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A Real-Time Adaptive Thermal Comfort Model for Sustainable Energy in Interactive Smart Homes: Part I

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Smart Multimedia (ICSM 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13497))

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Abstract

A successful smart city implementation needs to efficiently use natural and human resources. This can be achieved by dividing the smart city into smaller modules, such as a smart community, and even smaller such as a smart home, to allow energy management systems to monitor the city's behavior. The electricity end-user sector is often divided into the residential, commercial, and public transport, industrial, and agricultural sectors. On the other hand, HVAC systems constitute from 40% up to 60% of energy consumption in buildings. Nevertheless, householders do not entirely accept connected devices due to complex interfaces, lack of interest, or acquired habits of thermostat usage that affect thermal comfort, hence, usability and behavioral problems. Thermal comfort is widely defined as that state of mind which conveys satisfaction with the thermal surroundings. This paper obtains an adaptive comfort model for measuring these three features through energy simulations to compare them during the year. This paper analyzes three energy model scenarios to review the adaptive behavior of a community of twelve houses. Three energy models were simulated for Mexico City, Concord (California), and Ontario (Canada) and later deployed into an interactive online platform to determine what further actions are required to improve the quality of life of householders without losing thermal comfort and maximizing energy savings. Besides, this platform allows worldwide users to interact with the platform and learn how clothing insulation, activity, and location affect energy consumption and thermal comfort.

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Acknowledgments

Research Project supported by Tecnologico de Monterrey and CITRIS under the collaboration ITESM-CITRIS Smart thermostat, deep learning, and gamification project (https://citris-uc.org/2019-itesm-seed-funding/).

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Authors and Affiliations

  1. Institute of Advanced Materials for Sustainable Manufacturing, Tecnologico de Monterrey, Monterrey, MX, 64849, USA

    Juana Isabel Méndez, Adán Medina, Pedro Ponce & Arturo Molina

  2. Institute for Energy and Environment, University of California, Berkeley, CA, 94720, USA

    Therese Peffer

  3. Energy and Efficiency Institute, University of California, Davis, CA, 95616, USA

    Alan Meier

Authors
  1. Juana Isabel Méndez
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  2. Adán Medina
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  3. Pedro Ponce
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  4. Therese Peffer
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  5. Alan Meier
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  6. Arturo Molina
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Corresponding author

Correspondence to Juana Isabel Méndez .

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Editors and Affiliations

  1. University of Florence, Florence, Italy

    Stefano Berretti

  2. Dolby Labs, California, CA, USA

    Guan-Ming Su

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Méndez, J.I., Medina, A., Ponce, P., Peffer, T., Meier, A., Molina, A. (2022). A Real-Time Adaptive Thermal Comfort Model for Sustainable Energy in Interactive Smart Homes: Part I. In: Berretti, S., Su, GM. (eds) Smart Multimedia. ICSM 2022. Lecture Notes in Computer Science, vol 13497. Springer, Cham. https://doi.org/10.1007/978-3-031-22061-6_17

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  • DOI: https://doi.org/10.1007/978-3-031-22061-6_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-22060-9

  • Online ISBN: 978-3-031-22061-6

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