Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2617
Title: Human movement tracking in disaster prone area using adhoc sensor network for predefined path and routing algorithm
Authors: Kaundal, Vivek
Keywords: Computer Science
Routing Algorithm
AdHoc Sensor Network
Issue Date: Aug-2017
Publisher: UPES, Dehradun
Abstract: There is a great potential of wireless sensor networks in real time monitoring of disaster prone areas. The present work focuses on specially designed communication link establishment for the first 72 hours just after disaster, highlighting the capability of wireless sensor network especially in disaster prone area. The complete network consists of wireless nodes with integrated Xbee as a sensor to establish a communication link in between the pursuit (rescue) team and trapped people post disaster. Focusing on post disaster condition, the localization is done by unilateral algorithm which has an advantage over trilateration algorithm to help in localization of trapped people. The unilateral technique uses the state of the art VPM (Vector Parameter based Mapping) protocol to track trapped people from communication deprived area. Several tests have been performed on a designed test bed to find the location of trapped node. The results obtained from network are very encouraging as the trapped nodes are fully discoverable using a hybrid model having RSSI (Remote Signal Strength Indicator) as a key component. To optimize the unilateral method hybrid TLBO – unilateral method have been used. The localization of the anchor node (fixed node) by pursuit nodes (movable node) in outdoor location has been studied by performing two experiments. The first method is based on LNSM (Log Normal Shadowing Method) technique to localize the anchor node and the second method is based on Hybrid TLBO (Teacher Learning Based Optimization Algorithm)- Unilateral technique. In the first approach the ZigBee protocol has been used to localize the node, which uses RSSI (Received Signal Strength Indicator) values in dBm. LNSM technique is implemented in the self-designed hardware node and localization is studied for outdoor location.
URI: http://hdl.handle.net/123456789/2617
Appears in Collections:Thesis

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01_title.pdf11.78 kBAdobe PDFView/Open
02_certificate.pdf9.51 kBAdobe PDFView/Open
03_acknowledgement.pdf9.65 kBAdobe PDFView/Open
04_contents.pdf9.09 kBAdobe PDFView/Open
05_list of figures.pdf10.12 kBAdobe PDFView/Open
06_abstracts.pdf11.59 kBAdobe PDFView/Open
07_chapter1.pdf119.56 kBAdobe PDFView/Open
08_chapter2.pdf46.16 kBAdobe PDFView/Open
09_chapter3.pdf13.06 kBAdobe PDFView/Open
10_chapter4.pdf1.02 MBAdobe PDFView/Open
11_chapter5.pdf244.31 kBAdobe PDFView/Open
12_chapter6.pdf235.42 kBAdobe PDFView/Open
13_chapter7.pdf1.04 MBAdobe PDFView/Open
14_chapter8.pdf9.27 kBAdobe PDFView/Open
15_references.pdf47.35 kBAdobe PDFView/Open


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