The document describes Wireless Integrated Network Sensors (WINS) and their application for border security. WINS combine sensing, processing, decision making, and wireless networking capabilities in compact, low power systems. They consist of microsensor nodes that communicate in a multi-hop network. This allows distributed monitoring over a large area at low cost. For border security, WINS nodes can be deployed across the border to detect intruders through multimedia sensors including imaging, seismic, magnetic, and infrared sensors. The distributed sensor network provides more accurate detection over a wider area than existing techniques like unmanned aerial vehicles alone.

1. BORDER SECURITY USING
WIRELESS INTEGRATED NETWORK SENSORS (WINS)
A Technical Seminar Report
Submitted by
Sonam Tobgay
ECE2010100
Electronics and Communication Engineering
College of Science and Technology
Rinchending :: Phuentsholing
September 21st
2013

2. i
ABSTRACT
Wireless Integrated Network Sensors (WINS) 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, and wireless
networking capability in a compact, low power system. WINS systems combine micro sensor
technology with low power sensor interface, signal processing, and RF communication circuits.
The need for low cost presents engineering challenges for implementation of these systems in
conventional digital CMOS technology. This paper describes micro-power data converter,
digital signal processing systems, and weak inversion CMOS RF circuits. The digital signal
processing system relies on a continuously operating spectrum analyzer. Finally, the weak
inversion CMOS RF systems are designed to exploit the properties of high-Q inductors to
enable low power operation. This paper reviews system architecture and low power circuits for
WINS.

3. ii
ACKNOWLEDGEMENT
Firstly, I would like to acknowledge DR. Kazuhiro Muramatsu (Technical Seminar
Coordinator) for guiding us on how to go on with technical seminar writing. Without his
guidance our seminar report would not be in this state. Moreover, my sincere thanks goes to
my seminar guide Mr Tashi for guiding and giving timely feedback while writing my draft
seminar report. Mr Tashi has also tipped me on what should include in good seminar writing
and this idea helped me a lot while writing whole of my draft seminar report . I would also like
to thanks college ICT section for providing internet access for 24*7 which has helped in finding
sources for writing my seminar report.

4. iii
TABLE OF CONTENTS
BORDER SECURITY USING ..................................................................................................1
Abstract........................................................................................................................................i
ACKNOWLEDGEMENt...........................................................................................................ii
Table of Contents.......................................................................................................................iii
List of Figures............................................................................................................................iv
List of Abbreviations..................................................................................................................v
1 INTRODUCTION .......................................................................................................1
2 EXISTING BORDER PATROL TECHNIQUES .......................................................2
3 WINS SYSTEM ARCHITECTURE AND BORDER SENSE...................................3
4 WINS NODE ARCHITECTURE................................................................................4
Block Diagram of WINS ........................................................................................................6
5 ROUTING BETWEEN NODES AND SHORTEST DISTANCE ALGORITHM ....7
6 WINS MICRO SENSORS AND WINS MICRO SENSOR INTERFACE CIRCUITS
8
7 REMOTE BATTLE FIELD SENSOR SYSTEM (REMBASS):..............................11
8 WINS DIGITAL SIGNAL PROCESSING AND PSD COMPARISION ................14
9 WINS CHARACTERISTICS & APPLICATIONS ..................................................15
10 DESIGN CONSIDERATION ...................................................................................16
11 Conclusion .................................................................................................................17
References................................................................................................................................18

5. iv
LIST OF FIGURES
Figure 1 -Distributed sensors at Border......................................................................................2
Figure 2 -The wireless integrated network sensor (WINS) architecture...................................3
Figure 3 (a) Node Connections. (b) WINS nodes (shown as disks)..........................................5
Figure 4 shows the block diagram of the wireless integrated network sensor (WINS) . This
block diagram shows the working principle of the WINS. ........................................................6
Figure 5 -Nodal distance and Traffic..........................................................................................7
Figure 6 -Routing Matrix............................................................................................................7
Figure 7 (a) A micrograph of the thermopile junction array in.................................................9
Figure 8 -WINS Σ-∆ADC A block diagram of the pulse code modulator part of the Σ-∆ADC
showing the location of the input analog modulator and output digital demodulator chopping
blocks........................................................................................................................................10
Figure 9 - REMBASS...............................................................................................................11
Figure 10 -WINS micro power spectrum analyzer architecture...............................................14
Figure 11- Comparator plot......................................................................................................15
Figure 12- Enclosure ................................................................................................................16

6. v
LIST OF ABBREVIATIONS
Sl. No. Terms Descriptions
1 WINS Wireless integrated network sensors
2 REMBASS Remote battle field sensor system
3 UGS Unattended Ground Sensors
4 RSTA Reconnaissance, surveillance, and target acquisition
5 IR Passive infrared sensor
6 MAG Magnetic sensor
7 SA Seismic/acoustic sensor
8 SMS Sensor Monitoring Set
9 PMS Portable monitoring set
10 SSS Sensor Signal Simulator
11 FLOT Forward line of own troops

7. 1
1 INTRODUCTION
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 WINS network is a new monitoring and control capability for applications
in transportation, manufacturing, health care, environmental monitoring, and safety and
security. WINS combine micro-sensor technology, low power signal processing, low power
computation, and low power, low cost wireless networking capability in a compact system.
Recent advances in integrated circuit technology have enabled construction of far more capable
sensors, radios, and processors at low cost, allowing mass production of sophisticated systems
that link the physical world to networks. Scales will range from local to global, with
applications including medicine, security, factory automation, environmental monitoring, and
condition-based maintenance. Compact geometry and low cost allows WINS to be embedded
and distributed at a small fraction of the cost of conventional wire line sensor and actuator
systems. 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.
WINS Initiated in 1993 under Defence advance research project agency (DARPA) in
US. LWIM (Low power wireless integrated micro sensor) program began in 1995 for further
development of WINS sponsored by DARPA. In 1998, WINS NG introduced for wide variety
of application. The LWIM project for multi hop, self-assembled, wireless network algorithms
for operating at micro power levels.

8. 2
2 EXISTING BORDER PATROL TECHNIQUES
Border patrol has extensively been based on human involvement. However, the relative cost
for the increasing number of personnel as well as the diminishing accuracy through human-
only surveillance has required the involvement of high-tech devices in border patrol. Among
these, Unmanned Aerial Vehicles (UAVs) for aerial surveillance have recently been used to
automatically detect and track illegal border crossing. Due to the large coverage and high
mobility of the UAVs, the intensive human involvement in low-level surveillance activities can
be reduced. However, similar to the Conventional border patrol systems, UAVs alone cannot
cover the whole border at any time. Moreover, the UAVs have significantly higher costs and
accident rates than those of manned aircrafts and require large human footprint to control their
activities. In addition, inclement weather conditions can also impinge on the surveillance
capability of UAVs. [1]
Compared with the existing border patrol techniques, Border Sense provides the following
advantages: (1) the multimedia sensors provide accurate detection as well as large detection
range; (2) the ground sensors provide additional information that cannot be detected by the
multimedia sensors, e.g. in cases where the intruder is hidden behind an obstacle that cannot
be detected by the imaging sensor; (3) the underground sensors guarantee the proper system
functionalities where aboveground visible devices are not preferred for concealment purposes;
(4) mobile sensors provide intrusion tracking capability to track the intruders after they have
been detected; and (5) by in network processing, the heterogeneous sensors cooperatively
detect the intrusion and report the results to a remote administrator. Accordingly, both the
deployment and operational cost of the border patrol system can significantly be decreased.
Figure 1 -Distributed sensors at Border

9. 3
3 WINS SYSTEM ARCHITECTURE AND BORDER SENSE
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 1
- 100 kbps). The network design must consider the requirement to service dense sensor
distributions with an emphasis on recovering environment information. We exploit the small
separation between WINS nodes to provide multi hop communication, with the power
advantages outlined earlier. Since for short hops the transceiver power consumption for
reception is nearly equal to that of transmission, the protocol should be designed so that radios
are off as much of the time as possible. That is, the MAC should include some variant of TDMA.
This requires that the radios periodically exchange short messages to maintain local
synchronism. The abundant bandwidth that results from the spatial re-use of frequencies and
local processing ensures that relatively few conflicts will result in these requests, and so simple
mechanisms can be used. A low-power protocol suite that embodies these principles has been
developed, including boot-up, MAC, energy-aware routing, and interaction with mobile units.
It indicates the feasibility of achieving distributed low-power operation in a flat multi-hop
network.
The multi hop communication has been shown in the figure 2. The figure represents the
general structure of the wireless integrated network sensors (WINS) arrangement. –small wins
[2]
Figure 2 -The wireless integrated network sensor (WINS) architecture

10. 4
4 WINS NODE ARCHITECTURE
The WINS node architecture (Figure 3) 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 analyser must all operate at
micro power levels. In the event that an event is detected, the spectrum analyser 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 neighbouring 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
able, 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.

11. 5
Figure 3 (a) Node Connections. (b) WINS nodes (shown as disks).
The above figure shows the node connections deployed in WINS. By the fig it can be
seen that several nodes are connected together and also with the Gateway which is used for
Conventional Communication, Internet Connectivity and Remote Maintenance and Re-
configurability. This type of architecture will be low cost, consumes low power, multi hop,
multiply redundant and reconfigurable.
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 micro power 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. [3]

12. 6
Block Diagram of WINS
Figure 4 shows the block diagram of the wireless integrated network sensor (WINS) . This
block diagram shows the working principle of the WINS.

13. 7
5 ROUTING BETWEEN NODES AND SHORTEST
DISTANCE ALGORITHM
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 5. In the figure, the
distances between the nodes and the traffic between the nodes have 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 6 -Routing Matrix
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 -Nodal distance and Traffic

14. 8
In figure 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-λ
Ti = Time delay in sec
C= Capacity of the path in Bps
λ = Mean flow in packets/sec.
6 WINS MICRO SENSORS AND WINS MICRO SENSOR
INTERFACE CIRCUITS
Many important WINS applications require the detection of signal sources in the presence of
environmental noise. 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, micro
electromechanical systems (MEMS) technology provides an ideal path for implementation of
these highly distributed systems. WINS sensor integration relies on structures that are flip-chip
bonded to a low temperature, co-fired ceramic substrate. This 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 7.

15. 9
Figure 7 (a) A micrograph of the thermopile junction array in
(b)This dual pixel device provides object presence and motion sensing. The WINS thermopile
operates without the need for a voltage or current bias and provides a noise equivalent power
of 1.8 nW/(Hz)1/2 (a sensitivity level limited by thermal noise).
The WINS micro sensor systems must be monitored continuously by the CMOS micro power
analog -to-digital converter (ADC). As was noted above, power requirements constrain the
ADC design to power levels of 30µW or less.

16. 10
Implementation of low noise ADC systems in CMOS encounters severe “1/f” input noise with
input noise corner frequencies exceeding 100 kHz. An IF frequency of 1/8 th
of the ADC
sampling frequency is chosen. The low thermopile sensor source impedance limits the
amplitude of charge injection noise that would result from signal switching. The required
demodulation of the IF signal to the desired baseband is accomplished on the digital code
modulated signal, rather than on the analog signals. This both simplifies architecture and avoids
additional injected switching noise. The architecture of the chopped Σ-∆ ADC is shown in
Figure 8. [3]
Figure 8 -WINS Σ-∆ADC A block diagram of the pulse code modulator part of the Σ-∆ADC
showing the location of the input analog modulator and output digital demodulator chopping
blocks.

17. 11
7 REMOTE BATTLE FIELD SENSOR SYSTEM
(REMBASS):
What is UGS (Unattended Ground Sensors)?
A ground sensor is deployed permanently on the ground in the open. The deployment mode
varying from buried, to surface-mounted. An unattended sensor works autonomously, without
requiring human attention for its operation
It uses remotely monitored sensors emplaced along likely enemy avenues of approach.
REMBASS is a UGS system that detects, classifies, and determines direction of
movement of personnel, wheeled vehicles, and tracked vehicles. It provides worldwide
deployable, day/night, all-weather, early warning surveillance and target classification. Units
operate up to 90 days, or longer, without maintenance.
REMBASS sensors are built for any level of conflict, including special operations, low intensity
conflict, and counter narcotics operations. The sensors are placed along likely avenues of
approach or intrusion and respond to seismic and acoustic disturbances, infrared energy,
and magnetic field changes. The sensor information is incorporated into short, digital
messages and communicated by VHF radio burst transmission. [4]
Figure 9 - REMBASS.

18. 12
The system provides division, brigade, and battalion commanders with information from
beyond the forward line of own troops (FLOT), and enhances rear area protection. It can be
deployed anywhere in the world in a tactical environment in support of reconnaissance,
surveillance, and target acquisition (RSTA) operations. The system consists of eleven major
components;
(1) Magnetic Sensor: This is a hand-emplaced, MAG sensor. The MAG sensor detects
vehicles (tracked or wheeled) and personnel carrying ferrous metal. The monitor uses
two different (MAG and IR) sensors and their identification codes to determine
direction of travel.
(2) Seismic Acoustic Sensor: This is a hand-emplaced SA classifying sensor. It detects targets
and classifies them as unknown, wheeled vehicle, tracked vehicle, or personnel.
(3) Passive Infrared Sensor: This is a hand-emplaced, IR detecting sensor. The senor detects
tracked or wheeled vehicles and personnel. It also provides information on which to base a
count of objects passing through its detection zone and reports their direction of travel relative
to its location.
(4) Radio Repeater: This is an expendable/recoverable, digital/analog radio repeater used to
extend the broadcast range of radio messages from anti-intrusion sensors to a monitoring set. It
(5) Sensor Monitoring Set: The SMS has a dual channel receiver with a permanent hard copy
recorder and a temporary visual display (TVD). The SMS receives processes, displays, and
records sensor information relating to 60 sensor ID codes. Detections and classification are
displayed as: dashes (-) for unknown targets, (T) for tracked vehicles, (W) for wheeled vehicles,
and (P) for personnel. The TVD can simultaneously display up to ten sensor ID codes with
detection or classification information. A keyboard allows the operator to program the SMS
operation: set radio frequency (RF) channels, establish hard copy recorder format, initiate
system operational checks or built in test (BIT), and calculate target speed. A separate display
shows the keyboard functions and calculations.
(6) Radio Frequency Monitor: This is a single-channel PMS with a TVD. The PMS receives,
processes, and displays sensor ID codes and detection/classification messages.

19. 13
(7) Code Programmer: The programmer is a portable device used to program sensors and
repeaters to the desired operating channel, ID code, mission life, arm mode, and gain. It is also
used to condition newly installed batteries in sensors and repeaters. It has a built in visual self-
test to ensure the proper information programmed into the sensor or repeater.
(8) Antenna Group: The antenna group consists of an Omni -directional unity gain antenna, a
mast assembly, a pre-amplifier suitable for mast mounting and an RF multi- coupler. It is used
with the SMS and the PMS. Up to four monitoring devices can use the antenna group
simultaneously.
(9) Power Supply: The power supply is a custom fly back-type switching regulator that
converts external power sources (24 volts direct current (dc), 115 or 220 volts alternating
current) to 12 volts dc nominal prime power. The power supply can be used to power the SMS,
repeater or SSS.
(10) Mounting Rack: The mounting rack is an aluminum angle shock mounted rack. It is used
to mount the repeaters in helicopters.
(11) Sensor Signal Simulator (SSS): The SSS is similar in appearance to the SMS. It has the
capability to receive, record, edit, copy, and retransmit an operational scenario involving any
two of the 599 REMBASS channels. It also has the capability to transmit pre-recorded
scenarios. [4]

20. 14
8 WINS DIGITAL SIGNAL PROCESSING AND PSD
COMPARISION
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 analyser must be
implemented in the WINS digital signal processing system. The spectrum analyser 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
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 10 contains a set of parallel filters.
Figure 10 -WINS micro power spectrum analyzer architecture.
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 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 11. [4]

21. 15
Figure 11- Comparator plot
9 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
 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. [5]

22. 16
10 DESIGN CONSIDERATION
a. Reliability: The system must be reliable so that the probability of failures and faulty
operations must be very less.
b. Energy: There are four way in which node consumes energy.
 Sensing: Choosing right sensor for the job can improve the system performance and
to consume less power.
 Computation: The sensor must be chosen so that the speed of computation can be
very fast and less faults.
 Storing: The sensor must have sufficient storage to store the sensed data so that it
can be communicated.
 Communicating: The communicating between sensors is very important factor
when it is used for border security. There must not be any faults during
communicating the sensed data between various nodes and the gateway.
The sensor must be design to minimize the likelihood of environment effect of wind,
rain, snow etc. The enclosure is manufacture from clear acrylic material. Otherwise the sensor
may damage due to weather effects and may give fault results. [6]
Figure 12- Enclosure

23. 17
11 Conclusion
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.

24. 18
REFERENCES
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network(Elsevier), vol. 9, pp. 468-477, 2011.
[2] G. J. Pottie and W. J Kaiser, “Wireless Integrated Network Sensors (WINS):,” Principles
and Practice, p. 10, 21 sept 2013.
[3] G. Asada, M. Dong, T. Lin, F. Newberg and ,. Pottie, “Wireless Integrated Network
Sensors: Low Power Systems on a Chip,” Rockwell Science Center, vol. 2, pp. 17-21, 1997.
[4] Z. HAIG, “Networked unattended ground sensors for battlefield,” AARMS, vol. 3, no. 3, p.
387–399, 2004.
[5] S. Natkunanathan and J. Pham , “IRELESS INTEGRATED NETWORKED SENSORS:,”
56-125B Engineering, vol. 4, pp. 12-14, 1996.
[6] W. Fang, “An Adaptive Transmission Scheme for Wireless Sensor Networks,”
International Journal of Future Generation Communication and Networking, vol. 6, no.
no.1, pp. 45-48, 2013.

25. 19