REPORT ON THIN FILM TECHNOLOGY

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INTRODUCTION Recent technological improvements have made the deployment of small, inexpensive, low-power, distributed devices, which are capable of local processing and wireless communication, a reality. Such nodes are called as sensor nodes. Each sensor node [1] is capable of only a limited amount of processing. But when coordinated with the information from a large number of other nodes, they have the ability to measure a given physical environment in great detail. Thus, a sensor network can be described as a collection of sensor nodes which co-ordinate to perform some specific action. Unlike traditional networks, sensor networks depend on dense deployment and co-ordination to carry out their tasks. Wireless sensor networks have critical applications in the scientific, medical, commercial, and military domains. Wireless sensor networks are typically used in highly dynamic, and hostile environments with no human existence (unlike conventional data networks), and therefore,

they must be tolerant to the failure and loss of connectivity of individual nodes. The sensor nodes should be intelligent to recover from failures with minimum human involvement. Fig.1 Wireless sensor networks 2. WIRELESS SENSOR NETWORK ARCHITECTURE A wireless sensor network (WSN) is a network that is made of hundreds or thousands of sensor nodes which are densely deployed in an unattended environment with the capabilities of sensing, wireless communications and computations (i.e. collecting and disseminating environmental data). These spatially distributed autonomous devices cooperatively monitor physical and environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants, at different locations. Figure 2. Basic Architecture of Wireless Sensor Network. Each autonomic node in a sensor network is typically equipped with a radio transceiver or other wireless communication device, a processing unit which can be a small micro-controller, sensing unit, and an energy source, usually an alkaline battery. Sometimes, a mobilize is needed to move sensor node from current position and carry out the assigned tasks. Since the sensor may be mobile, the base station may require accurate location of the node which is done by location finding system. The size of a single sensor node can vary from shoebox-sized nodes down to devices of the size of grain of dust. 2.1 Data Collection versus Event Detection: In general wireless sensor networks can be categorized into one of the two types, data collection or event detection networks.

In many applications where data collection is the goal, the sensors may be required to collect data for short periods at set times of the day. In this case, most of the time the sensor node will be asleep thus conserving power. However, where a wireless sensor network is to be employed for event detection, such as detecting the ignition of a fire, it would be anticipated that the sensor nodes must remain awake thus consuming their precious limited power. Fig 3. The typical architecture of the sensor node 2.2 Components of sensor node:- The main components of a sensor node are a microcontroller, transceiver, external memory, power source and one or more sensors. • Controller The controller performs tasks, processes data and controls the functionality of other components in the sensor node. While the most common controller is a microcontroller,

other alternatives that can be used as a controller are: a general purpose desktop microprocessor, digital signal processors. • Transceiver Sensor nodes often make use of ISM (Industrial, Scientific, Medical) [2]bands i.e. 902-928MHz (915MHz band), 2.4-2.4835GHz (2.4GHz band), 5.735-5.825GHz (5.8 GHz band) which gives free radio spectrum allocation and global availability. The possible choices of wireless transmission technique are Radio frequency (RF), Optical communication (Laser) and Infrared. The functionality of both transmitter and receiver are combined into a single device known as transceivers. Transceivers often lack unique identifiers. The operational states are transmit, receive, idle, and sleep. • External memory It is used to store the data and program. • Power source Batteries, rechargeable and non-rechargeable, are the main source of power supply for sensor nodes. They are also classified according to electrochemical material used for the electrodes such as NiCd (nickel-cadmium), NiZn (nickel-zinc), Nimh (nickel-metal hydride), and lithium-ion. • Sensors Sensors are hardware devices that produce a measurable response to a change in a physical condition like temperature or pressure. Sensors measure physical data of the parameter to be monitored. The continual analog signal produced by the sensors is digitized by an analog-to-digital converter and sent to controllers for further processing.

Sensors are classified into three categories: passive, omni-directional sensors; passive, narrow-beam sensors; and active sensors. Passive sensors sense the data without actually manipulating the environment by active probing. They are self powered; that is, energy is needed only to amplify their analog signal. Active sensors actively probe the environment, for example, a sonar or radar sensor, and they require continuous energy from a power source. Narrow-beam sensors have a well-defined notion of direction of measurement, similar to a camera. Omni-directional sensors have no notion of direction involved in their measurements. Fig 4.

A general model of a smart sensor 3. TOOLS FOR DEVELOPING A WIRELESS SENSOR NETWORK A variety of hardware and tools are available for deploying and testing wireless sensor networks. Brief descriptions are provided hereafter. 3.1 Sensor Mote Hardware Requirements: Currently one of the most popular research platforms is the Mica2 sensor mote [3](sensor node which is available in market). It uses the TinyOS (TOS) Distributed Software Operating System, has a 325, 433 or 868/916 MHz multi-channel radio transceiver and an expansion connector that can be used for light, temperature, PH, barometric pressure, acceleration and magnetic sensor boards. Figure 5:Mica2 Sensor Mote Figure 6: Injection molded housing assembly for the Mica 2 3.2 Software Requirements: 1. TinyOS (TOS) 2. TOSSIM 3. TinyViz 4. Algorithms 1.) TinyOS The limited processing capabilities of the motes, precludes the use of standard operating systems.

The motes use TinyOS. TinyOS is a programming framework[4], developed at the University of California, Berkeley, for embedded systems and a set of components that enable building an application specific operating system into each application. The programming language capabilities for TinyOS are provided through a stylized version of C using a customized compiler called nesC. 2.) TOSSIM TOSSIM is a simulator for TinyOS networks, users can compile a TinyOS application into the TOSSIM framework where they can then debug, test, and analyze algorithms in a controlled and repeatable environment. 3.) TinyViz TinyViz is a graphical interface that can be used with TOSSIM. It can be attached to a running simulation and with the use of plug-ins can be used to visualize such things as network traffic. Users can write their own plug-ins for events they wish to visualize. In view of the potential expense of real-world trials, the development of a simulator to assess the feasibility of a wireless sensor network for this application would need to be carried out. It is anticipated that this could be undertaken as additional research. 4.)

Algorithms The algorithmic approach to modelling, simulating and analyzing WSNs differentiates itself from the protocol approach by the fact that the idealised mathematical models used are more general and easier to analyze. However, they are sometimes less realistic than the models used for protocol design, since an algorithmic approach often neglects timing issues, protocol overhead, the routing initiation phase and sometimes distributed implementation of the algorithms 4. DESIGN FACTORS IN WIRELESS SENSOR NETWORK Following are some of the basic design factors of wireless sensor network which serve as guidelines for development of protocols and algorithms for WSN communication architecture. 1. Fault Tolerance, Adaptability and Reliability: Sensor networks are required to operate through adapting to the environmental changes that sensors monitor.

The networks should be self-learning. Reliability is the ability to maintain the sensor network functionalities without any interruption due to sensor node failure. Sensor node may fail due to lack of energy, physical damage, communications problem, inactivity, or environmental interference. The network should be able to detect failure of a node and organize itself, reconfigure and recover from node failures without losing any information. 2. Power Consumption and Power management: One of the components of sensor nodes is the power source which can be a battery. The wireless sensor node being a microelectronic device, can only be equipped with a limited power source. Over the remote inaccessible place with less human control and existence, power sources play critical role in survival of sensor nodes. Power source should be intelligently divided over sensing, computation, and communications phases as per requirement. Sensors can be hibernated when inactive.

Lots of current researches are focusing on designing power-aware protocols and algorithms for wireless sensor networks. Recently, solar energy is also considered as an option for empowering remote sensor nodes which are exposed environment. 3. Network Efficiency and Data Aggregation: Flooding raw sensed data over the network can easily congest the network. Some critical applications like intruder detectors require urgent transmission and faster processing of data which may degrade performance and loose reliability due to congestion or latency in the network. Intelligent aggregation of sensed data and elimination of unwanted and redundant information and data compression can be a solution for efficient resource and energy utilization and congestion avoidance. Many algorithms like directed diffusion are proposed to facilitate data aggregation and dissemination within the context of WSNs. 4. Intelligent Routing: In many applications,

sensor nodes are moving nodes and can change place dynamically. Routing protocols must be adaptive to these changes and should be self-healing and self-configuring. The information should be persistent in spite of changes in network nodes. Low processing capacity of a node creates many challenges for routing packets throughout the neighbouring nodes intelligently. Some applications may require a faster communication and instant response. Routing algorithms should be intelligent to choose minimum hop and minimum distance paths for data transfer. 5. Management challenge – Managing the communication over heterogeneous networks is basic challenge in self-managed system because policies and communication protocols plan an important role in network communication. Also,

it is necessary to balance the level of detail the network is providing to the client against the rate at which energy is being consumed while gathering the data. Clearly, it is preferable to have the network automatically do this tuning, rather than requiring manual intervention. 5. SENSORS FOR DIFFERENT ENVIRONMENTS Sensor or Transducers:- A transducer [5] is a device that converts energy from one domain to another. In our application, it converts the quantity to be sensed into a useful signal that can be directly measured and processed. Since much signal conditioning (SC) and digital signal processing (DSP) is carried out by electronic circuits,

the outputs of transducers that are useful for sensor networks are generally voltages or currents. Sensory transduction may be carried out using physical principles, some of which we review here. Fig. 7: Sensory Transducer Mechanical Sensors include those that rely on direct physical contact. 1.) The Piezoresistive Effect converts an applied strain to a change in resistance that can be sensed using electronic circuits such as the Wheatstone Bridge. The relationship is , with R the resistance, e the strain, and S the gauge factor which depends on quantities such as the resistivity and the Poisson’ ratio of the material.

There may be a quadratic term in e for some materials. Metals and semiconductors exhibit piezoresistivity. The Piezoresistive effect in silicon is enhanced by doping with boron (p-type silicon can have a gauge factor up to 200). With semiconductor strain gauges, temperature compensation is important. 2.) Capacitive Sensors typically have one fixed plate and one movable plate. When a force is applied to the movable plate, the change in capacitance C is given as , with the resulting displacement,

A the area, and e the dielectric constant. Changes in capacitance can be detected using a variety of electric circuits and converted to a voltage or current change for further processing. Inductive sensors, which convert displacement to a change in inductance, are also often useful. 3.) Thermal Sensors are a family of sensors used to measure temperature or heat flux. ? Thermo-Mechanical Transduction is used for temperature sensing and regulation in homes and automobiles. On changes in temperature T, all materials exhibit (linear) thermal expansion of the form , with L the length and a the coefficient of linear expansion. One can fabricate a strip of two joined materials with different thermal expansions. Then, the radius of curvature of this thermal bimorph depends on the temperature change. Fig. 8: Thermal bimorph ?

Thermo resistive Effects are based on the fact that the resistance R changes with temperature T. For moderate changes, the relation is approximately given by for many metals by , with aR the temperature coefficient of resistance. The relationship for silicon is more complicated but is well understood. Hence, silicon is useful for detecting temperature changes. ?

Thermocouples are based on the thermoelectric Seebeck effect, whereby if a circuit consists of two different materials joined together at each end, with one junction hotter than the other, a current flows in the circuit. This generates a Seebeck voltage given approximately by with T1, T2 the temperatures at the two junctions. The coefficients depend on the properties of the two materials. Semiconductor thermocouples generally have higher sensitivities than do metal thermocouples. Thermocouples are inexpensive and reliable, and so are much used. Typical thermocouples have outputs on the order of 50 µV/oC. 4.) Optical Transducers convert light to various quantities that can be detected. These are based on one of several mechanisms. In the photoelectric effect one electron is emitted at the negative end of a pair of charged plates for each light photon of sufficient energy.

This causes a current to flow. In photoconductive sensors, photons generate carriers that lower the resistance of the material. In junction-based photosensors, photons generate electron-hole pairs in a semiconductor junction that causes current flow. This is often misnamed the photovoltaic effect. Measurements for Wireless Sensor Networks Measurand Transduction Principle PhysicalProperties Pressure Piezoresistive, capacitive Temperature Thermistor, thermo-mechanical, thermocouple Humidity Resistive, capacitive Flow Pressure change, thermistor Motion Properties Position E-mag, GPS, contact sensor Velocity Doppler,

Hall effect, optoelectronic Angular velocity Optical encoder Acceleration Piezoresistive, piezoelectric, optical fiber Contact Properties Strain Piezoresistive Force Piezoelectric, piezoresistive Torque Piezoresistive, optoelectronic Slip Dual torque Vibration Piezoresistive, piezoelectric, optical fibre, Sound, ultrasound Presence Tactile/contact Contact switch, capacitive Proximity Hall effect, capacitive, magnetic, seismic, acoustic, RF Distance/range E-mag (sonar, radar, lidar), magnetic, tunneling Motion E-mag, IR, acoustic, seismic (vibration) Biochemical Biochemical agents Biochemical transduction Identification Personal features Vision Personal ID Fingerprints, retinal scan, voice, heat plume, vision motion analysis Table 1: Table Shows Physical Principles Used To Measure Various Quantities 6. APPLICATION The applications for WSNs are varied, typically involving some kind of monitoring, tracking, or controlling. Specific applications include habitat monitoring, object tracking, fire detection, land slide detection and traffic monitoring • Area monitoring In area monitoring, the WSN is deployed over a region where some phenomenon is to be monitored.

When the sensors detect the event being monitored (heat, pressure, sound, light, electro-magnetic field, vibration, etc.), the event is reported to one of the base stations, which then takes appropriate action (e.g., send a message on the internet or to a satellite). • Greenhouse monitoring Wireless sensor networks are also used to control the temperature and humidity levels inside commercial greenhouses. When the temperature and humidity drops below specific levels, the greenhouse manager must be notified via e-mail or cell phone text message, or host systems can trigger misting systems, open vents, turn on fans, or control a wide variety of system responses. • Landslide detection A landslide detection system, makes use of a wireless sensor network to detect the slight movements of soil and changes in various parameters that may occur before or during a landslide. And through the data gathered it may be possible to know the occurrence of landslides long before it actually happens. • Water/Wastewater monitoring There are many opportunities for using wireless sensor networks within the water/wastewater industries.

Facilities not wired for power or data transmission can be monitored using industrial wireless I/O devices and sensors powered using solar panels or battery packs. • Agriculture Using wireless sensor networks within the agricultural industry is increasingly common. Gravity fed water systems can be monitored using pressure transmitters to monitor water tank levels, pumps can be controlled using wireless I/O devices, and water use can be measured and wirelessly transmitted back to a central control center for billing. Irrigation automation enables more efficient water use and reduces waste. • Building Monitoring Sensors can also be used in large buildings or factories monitoring climate changes.

Thermostats and temperature sensor nodes are deployed all over the building’s area. In addition, sensors could be used to monitor vibration that could damage the structure of a building. • Military Monitoring: Military uses sensor networks for battlefield surveillance; sensors could monitor vehicular traffic, track the position of the enemy.