Submitted by
Surbhi sinha

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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.