Abstract
Energy efficiency has aroused great interest in research worldwide, because energy consumption has increased in recent years, especially in the residential sector. The advances in energy conversion, along with new forms of communication, and information technologies have paved the way for what is now known as smart homes. The Internet of Things (IoT) is the convergence of various heterogeneous technologies from different application domains that are used to interconnect things through the Internet, thus allowing for the detection, monitoring, and remote control of multiple devices. Home automation systems (HAS) combined with IoT, big data technologies, and machine learning are alternatives that promise to contribute to greater energy efficiency. This work presents HEMS-IoT, a big data and machine learning-based smart home energy management system for home comfort, safety, and energy saving. We used the J48 machine learning algorithm and Weka API to learn user behaviors and energy consumption patterns and classify houses with respect to energy consumption. Likewise, we relied on RuleML and Apache Mahout to generate energy-saving recommendations based on user preferences to preserve smart home comfort and safety. To validate our system, we present a case study where we monitor a smart home to ensure comfort and safety and reduce energy consumption.
Highlights
Nowadays, increasing energy efficiency is used to face the great world challenges, such as energy security, air pollution, climate change and economic crises, among others
We analyze the data collected by Home Energy Management Systems (HEMS)-Internet of Things (IoT) during the case study to identify energy consumption patterns and understand the circumstances encouraging such patterns
We identified two smart homes where energy consumption was disproportionate with respect to the number of inhabitants
Summary
Nowadays, increasing energy efficiency is used to face the great world challenges, such as energy security, air pollution, climate change and economic crises, among others. Energy efficiency alternatives have the power to optimize energy consumption and reduce greenhouse gas emissions, contributing positively to the preservation of natural ecosystems and human health. Energy efficiency has aroused great interest in research worldwide, because energy consumption has increased in recent years, especially in the residential sector. For this reason, organizations and governments worldwide are proposing actions for energy conservation with the purpose of reducing energy-related inconveniences. The residential sector is attributed a high energy consumption; home automation systems (HAS), combined with IoT, are alternatives that promise to contribute to greater energy efficiency [2]
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