An IoT Framework for Modeling and Controlling Thermal Comfort in Buildings

Authors

Fadi Alsaleem, University of Nebraska-LincolnFollow
Mehari K. Tesfay, University of Nebraska-LincolnFollow
Mostafa Rafaie, University of Nebraska-LincolnFollow
Kevin Sinkar, DunAn Microstaq, Inc.
Dhaman Besarla, DunAn Microstaq, Inc.
Parthiban Arunasalam, DunAn Microstaq, Inc.

Document Type

Article

Date of this Version

6-2020

Citation

Alsaleem F, Tesfay MK, Rafaie M, Sinkar K, Besarla D and Arunasalam P (2020) An IoT Framework for Modeling and Controlling Thermal Comfort in Buildings. Front. Built Environ. 6:87. doi: 10.3389/fbuil.2020.00087

Comments

Copyright © 2020 Alsaleem, Tesfay, Rafaie, Sinkar, Besarla and Arunasalam.

Abstract

Humans spend more than 90% of their day in buildings, where their health and productivity are demonstrably linked to thermal comfort. Building thermal comfort systems account for the largest share of U.S energy consumption. Despite this high-energy cost, due to building design complexity and the variety of building occupant needs, addressing thermal comfort in buildings remains a difficult problem. To overcome this challenge, this paper presents an Internet of Things (IoT) approach to efficiently model and control comfort in buildings. In the model phase, a method to access and exploit wearable device data to build a personal thermal comfort model has been presented. Various supervised machine-learning algorithms are evaluated to produce accurate personal thermal comfort models for each building occupant that exhibit superior performance compared to a general model for all occupants. The developed comfort models were used to simulate an intelligent comfort controller that uses the particle swarm optimization(PSO) method to search for optimal control parameter values to achieve maximum comfort. Finally, a framework for experimental validation of the new proposed comfort controller that interactively works with the HVAC element has been introduced.