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Analysis of BASNs Battery Performance at Different Temperature Conditions Using Artificial Neural Networks (ANN)

  • B. BanuselvasaraswathyEmail author
  • R. Vimalathithan
  • T. Chinnadurai
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1048)

Abstract

In Body Area Sensor Network (BASN), battery power management is an important issue to be addressed to extend the lifetime of the sensor with increased performance. The lifetime of the battery relies on several factors like charging and discharging cycles, Voltage rating, current ratings, and temperature. The temperature variation in the battery leads to increased performance but shortens its lifetime due to the internal chemical reaction that occurs inside the battery. Therefore, it is essential to analyze the temperature variations to enhance the battery lifetime as well as to improve the lifetime of entire sensor network. In this paper, BASNs battery efficiency is analyzed at different temperature profile, charging, and discharging cycles. The voltage is measured from the obtained results. As rise in temperature influence the battery discharging capacity. Thus, maintaining optimal temperature is very essential in BASNs battery to increase the lifetime of battery. Further, Artificial Neural Network (ANN) is developed to examine the experimental results to obtain the optimum battery operating temperature.

Keywords

Body area sensor networks Battery performance Temperature variations Artificial neural networks 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • B. Banuselvasaraswathy
    • 1
    Email author
  • R. Vimalathithan
    • 2
  • T. Chinnadurai
    • 3
  1. 1.Department of ECESri Krishna College of TechnologyCoimbatoreIndia
  2. 2.Department of ECEKarpagam College of EngineeringCoimbatoreIndia
  3. 3.Department of ICESri Krishna College of TechnologyCoimbatoreIndia

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