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.

1. Presented By....
SAURABH R. GIRATKAR
Guided By Co-Guide By
Prof. P. G. Kaushik Prof. R. R. Agrawal
JAWAHARLAL DARDA INSTITUTE OF ENGINEERING & TECHNOLOGY,
YAVATMAL
DEPARTMENT OF ELECTRONICS & TELECOMMUNICATION ENGINEERING

2. OVERVIEW…
 WINS Introduction
 Evolution
 Working Principle
 SystemArchitecture
 NodeArchitecture
 Micro sensor
 Digital Signal Processing
 SpectrumAnalysis
 Characteristics & applications
 Cons & Pros
 Reference
 Conclusion

3. 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.

4. INTRODUCTION…
 WIRE LESS INTEGRATED NETWORK SENSOR (WINS).
 WINS provide a new monitoring and control capability for
monitoring the Border of the country.
 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.
 It is reasonably faster.
 On global scale wins will permit monitoring of land ,water
and air resources for environment monitoring.

5. Evolution Of WINS…
 WINS Initiated in 1993 under
DARPA in US.
 LWIM 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.

6. Distributed sensor at Border…

7. 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

8. 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 betweenWINS nodes
sensor
actuator
signal processing for
event detection
control
Processing
event classification &
identification
wireless
internet
interface
continuously vigilant operation low-duty cycle operation

9. 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.

10. 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.

11. Micro Sensor and Thermal
Conductivity…

12. 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

13. Assembled Sensor Boards…

14. 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 theWINS.
 The spectrum analyzer resolves theWINS input data into a low-resolution
power spectrum.
WINS micropower spectrum analyzer architecture

15. 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.

16. 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.

17. Pros & Cons
 PROS:
 It avoid hell lot of wiring.
 It can accommodate new devices at any time.
 Its flexible to go through physical partitions.
 It can be accessed through a centralized monitor.
 CONS:
 Its damn easy for hackers to hack it as we cant control
propagation of waves.
 Comparatively low speed of communication.
 Gets distracted by various elements like Blue-tooth.

18. 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.

19. Reference…
 http://en.wikipedia.org/wiki/WINS
 http://en.wikipedia.org/wiki/Micro_sensors
 M. J. Dong, G.Yung, andW. J. Kaiser,“Low Power Signal Processing
Architectures for Network Microsensors”, 1997 International
Symposium on Low Power Electronics and Design, Digest ofTechnical
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”.

20. 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.