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https://dr.ddn.upes.ac.in//xmlui/handle/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 |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | 11.78 kB | Adobe PDF | View/Open | |
02_certificate.pdf | 9.51 kB | Adobe PDF | View/Open | |
03_acknowledgement.pdf | 9.65 kB | Adobe PDF | View/Open | |
04_contents.pdf | 9.09 kB | Adobe PDF | View/Open | |
05_list of figures.pdf | 10.12 kB | Adobe PDF | View/Open | |
06_abstracts.pdf | 11.59 kB | Adobe PDF | View/Open | |
07_chapter1.pdf | 119.56 kB | Adobe PDF | View/Open | |
08_chapter2.pdf | 46.16 kB | Adobe PDF | View/Open | |
09_chapter3.pdf | 13.06 kB | Adobe PDF | View/Open | |
10_chapter4.pdf | 1.02 MB | Adobe PDF | View/Open | |
11_chapter5.pdf | 244.31 kB | Adobe PDF | View/Open | |
12_chapter6.pdf | 235.42 kB | Adobe PDF | View/Open | |
13_chapter7.pdf | 1.04 MB | Adobe PDF | View/Open | |
14_chapter8.pdf | 9.27 kB | Adobe PDF | View/Open | |
15_references.pdf | 47.35 kB | Adobe PDF | View/Open |
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