Open AccessMachine Learning in Smart Home Energy Monitoring System
Author(s) -
Gengyi Xiao
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/769/4/042035
Subject(s) - adaptability , cloud computing , home automation , computer science , energy (signal processing) , embedded system , smart system , real time computing , artificial intelligence , operating system , internet of things , ecology , statistics , mathematics , biology
In order to solve the insufficiency of the existing smart home energy monitor ing system in autonomous adaptability, a smart home energy monitoring system based on machine learning and embedded technology is proposed. The system uses a gatewa y to collect sensor data, and then uses a cloud computing platform running Hadoop and machine learning algorithms to learn and identify user behaviours to achieve autonom ous decision-making capabilities. Through the analysis of examples, it can be seen that the solution greatly improves the humanization of the smart home system.