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Development of Sustainable Indoor Air Quality for Air-Conditioning System Using Smart Control Techniques

Oye, Tosin T.; Gupta, Naren; Goh, Keng; Oye, Toyosi K.

Authors

Tosin T. Oye

Naren Gupta

Toyosi K. Oye



Abstract

Air-conditioning as a technical solution to protect inhabitants from excessive heat exposure creates the challenge of expanding indoor health effects. While air-conditioning has mostly been applied as an improvement to living conditions, health and environmental problems associated with its use frequently occurs. Therefore, this paper challenges and extends existing knowledge on sustainability related to the smart air-conditioning systems. The decrease of CO2 level in building requires an intelligent control system because energy utilisation has been legitimately connected with wellbeing and eventually to operational expenses. A building’s indoor environmental essential factors of comfort are IAQ, visual and thermal. Through an appropriate structured controller, the performance of indoor control system can be altogether improved. It merits creating innovative control techniques to optimise the indoor environment quality for air-conditioning system. The newly proposed backpropagation neural network was optimised using Matlab to control the CO2 level appropriately while carefully taking into account the performance of system controllers such as the stability, adaptability, speed response and overshoot. The controller of indoor environment was designed, and the proportional-integral-derivative control was utilised as a result of its suitability. The smart controllers were designed to regulate the parameters automatically to ensure the optimised control output. The indoor CO2 possesses an appropriate time constant and settling time of 2.1s and 27.3s, respectively. Therefore, utilising smart control techniques to exterminate various indoor health effects is expected to produce sustainable living conditions.

Journal Article Type Article
Acceptance Date Nov 7, 2021
Online Publication Date Nov 18, 2021
Publication Date 2021
Deposit Date Jul 11, 2022
Publicly Available Date Jul 11, 2022
Journal Environmental Management and Sustainable Development
Print ISSN 2164-7682
Publisher Macrothink Institute
Peer Reviewed Peer Reviewed
Volume 11
Issue 1
DOI https://doi.org/10.5296/emsd.v11i1.19027
Keywords Sustainability, Air-conditioning, Indoor air quality, CO2, Neural networks, Proportional-integral-derivative, Backpropagation
Public URL http://researchrepository.napier.ac.uk/Output/2885992

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