example of a system, and in it we can identify a number of sub-systems whose functions are clearly distinguished from each other. The principal sub-systems within an intelligent sensor are:

  • A primary sensing element
  • Excitation Control
  • Amplification (Possibly variable gain)
  • Analogue filtering
  • Data conversion
  • Compensation
  • Digital Information Processing
  • Digital Communication Processing

The figure illustrates the way in which these sub-systems relate to each other. Some of the realizations of intelligent sensors, particularly the earlier ones, may incorporate only some of these elements.

The primary sensing element has an obvious fundamental importance. It is more than simply the familiar traditional sensor incorporated into a more up-to-date system. Not only are new materials and mechanisms becoming available for exploitation, but some of those that have been long known yet discarded because of various difficulties of behaviour may now be reconsidered in the light of the presence of intelligence to cope with these difficul­ties.

Excitation control can take a variety of forms depending on the circumstances. Some sensors, such as the thermocouple, convert energy directly from one form to another without the need for additional excitation. Others may require fairly elaborate forms of supply. It may be alternating or pulsed for subsequent coherent or phase-sensitive detection. In some circumstances it may be necessary to provide extremely stable supplies to the sensing element, while in others it may be necessary for those supplies to form part of a control loop to maintain the operating condition of the clement at some desired optimum. While this aspect may not be thought fundamental to intelligent sensors there is a largely unexplored range of possibilities for combining it with digital processing to produce novel instrumentation techniques.

Amplification of the electrical output of the primary sensing element is almost invariably a requirement. This can pose design problems where high gain is needed. Noise is a particular hazard, and a circumstance unique to the intelligent form of sensor is the presence of digital buses carrying signals with sharp transitions. For this reason circuit layout is a particularly important part of the design process.

Analogue filtering is required at minimum to obviate aliasing effects in the conversion stage, but it is also attractive where digital filtering would lake up too much of the real-time processing power available.

Data conversion is the stage of transition between the continuous real world and the discrete internal world of the digital processor. It is important to bear in mind that the process of analogue to digital conversion is a non-linear one and represents a potentially gross distortion of the incoming information. It is important, however, for the intelligent sensor designer always to remember that this corruption is present, and in certain circumstances it can assume dominating importance. Such circumstances would include the case where the conversion process is part of a control loop or where some sort of auto-ranging, overt or covert, is built in to the operational program.

Compensation is an inevitable part of the intelligent sensor. The operating point of the sensors may change due to various reasons. One of them is temperature. So an intelligent sensor must have an inbuilt compensation setup to bring the operating point back to its standard set stage.

Information processing is, of course, unique to the intelligent form of sensor. There is some overlap between compensation and information processing, but there are also significant areas on independence.

An important aspect is the condensation of information, which is necessary to preserve the two most precious resources of the industrial measurement system, the information bus and the central processor. A prime example of data condensa­tion occurs in the Doppler velocimctcr in which a substantial quantity of informa­tion is reduced to a single number representing the velocity. Sensor compensation will in general require the processing of incoming information and in some circumstances will represent the major processing task. The intelligent sensor, to some degree, can be responsible for checking the integrity of its information; whether, for example, the range and behaviour of the incoming variables is physically reasonable.

It can, however, destroy information or introduce false information. This must be regarded as a major hazard in intelligent sensor design, as it is so easy to insert a process realized intuitively in software which may not be fully understood.

A final, but extremely important, element is communications processing. It is so important that it requires a processor of its own, though this may be realized as part of the main processor chip. The natural form of communication for the intelligent sensor processor is the multi-drop bus, which can produce enormous cost savings over the traditional star topology network. A most important attribute of the intelligent sensor concept is addressability, which is of course essential to the multi-drop principle and a powerful aid to the logical organization of sensor systems operation, but it docs introduce limitations. Addressability implies some form of polling of the devices, and though this may be prioritized in various ways, it does imply a constraint on the response time of the system to changes at any particular sensor site. A major contribution of intelligence is the integrity of communication. The transmission process can be protected by various forms of redundant coding, of which parity checking is the simplest example. In crucial applications information can be double checked by means of a high level handshake dialogue, in which the central processor asks for the information and then returns it to the sensor for confirmation. This deals with almost every possible fault except where the sensing element, though behaving apparently reasonably, is wrong. In such a case the only cure is the triplication of sensor elements, or in the extreme the triplication of intelligent sensors.

3.2.2 Hardware structures

Hardware structures for intelligent sensors can reveal great variety (Brignell 1984). Obviously such structures are greatly affected by the enabling technologies em­ployed. There is generally a need to mix technologies: an instrumentation amplifier, for example, poses different problems from a microprocessor, and to try to realize them in the same technology requires special and demanding circuit design techniques.

Minimal structure

In the minimal hardware structure of an intelligent sensor, the basic and most essential element is digital processing. It also contains input amplification and a data conversion unit. The basic structure is shown in the figure 3.2.2A. Note that a minimum requirement is the monitoring line at least for temperature which is an ever-present cross-sensitivity.

Analogue output

Although digital systems are becoming more and more the norm there remains a requirement for analogue output. The intelligent sensor with analogue output effectively replaces the dumb sensor, but obviates its imperfections. It is, however, useful to discuss the implementation of analogue output, as it provides a platform for a discussion of a number of important intelligent sensor concepts.

The obvious way to implement analogue output is to provide a DAC, so that the output is available with a precision defined by that of the converter. There are, however, important variations which have some potential for improved perfor­mance. Figure 3.2.2B shows one of these. Instead of calculating the required output the digital processor calculates the difference between the actual amplified sensor signal and the ideal output (after corrections for non-linearity, drift etc.). This difference is output as a correction, which is added to the original signal in a summing amplifier. By judicious selection of the weighting applied by the summ­ing resistors, this smaller corrections signal can be made to span the whole of the DAC output range. As a consequence the effective precision of the total output can be made much greater than the inherent precision of the DAC.

To take a simple example, imagine that the maximum anticipated error is 5% of full scale. A DAC of only eight hits could be used to span this 5%, and the effective precision at the summed output is one part in 28/0.05, or better than 12 bits. Of course, as it stands this is not a satisfactory solution, since the errors in the summing resistors have to be taken into account, which is a useful point at which to emphasize the power of providing for an auto-calibration cycle. If we expand the system by providing a multi-way analogue switch at the input, which is under control of the processor, any errors associated with that switch will be common to all inputs. The extended system is illustrated in figure 3.2.2C. This simple addition permits a variety of different calibration strategies. First, by switching in a reference voltage and then ground, the span in terms of voltage can be accurately assessed. Then, by switching in the output voltage a sweep of the whole range can be made to check for any sources of non-linearity, such as missing codes in the two data conversion stages. For temperature calibration the sensor is taken through its working range of temperatures. It is not necessary for the temperature to be known in any particular external units, but it is necessary for thermal equilibrium to be reached at a sufficient number of calibration points. Auto-calibration can be carried out on power-up, or it can be interleaved with carrying out the required functions of the sensor, provided the particular measurement strategy permits this.

It will be seen that the resulting sensor system is independent of errors produced by analogue component tolerances, and this exemplifies the intelligent sensor approach to accuracy. In the production stage there will generally also be a calibration cycle in which the target physical variable is swept through its range, and in certain applications it is possible to expose the sensor to calibrated signals in between operations.


One of the most important characteristics of intelligent sensors is the provision of a self-check cycle. It was a major adverse criticism of the original concept that the extra complications would reduce reliability, and without self-check this complaint would be valid. In a system such as that shown in figure 3.2.2C, the input signal switches allow a variety of test inputs to be applied. It should be noted that for the sake of clarity this figure has been somewhat simplified. It would, for example, be necessary to provide an attenuator so that the signals do not overload the amplifier. Also, without further switching elements, we have created a complete feedback loop. This has two implications: the effect of the DAC voltage is diluted by an amount determined by the amplifier gain, and there are stability consider­ations.

A complete self-check cycle may be implemented as follows. First, the input is switched to ground in order to check for any input offset drift. Small values of drift can be stored and applied as a digital correction, but large values of offset indicate a pathological condition which should be signaled via the communications processor as soon as the sensor is polled.

Second, a standard input derived from an internal reference voltage source is applied. This allows the gain to he checked and, if applied over a period, tests for intermittency.

Third, the input is switched to receive the DAC output via an attenuator, and a linear ramp is generated digitally. This simple test achieves a number of objectives. If the ramp is reproduced faithfully the linearity of the analogue components, the DAC and the ADC are all confirmed. Particular non-linearities that will be screened are missing bits in the DAC and ADC.

We should add here a remark on how the test procedure can be extended to differential amplifiers, as these are very common in intelligent sensors, because of the attractions of bridge configurations. An extra switch is required for the extra input, and the routine is as follows:

  • Apply zero volts to both inputs
  • Apply zero volts to one input and a reference voltage to the other
  • Reverse these connections
  • Apply reference voltage to both

These four stages allow for testing of the gain and the common mode rejection ratio. Ramp tests may be added if desired.

The completion of these tests ensures that all the electronic sub-systems are functioning correctly. The next stage is more difficult and very context dependent, and this is the testing of the primary sensor element. In some cases it is possible to arrange for known physical signals to be applied to the sensor, in which case a complete and proper calibration cycle can be carried out, but in the general case we have to assume that such a procedure would produce an unwarranted inter­ference with the operation of the target system, and we have to make do with less satisfactory information.

Sometimes it is feasible to apply rather sophisticated methods. For example, it may be possible to apply a disturbing stimulus to the target system in the form of a pseudo-random sequence of a magnitude below the threshold that would interfere with operation. The response of the system and the sensor could then be recovered by a process of cross-correlation.

Even without such elaborations it is possible to obtain some information to indicate whether the sensor is behaving correctly by, in effect, asking certain questions:

Is the output a reasonable value? That is to say. is it in range? Is it consistent with the prevailing conditions and plant history?

Is the rate of change of output reasonable? For example, a temperature sensor embedded in a thermal mass will have a constrained rate of response, and any more rapid changes would indicate some form of intermittency.

Is the output actually changing? In an active plant one would expect small changes to be occurring continuously. If they are not it is at least worth flagging a query to central control.

Is the output consistent with that of adjacent sensors? This question could be posed centrally, but it is also possible for the intelligent sensor to pick up the responses of its neighbours directly off the bus, thereby carrying out one of our prime requirements to relieve central control of unnecessary calculation.

There is, however, no escape from the fact that this part of the operation is extremely sensitive to context, and must be tackled case by case. Of course to obtain complete reliability one must resort to duplication or triplication. This option can be applied to the whole intelligent sensor, but as the electronic sub-systems arc fully self-testing, a much cheaper option is to duplicate or triplicate the primary sensors, using signal switches to cycle between them. In the latter case the program can include a voting procedure, so that two correct primary sensors can outvote a discrepant one. It is important, however, to ensure that the pathological condition is signaled to control, because a second primary sensor failure would be fatal.

Often primary sensor faults are simple in nature and therefore easily detected, such as going open- or short-circuit, but there are many other faults that are slower to appear and more difficult to deal with. Examples are the accumulation of various forms of detritus, oxidation, fatigue and migration of materials. In such cases there is a stage at which it is not clear whether there is a fault or not, so it is important to establish within the high level communications protocol a means of signaling a possible incipient fault to prompt a human inspection before more damaging conditions are established.

Clearly this is an area where it is very difficult to generalize, but the above account establishes some of the principles that can be applied.

General purpose structures

In the early days of intelligent instrumentation it was particularly convenient to have available a system that was totally configurable by software and it still has its advantages, particularly in the development phase. The main disadvantages are, first, that in designing such a system one is obliged to make decisions (e.g. the speed-precision trade-off) that will not always be appropriate and, second, in any application much of the system will be redundant. The latter point would not be important if a number of systems were manufactured, as the economics of scale would cancel out the waste.

Figure 3.2.2D shows diagrammatically a system which was initiated as a project in the early 1980s by one of the authors (the so-called Janus project). It was realized as a circuit board and achieved a relatively brief existence as a commercial device. It is, however, very useful in the present context, as it illustrates many of the principles that had been developed up to that point and are major planks in the whole philosophy presented in this book.

The central component of this system is a digital controller of a number of analogue multiplexers. This controller is connected to the bus of the microprocessor and is mapped as a block of its memory, so that the system is reconfigured by writing control words to the block.

One set of analogue multiplexers provides signal selection to the differential input amplifier. This provides for sensor compensation by the sensor-within-a-sensor method or by the sensor array. There is also provision for connection to an internally generated reference voltage and ground for self-check purposes. Another multiplexer controls a resistor network to provide gain selection in the input amplifier. A 12-bit ADC gives data input into the microprocessor.

There is also provision for voltage output from an 8-bit DAC, which may be utilized as an external voltage for such applications as sensor excitation or as an internal offset to the input amplifier. Note the importance of offset provision before data conversion (Brignell 1986).

An essential adjunct to such a system is a software system which simplifies the interface problems for the user, and allows all the system settings to be made by means of simple high level commands. A board such as that shown in figure 3.2.2D can be a very useful in intelligent systems development. Also present, but not shown, was a serial bus communications controller which allowed many such boards to be addressed on a single bus. Associated board level components were an intelligent bus controller which resided in a PC and an intelligent bus repeater, which allowed a network to be extended to kilometers in length.

3.3.3 Software Structures

The art of good programming is a substantial discipline in its own right, and it would not be appropriate to delve into it in a short text such as this. It is, however, worthwhile to examine one or two structures that are peculiarly appropriate to intelligent sensor systems. In passing we might also make a remark about the choice of programming language. There arc pressures in intelligent sensor design to work at the lowest level of programming, machine code, as this gives the highest speed and the most compact code. Where speed is not a special consideration, however, there are sound reasons for opting for a more portable language such as ‘C’ The main argument in favour of this option is that it reduces the tendency to ‘re-invent the wheel’; since procedures can be programmed once and for all. It also reduces the necessity to learn a variety of low level languages and gives a common format which is universally understood.

Look up tables

One of the more powerful concepts that entered at the dawn of computing was the processing of arrays. The Look Up Table (LUT) is a simple example of array processing that is of enormous significance in intelligent sensors. The basic idea is that one or more input variables are used as pointers to values stored in an array, which are then used for further processing. The first and most prominent use of LUTs was in linearization. Before the emergence of digital electronics non-linearity was a problem so overwhelming that it was almost universally avoided. The LUT changed all that, though the problem is now so reduced in importance that it is easy to forget that there arc still pathological cases that arc immune to correction.

Another important application for our purposes is in the switching of sets of coefficients. If you require a number of digital filters, or cascaded sections of digital filters, it is not necessary to duplicate the code that implements a filter. It is merely necessary to change the base address of a pointer so that a new set of filter coefficients can be picked up from a different LUT, and use the same code with a different set of coefficients.

LUTs may also be of two or more dimensions. A very important application of multi-dimensional LUTs is in correction for cross-sensitivity. In this case one pointer will be derived from the uncorrected input variable, while the others will be derived from the interfering variables. By far the most important case is the two dimensional case in which the second variable is temperature, which is of universal concern as a cross sensitivity.

Assume that the input variable is derived from an ADC of A/ bits precision. Then the top N bits are masked off by a logical AND operation with the mask (2N- l) 2M-N. The masked value is shifted down M-N places (i.e. multiplied by 2N-M). This is now the incremental address that can be added to the base address (the location of the lowest entry in the LUT) to point to the desired value.

To illustrate the point with numerical values let us assume we have a table of size 32 (N=5), and the input ADC is of 8-bits precision. The input variable is masked off with the mask 11111000 and shifted right three places to give a five bit incremental address, which when added to the base address points to the required value.

Evidently we have thrown away three (M-N) bits of information. What we do next is a classical example of the trade-off between speed, precision and storage. We can ignore the loss and go for maximum speed, we can make M=N and go for maximum precision at the expense of storage or we can use the bottom M-N bits to provide a linear interpolation between the selected entry and the next one up, and sacrifice some speed to gain precision. Indeed we can use higher degree interpolation formulae to gain precision and conserve storage at the expense of speed. The choice made depends on the demands of the particular application.

For reference in this case the linear interpolation formula reduces to

Figure 3.3.3B shows how a two dimensional LUT is arranged in the store and how it is thought of conceptually. If the two variables, say x and y. are masked off to M bits of precision, the new incremental address is formed from 2Mx + y, so that the layout of the area of storage containing the LUT is as shown on the left-hand side of the figure. It is helpful, however, to conceive of the arrangement as a two dimensional one, as illustrated on the right of the figure.

There is a variety of ways in which the entries can he loaded into the LUT They might be derived from a model, a common calibration curve for the family of sensors or (most preferably) by means of an individual calibration cycle.

Cyclic buffers

Another software structure important in intelligent instrumentation is the cyclic buffer. It can be implemented in a way similar to the LUT, in that it is based on masked pointers. These are incremented every time there is a read or write operation, and because the bottom n bits are masked they return to zero every time they reach 2n. In this way, although the buffer is a linear array it behaves as though it was a circle, and the pointers behave like the hands of a clock (figure 3.3.3C).

Cyclic buffers can have a number of useful applications. They are invaluable in linking two processes that are unsynchronized, such as a constant sampling rate and the random availability of communications access on a bus. We must always remember, however, that our simple law of information flow always applies, and the input and output demands of the buffer must align on average or information will inevitably be destroyed.

Another application of cyclic buffers is in the realization of digital filters and other processes requiring delay (e.g. real time correlation). Here the read pointers arc linked rigidly to the write pointer to achieve fixed delays.

A third useful application area is in what might be called the software transient recorder. The transient recorder is a device that behaves like an oscilloscope except that it enables per- trigger information to be reproduced. The way it operates is that a signal is sampled continually, with each new datum erasing the one that came 2n samples before. When a certain trigger condition occurs (e.g. the signal reaches a given level) the sampling process is stopped after, say, k further samples have been obtained. There are then k post trigger data and 2n – k pre-trigger data. These can be displayed continually by reading them repeatedly to a screen, or transferred to a linear array, care being taken that the first datum is at the beginning of the array. The software transient recorder is invaluable in such applications as impulse or step testing, where it removes any need to synchronize with the stimulating signal.

Signal processing structures

When the numbers being processed are a time series, as is usually the case with sampled data from a sensor, then a powerful set of processes becomes available through the application of advances in linear algebra.

There are two main classes of signal process as far as we are concerned. These we will call block processes and stream processes. In block processing a finite number of samples is acquired, and the whole block of samples is processed once acquisition is complete. This is not normally a real time operation, though there are variations which make it effectively so. In stream processing the samples are acquired continuously and operated on as soon as they arrive. This is normally a real time process and the number of samples is effectively unbounded.

Block processing may be exemplified by the general linear algebraic relation­ship, where a new vector of variables, yj is obtained from the original set, xi by multiplication by a rectangular array of coefficients

This is, in our terms, the recursive digital filter, which again, via the r-transform, give us a powerful tool in manipulating signals. The power of the idea of recursion, in which a process can operate on its own outputs as well as the inputs, can hardly be overstated. We saw a simple example in the case of the running mean smoothing filter, and the compaction obtained there is typical.

Indirect software structures

Most of our numerical methods arc direct, or closed, structures, but it is easy to forget that the power of the digital processor enables us to use indirect, or open, methods. Many scientists and engineers seem to have distaste for ‘guesswork’, because of their formal training in analytical methods, but often such methods yield significant solutions where none would be otherwise available.

The most familiar of such methods are the root finding iterations, such as Newton, but there is a highly developed set of tools which are in the nature of optimization. In order to facilitate an optimization technique there are three prior requirements;

  • A set of adjustable parameters or coefficients which fully define a process.
  • A measure of ‘goodness’.
  • A means of making an educated guess at a better set of parameters.

Given these three factors we can use a method of trial and error to arrive at an optimum solution. Normally we also need a criterion for stopping the process, either sufficient accuracy or a limiting number of iterations, but in the sort of on-line process we find in intelligent systems it is possible to keep the process going on indefinitely, so that changes in the outside world can be tracked, and an operating point held at optimum.

The two basic classes of optimization process are gradient methods and gra­dient-free methods. However, because the process of taking a gradient enhances high frequency noise, we normally prefer the latter class in transducer applications.

Software shells

The idea of a software shell is now a familiar one, as the term is used with common computer operating systems. It is a very important concept with the sort of systems we are discussing here. The user of intelligent sensor systems is normally an instrumentation engineer. It is therefore absolutely vital for the design of the intelligent sensor system to include the design of a software shell. This is not only important in protecting the user from the intricacies of internal operation, but like the shell of an egg it also protects the contents from being damaged by external events. Figure 3.3.3D shows diagrammatically the software ar­rangements developed alongside the generalized hardware unit described in 3.2.2.

Chapter 4

4.1 Home Automation

We find new technology coming in deeper and deeper into our personal lives, as the world gets more and more technologically advanced, even at our home. Home automation is becoming more and more popular around the world and is becoming a common practice. The process of home automation works by making everything in the house automatically controlled using technology to control and do the jobs that we would normally do manually.

Home automation (Domotics) is the field specializing in the general and specific automation requirements of homes and apartments for their better safety, security and comfort of its residents. Domotics is being implemented into more and more homes of people in order to maintain their safety, independence and comfort. These Smart Homes allow the general user to monitor their entire house through a single unit or through a network. For the disabled people, intelligent homes give them opportunity for independence, which will help them gain confidence and determination. Smart Homes can provide both the elderly and disabled with many different types of emergency assistance systems, automated timers, fall prevention, security features, and other alerts. Smart home systems will enable family members to monitor their loved ones from anywhere through internet.

In a more advanced automation systems, room are installed with sensors that can detect the presence of human beings and even identify the person inside the room. The control centre then can set the desired lighting and temperature setting depending on the person, the time of the day and other factors. Automation tasks may also include the setting of air conditioning to an energy saving mode when the house is unoccupied, and restoring to its desired temperature depending on a preset time or the presence of a person in the room. More complicated automation systems are capable of maintaining an inventory of products, recording their usage through a Radio Frequency ID (RFID) tag, prepare a shopping list or even automatically order their replacements.

Other practical implementation of home automation system is to alert the occupants of the house when the sensors detect a fire or smoke by blinking the entire lights of the house.

As we age, we face declining abilities from age-related diseases and the aging process itself. Our home can assist or hinder our ability to complete self-care and household activities. In this chapter we focus on the very latest technology, as well as future technology, that can and will assist us in living independently at home. There is growing interest in the concept of “smart houses”. What is it that a smart house actually does, or offers to its residents? The following list summarizes the discussion smart house functions, organizing these functions into “levels” based on complexity and how long the function has been available; in some cases they are not yet available in product form.

Level 1: Offers Basic Communications

  • Offers interactive voice and text communication (phone and email)
  • Provides link to World Wide Web
  • Offers TV (full range of stations) & radio (AM and FM)

Level 2: Responds to Simple Control Commands from Within or Outside the Home

  • Unlock / lock door
  • Check for doors / windows open or unlocked
  • Turn on lights
  • Check for land-mail
  • Get help (in the case of a fall or other problem)

Level 3: Automates Household Functions

  • Air temperature, humidity
  • Lights on/off at predetermined times
  • House made secure at certain times
  • Music, TV on/off at certain times

Level 4: Tracks Location in the Home, Tracks Behaviors, and Tracks Health Indicators

  • Determines activity patterns
  • Determines sleep patterns
  • Determines health status (vital signs, blood glucose, weight)

Level 5: Analyzes Data, Makes Decisions, Takes Actions

A. Issues alerts

A1. To resident

  • Mail has been delivered
  • Person (name given, or stranger stated) at door announced
  • Water leaks
  • Stove has been left on
  • Door is unlocked

A2. To distant care provider

Altered, problematic activity or sleep pattern, or health problem

A3. To formal service provider

Health alert

B. Provides Reports

To resident, care provider, and formal service provider on status

C. Makes changes in automated functions based on learned preferences

Adjusts lights, temperature, music to resident’s use patterns—can be overridden Easily

Level 6: Provides Information, Reminders, and Prompts for Basic Daily Tasks

  • Notification mail has arrived, someone is at the door, stove was left on
  • Medication reminder
  • Hydration reminder
  • Meal reminder
  • Task prompting
  • Washing, grooming
  • Dressing
  • Toileting/hygiene
  • Exercise
  • Meal preparation
  • Social contacts (e.g., “call. . . .”)
  • Household cleaning

Level 7: Answer questions

  • “Have I . . . (brushed my teeth, taken my medications, put all the ingredients in the dish I am preparing”
  • Orientation—time, day, month, year, season
  • What is happening today?
  • General information (any question that could be searched on Google)

Level 8: Make household arrangements

  • Schedule maintenance and repair visits
  • Order medications
  • Prepare grocery lists and send to grocery for delivery
  • Prepare meals
  • Handle house cleaning

Smart House Level I: Offers Basic Communications

Level I technology is necessary for a smart house, but simply having level I technology does not alone make it a smart house. At Level I, technology relates to communications, providing residents with the means to communicate with and receive communications from others beyond the home. Telephones represent one example of communications technology, one that has been available for over 100 years, providing voice communication with others who have the same technology. Today, especially with mobile phones, they exist almost everywhere. The telephone is especially important for older persons with disabilities. Almost one-third live alone, and for those with limited mobility, the telephone provides opportunities for socialization. In a study of older adults living in rural areas, frequent loneliness was found to be associated with frequent use of the telephone. The telephone also provides a mechanism for calls for help. Many people use the telephone for shopping, banking, and arranging other personal services.

Internet access is an important communication technology, essential if a home is to be considered “smart.” And for optimal use of the internet in a smart house, high-speed access is very important. Television and radio offer additional communication, although traditionally the communication has been one-way. This is also changing, if we have Web-TV, an inexpensive way of turning a TV into a web device. TVs are being sold as components; for example, a flat screen monitor hanging on a wall can display TV or input from a computer. Traditional TV, along with other electronic entertainment, is being designed in smart homes as multimedia centers, offering a range of options for media.

Smart House Level 2: Responds to Simple Control Commands from Within

Or Outside the Home

At this level, anything in the house that uses electrical power can be “operated” without having to use a switch or control button attached to, or wired into, the appliance or device. Examples of household items that could be controlled include: door locks with an electronic mechanism to set the bolt; lights; small appliances; thermostats; and mechanically controlled curtains and windows. Ideally, voice commands would provide the simplest way to issue the commands. Most systems currently sold use a remote control device similar to a TV remote. Many systems also allow distant operation through a phone.

Smart House Level 3: Automates Household Functions

Heating and air conditioning systems that use a thermostat automate air temperature in the house. Keep in mind that the first thermostat for controlling room temperature was invented in 1885, and the first home air conditioners appeared in 1928. Today, for the most part, we take automation of our air temperature for granted. It has been possible to automate other aspects of our home such as when lights go on and off, when music or television is turned on, when the security system is set, and when our lawn sprinklers go on and off. Today we have products that offer more flexibility or features in this level of automation. Computer-based smart home products allow more easy setup for the on-off cycle, and different scenarios can be programmed for different periods, such as “weekends at home,” “vacation mode traveling,” and “work-week mode.” In some systems, the preset cycles can be broken or interrupted easily, either in the home or through a phone call.

Smart House Level 4: Tracks Location in the Home, Tracks Behaviors, and

Tracks Health Indicators

A number of university and corporate labs are working on development of systems to track where a person is located in their home. If the home “knows” where you are, it can take appropriate actions in that room or area. For example, if the smart house is going to issue a reminder (time to take medications) or alert (someone at the front door), it can provide the reminder or alert in the exact location where the resident is sitting or standing. If the resident falls, an alert can be issued stating just where the person is located in the home. The smart house can also track behaviors, such as trips to the bathroom, visits to the kitchen and refrigerator, tossing and turning in bed, and time spent sleeping, sitting, or exercising. Tracking health indicators could include taking measurements of vital signs and weight.

Smart House Level 5: Analyzes Data, Makes Decisions, Takes Actions

Knowing typical patterns for the smart home’s resident, deviations from this pattern could be indicators of a problem, and the smart house could check with the resident, or a family member, to be sure the person was well. Likewise, if a person was losing too much weight, they could be alerted, or a care provider could be notified. The smart house is also capable of compiling health status reports for the resident, for a family care provider, or for a formal service provider such as a physician. Tracking key health information related to the resident’s condition on a daily basis can lead to quickly identifying deviations from what is normal for that person. The smart house can also learn the resident’s preferences in such areas as lighting, temperature, and music. The smart house will then either directly makes adjustments (such as raising the temperature in the home just before the person gets out of bed) or “ask” the resident if they would like the adjustment made.

Smart House Level 6: Provides Information, Reminders, and Prompts for

Basic Daily Tasks

The smart house will “know” when mail has been delivered, when someone is at the front door, when the stove has been left on too long, or when the resident has gone too long without a drink of water or has forgotten to take medications. It will prompt the resident that the mail has arrived, to take a drink of water or medications, or that it is time to have dinner. For someone with more significant cognitive impairment, who has difficulty even with basic daily tasks such as dressing and grooming, the smart house will prompt the person with voice and visual cues through each step in the activity.

Smart House Level 7: Answer Questions

Those of us who regularly use the internet appreciate the ease with which we can get answers to almost any question; typically we use Google or some other internet search engine. For questions that go beyond the resident’s individual experience, the smart house, with a voice recognition interface, will accept questions, go to the web to seek the answers, and respond with an answer back to the resident. For more personal questions, such as “Have I taken my medications this morning?” the smart house will search its own database and respond appropriately.

Smart House Level 8: Make Household Arrangements

The smart house will know when the furnace filter needs to be cleaned and when medications should be ordered, and it will handle all details of those transactions. The smart house will track food consumption, seek input from the resident on the menu for the next several days or more, prepare grocery lists, order the groceries, and arrange for deliveries. When an appliance requires repairs, the smart house will recognize the need and arrange for someone to come to the home to make the repair.

4.2 Scopes of Home Automation

The scopes of home automation can be as simple as controlling the lighting of a room to as complex as to set the room conditions depending on the person inside the room. The domotics field is expanding each day in order to fulfill man’s dream for luxury and comfort. The common areas which are automated in the home include lighting, security, climate control, auto curtains, sprinkler system, fire alarm etc.

4.2.1 Lighting

One of the most common areas of automation is the home lighting. It can be as simple as basic switching ON/OFF to as complex as adjusting itself to the mood of a person or people in the room. The lighting can be subdivided into internal and external lighting.

External Lighting

External lighting refers to the controlling the lights outside the house including ones in the balcony and verandah. The objective is very obvious, i.e. the lights should turn ON when night falls and it should be turned OFF when day breaks. However there are some limitations to this. If the controller is set to a time frame, i.e. turn ON/OFF at specified time the lights may be turned only during that time. As the season changes, the sun rise and setting time varies by 1 hour or so. In such cases this controller is impractical. So we can use an ambient light sensor, which senses the amount of light falling on it and tells the controller to turn ON/OFF the lights depending on the light intensity. This intensity level can be adjusted to attain perfect synchronism.

Other than the regular lighting, flood lights may be provided around the house. This can be used in a party or gathering, but normally this light will be in the OFF state. The flood lights are connected to the security system of the house, and incase of any security breach, the flood lights will be turned ON.

Internal Lighting

The internal lighting is one of the major scopes of home automation. Different setting is used in the different rooms of the house. But all the rooms have the basic setting of turning ON when a person is inside the room. However in case of the living room, kitchen and dining room; the case is different. It is almost similar to external lighting, i.e. turn ON/OFF depending on the intensity of light falling on the light sensor.

Let us consider the living room. Living room is the place where most of the family activities take place. Most of the people will be in the living room at a given instant of time. Moreover guests are seated in the living room. The living room has a light sensor which turns ON the lights inside the room when the day light is less. Similarly it turns OFF the light when the day light is more. The living room is also set with an automatic electronic dimmer. This dimmer is used along with a controller in which we can preset certain moods in the room. For example, the mood during a party is different from a mood during a family prayer. In this way the dimmer and controller together adjusts the room lighting depending on the occasion. The manual switches are replaced with an electronic controller in order to adjust the various setting of the house.

The kitchen and dining room has almost the same setting as the living room except the mood controller. However there is an electronic controller in the wall to turn off the lights when going to sleep. Or a timer can be set up to turn off the lights at a specific time.

The bed rooms are equipped with an occupancy controller. Also called motion sensors, occupancy controls are the most widely used form of automatic lighting control. These sensors can be used in a variety of spaces to keep lights off when they are not needed. Most occupancy sensors detect motion based on passive infrared and/or ultrasonic methods of operation. Depending on the space type, the sensor can replace wall mounted light switches or can be mounted remotely, retaining the normal switching for use as override switches, which allows the lighting to be kept off even when the space is occupied. This sensor will turn ON the lights when a person enters the room and turns OFF when the person leaves the room. When going to sleep the timer in the controller can be setup to turn OFF the lights at a specified time. The ambient light sensor is also fitted in the room which helps to turn ON during night time and not to turn ON during day time.

The bathrooms are equipped with a normal occupancy sensor, which turns ON the light when someone enters and turns OFF when the person leaves. This is put along with an ambient sensor so that the light is used only if there is not enough light in the bathroom.

4.2.2 Automatic Curtains

Another scope of automation in house is using automatic curtains. Similar to lighting curtains allow more light into the house, therefore we can easily link it with a light sensor. The light sensor detects day light and allows the curtains to be fully open. When the night falls the light falling on the sensor is reduced and the curtains are set to close automatically. The automatic setting can be overridden. The controller of the curtains is connected to the central controller where we can set the curtains to be open or close manually. A remote controller can be linked to the curtains allowing the user to control the curtains manually.

4.2.3 Temperature and Humidity Control

The air conditioning in a smart home is fully automated. Which means that the user doesn’t have to control or set the values of temperature every day, instead the values once set will be recorded and the automation system will set the room temperature to the desired level at all times. The user sets a particular temperature in the central controller and the automation system then compares the room temperature with this set value. If the room temperature is higher than the set value, the automation system enables the air conditioning and monitors the room temperature till it achieves the desired value. Once desired set value is reached, the automation system turns OFF the air conditioning. An occupancy sensor setup inside the room detects the presence of a person in the room. If no one is present in the room, the air conditioning system is automatically turned OFF. The time for it to turn OFF can be preset by the user. Manuel overriding of all the air conditioning setting can be done at the central console.

Another automation system to control the room temperature is provided with a timer in which the user can set a particular time for the air conditioning to turn ON. The automation system will turn ON the air conditioning at this specified instant of time.

A much more complex automation system is equipped with a person detection system, which automatically identifies the family member and sets the room temperature automatically, which is required by the user. This type of automation system is highly complex and very costly. It has got an image processing chip and a very complex algorithm. This automation system can be made affordable by using RFID tags. All the air conditioning automation system is preset in such a way as to turn OFF the system when detecting an open window or an open door.

4.2.4 Security and safety control

Security and safety consist of those measures to provide the protection of property, life, materials and facilities against fire, damage, unauthorized entry, theft and any other dishonest, illegal or criminal acts that might happen to the house. Architects and engineers aim to find cost- effective solutions addressing the security and safety concerns of people residing in t he homes, which not only comply with government regulations, but also provide enhanced protection. Some of the commonly used security and safety features in houses include:

  • Closed circuit television (CCTV) systems;
  • Access control systems;
  • Burglar alarm systems;
  • Fire alarm systems.

CCTV systems

For decades, CCTV has been implemented and integrated in safety and security applications. The purpose of CCTV in security solutions is to provide remote ‘eyes’ for security operators by providing live- action displays from a distance and/or to keep a video record of the spaces under monitoring. With today’s labour costs, CCTV is a cost- effective means for expanding security and safety control. Certainly, the main objective of CCTV systems should not be to record ‘thieves’, but rather to prevent theft. There are two basic categories of CCTV systems: analogue CCTV systems and digital CCTV systems (or IP surveillance systems).

A typical analogue CCTV system includes the basic components of camera, monitor, video switcher and video recorder. One physical device may integrate the functions of two or more components among monitor, video switcher and video recorder.

A camera is the basis of any CCTV system. The camera creates the picture that will be transmitted to the monitoring or control position. However, CCTV is not just a simple camera- cable- monitor arrangement. The basic function of a CCTV camera is to convert the physical scene viewed by the camera into an optical picture. By a focusing process, the scene is placed upon a special camera imaging tube which scans the imaged scene and breaks it down into various picture elements. These elements are then transmitted and converted into varying illumination levels that correspond to the video signal, which is ultimately converted into a visual scene on the system monitor. The CCTV system should have the means of recording, such as using VCR (video cassette recorder), computer disc or other storage media, to maintain permanent records of what the cameras have seen. Cameras used in CCTV systems may be installed with lenses of fixed length. Many cameras used in CCTV systems are movable with lenses of adjustable length as in many applications the areas to be covered would need many fixed cameras. The cameras can be controlled to rotate horizontally and vertically from a remote location. In conventional analogue CCTV systems, the cameras are linked to the video monitor or video switcher via coaxial cables and each camera needs its own cable connection. The camera may obtain power from the video switcher or monitor for its operation via the same coaxial cable for video signals, known as the line- power camera. The camera may alternatively get power by connecting to the main power supply, known as a mains- powered camera. Figure 4.2.4A illustrates the basic configuration of a small- scale line- powered CCVT system without recording. Figure 4.2.4B illustrates the basic configuration of a small scale mains- powered CCVT system with recording. The arrangement of a mains- powered CCTV system allows much more flexibility in designing complex CCTV systems.

The picture created by the camera needs to be reproduced at the control position. A CCTV monitor is virtually the same as a television receiver (a TV could actually be used if it is cost effective) except that it does not need or have the tuning circuits. When multiple cameras are involved in a CCTV system, video switchers are required as shown in Figures 4.2.4A and 4.2.4B. Using a video switcher, the picture of any camera may be selected to be displayed on the screen or it can be set to display the pictures of the cameras in turn according to pre- set speed and sequence. The video switcher may allow the display of the pictures of multiple cameras on the screen at the same time.

Access- control systems

Access control is the ability to permit or deny the use of a particular resource by a particular entity. Physical access by a person is controlled on the basis of authorization, payment and the like. In physical security, the term access control refers to the practice of restricting entrance to a property, a building or room to authorized persons. Physical access control can be achieved through mechanical means such as locks and keys, or through technological means such as advanced access- control systems.

Locks and keys have been used to control access to buildings and rooms for hundreds if not thousands of years. Today, the traditional key- based lock is still the most popular means used for access control of buildings, rooms and even commercial spaces. However, electric (or electronic) locks are commonly used nowadays to provide more effective or more secure access control. Electric locks are sometimes standalone with an electronic control panel mounted directly on the lock. More often electric locks are connected to an access- control system. Access- control locks are also designed in different forms to suit different applications such as to control access to public transportation, car parks, and construction sites and even for immigration control.

Electronic access control uses computers to overcome the limitations of mechanical locks and keys. A wide range of credentials can be used to replace mechanical keys. The electronic access- control system grants access based on the credential presented. When access is granted, the door is unlocked for a predetermined time and the transaction is recorded. When access is refused, the door remains locked and the attempted access is recorded by the access control system or even by a CCTV system. Figure 4.2.4C shows the basic components and configuration of a typical door access control system. When a credential is presented to a reader, the reader sends the credential’s information, typically a series of numbers, to the control panel (a digital processor). The control panel compares the credential’s number to an access- control list, and grants or denies the request. When access is denied based on the access control list, the door remains locked. If there is a correct match between the presented credential and one in the access- control list, the control panel sends

a signal to unlock the door. There are usually three groups of credentials used for access control, referring to something a person knows (such as PIN, Personal Identification Number), something a person has (such as an access card), or a biometric feature (something the body of a person has, such as a fingerprint). Accordingly, access- control systems typically employ:

  • PIN access control;
  • Card access control;
  • Biometric access control.

Often some combination of them is used for high reliability of the access control system.

Burglar alarm systems

The use of burglar alarm systems (or intrusion- detection systems) is to detect unwanted attempts in accessing a space or object. The main functions of burglar alarm systems can be divided into three categories including: perimeter protection, area/space protection and object/spot protection. Various sensing devices of very different mechanisms are available for detection at different situations. Intrusion- detection systems also often refer to the systems for protecting computers or other information systems from unwanted access.

Functions of burglar alarm systems

Perimeter protection is usually achieved by mounting sensing devices on doors, windows, vents, skylights or any openings to the home. The advantage of perimeter protection is simplicity of design. Its disadvantage is that only the openings are protected. Typical sensors used for perimeter protection include door contact, electric field fence sensor, infrared beam sensor and glass break detectors.

Area/space protection systems are designed to protect the interior spaces of a facility. Sensing devices used for space protection are particularly effective against ‘stay- behind’ intruders. The detection sensors can be classified into four main categories including audio, pressure, electronic vibration and motion detection. The advantage of area/space protection systems is that they provide a highly sensitive, invisible means of detection. Their disadvantage is that incorrect application and installation can result in frequent false alarms. In many practical applications, space protection is used as a backup to the perimeter protection system. Typical sensors used for area/space protection include passive infrared detector (PIR), photoelectric beams, and ultrasonic detector and pressure- sensitive mats.

Object/spot protection aims at providing direct protection for specific items, including direct security for high- value items. Such a detection method is the final stage of a comprehensive protection system. Typical sensors used for object/spot protection include capacitance/proximity detectors and electronic vibration detectors.

Fire alarm systems

The function of fire alarm systems is to detect the presence of unwanted fire in the protected spaces by monitoring environmental changes associated with combustion. Fire alarm systems may be activated automatically, manually or usually both. The purpose of using fire alarm systems is to notify people to evacuate in the event of a fire or other emergency, to call the fire protection department for emergency aid, and to activate other associated systems to control the spread of fire and smoke. It is worth noting that the fire alarm system is an essential measure but not the only measure for the fire safety of a building in terms of both regulations and reality. Concerning fire alarm systems, it is critical to properly select and place the detectors according to the layout and use of spaces.

Typical fire detectors

A fire alarm can be initiated manually or automatically. Manually operated devices, such as a ‘break- glass’ alarm, provide the means for occupants to activate the fire alarm system when they observe a fire or smoke. Automatic fire detectors commonly used can be summarized into the following types, including: heat detector (or heat- sensing fire detector), smoke detector (or smoke- sensing fire detector) and flame detector (or flame- sensing radiant energy fire detector). Different types of detectors have different detection speeds and probability of false alarms. Different types may be used to increase the detection speed and to enhance system reliability.

Heat detectors: A heat detector detects fire by sensing changes in ambient temperature. Typically, if the ambient temperature rises above a predetermined threshold an alarm signal is triggered. Heat detectors may work on the basis of rate- of- rise of temperature, fixed temperature or both. Rate- of rise heat detectors are activated by the sudden rise in ambient temperature. A sudden temperature rise above a change- rate threshold, such as 8 K per minute, will activate the alarm. Fixed- temperature heat detectors are activated when the ambient temperature reaches a fixed threshold, such as 58°C. Heat detectors are usually installed in spaces, such as kitchens or utility areas, laundry rooms or garages, where smoke and fire detectors should not be installed. This will allow extra time to evacuate the building or to put out the fire if possible.

Smoke detectors: Smoke detectors detect smoke and issue signals to fire alarm systems. There are many different smoke detectors based on different mechanisms and designs. Common types include: ionization smoke detectors, photoelectric (optical) smoke detectors, air- sampling smoke detectors and carbon monoxide/carbon dioxide detectors. An ionization detector contains a small amount of radioactive material that ionizes the air between a positive and negative electrode. The conductance between the electrodes is measured. Introduction of smoke into the

Sampling chamber of the detector reduces the conductance between the electrodes. When the conductance falls below a pre- set threshold, the detector is triggered.

A key element of a photoelectric detector is the light sensor. In a smoke detector, the light sensor is provided with a light source (e.g. infrared LED) and a lens to concentrate the light into a beam at an angle to the light sensor. In the absence of smoke, the light passes in front of the detector in a straight line. When smoke enters the optical chamber across the path of the light beam, some light is scattered by the smoke particles and directed at the sensor; thus the alarm is triggered.

An air- sampling smoke detector detects microscopic particles of smoke. Most air- sampling detectors are aspirating smoke detectors, which work by actively drawing air through a network of small- bore pipes laid out above or below a ceiling in parallel runs covering a protected area. Small holes drilled into each pipe form a matrix of holes (sampling points), providing an even distribution across the pipe network. Air samples are drawn past a sensitive optical element to detect the extremely small particles of combustion. These types of sensors are used in high- value or mission- critical areas. Smoke detection systems using air- sampling smoke detectors can provide multiple levels of alarm threshold, such as alert and action, and therefore achieve high sensitivity in smoke detection.

Flame detectors: Flame detectors detect flames directly by using optical sensors. Common types of flame detector include: ultraviolet (UV) flame detectors, infrared (IR) flame detectors and UV/IR flame detectors. Ultraviolet flame detectors work with wavelengths shorter than 300 nm. These detectors detect fires and explosions within 3-4 ms due to the UV radiation emitted at the instant of their ignition. False alarms can be triggered by UV sources such as lightning, arc welding and sunlight. In order to reduce false alarms a time delay is often included in the detector design. Infrared flame detectors work within the infrared spectral band. Hot gases emit a specific spectral pattern in the infrared region, which can be sensed with a thermal imaging camera. AUV/IR flame detector is the combination of ultraviolet detection and infrared detection, which confirms the fire by using UV and IR thresholds in ‘AND’ configuration to minimize false alarms.

4.2.5 Garage Door

The garage is a part of the house. It is usually constructed at one corner of the house with a door which opens into the house. The garage door protects the car from the weather conditions. Some people use garages to store unwanted home furniture. But if the garage is used to park the car, then an automatic garage door will help the driver to park it easily. A normal garage door is manual in operation and requires the driver to open it manually which is very tedious. An automated system for garage opening and closing will help the driver to avoid this.

The automated garage door opener is equipped with a car sensor which is usually a long rectangular coil buried in front of the garage. The coil will produce an electrical signal when a car is just above the coil. This signal generated by the sensor is fed to a controller which sends a signal to open the garage door. Once the door is opened the car is driven into the garage. Once the car is in the garage the garage door is closed by the controller. The inside of the garage is also equipped with a car sensor in the garage floor. So once the car is inside the garage, this sensor coil will send a signal to the controller. If a second car appears in front of the garage, then the controller will check for signal from the sensor coil inside the garage. If there is a car present inside the garage , then the controller will not send a signal to open the garage door.

The automated garage door is also equipped with a remote control to open and close the garage door using the remote. So if the user wants to take the car out for a drive then the user can use this remote to open the garage door from inside the car itself.

While closing the garage door, if an object is in its path, then the garage door must stop its operation. If a child or a pet is the object, this operation will prevent the object from being crushed by the garage door. This is done with the help of an infrared sensor. The sensor is fixed at regular intervals along the side of the garage door. While closing and opening the garage door, the controller will check for any change in signals from these sensors. If any change in signal value is detected, then the operation of the garage door is stopped. And the operation is resumed once the signal values are returned to the initial value.

4.2.6 Lawn Sprinkler System

Most of the landed house has a lawn and people find it very hard to maintain the lawn just because of the fact that lawn needs watering everyday. People always forget to water the lawn or they tend to flood the lawn. So an automatic sprinkler system is needed for the lawn. This system consists of a dampness sensor which is buried in the soil. If the soil is not damp enough; the sprinkler system is turned on by the controller. The sprinkler is turned OFF automatically after a specified time frame or if the dampness sensor gives a proper signal.

The sprinkler system is connected to a controller which is standalone and can be connected to the central controller by a wireless connection. It is possible to control the timer and other settings of the sprinkler from inside the home itself. The signal from the sprinkler controller is connected to a solenoid valve which is used to turn ON and OFF the sprinler system.

4.2.7 Automatic Washer

The washer is a basic necessity in every home. The most modern washers are capable of washing, rinsing and drying automatically. But the user needs to give the commands for these functions. In a modern automatic washer the user doesn’t have to do anything. The soiled clothes are put directly in the washer after use. The washer then continually monitors the weight of the clothes in the tub. Once the weight reaches a defined SET value, the washer starts is the operation and finishes with the drying operation. After the drying function, the washer generates an alarm signal to remove the washed clothes. After removing the washed clothes, the alarm is disabled and the washer is ready for operation again.

Each setting of the washer can be predefined in the central controller. The setting like washing time, washing level, spinning time, rinsing time, and washer load etc. can be adjusted depending on the user’s choice.

4.2.8 Emergency Power Back Up System

When bad weather or other conditions interrupt power service, homeowners can find them unable to heat or cool their homes or run necessary appliances and lights. While fireplaces can provide some heat and flashlights or lanterns can provide light, many appliances will remain unusable until power from the grid is restored.

The back up system refers to the power back up incase of a power cut or load shedding. This is more common in underdeveloped countries. But it may happen in developed countries too. The power failure can be caused by a number of reasons from line faults to open circuit faults. So it is always safe to employ a back up system as the entire home is automated.

The main back up is provided by a line inverter which is connected to the entire wiring of the house. The main back up will provide a temporary power for few hours. By this time most of the faults will be cleared. However if the fault is a complex one then this back up will not do. So there is a secondary back up system for the automation system alone which provides basic lighting and communication medium.So in case of a major fault, the automation system is configured in such a way as to comfort the people living.

Emergency backup systems currently available on the market make it possible for homeowners to have continued access to electrical service during power outages. These systems are typically based either on fossil-fuel-powered generators or on battery-based storage systems. While the goal of both approaches is the same – to produce backup power – they each have advantages and disadvantages. For emergency backup power during typical power outages, battery-based systems represent a fairly simple and silent alternative.

The two basic components of battery-based storage systems are an inverter/charger and a set of DC batteries. The inverter/charger converts AC power from the grid to DC to charge the batteries. When power from the grid is lost, the inverter converts the DC battery power to AC for use in the home.

The length of time that a battery-based storage system can provide emergency power to the home depends on its overall capacity and the type and number of appliances connected to the backup system. Battery-based systems are not designed to provide power over an extended length of time. For example, product literature by a producer of backup power systems indicates that a typically configured 2000-4000 watt system can provide typical priority household appliance loads for 2 to 12 hours. However, power conservation can extend operating time considerably longer. Additionally, fossil fuel-fired generators or photovoltaic equipment can be integrated into some systems to replenish or supplement the batteries when power is not available from the grid, or to help the batteries support the home’s load.

4.2.9 Communication System

4.3 Domotic Standards

The data from the intelligent sensor must be transferred to the central control. In order to transfer the data, a certain domotics standard must be used. Several standards have been created over the past few decades. Some of the standards use communication and control wiring for data transfer, some embed high frequency signals in the powerline, some standards make use of radio frequency (RF) signals or other wireless methods, and some standards use a combination of several methods. Control wiring is toughest method to install in an existing home wiring. Some of the home appliances are fitted with a USB port which can be connected to the domotics network to control it. Bridges can be used to translate data from one standard to another. Specific domotic standards include X10, INSTEON, Universal Powerline Bus (UPB), KNX, UPnP, ZigBee and Z-Wave.

X10 Standard

X10 is an international and open industry standard used for communication between devices used for home automation. It uses the home’s powerline wiring for control and signaling, where the signal consists of short radio frequency pulses representing digital information. A radio based transport is also defined. X10 was developed by Pico Electronics of Glenrothes, Scotland in 1975, in order to control the devices and appliances remotely. It was the first domotic technology and still remains the most widely available.

The digital data consists of a command and an address sent from a controller to a device. More advanced controllers can also make equally advanced devices to respond with their status. This status may be as simple as “on” or “off” or the current dimming level, or even the temperature reading of other sensor. Devices are usually plugged into the wall where a lamp, radio, or other household appliance is plugged; however some built-in controllers are available now for ceiling fixture and wall switches.

INSTEON Standard

INSTEONis a home automation networking technology invented by Smart Labs Technology. INSTEON was developed primarily for basic lighting and appliance control, similar to the technology it was designed to replace X10.INSTEON is designed to enable devices to be networked together using the powerline and radio frequency (RF). All INSTEON devices are peers, which means that each device can receive, transmit, and repeat any message of the INSTEON protocol, without the need of a master controller or a complex routing software. Both power line and RF physical layers are used in the system.

INSTEON is an integrated dual-mesh network that combines the home’s existing electrical wiring with radio frequency protocol to control home electronic appliances, which work independently. This is intended to improve reliability by providing a backup system in case of wireless interference. Because this is a peer-to-peer network, the devices do not require network supervision, which reduces the need for controllers and routing tables.

In each transmission, a two bit ‘hops’ field that starts at 3 and is decremented each time, when a node in the network repeats a message. The repetition scheme is designed in such a way that all of the nodes repeat the messages in precise synchronism with one another, which makes the repetitions collide by design and strengthen one another in harmony.

Devices following INSTEON protocol are set up using a Plug and Tap method. Each device has a unique ID, which eliminates the need to set addresses or manipulate code wheels. Two INSTEON devices can be linked manually though itself. Even though a basic system can be installed without a controller or PC, such a device may be later added for advanced home management.

Universal Powerline Bus

Universal Powerline Bus (UPB)is an industry emerging standard for communication between devices used for domotics. It uses the home’s powerline wiring for control and signaling. UPB was developed by PCS Powerline Systems of Northridge, California and released in 1999. Based on the concept of the ubiquitous X10 standard, UPB has an improved transmission rate and higher reliability.

In this method, a series of precisely timed electrical pulses (called UPB Pulses) are superimposed on top of the normal AC power waveform (sine wave). Receiving UPB devices can easily detect and analyze these UPB Pulses and pull out the encoded digital information from them.

UPB Pulses are generated by charging a capacitor to a high voltage and then discharging that capacitor’s voltage into the powerline at a precise time. This quick discharging of the capacitor creates a large “spike” (or pulse) on the powerline that is easily detectable by receiving UPB devices wired large distances away on the same powerline.

HomePlug (IEEE P1901)

The HomePlug Powerline Alliance was founded in 2000 to promote and standardize networking over power lines. The installation of a powerline network is mainly plugging in the powerline device and connecting it to the device you want on the network. A typical installation starts with connecting a powerline adapter to a router with a Ethernet cable, and then plugging the powerline adapter into the nearest power outlet. To add other devices to the network simply plug in a powerline adapter to an outlet near the device to be connected, and connect that device to the adapter via Ethernet. The powerline adapter can also be plugged into a hub or switch when multiple devices (computers, printers, IP phones, etc.) need to be connected in a single room.

Due to problems with early (pre-HomePlug 1.0) powerline technology propagating signals effectively across electrical phases in a house, there is a perception that powerline is an unreliable solution which only works in newer houses, or over short distances. This problem was effectively solved with HomePlug 1.0, and succeeding specifications such as HomePlug AV have made further improvements in whole home coverage.

Among other things, HomePlug allows the use of Ethernet in bus topology, which is very desirable in some circumstances. This is achieved by use of advanced OFDM modulation that allows co-existence of several distinct data carriers in the same wire. The use of OFDM also allows turning off (masking) one or more of the sub-carriers which overlap previously allocated radio spectrum in a given geographic region

Since signals may travel outside the user’s residence or business and be eavesdropped on, HomePlug includes the ability to set an encryption password. The HomePlug specification requires that all devices are set to a default out-of-box password — although a common one. Users should change this password.

To simplify the process of configuring passwords on a HomePlug network, each device has a built-in master password, chosen at random by the manufacturer and hard-wired into the device, which is used only for setting the encryption passwords. A printed label on the device lists its master password.

The data at either end (Ethernet side) of the HomePlug link is not encrypted (unless an encrypted higher-layer protocol such as TLS or IPSec is being used), only the link between HomePlug devices is encrypted. The HomePlug AV standard uses 128-bit AES, while the older versions use the less secure DES.

Since HomePlug devices typically function as transparent network bridges, computers running any operating system can use them for network access. However, some manufacturers only supply the password-setup software in a Microsoft Windows version; in other words, enabling encryption requires a computer running Windows. Once the encryption password has been configured, Windows will no longer be needed, so in the case of a network where all computers run other systems a borrowed laptop could be used for initial setup purposes.


CEBus, short for Consumer Electronics Bus, also known as EIA-600, is a set of electrical standards and communication protocols for electronic devices to transmit commands and data. It is suitable for devices in households and offices to use, and might be useful for utility interface and light industrial applications.

he CEBus standard includes such things as spread spectrum modulation on the power line. Spread spectrum involves starting a modulation at one frequency, and altering the frequency during its cycle. The CEBus power line standard begins each burst at 100kHz, and increases linearly to 400kHz during a 100 microsecond duration. Both the bursts (referred to as “superior” state) and the absence of burst (referred to as the “inferior” state) create similar digits, so a pause in between is not necessary.

A digit 1 is created by an inferior or superior state that lasts 100 microseconds, and a digit 0 is created by an inferior or superior state that lasts 200 microseconds. Consequently, the transmission rate is variable, depending upon how many of the characters are one and how many are zero; the average rate is about 7,500 bits per second. A 400 microsecond burst is an end of frame indicator and also saves time. For example, if the 32-bit destination address field has some of its most significant bits zero, they need not be sent; the end of frame delimits the field and all receiving devices assume the untransmitted bits are zero.

CEBus transmissions are strings or packets of data that also vary in length, depending upon how much data is included. Some packets can be hundreds of bits in length. The minimum packet size is 64 bits, which at an average rate of 7,500 bits per second, will take about 1/117th of a second to be transmitted and received.

The CEBus standard involves device addresses that are set in hardware at the factory, and include 4 billion possibilities. The standard also offers a defined language of many object oriented controls which include commands such as volume up, fast forward, rewind, pause, skip, and temperature up or down 1 degree.


Z-Wave is a proprietary wireless communications protocol designed for home automation, specifically to remote control applications in residential and light commercial environments. The technology uses a low-power RF radio embedded or retrofitted into home electronics devices and systems, such as lighting, home access control, entertainment systems and household appliances.

The technology was developed by Zensys (who are now owned by Sigma Designs), and is supported by the Z-Wave Alliance, an international consortium of manufacturers that provide interoperable Z-Wave enabled devices.

Z-Wave is a low-power wireless technology designed specifically for remote control applications. Unlike Wi-Fi and other IEEE 802.11-based wireless LAN systems that are designed primarily for high-bandwidth data flow, the Z-Wave RF system operates in the sub Gigahertz frequency range and is optimized for low-overhead commands such as on-off (as in a light switch or an appliance) and raise-lower (as in a thermostat or volume control), with the ability to include device metadata in the communications.

Because Z-Wave operates apart from the crowded 2.4GHz frequency, it is largely impervious to interference from common household wireless electronics. This freedom from household interference allows for a standardized low-bandwidth control medium that can be reliable alongside common wireless devices.

As a result of its low power consumption and low cost of manufacture, Z-Wave is easily embedded in consumer electronics products, including battery operated devices such as remote controls, smoke alarms and security sensors. Z-Wave is currently supported by over 200 manufacturers worldwide and appears in a broad range of consumer products in the U.S. and Europe.

Z-Wave mesh networks can begin with a single controllable device and a controller. Additional devices can be added at any time, as can multiple controllers, including traditional hand-held controllers, key-fob controllers, wall-switch controllers and PC applications designed for management and control of a Z-Wave network.

A device must be “included” to the Z-Wave network before it can be controlled via Z-Wave. This process (also known as “pairing” and “adding”) is usually achieved by pressing a sequence of buttons on the controller and the device being added to the network. This sequence only needs to be performed once, after which the device is always recognized by the controller. Devices can be removed from the Z-Wave network by a similar process of button strokes.

This inclusion process is repeated for each device in the system. Because the controller is learning the signal strength between the devices during the inclusion process, the devices themselves should be in their intended final location before they are added to the system.


Ethernet is a family of frame-based computer networking technologies for local area networks (LANs). The name comes from the physical concept of the ether. It defines a number of wiring and signaling standards for the Physical Layer of the OSI networking model as well as a common addressing format and Media Access Control at the Data Link Layer.

Ethernet is standardized as IEEE 802.3. The combination of the twisted pair versions of Ethernet for connecting end systems to the network, along with the fiber optic versions for site backbones, is the most widespread wired LAN technology. It has been in use from around 1980 to the present, largely replacing competing LAN standards such as token ring, FDDI, and ARCNET.

Ethernet was originally based on the idea of computers communicating over a shared coaxial cable acting as a broadcast transmission medium. The methods used show some similarities to radio systems, although there are fundamental differences, such as the fact that it is much easier to detect collisions in a cable broadcast system than a radio broadcast. The common cable providing the communication channel was likened to the ether and it was from this reference that the name “Ethernet” was derived.

From this early and comparatively simple concept, Ethernet evolved into the complex networking technology that today underlies most LANs. The coaxial cable was replaced with point-to-point links connected by Ethernet hubs and/or switches to reduce installation costs, increase reliability, and enable point-to-point management and troubleshooting. Star LAN was the first step in the evolution of Ethernet from a coaxial cable bus to a hub-managed, twisted-pair network. The advent of twisted-pair wiring dramatically lowered installation costs relative to competing technologies, including the older Ethernet technologies.

Above the physical layer, Ethernet stations communicate by sending each other data packets, blocks of data that are individually sent and delivered. As with other IEEE 802 LANs, each Ethernet station is given a single 48-bit MAC address, which is used to specify both the destination and the source of each data packet. Network interface cards (NICs) or chips normally do not accept packets addressed to other Ethernet stations. Adapters generally come programmed with a globally unique address, but this can be overridden, either to avoid an address change when an adapter is replaced, or to use locally administered addresses.

Despite the significant changes in Ethernet from a thick coaxial cable bus running at 10 Mbit/s to point-to-point links running at 1 Gbit/s and beyond, all generations of Ethernet (excluding early experimental versions) share the same frame formats (and hence the same interface for higher layers), and can be readily interconnected.


Wi-Fi is a popular wireless networking technology that uses radio waves to provide wireless high-speed network connections. The Wi-Fi Alliance, the organization that owns the Wi-Fi (registered trademark) term specifically defines Wi-Fi as any “wireless local area network (WLAN) products that are based on the Institute of Electrical and Electronics Engineers’ (IEEE) 802.11 standards.”

Initially, Wi-Fi was used in place of only the 2.4GHz 802.11b standard, however the Wi-Fi Alliance has expanded the generic use of the Wi-Fi term to include any type of network or WLAN product based on any of the 802.11 standards, including 802.11b, 802.11a, dual-band, and so on, in an attempt to stop confusion about wireless LAN interoperability.

Wi-Fi works with no physical wired connection between sender and receiver by using radio frequency (RF) technology, a frequency within the electromagnetic spectrum associated with radio wave propagation. When an RF current is supplied to an antenna, an electromagnetic field is created that then is able to propagate through space. The cornerstone of any wireless network is an access point (AP). The primary job of an access point is to broadcast a wireless signalthat computers can detect and “tune” into. In order to connect to an access point and join a wireless network, computers and devices must be equipped with wireless network adapters. The intelligent sensor may be equipped with a Wi-Fi transmitter receiver to give information to the central console.

A wireless access point (WAP) connects a group of wireless devices to an adjacent wired LAN. An access point is similar to a network hub, relaying data between connected wireless devices in addition to a (usually) single connected wired device, most often an ethernet hub or switch, allowing wireless devices to communicate with other wired devices.

Wireless adapters allow devices to connect to a wireless network. These adapters connect to devices using various external or internal interconnects such as PCI, miniPCI, USB, ExpressCard, Cardbus and PC Card. Most new laptop computers are equipped with internal adapters. Internal cards are generally more difficult to install.

Wireless routers integrate a Wireless Access Point, ethernet switch, and internal Router firmware application that provide IP Routing, NAT, and DNS forwarding through an integrated WAN interface. A wireless router allows wired and wireless ethernet LAN devices to connect to a (usually) single WAN device such as cable modem or DSL modem. A wireless router allows all three devices, mainly the access point and router, to be configured through one central utility. This utility is usually an integrated web server that is accessible to wired and wireless LAN clients and often optionally to WAN clients.

Wireless network bridges connect a wired network to a wireless network. This is different from an access point in the sense that an access point connects wireless devices to a wired network at the data-link layer. Two wireless bridges may be used to connect two wired networks over a wireless link, useful in situations where a wired connection may be unavailable, such as between two separate homes.

Wireless range extenders or wireless repeaters can extend the range of an existing wireless network. Range extenders can be strategically placed to elongate a signal area or allow for the signal area to reach around barriers such as those created in L-shaped corridors. Wireless devices connected through repeaters will suffer from an increased latency for each hop. Additionally, a wireless device connected to any of the repeaters in the chain will have a throughput that is limited by the weakest link between the two nodes in the chain from which the connection originates to where the connection ends.

The table below shows the various domotic standards used and their specifications.


Transmission medium

Transmission speed

Maximum distance

to the device

Ethernet {IEEE 802.3}

Unshielded twisted pair

10 Mbit/s – 1 Gbit/s

100 m

Optical fiber

1 Gbit/s – 10 Gbit/s

2 km – 15 km


HomePlug {IEEE P1901}

Electrical wiring

14 Mbit/s – 200 Mbit/s

200 m

Universal Powerline Association

Electrical wiring

200 Mbit/s

200 m

ITU G.hn {G.9960}

Electrical wiring / Telephone line / Coaxial cable

up to 1 Gbit/s



Telephone line

10 Mbit/s

300 m

Wi-Fi {IEEE 802.11}

Radio frequency

11 Mbit/s – 248 Mbit/s

30 m – 100 m

FireWire {IEEE 1394}

Unshielded twisted pair / Optical fiber

400 Mbit/s – 3.2 Gbit/s

4.5 m – 70 m


Radio frequency

1 Mbit/s – 10 Mbit/s

10 m – 100 m



9600 bit/s – 4 Mbit/s

2 m


Twisted pair / Electrical wiring / Radio frequency / Infrared / Ethernet / Wi-Fi

1200 bit/s – 9600 bit/s

1000 m

LonWorks {ISO/IEC 14908}

Twisted pair / Electrical wiring / Radio frequency / Infrared / Coaxial / Optical fiber / IP tunneling

1.70 kbit/s-1.28 Mbit/s

1500 m – 2700 m


Electrical wiring / Radio frequency

1.2 kbit/s

1,000 m+ (Electrical wiring), 50 m+ (Wireless)


Electrical wiring

50 bit/s – 60 bit/s


European Installation Bus / KNX {ISO/IEC 14543-3}

Twisted pair / Electrical wiring / Radio frequency / Infrared / Ethernet

1200 bit/s – 9600 bit/s

300 m – 1000 m


Twisted pair / Electrical wiring

2.4 kbit/s – 48 kbit/s



Twisted pair

4800 bit/s

200 m – 1500 m

ZigBee / ZigBee Pro{

Radio frequency

20 kbit/s – 250 kbit/s

10 m – 1500 m


Radio frequency

9.6 kbit/s – 40 kbit/s

1 m – 75 m


Twisted pair

12 Mbit/s – 480 Mbit/s

5 m

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