Title: Analysis and handling of biased data provided by wireless sensor networks with lack of energy

Authors: Fernando Lima Vicente; Adilson E. Guelfi; Anderson Aparecido Alves da Silva; Marcelo Teixeira de Azevedo; Bruno Elton da Luz; Eduardo Takeo Ueda; Sergio Takeo Kofuji

Addresses: Instituto de Pesquisas Tecnológicas (IPT), São Paulo, Brazil ' Universidade do Oeste Paulista, São Paulo, Brazil ' Instituto de Pesquisas Tecnológicas (IPT), São Paulo, Brazil; Universidade de São Paulo (USP), São Paulo, Brazil; Centro Universitário SENAC, São Paulo, Brazil; Universidade Paulista (UNIP), São Paulo, Brazil ' Universidade de São Paulo (USP), São Paulo, Brazil ' Instituto de Pesquisas Tecnológicas (IPT), São Paulo, Brazil ' Instituto de Pesquisas Tecnológicas (IPT), São Paulo, Brazil ' Universidade de São Paulo (USP), São Paulo, Brazil

Abstract: Wireless sensor networks consist of several battery-powered microelectronic devices whose purpose is to monitor the environment in which they are deployed. When a device's battery is almost completely discharged, it can stop working or start producing distorted or biased data, making monitoring unfeasible. Thus, many works seek to control the energy level of the sensor node to avoid the described behavior. However, battery-powered wireless networks inevitably run out of energy at some point in time. In this way, the objective of this study is to propose, implement, and compare methods that treat the data which are biased due to the lack of energy of the network devices. This method consists of joining estimating mechanisms like Kalman filter and GM (1, 1) with another technique to measure the reliability of the network devices based on the available energy in the nodes' batteries.

Keywords: wireless sensor network; WSN; Kalman filter; bias error; battery life time.

DOI: 10.1504/IJSNET.2023.129808

International Journal of Sensor Networks, 2023 Vol.41 No.3, pp.137 - 151

Received: 29 Jan 2022
Accepted: 21 Jun 2022
Published online: 30 Mar 2023 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article