TY  - JOUR
AU  - Yano, Inacio Henrique 
AU  - Oliveira, Vitor ChavesDe 
AU  - Fagotto, Eric Alberto Mello 
AU  - Mota, Alexandre De Assis 
AU  - Mota, Lia Toledo Moreira 
PY  - 2013
TI  - Predicting Battery Charge Depletion in Wireless Sensor Networks Using Received Signal Strength Indicator
JF  - Journal of Computer Science
VL  - 9
IS  - 7
DO  - 10.3844/jcssp.2013.821.826
UR  - https://thescipub.com/abstract/jcssp.2013.821.826
AB  - 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.