HEMS-IoT: A Big Data and Machine Learning-Based Smart Home System for Energy Saving

Isaac Machorro-Cano, Giner Alor-Hernández, Mario Andrés Paredes-Valverde, Lisbeth Rodríguez-Mazahua, José Luis Sánchez-Cervantes and José Oscar Olmedo-Aguirre
Additional contact information
Isaac Machorro-Cano: Tecnológico Nacional de México (I. T. Orizaba), Av. Oriente 9, 852. Col. Emiliano Zapata, Orizaba 94320, Veracruz, Mexico
Giner Alor-Hernández: Tecnológico Nacional de México (I. T. Orizaba), Av. Oriente 9, 852. Col. Emiliano Zapata, Orizaba 94320, Veracruz, Mexico
Mario Andrés Paredes-Valverde: Tecnológico Nacional de México (I. T. Orizaba), Av. Oriente 9, 852. Col. Emiliano Zapata, Orizaba 94320, Veracruz, Mexico
Lisbeth Rodríguez-Mazahua: Tecnológico Nacional de México (I. T. Orizaba), Av. Oriente 9, 852. Col. Emiliano Zapata, Orizaba 94320, Veracruz, Mexico
José Luis Sánchez-Cervantes: CONACYT-Tecnológico Nacional de México (I. T. Orizaba), Av. Oriente 9,852. Col. Emiliano Zapata, Orizaba 94320, Veracruz, Mexico
José Oscar Olmedo-Aguirre: Department of Electrical Engineering, CINVESTAV-IPN, Av. Instituto Politécnico Nacional 2,508, Col. San Pedro Zacatenco, Delegación Gustavo A. Madero, Mexico City 07360, Mexico

Energies, 2020, vol. 13, issue 5, 1-24

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.

Keywords: domotic; energy saving; IoT; machine learning; monitoring (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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