Wireless Sensor Network Localization using Artificial Intelligence and Simulated Annealing Optimization | Zendy

Safae El Abkari | Zendy; Abdelilah Jilbab | Zendy; Jamal El Mhamdi | Zendy

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Wireless Sensor Network Localization using Artificial Intelligence and Simulated Annealing Optimization

Author(s) -

Safae El Abkari,

Abdelilah Jilbab,

Jamal El Mhamdi

Publication year - 2020

Publication title -

international journal of recent technology and engineering (ijrte)

Language(s) - English

Resource type - Journals

ISSN - 2277-3878

DOI - 10.35940/ijrte.f8911.038620

Subject(s) - simulated annealing , wireless sensor network , computer science , artificial neural network , artificial intelligence , heuristic , network topology , machine learning , distributed computing , data mining , computer network

In recent years localization of nodes in wireless sensor networks (WSNs) has become one the main features of applications. In fact, this issue has been widely explored by the scientific community that proposed many approaches in order to localize network nodes. However, artificial neural network (ANN) can be used as an operating method. Therefore, we aim in this paper to select the best suited structure of ANN to localize in WSN using a meta-heuristic technique. To optimize this procedure, we use the Simulated Annealing (SA) algorithm. We constituted a network of ESP8266 modules to create our WSN topology as well as the training and the testing data to evaluate the performances.

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