Wireless Integrated Network Sensors (WINS) : A Border

security solution

Prepared By....

Deepak Kumar MohapatraPijush Kumar Banerjee

OVERVIEW…

• WINS Introduction• Evolution• Working Principle • System Architecture• Node Architecture• Micro sensor• Digital Signal Processing• Spectrum Analysis• Characteristics & applications• Reference• Conclusion

ABSRACT…• Provides a new monitoring for the

borders of the country.

• Easy identification of strangers or some terrorists entering the border area.

• Border area is partitioned into no. of mutually connected nodes.

• Noise detection, Image processing, Biometric scanning, Thermal detection, Density comparison, AV modulation etc. are the main key roles.

INTRO…

• WIRE LESS INTEGRATED NETWORK SENSOR (WINS).• Require a few microwatt of power to operate, so it is

cheaper than the conventional radar system.• It produce a less amount delay to detect the target and

reasonably faster.

Evolution Of WINS…

WINS Initiated in 1993 under Defence advance research project agency (DARPA) in US.

LWIM (Low power wireless integrated micro sensor) program began in 1995.

In 1998, WINS introduced for wide variety of applications such as multihop, self-assembled, wireless network algorithms for operating at micropower levels.

Distributed sensor at Border…

Working Principle…

WINS System Architecture…

• WINS architecture includes sensor, data converter, signal processing, and control functions.

• The micro power components operate continuously for event recognition, while the network interface operates at low duty cycle.

Continuous operation low duty cycle

WINS Node Architecture…

1998: WINS developed by the authors contiguous sensing, signal processing for event detection, local control of actuators, event classification, communication at low power Event detection is contiguous micropower levels Event detected => alert process to identify the event Further processing? Alert remote user / neighboring node? Communication between WINS nodes

sensor

actuator inte

rfac

e

signal processing for event detection

control

Processing

event classification & identification

wireless internet interface

continuously vigilant operation low-duty cycle operation

Cont…WINS nodes are distributed at high density in an

environment to be monitored.WINS node data is transferred over the asymmetric

wireless link to an end user.

Nodes connection of WINS…

WINS MICRO SENSORS… The detector shown is the thermal detector. It just captures the

harmonic signals produced by the footsteps of the stranger entering the border. Whole area is partitioned into hexagonal region.

These signals are then converted into their PSD values and are then compared with the reference values set by the user.

Detection Procedure...

Micro Sensor and Thermal Conductivity…

TC v/s Pressure characteristics

Operation...

Sensor boards…

(a) Mica network Board(b) Mica Sensor Board(c) Mica Power Board(d) TWR-ISM-002 Radar Board(e) All of the boards attached together. Packaging

Assembled Sensor Boards…

WINS DSP… 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.

The spectrum analyzer resolves the WINS input data into a low-resolution power spectrum.

WINS micropower spectrum analyzer architecture

Spectrum Analysis…

WINS Characteristics & Applications…

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.

Cont… Applications:• 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.

• On a local, enterprise scale, WINS will create a manufacturing information service for cost and quality control.

Unanticipated Faulty Behavior…

• We experienced several failure as a result of undetectable, incorrectly download program and depleted energy level etc.

• For example node will detect false event when sensor board is overheated.

Reference… http://en.wikipedia.org/wiki/WINS

http://en.wikipedia.org/wiki/Micro_sensors

M. J. Dong, G. Yung, and W. J. Kaiser, “Low Power Signal Processing Architectures for Network Microsensors”, 1997 International Symposium on Low Power Electronics and Design, Digest of Technical Papers (1997).

A. A. Abidi, “Low-power radio-frequency ICs for portable communications”, Proceedings of the IEEE, 83, (1995).

D. B. Leeson, “A simple model of feedback oscillator noise spectra”.

Conclusion… Densely distributed sensor

networks. Application specific

networking architectures Development platforms are

now available . The network is self-

monitoring and secure. Now it is possible to secure

the border with an invisible wall of thousands or even millions of tiny interconnected sensors.