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The main challenge in shielding lengthy stretches of borders is the requirement for exhaustive human participation in patrolling the grounds. Conventional boundary patrol system…
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BORDER SURVEILLANCE USING WIRELESS SENSOR NETWORK Introduction Border patrol systems have lately got interest to tackle the concerns regarding national security. The main challenge in shielding lengthy stretches of borders is the requirement for exhaustive human participation in patrolling the grounds. Conventional boundary patrol system comprises security checkpoints along with border troops. The protection checkpoints are built on the international roads in which all vehicle traffic is halted to detect and arrest unlawful aliens, drugs, in addition to other illegal activity. Every border troop controls and watches a specific segment of the border. The troops guard the border according to prearranged route as well as the time interval (Ammari 12).
Existing border patrol techniques
Border patrol has widely depended on human participation. On the other hand, the relative cost for the growing number of workers as well as the retreating precision through human-only supervision has called for the contribution of high-tech devices in border patrol (Ammari 36). Amongst these, Unmanned Aerial Vehicles (UAVs) for mid-air surveillance have lately been used to track routinely and detect track unlawful border crossing. Due to the outsized coverage as well as high mobility of the UAVs, the concentrated human participation in low-level surveillance practices can be minimized.
Deployment methodology
In applications of border patrol, the established supervising network ought to cover a considerably large monitoring region. On the other hand, the radius of sensing of a single sensor node is usually limited. Consequently, many sensor nodes are expected to complete the coverage need. In addition, different kinds of sensor nodes like underground, camera, ground, and mobile sensors provide dissimilar coverage potentials. In addition, every sensor type has a special cost, sensing radius, as well as sensing accuracy (Aykanat54). As a result, a most favorable deployment approach is required to settle on the number along with locations of sensor nodes with varied capabilities.
The primary objective of the deployment
The primary objective of the deployment is to get the deployment tactic using the bare minimum number of each category of sensors to cover the entire surveillance area furthermore to accomplish desired intrusion detection likelihood. The aim is sensing the surroundings as well as communicating the findings to the data gathering center (Aykanat54). Most employment areas are envisaged for WSNs ranging from military surveillance to the monitoring of endangered species of animal populations. The research on the node placement together with coverage issues deals with effective use of sensor nodes in the networking field. A sensor node watches over only a limited region from its locality. Thus, data cannot be acquired from an area that is not covered by one or more sensor node.
A network model denotes the region covered by a particular sensor at a particular location. This model can be either probabilistic or deterministic. A probabilistic network model establishes the likelihood that an incident will be detected at a certain location whereas a deterministic network model denotes the region covered by a sensor node. So as to ensure coverage, sensor nodes should be deterministically located in the environment. Nevertheless, in many applications sensor nodes are deployed randomly (Ang and Kah 24).
Detection-oriented communication
To enhance accurate and timely object detection, effective and efficient communication procedures are needed to support two forms of transmissions: camera-remote center transmission and sensor-camera transmission (Ang and Kah 24). Camera-remote center transmission allows camera towers to transmit captured images to the remote control center whilst sensor-camera transmission enables underground/ ground sensors to report doubtful actions to camera towers.
Works cited
Ammari, Habib M. The Art of Wireless Sensor Networks: Volume 1: Fundamentals. Berlin, Heidelberg: Imprint: Springer, 2014. Internet resource.
Ang, Li-minn, and Kah P. Seng. Visual Information Processing in Wireless Sensor Networks: Technology, Trends, and Applications. Hershey, PA: Information Science Reference, 2012. Print.
Aykanat, Cevdet. Computer and Information Sciences - Iscis 2004: 19th International Symposium, Kemer-Antalya, Turkey, October 27-29, 2004 ; Proceedings. Berlin [u.a.: Springer, 2004. Print.
Kwiecień, Andrzej, Piotr Gaj, and Piotr Stera. Computer Networks: 20th International Conference, Cn 2013, Lwówek Śląski, Poland, June 17-21, 2013, Proceedings. , 2013. Internet resource.
Li, Yingshu, My T. Thai, and Weili Wu. Wireless Sensor Networks and Applications. New York: Springer, 2008. Internet resource.
Mao, Guoqiang, and Bariș Fidan. Localization Algorithms and Strategies for Wireless Sensor Networks. Hershey, PA: Information Science Reference, 2009. Print. Read More
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