@article {10.3844/jcssp.2013.821.826,
article_type = {journal},
title = {Predicting Battery Charge Depletion in Wireless Sensor Networks Using Received Signal Strength Indicator},
author = {Yano, Inacio Henrique and Oliveira, Vitor ChavesDe and Fagotto, Eric Alberto Mello and Mota, Alexandre De Assis and Mota, Lia Toledo Moreira},
volume = {9},
number = {7},
year = {2013},
month = {Jun},
pages = {821-826},
doi = {10.3844/jcssp.2013.821.826},
url = {https://thescipub.com/abstract/jcssp.2013.821.826},
abstract = {This article aims to identify an adequate mathematical model to predict battery power depletion at the nodes of a Wireless Sensor Network (WSN), by analyzing the Received Signal Strength Indicator (RSSI). Six general models were tested, the simplest Average model, Linear Regression model, Autoregressive (AR) models and Autoregressive Moving Average (ARMA) models.The selected model (AR) presented a low absolute mean residue and adequately represents the charge depletion process, permitting to predict its behavior and to detect the best moment to replace batteries in the WSN nodes.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}