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3D Localization and Wireless Sensor NetworksAuthor: Balakrishna Pillalamarri Date: 2017-05-22 Report no: IIIT/TH/2017/25 Advisor:Garimella Ramamurthy AbstractIndoor positioning is gaining momentum for its various applications. As we know that Global Positioning System (GPS) does not work well indoors, while todays more sensitive GPS chips can sometimes get a location x (via receiving signals from enough satellites to determine a location) inside a building. The re- sulting location is typically not accurate enough to be useful. The signals from the satellites are attenuated and scattered by roofs, walls and other objects. Besides, the error range of many GPS chips (tennis court) can be larger than the indoor space itself (small grocery store)! Some indoor positioning solutions work similar to GPS. Many companies tap into Wi-Fi signals that are all around us - including when we are indoors. With a good map of the locations of the access points, a Wi-Fi receiver like a cell phone can be located even indoors. Any application that would depend on indoor positioning may need an exact location. This work on indoor localization in 3D using spherical co-ordinates would have an edge to all the future needs. A combination of Pico, Femto, Wi-Fi, otherwise termed as hybrid localization techniques are used in conjunction with leveling and sectoring. Leveling and sectoring are discussed using base station and Wi-Fi access points and the received signal strength (RSS) nger prints are used to aid in precise localization. Indoor localization applied to physical analytics is also discussed. This thesis work also focuses in an improvement over our above discussed works in terms of achieving more accuracy and reduction of delay in the Wireless Sensor Networks (WSNs). This is achieved by using the Received Channel Power Indi- cator (RCPI) in contrast to RSS. We assume that RCPI shall be used by all chip vendor for all the Wi-Fi devices coming into the market due to its precise way of measuring the Received signal power. This work also focuses on Wireless Sensor Networks (WSN) with respect to the need for optimizing the parallel distributed computational architecture.It also discussed how it can be acheived using our proposed model. This gains impor- tance as identication of an event in WSNs should be done as fast as possible by minimizing the delay. Optimizing the grid based architecture for time complexity, transmission delay and fault tolerance in computing the fusion functions, our work also focuses on localizing an event in an outdoor WSN and respond to the event based on the need as soon as possible. Hence our overall work on 3D localization and wireless sensor networks helps us localize events in both indoor as well as outdoor with reduced time-complexity as well as delay parameters. Full thesis: pdf Centre for Communications |
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