A Proposed Fuzzy Logic Approach for Conserving the Energy of Data Transmission in the Temperature Monitoring Systems of Internet of Things

TL;DR

This paper introduces a fuzzy logic method to optimize energy use in IoT temperature monitoring by filtering data based on context, achieving significant energy savings while maintaining effective monitoring.

Contribution

It presents a novel fuzzy logic approach for energy conservation in IoT temperature sensors, focusing on data filtering based on environmental and operational factors.

Findings

Energy consumption reduced by 11.8% in experiments

Effective data filtering maintains monitoring quality

Applicable to indoor temperature and humidity systems

Abstract

One of the primary challenges facing the Internet of Things is the reservation and efficient consumption of energy resources, especially in those types of applications that require continuous monitoring or suffer from lacking ongoing energy resources. Despite this, the indoor temperature and humidity monitoring systems are unconcerned about the insignificant amount of energy consumed during critical times when sending unimportant or useless data to the control rooms servers. This paper proposes a fuzzy logic-based approach for reducing the amount of energy spent in indoor temperature and humidity monitoring systems by filtering data that is sent to servers based on several surrounding circumstances such as time of data recording and current energy consumption amount while maintaining constant monitoring. The experimental results on the Appliances Energy Prediction dataset show that the proposed fuzzy-based approach successfully reduces energy consumption in temperature and humidity monitoring systems by 11.8% .