WIRELESS SENSOR TECHNOLOGY

As we saw in earlier chapters, a WSN consists of a group of dispersed sensors (motes) that have the responsibility of covering a geographic area (the sensor field) in terms of some measured parameter (also known as the measurand); alternatively, a sensor supports a point-to-point link in which the ‘‘reader’’ end is attached to a wireline network (e.g., a stationary tag reader sensing a mobile tag). Sensor nodes have wireless communication capabilities and some logic for
signal processing, topology management (if and where applicable), and transmission handling (including digital encoding and possibly encryption and/or forward error correction). Figure depicts the progression of sensor technology over time during the past few years. WSNs that combine physical sensing of parameters such as temperature, light, or seismic events with computation and networking capabilities are expected to become ubiquitous in the future [3.3]. Successful development of low-cost robust miniaturized sensors and detection equipment (such as mass spectrometers and chromatographs) will be of benefit; design of such systems
is now being encouraged by U.S. research agencies (e.g., the National Science Foundation) [3.5]. Some sensor applications also support e-money purchases at point-of-sale locations such as from soft-drink machines, kiosks, gas stations, and checkout counters. At the design level a WSN sits at the confluence of research in disciplines such as database query processing, networking, algorithms, and distributed systems [3.3]; hence, a lot of thought and engineering go into the development of both WNs and WSNs. The basic functionality of a WN generally depends on the application, but the following requirements are typical [3.4]:

1. Determine the value of a parameter at a given location. For example, in an environment-oriented WSN, one might need to know the temperature, atmospheric pressure, amount of sunlight, and the relative humidity at a number of locations. This example shows that a given WN may be connected to different types of sensors, each with a different sampling rate and range of allowed values.

2. Detect the occurrence of events of interest and estimate the parameters of the events. For example, in a traffic-oriented WSN, one would like to detect a vehicle moving through an intersection and estimate the speed and direction of the vehicle.

3. Classify an object that has been detected. For example, is a vehicle in a traffic sensor network a car, a minivan, a light truck, a bus?

4. Track an object. For example, in a military WSN, track an enemy tank as it moves through the geographic area covered by the network.

Naturally, the data collected must be transmitted to the appropriate data-consumption entity in a timely fashion. In many cases there are real-time or near-real-time requirements; for example, the detection of an intruder should be communicated to the police in real time so that relevant action can be taken promptly.
Sensors are either passive or active devices. Passive sensors in single-element form include, among others, seismic-, acoustic-, strain-,
humidity-, and temperature-measuring devices. Passive sensors in array form include optical- (visible, infrared 1 mm, infrared 10 mm) and biochemical-measuring devices. Arrays are geometrically regular clusters of WNs (e.g., following some topographical grid arrangement). Passive sensors tend to be low-energy devices. Active sensors include radar and sonar; these tend to be high-energy systems. Sensing principles include, but are not limited to, mechanical, chemical, thermal, electrical, chromatographic, magnetic, biological, fluidic, optical, ultrasonic, and mass sensing. WNs may be exposed to hostile environments; the environment may include high temperatures, high vibration or noise levels, or corrosive chemicals. WNs may be incorporated in mobile robotic systems; they could also be integral to manufacturing systems. As discussed in Chapter 1, embedded sensing refers to the synergistic incorporation of microsensors in structures or environments; embedded sensing enables spatially and temporally dense monitoring of the system under consideration (e.g., an environment, a building, a battlefield). In biological systems, the sensors themselves must not affect the system or organism adversely [3.5]. The technology for sensing and control includes electric and magnetic field sensors; radio-wave frequency sensors; optical-, electrooptic-, and infrared sensors; radars; lasers; location and navigation sensors; seismic and pressure-wave sensors; environmental parameter sensors (e.g., wind, humidity, heat); and biochemical national security–oriented sensors. Typical sensor parameters (measurands) include:

1. Physical measurement. Examples include two-axis magnetometers; light and ultraviolet intensity (photo resistor); radiation levels, radio, and microwave; humidity, temperature (thermistor), atmospheric pressure, fog, and dust; sound and acoustics; two-axis accelerometers, shock wave, seismic, physical pressure, and motion; video and image (visible or infrared); and location (GPS) and locomotion measurements.

2. Chemical and biological measurements. Examples include the presence or concentration of a substance or agent at specified concentration levels (there are no less than 50 biological agents of interest [3.9]).

3. Event measurement. Examples include determination of the occurrence of human-made or natural events, including cyber-level events; tracking of internal and external events.
Small, low-cost, robust, reliable, and sensitive sensors are needed to enable the realization of practical and economical sensor networks. Although a large number measurands are of interest for WSN applications, commercially available sensors exist for many of these measurands; one prominent exception is that a wide range
of appropriate chemical sensors is not yet broadly available [3.8].
Sensor nodes come in a variety of hardware configurations: from nodes connected to a LAN and attached to permanent power sources, to nodes communicating via wireless multihop RF radio powered by small batteries [3.3]. The trend is toward very large scale integration (VLSI), integrated optoelectronics, and nanotechnology; in particular, work is under way in earnest in the biochemical arena. The goal of recent research and engineering is to build cubic millimeter (mm3)– scale advanced WNs and motes. As shown in Figure 3.1, motes developed in the early 2000s were on the order of a cubic inch (this is approximately 16,387 mm3). By 2007, researchers expect to have 1-mm3 nodes able to operate in a functional network (e.g., SpeckNet research [3.1]).

Hardware and Software

Related to WN design, the following functionality typically needs to be supported:
intrinsic node functionality; signal processing, including digital signal
processing (e.g., FFT/DCT), compression, forward error correction, and encryption; control and actuation; clustering and in-network computation; self-assembly; communication; routing and forwarding; and connectivity management. To support this functionality, the hardware components of a WN include the sensing and actuation unit (single element or array), the processing unit, the communication
unit, the power unit, and other application-dependent units. Figure 3.2 (which builds on Figure) shows hardware and software components of a typical sensing node.
As we noted in Chapter 1, the following are important sensor-node issues (refer to Table 1.1): sensor type, sensor power consumption, operating environment, computational and sensing capabilities, signal-processing capabilities, connectivity, and telemetry and control of remote devices. Clearly, the sensor node architecture, scope, and complexity depend on the application.
Sensors, particularly Smart Dust and COTS motes [3.2], have four basic hardware subsystems:
1. Power. An appropriate energy infrastructure or supply is necessary to support operation from a few hours to months or years (depending on the application).
2. Computational logic and storage. These are used to handle onboard data processing and manipulation, transient and short-term storage, encryption, forward

wireless sensor diagram

error correction (FEC), digital modulation, and digital transmission. WNs have computational requirements typically ranging from an 8-bit microcontroller to a 64-bit microprocessor. Storage requirements typically range from 0.01 to 100 gigabytes (GB).

3. Sensor transducer(s). The interface between the environment and the WN is the sensor. Basic environmental sensors include, but are not limited to, acceleration, humidity, light, magnetic flux, temperature, pressure, and sound.

4. Communication. WNs must have the ability to communicate either in C1WSN arrangements (mesh-based systems with multihop radio connectivity among or between WNs, utilizing dynamic routing in both the wireless and wireline portions of the network), and/or in C2WSN arrangements (point-to-point or multipoint-topoint
systems generally with single-hop radio connectivity to WNs, utilizing static routing over the wireless network with only one route from the WNs to the companion terrestrial or wireline forwarding node). Researchers have developed many protocols specifically for WSNs. Transmission range, transmission impairments, modulation techniques, routing, and network topologies are issues of interest. Distances range from a few meters to a few kilometers; lower-layer communication protocols tend to be of the IEEE 802.11/802.15/802.16 class,
although other methods have also been used. Throughput ranges from 10 to 256 kbps in most applications (some of the video-based application may require more bandwidth).

Sensors typically have five basic software subsystems:

1. Operating system (OS) microcode (also called middleware). This is the boardcommon microcode that is used by all high-level node-resident software modules to support various functions. As is generally the case, the purpose of an operating system is to shield the software from the machine-level functionality of the
microprocessor. It is desirable to have open-source operating systems designed specifically for WSNs; these OSs typically utilize an architecture that enables rapid implementation while minimizing code size. TinyOS is one such example of a commonly used OS.

2. Sensor drivers. These are the software modules that manage basic functions of the sensor transceivers; sensors may possibly be of the modular/plug-in type, and depending on the type and sophistication, the appropriate configuration and settings
must be uploaded into the sensor (drivers shield the application software from the machine-level functionality of the sensor or other peripheral).

3. Communication processors. This code manages the communication functions, including routing, packet buffering and forwarding, topology maintenance, medium access control (e.g., contention mechanisms, direct-sequence spread-spectrum mechanisms), encryption, and FEC, to list a few (e.g., see Figure 3.3).

4. Communication drivers (encoding and the physical layer). These software modules manage the minutia of the radio channel transmission link, including clocking and synchronization, signal encoding, bit recovery, bit counting, signal levels, and modulation.

5. Data processing mini-apps. These are numerical, data-processing, signalvalue storage and manipulations, or other basic applications that are supported at the node level for in-network processing.

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