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Indoor Localisation of Wireless Sensor Nodes Towards Internet of Things
Author(s) -
Prosper Zanu Sotenga,
Karim Djouani,
Anish Kurien,
Martin Mwila
Publication year - 2017
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2017.05.299
Subject(s) - computer science , internet of things , wireless sensor network , wireless , computer network , the internet , telecommunications , computer security , world wide web
Internet of Things (IoTs) is an emerging technology that is envisioned to revolutionise the enabling environment and to provide autonomous, ubiquitous and pervasive computing within Wireless Sensor Networks (WSNs). IoTs are usually associated with the acquisition of sensor node information and controlling of “things”. However, the absence of location information of these sensor nodes compromises the intelligence of the IoT network. Therefore, this work is motivated by the recent advances in the two important areas of WSNs namely, indoor localisation and IoTs. This paper therefore presents a framework that integrates indoor localisation of sensor nodes and IoTs in a real world scenario. The focus is mainly on the implementation issues regarding localisation algorithm complexity, hardware computational capabilities and Internet/Intranet enabled connectivity for access to the sensor nodes’ location information. A sensor node prototype is developed using specialised electronic components and proprietary protocols to provide a capable platform for embedding a distributive online localisation algorithm based on Received Signal Strength (RSSI) and Gauss-Newton Algorithm (GNA). The algorithm is first simulated before porting it to the sensor node prototypes. A gateway device and an IoT framework are also proposed and implemented based on Linux, Apache, MySQL, PHP (LAMP) server to provide global and local access to sensor nodes’ location information. The Root Mean Square Error (RMSE) of the IoT logged estimated coordinates from the prototype nodes and the estimated coordinates from the simulation are computed and compared. The computational power of the hardware is analysed based the time it takes to perform the GNA based localisation process.

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