Discovery of Resident Behavior Patterns Using Machine Learning Techniques and IoT Paradigm

Josimar Reyes-Campos, Giner Alor-Hernández, Isaac Machorro-Cano, José Oscar Olmedo-Aguirre, José Luis Sánchez-Cervantes and Lisbeth Rodríguez-Mazahua
Additional contact information
Josimar Reyes-Campos: 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
Isaac Machorro-Cano: 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
José Luis Sánchez-Cervantes: CONACYT-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

Mathematics, 2021, vol. 9, issue 3, 1-25

Abstract: In recent years, technological paradigms such as Internet of Things (IoT) and machine learning have become very important due to the benefit that their application represents in various areas of knowledge. It is interesting to note that implementing these two technologies promotes more and better automatic control systems that adjust to each user’s particular preferences in the home automation area. This work presents Smart Home Control, an intelligent platform that offers fully customized automatic control schemes for a home’s domotic devices by obtaining residents’ behavior patterns and applying machine learning to the records of state changes of each device connected to the platform. The platform uses machine learning algorithm C4.5 and the Weka API to identify the behavior patterns necessary to build home devices’ configuration rules. Besides, an experimental case study that validates the platform’s effectiveness is presented, where behavior patterns of smart homes residents were identified according to the IoT devices usage history. The discovery of behavior patterns is essential to improve the automatic configuration schemes of personalization according to the residents’ history of device use.

Keywords: behavior patterns; comfort; domotic; Internet of Things; machine learning (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2227-7390/9/3/219/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/3/219/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:3:p:219-:d:485180

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().