BORDER SECURITY USING WIRELESS INTEGRATED NETWORK SENSORS (WINS)
#1

Wireless Integrated Network Sensors (WINS) now provide a new monitoring and control capability for monitoring the borders of the country. Using this concept we can easily identify a stranger or some terrorists entering the border.

The border area is divided into number of nodes. Each node is in contact with each other and with the main node. The noise produced by the foot-steps of the stranger are collected using the sensor. This sensed signal is then converted into power spectral density and the compared with reference value of our convenience. Accordingly the compared value is processed using a microprocessor, which sends appropriate signals to the main node. Thus the stranger is identified at the main node.

A series of interface, signal processing, and communication systems have been implemented in micro power CMOS circuits. A micro power spectrum analyzer has been developed to enable low power operation of the entire WINS system.
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#2
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Wireless Integrated Network Sensors (WINS) provide distributed network and Internet access to sensors, controls, and processors that are deeply embedded in equipment, facilities, and the environment. The Wireless Integrated Network Sensors (WINS) network is a new monitoring and control capability for applications intransportation, manufacturing, health care, environmental monitoring, and safety and security,border security. Wireless Integrated Network Sensors WINS networks provide sensing, local control, and embedded intelligent systems in structures, materials, and environments Wireless Integrated Network Sensors combine microsensor technology, low power signal processing, low power computation, and low power, low cost wireless networking capability in a compact system..

and read
http://reference.kfupm.edu.sa/content/w/...w_6053.pdf
http://seminarsprojects.in/attachment.php?aid=736
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#3
[attachment=1663]
[attachment=1664]
[attachment=1665]

ABSTRACT
Wireless Integrated Network Sensors (WINS) now provide a new monitoring and control capability for monitoring the borders of the country. Using this concept we can easily identify a stranger or some terrorists entering the border. The border area is divided into number of nodes. Each node is in contact with each other and with the main node. The noise produced by the foot-steps of the stranger are collected using the sensor. This sensed signal is then converted into power spectral density and the compared with reference value of our convenience. Accordingly the compared value is processed using a microprocessor, which sends appropriate signals to the main node. Thus the stranger is identified at the main node. A series of interface, signal processing, and communication systems have been implemented in micro power CMOS circuits. A micro power spectrum analyzer has been developed to enable low power operation of the entire WINS system.
Thus WINS require a Microwatt of power. But it is very cheaper when compared to other security systems such as RADAR under use. It is even used for short distance communication less than 1 Km. It produces a less amount of delay. Hence it is reasonably faster. On a global scale, WINS will permit monitoring of land, water, and air resources for environmental monitoring. On a national scale, transportation systems, and borders will be monitored for efficiency, safety, and security.
BORDER SECURITY USING
WIRELESS INTEGRATED NETWORK SENSORS (WINS)
1. INTRODUCTION
Wireless Integrated Network Sensors (WINS) combine sensing, signal processing, decision capability, and wireless networking capability in a compact, low power system. Compact geometry and low cost allows WINS to be embedded and distributed at a small fraction of the cost of conventional wireline sensor and actuator systems. On a local, wide-area scale, battlefield situational awareness will provide personnel health monitoring and enhance security and efficiency. Also, on a metropolitan scale, new traffic, security, emergency, and disaster recovery services will be enabled by WINS. On a local, enterprise scale, WINS will create a manufacturing information service for cost and quality control. The opportunities for WINS depend on the development of scalable, low cost, sensor network architecture. This requires that sensor information be conveyed to the user at low bit rate with low power transceivers. Continuous sensor signal processing must be provided to enable constant monitoring of events in an environment. Distributed signal processing and decision making enable events to be identified at the remote sensor. Thus, information in the form of decisions is conveyed in short message packets. Future applications of distributed embedded processors and sensors will require massive numbers of devices. In this paper we have concentrated in the most important application, Border Security.
2. WINS SYSTEM ARCHITECTURE
Conventional wireless networks are supported by complex protocols that are developed for voice and data transmission for handhelds and mobile terminals. These networks are also developed to support communication over long range (up to 1km or more) with page link bit rate over 100kbps. In contrast to conventional wireless networks, the WINS network must support large numbers of sensors in a local area with short range and low average bit rate communication (less than 1kbps). The network design must consider the requirement to service dense sensor distributions with an emphasis on recovering environment information. Multihop communication yields large power and scalability advantages for WINS networks. Multihop communication, therefore, provides an immediate advance in capability for the WINS narrow Bandwidth devices. However, WINS Multihop Communication networks permit large power reduction and the implementation of dense node distribution. The multihop communication has been shown in the figure 2. The figure 1 represents the general structure of the wireless integrated network sensors (WINS) arrangement.
Continuous operation low duty cycle
Figure 1. The wireless integrated network sensor (WINS) architecture.
3. WINS NODE ARCHITECTURE
The WINS node architecture (Figure 1) is developed to enable continuous sensing, event detection, and event identification at low power. Since the event detection process must occur continuously, the sensor, data converter, data buffer, and spectrum analyzer must all operate at micro power levels. In the event that an event is detected, the spectrum analyzer output may trigger the microcontroller. The microcontroller may then issue commands for additional signal processing operations for identification of the event signal. Protocols for node operation then determine whether a remote user or neighboring WINS node should be alerted. The WINS node then supplies an attribute of the identified event, for example, the address of the event in an event look-up-table stored in all network nodes. Total average system supply currents must be less than 30A. Low power, reliable, and efficient network operation is obtained with intelligent sensor nodes that include sensor signal processing, control, and a wireless network interface. Distributed network sensor devices must continuously monitor multiple sensor systems, process sensor signals, and adapt to changing environments and user requirements, while completing decisions on measured signals.
Figure 2. WINS nodes (shown as disks)
For the particular applications of military security, the WINS sensor systems must operate at low power, sampling at low frequency and with environmental background limited sensitivity. The micro power interface circuits must sample at dc or low frequency where 1/f noise in these CMOS interfaces is large. The micropower signal processing system must be implemented at low power and with limited word length. In particular, WINS applications are generally tolerant to latency. The WINS node event recognition may be delayed by 10 “ 100 msec, or longer.
4. WINS MICRO SENSORS
Source signals (seismic, infrared, acoustic and others) all decay in amplitude rapidly with radial distance from the source. To maximize detection range, sensor sensitivity must be optimized. In addition, due to the fundamental limits of background noise, a maximum detection range exists for any sensor. Thus, it is critical to obtain the greatest sensitivity and to develop compact sensors that may be widely distributed. Clearly, microelectromechanical systems (MEMS) technology provides an ideal path for implementation of these highly distributed systems. The sensor-substrate Sensorstrate is then a platform for support of interface, signal processing, and communication circuits. Examples of WINS Micro Seismometer and infrared detector devices are shown in Figure 3. The detector shown is the thermal detector. It just captures the harmonic signals produced by the foot-steps of the stranger entering the border. These signals are then converted into their PSD values and are then compared with the reference values set by the user.
Figure 3. Thermal Infrared Detector
5. ROUTING BETWEEN NODES
The sensed signals are then routed to the major node. This routing is done based on the shortest distance. That is the distance between the nodes is not considered, but the traffic between the nodes is considered. This has been depicted in the figure 4. In the figure, the distances between the nodes and the traffic between the nodes has been clearly shown. For example, if we want to route the signal from the node 2 to node 4, the shortest distance route will be from node 2 via node 3 to node 4. But the traffic through this path is higher than the path node 2 to node 4. Whereas this path is longer in distance.
Figure 4. Nodal distance and Traffic
6. SHORTEST DISTANCE ALGORITHM
In this process we find mean packet delay, if the capacity and average flow are known. From the mean delays on all the lines, we calculate a flow-weighted average to get mean packet delay for the whole subnet. The weights on the arcs in the figure 5 give capacities in each direction measured in kbps.
Figure 5. Subnet with line capacities Figure 6.s Routing Matrix
In fig 6 the routes and the number of packets/sec sent from source to destination are shown. For example, the E-B traffic gives 2 packets/sec to the EF line and also 2 packets/sec to the FB line. The mean delay in each line is calculated using the formula
Ti =1/(µc-)
Ti = Time delay in sec
C = Capacity of the path in Bps
µ = Mean packet size in bits
= Mean flow in packets/sec.
¬¬
The mean delay time for the entire subnet is derived from weighted sum of all the lines. There are different flows to get new average delay. But we find the path, which has the smallest mean delay-using program. Then we calculate the Waiting factor for each path. The path, which has low waiting factor, is the shortest path. The waiting factor is calculated using
W = i /
i = Mean packet flow in path
= Mean packet flow in subnet
The tabular column listed below gives waiting factor for each path.
Figure 5. WINS Comparator response
7. WINS DIGITAL SIGNAL PROCESSING
If a stranger enters the border, his foot-steps will generate harmonic signals. It can be detected as a characteristic feature in a signal power spectrum. Thus, a spectrum analyzer must be implemented in the WINS digital signal processing system. The spectrum analyzer resolves the WINS input data into a low-resolution power spectrum. Power spectral density (PSD) in each frequency bins is computed with adjustable band location and width. Bandwidth and position for each power spectrum bin is matched to the specific detection problem. The WINS spectrum analyzer must operate at W power level. So the complete WINS system, containing controller and wireless network interface components, achieves low power operation by maintaining only the micropower components in continuous operation. The WINS spectrum analyzer system, shown in Figure 7, contains a set of parallel filters.
Figure 7. WINS micropower spectrum analyzer architecture.
8. PSD COMPARISION
Each filter is assigned a coefficient set for PSD computation. Finally, PSD values are compared with background reference values In the event that the measured PSD spectrum values exceed that of the background reference values, the operation of a microcontroller is triggered. Thus, only if an event appears, the micro controller operates. Buffered data is stored during continuous computation of the PSD spectrum. If an event is detected, the input data time series, including that acquired prior to the event, are available to the micro controller. The micro controller sends a HIGH signal, if the difference is high. It sends a LOW signal, if the difference is low. For a reference value of 25db, the comparison of the DFT signals is shown in the figure 8.
Figure 8. Comparator plot
9. WINS MICROPOWER EMBEDDED RADIO
WINS systems present novel requirements for low cost, low power, short range, and low bit rate RF communication. Simulation and experimental verification in the field indicate that the embedded radio network must include spread spectrum signaling, channel coding, and time division multiple access (TDMA) network protocols. The operating bands for the embedded radio are most conveniently the unlicensed bands at 902-928 MHz and near 2.4 GHz. These bands provide a compromise between the power cost associated with high frequency operation and the penalty in antenna gain reduction with decreasing frequency for compact antennas. The prototype, operational, WINS networks are implemented with a self-assembling, multihop TDMA network protocol.
The WINS embedded radio development is directed to CMOS circuit technology to permit low cost fabrication along with the additional WINS components. In addition, WINS embedded radio design must address the peak current limitation of typical battery sources, of 1mA. It is critical, therefore, to develop the methods for design of micropower CMOS active elements. For LC oscillator phase noise power, S, at frequency offset of away from the carrier at frequency with an input noise power, Snoise and LC tank quality factor, Q, phase noise power is:
Now, phase noise power, Snoise, at the transistor input, is dominated by 1/f noise. Input referred thermal noise, in addition, increases with decreasing drain current and power dissipation due to the resulting decrease in transistor transconductance. The tunability of micropower CMOS systems has been tested by implementation of several VCO systems to be discussed below. The embedded radio system requires narrow band operation and must exploit high Q value components.
10. CONCLUSION
A series of interface, signal processing, and communication systems have been implemented in micropower CMOS circuits. A micropower spectrum analyzer has been developed to enable low power operation of the entire WINS system. Thus WINS require a Microwatt of power. But it is very cheaper when compared to other security systems such as RADAR under use. It is even used for short distance communication less than 1 Km. It produces a less amount of delay. Hence it is reasonably faster. On a global scale, WINS will permit monitoring of land, water, and air resources for environmental monitoring. On a national scale, transportation systems, and borders will be monitored for efficiency, safety, and security.
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#4
plz provide me with some more matter regarding border security using wins and is this technology is in use currently??
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#5
plz send me the complete report
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#6
any registered user can download the report from attachment http://studentbank.in/report-border-secu...nsors-wins
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#7
Can u please help me by sending complete details of each module....like circuit diagrams and experimental data so on....im interested in doing this project for my final year b.tech...thanx in advance....

tagore.chandan@ gmail.com

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#8
go through the following thread please..

http://studentbank.in/report-border-secu...rk-sensors
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#9
please send the information and ppt regarding this.
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#10
please visit the previous page for ppt and reports on this topic.
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#11
Thanks 4 ur reportSmileplz send ppt and complete report on border security using wireless integrated network sensors..........
thanks 4 ur report. .pls send d ppt nd complete details on border security using wireless integrated network sensors(WINS)..
pls send d ppt tday. .
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#12
presented by:
M. Sai Anil Kumar
B. V. Vinod K Reddy

[attachment=9287]
Border Security Using W.I.N.S
Introduction:

 Wireless Integrated Network Sensors (WINS) has
a. Sensing
b. Signal Processing
c. Decision Capability
d. Wireless Networking Capability
W.I.N.S. Architecture
Wireless Networks

 Supported by Complex Protocols.
 Long Range
 Bit Rate of 100 kbps
W.I.N.S. Network
 Support Number of Sensors.
 Short Range
 Bit Rate less than 1 kbps
Node Architecture
 Node Architecture must enable
 Continuous Sensing
 Event Detection
 Event Identification
 At Low Cost
W.I.N.S. Micro Sensors
 Source Signals decay in Amplitude.
 Maximize Range à Optimized Sensitivity
 Critical to Develop Sensors.
 M.E.M.S. Technology is Ideal.
 Sensor Substrate is useful in processing and communication.
Routing Between Nodes:
 Routing is based on Shortest distance.
 Traffic between nodes is considered.
D.S.P. In W.I.N.S.
 Spectrum Analyzer is used.
 It resolves input as Low Resolution Power Spectrum.
P.S.D. Comparison:
 P.S.D. values are compared with reference values.
 If Event occurs, levels changes and Micro Controller Triggers.
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#13
Presented By:
POOJA.V.VERNEKAR

[attachment=10898]
ABSTRACT
Wireless Integrated Network Sensors (WINS) now provide a new monitoring and control capability for monitoring the borders of the country. Using this concept we can easily identify a stranger or some terrorists entering the border. The border area is divided into number of nodes. Each node is in contact with each other and with the main node. The noise produced by the foot-steps of the stranger is collected using the sensor. This sensed signal is then converted into power spectral density and the compared with reference value of our convenience. Accordingly the compared value is processed using a microprocessor, which sends appropriate signals to the main node. Thus the stranger is identified at the main node. A series of interface, signal processing, and communication systems have been implemented in micro power CMOS circuits. A micro power spectrum analyzer has been developed to enable low power operation of the entire WINS system.
Thus WINS require a Microwatt of power. But it is very cheaper when compared to other security systems such as RADAR under use. It is even used for short distance communication less than 1 Km. It produces a less amount of delay. Hence it is reasonably faster. On a global scale, WINS will permit monitoring of land, water, and air resources for environmental monitoring. On a national scale, transportation systems, and borders will be monitored for efficiency, safety, and security.
BORDER SECURITY USING
WIRELESS INTEGRATED NETWORK SENSORS (WINS)
1. INTRODUCTION

Wireless Integrated Network Sensors (WINS) combine sensing, signal processing, decision capability, and wireless networking capability in a compact, low power system. Compact geometry and low cost allows WINS to be embedded and distributed at a small fraction of the cost of conventional wireline sensor and actuator systems. On a local, wide-area scale, battlefield situational awareness will provide personnel health monitoring and enhance security and efficiency. Also, on a metropolitan scale, new traffic, security, emergency, and disaster recovery services will be enabled by WINS. On a local, enterprise scale, WINS will create a manufacturing information service for cost and quality control. The opportunities for WINS depend on the development of scalable, low cost, sensor network architecture. This requires that sensor information be conveyed to the user at low bit rate with low power transceivers. Continuous sensor signal processing must be provided to enable constant monitoring of events in an environment. Distributed signal processing and decision making enable events to be identified at the remote sensor. Thus, information in the form of decisions is conveyed in short message packets. Future applications of distributed embedded processors and sensors will require massive numbers of devices. In this paper we have concentrated in the most important application, Border Security.
2. WINS SYSTEM ARCHITECTURE
Conventional wireless networks are supported by complex protocols that are developed for voice and data transmission for handhelds and mobile terminals. These networks are also developed to support communication over long range (up to 1km or more) with page link bit rate over 100kbps. In contrast to conventional wireless networks, the WINS network must support large numbers of sensors in a local area with short range and low average bit rate communication (less than 1kbps). The network design must consider the requirement to service dense sensor distributions with an emphasis on recovering environment information. Multihop communication yields large power and scalability advantages for WINS networks. Multihop communication, therefore, provides an immediate advance in capability for the WINS narrow Bandwidth devices. However, WINS Multihop Communication networks permit large power reduction and the implementation of dense node distribution. The multihop communication has been shown in the figure 2. The figure 1 represents the general structure of the wireless integrated network sensors (WINS) arrangement.
3. WINS NODE ARCHITECTURE
The WINS node architecture (Figure 1) is developed to enable continuous sensing, event detection, and event identification at low power. Since the event detection process must occur continuously, the sensor, data converter, data buffer, and spectrum analyzer must all operate at micro power levels. In the event that an event is detected, the spectrum analyzer output may trigger the microcontroller. The microcontroller may then issue commands for additional signal processing operations for identification of the event signal. Protocols for node operation then determine whether a remote user or neighboring WINS node should be alerted. The WINS node then supplies an attribute of the identified event, for example, the address of the event in an event look-up-table stored in all network nodes. Total average system supply currents must be less than 30A. Low power, reliable, and efficient network operation is obtained with intelligent sensor nodes that include sensor signal processing, control, and a wireless network interface. Distributed network sensor devices must continuously monitor multiple sensor systems, process sensor signals, and adapt to changing environments and user requirements, while completing decisions on measured signals.
For the particular applications of military security, the WINS sensor systems must operate at low power, sampling at low frequency and with environmental background limited sensitivity. The micro power interface circuits must sample at dc or low frequency where “1/f” noise in these CMOS interfaces is large. The micropower signal processing system must be implemented at low power and with limited word length.The WINS node event recognition may be delayed by 10 – 100 msec, or longer.
4. ROUTING BETWEEN NODES
The sensed signals are then routed to the major node. This routing is done based on the shortest distance. That is the distance between the nodes is not considered, but the traffic between the nodes is considered.
5. WINS DIGITAL SIGNAL PROCESSING
If a stranger enters the border, his foot-steps will generate harmonic signals. It can be detected as a characteristic feature in a signal power spectrum. Thus, a spectrum analyzer must be implemented in the WINS digital signal processing system. The spectrum analyzer resolves the WINS input data into a low-resolution power spectrum. Power spectral density (PSD) in each frequency “bins” is computed with adjustable band location and width. Bandwidth and position for each power spectrum bin is matched to the specific detection problem. The WINS spectrum analyzer must operate at W power level. So the complete WINS system, containing controller and wireless network interface components, achieves low power operation by maintaining only the micropower components in continuous operation. The WINS spectrum analyzer system, shown in Figure 7, contains a set of parallel filters.
6. PSD COMPARISION
Each filter is assigned a coefficient set for PSD computation. Finally, PSD values are compared with background reference values In the event that the measured PSD spectrum values exceed that of the background reference values, the operation of a microcontroller is triggered. Thus, only if an event appears, the micro controller operates. Buffered data is stored during continuous computation of the PSD spectrum.
CONCLUSION
A series of interface, signal processing, and communication systems have been implemented in micropower CMOS circuits. A micropower spectrum analyzer has been developed to enable low power operation of the entire WINS system. Thus WINS require a Microwatt of power. But it is very cheaper when compared to other security systems such as RADAR under use. It is even used for short distance communication less than 1 Km. It produces a less amount of delay. Hence it is reasonably faster. On a global scale, WINS will permit monitoring of land, water, and air resources for environmental monitoring. On a national scale, transportation systems, and borders will be monitored for efficiency, safety, and security.
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#14
can u send me the pdf formate of boarder security of wireless integrated network sensor(wins)
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#15
i want pdf of BORDER SECURITY USING WIRELESS INTEGRATED NETWORK SENSORS (WINS
)by tommorrow plz send it to my mail by tommorrow morning
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#16
Presented by;
Vinay kumar

[attachment=11110]
Border security using Wireless Integrated Network Sensors(WINS)
INTRODUCTION
WIRE LESS INTEGRATED NETWORK SENSOR(WINS)

• WINS provide a new monitoring and control capability for monitoring the Border of the country.
• WINS require a microwatt of power so it is very cheaper than other security system such as Radar and produce less amount of delay.
• It produce a less amount delay to detect the target.
• It is resonably faster.
• On global scale wins will permit monitoring of land ,water and air resources for environment monitoring.
DEVELOPMENT OF WINS
• WINS Initiated in 1993 under Defence advance research project agency(DARPA)in US.
• LWIM (Low power wireless integrated microsensor)program began in 1995 for further development os WINS sponsored by DARPA.
• In 1998, WINS NG introduced for wide varity of application.
• the LWIM project à multihop, self-assembled, wireless network
algorithms for operating at micropower levels
• A general picture
• Distributed sensor at Border
Block diagram of WINS
Nodes connection of WINS

REMBASS
• Remotely monitored battlefield sensor system(REMBASS)
• Use now a day in unattended ground sensor(UGS)
• These sensor used seismic-acoustic energy,infrared energy and magnetic field to detect enemy activity.
Physical Principles
• When are distributed sensors better?
A. Propagation laws for sensing
All signals decay with distance
e.g. electromagnetic waves in free space (~ 1/d2)
in other media (absorption, scattering, dispersion)
• Sensor board
• WINS characteristics & application
Characteristics:
• Support large numbers of sensor.
• Dense sensor distributions .
• These sensor are also developed to support short distance RF communication
• Internet access to sensors, controls and processor
• Applications: Industries, transportation, and safety & security.
• Design consideration
Reliability
• Energy :There are four way in which node consume energy
1. Sensing
2. Computation
3. Storing
4. Communicating
• Sensing:Choosing right sensor for thr job can improve the system performance.
Packaging
• The sensor must be design to minimize the liklihood of environment effect of wind, rain,snow etc.
• The enclosure is manufacture from clear acrylic material.
• Unanticipated faulty behavior
• We experienced several failure as a result of undetectable, incorrectly download program and depeleted energy level etc.
• For example node will detect false event when sensor board is overheated.
Conclusion
• Densely distributed sensor networks.
• Application specific networking architectures
• Development platforms are now available .
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#17
Submitted By
SUMEET SHROFF

[attachment=12188]
INTRODUCTION
 WIRELESS INTEGRATED NETWORK SENSOR(WINS).
 WINS PROVIDES A NEW MONITERING AND CONTROL CAPABILITY FOR MONITERING THE BORDER.
 WINS REQUIRE A MICROWATT OF POWER SO IT IS VERY CHEAPER THAN OTHER SECURITY SYSTEM SUCH AS RADAR.
 IT PRODUCES A LESS AMOUNT OF DELAY TO DETECT THE TARGET.
 IT IS REASONABLY FASTER.
 ON GLOBAL SCALE WINS WILL PERMIT MONITORING OF LAND,WATER AND AIR RESOURCES FOR ENVIRONMENT MONITORING.
DEVELOPMENT OF WINS
 WINS INITIATED IN 1993 UNDER DEFENCE ADVANCE RESEARCH PROJECT AGENCY(DARPA) IN US.
 LWIM (LOW POWER INTEGRATED MICROSENSOR) PROGRAM BEGAN IN 1995 FOR FURTHER DEVELOPMENT OF WINS BY DARPA.
 IN 1998,WINS INTODUCED FOR VARIETY OF APPLICATION.
WINS CHARACTERSICS
 SUPPORTS A LARGE NUMBER OF SENSORS.
 DENSE SENSOR DISTRIBUTION.
 SUPPORTS SHORT DISTANCE RF COMMUNICATION.
 INTERNET ACCESS TO SENSORS, CONTROLS AND PROCESSORS.
APPLICATION
 INDUSTRIES.
 TRANSPORTATION.
 SAFETY AND SECURITY.
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#18
Submitted by
Surbhi sinha

[attachment=13044]
Border Security Using Wireless Integrated Network Sensor
(WINS)
ABSTRACT

Wireless Integrated Network Sensor now provide a new monitoring and control capability for transportation, manufacturing, health care, environmental monitoring and safety and security. WINS combine sensing, signal processing, decision capability in a compact, low power system. A very important benefit of continuing advances in CMOS IC technology is the ability to construct a wide variety of micro electrical-mechanical systems (MEMS) including sensors and RF components. These building blocks enable the fabrication of complete systems in a low cost module, which include sensing, signal processing, and wireless communications. Together with innovative and focused network design techniques that will make possible simple deployment and sustained low power operation, the small size and cost can be enabling for a very large number of law enforcement and security applications, including remote reconnaissance and security zones ranging from persons to borders. We outline how the application can be exploited in the network design to enable sustained low-power operation. In particular, extensive information processing at nodes, hierarchical decision making, and energy conserving routing and network topology management methods will be employed in the networks under development.
Keywords: wireless, sensors, networks
1. INTRODUCTION
Wireless Integrated Network Sensors (WINS) combine sensing, signal processing, decision capability, and wireless networking capability in a compact, low power system. Compact geometry and low cost allows WINS to be embedded and distributed at a small fraction of the cost of conventional wireline sensor and actuator systems. Wireless integrated network sensor (WINS) nodes can include MEMS components such as sensors, RF components, and actuators, and CMOS building blocks such as interface pads, data fusion circuitry, specialized and general purpose signal processing engines, and microcontrollers. The more complicated but low duty cycle applications would for example be run in the general purpose processors, while frequently invoked operations would be run on specialized circuits to save power. The node may be powered by batteries, photocells, or power mains. It might alternatively scavenge power from vibrations, acoustic or millimeter wave energy through use of MEMS resonators or piezoelectric. On a local, wide-area scale, battlefield situational awareness will provide personnel health monitoring and enhance security and efficiency. Also, on a metropolitan scale, new traffic, security, emergency, and disaster recovery services will be enabled by WINS. On a local, enterprise scale, WINS will create a manufacturing information service for cost and quality control. The opportunities for WINS depend on the development of scalable, low cost, sensor network architecture. This requires that sensor information be conveyed to the user at low bit rate with low power transceivers. Continuous sensor signal processing must be provided to enable constant monitoring of events in an environment. Distributed signal processing and decision making enable events to be identified at the remote sensor. Thus, information in the form of decisions is conveyed in short message packets. Future applications of distributed embedded processors and sensors will require massive numbers of devices. In this paper we have concentrated in the most important application, Border Security. Thus WINS require a Microwatt of power. But it is very cheaper when compared to other security systems such as RADAR under use. It is even used for short distance communication less than 1 Km. It produces a less amount of delay. Hence it is reasonably faster.
2. Physical Principle
2.1Propagation laws for sensing.

All signals decay with distance as a wavefront expands. For example, in free space, electromagnetic waves decay in intensity as the square of the distance; in other media, they are subject to absorption and scattering effects that can induce even steeper declines in intensity with distance. Many media are also dispersive (such as via multipath or low-pass filtering effects), so a distant sensor requires such costly operations as deconvolution (channel estimation and inversion) to partially undo the dispersion [12]. Finally, many obstructions can render electromagnetic sensors useless. Regardless of the size of the sensor array, objects behind walls or under dense foliage cannot be detected.
As a simple example, consider the number of pixels needed to cover a particular area at a specified resolution. The geometry of similar triangles reveals that the same number of pixels is needed whether the pixels are concentrated in one large array or distributed among many devices. For free space with no obstructions, we would typically favor the large array, since there are no communications costs for moving information from the pixels to the processor. However, coverage of a large area implies the need to track multiple targets (a very difficult problem), and almost every security scenario of interest involves heavily cluttered environments complicated by obstructed lines of sight. Thus, if the system is to detect objects reliably, it has to be distributed, whatever the networking cost. There are also example situations (such as radar) in which it is better to concentrate the elements, typically where it is not possible to get sensors close to targets. There are also many situations in which it is possible to place sensors in proximity to targets, bringing many advantages.
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#19


to get information about the topic Data Security In Wireless Networks full report,ppt and related topic refer the page link bellow

http://studentbank.in/report-data-securi...anr-report

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http://studentbank.in/report-wireless-in...ull-report

http://studentbank.in/report-secure-wire...munication

http://studentbank.in/report-network-security-projects

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http://studentbank.in/report-security-in...ull-report
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