Abstract
With the onset of the Internet revolution and development in hardware, IoT has become an integral part of our lives, optimising various aspects of day-to-day activities. An important role of IoT is played in providing thermal comfort through smart heating, ventilation, and air conditioning (HVAC) systems. The smart AC proposed in this paper aims to create a pleasant thermal environment with minimal human intervention, according to various personal and environmental parameters using a case-based expert system. The novelty of this system is a case-based expert system that has been implemented with querying and analytics to identify and set the temperature of the AC. Based on users’ prior settings, preferences, and ambient conditions, the knowledge base will continue to expand. Moreover, if the user overrides the actuated temperature with a preference of his/her own, this will be stored as a new case in the case database. This smart AC system also considers the theory that resulted from studies on the variation in human temperature caused by human thermoregulation. Integrating all of these factors, the most similar case is extracted from the case database using the k-NN regression similarity criteria. The system has been optimised to minimise the number of re-computations with respect to actuation and the number of retrievals performed on the knowledge base. Equipped with cloud-based data utilisation, behavioural query analytics, and historical query analytics, this futuristic system possesses the ability to automatically perform optimal actuation on the air conditioner, making it more convenient and user friendly than its present-day counterparts.
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Sundaram, A., Ravishankar, H., Subbiah, U., Kadiresan, N., Karthika, R. (2021). Case-Based Expert System for Smart Air Conditioner with Adaptive Thermoregulatory Comfort. In: Paprzycki, M., Thampi, S.M., Mitra, S., Trajkovic, L., El-Alfy, ES.M. (eds) Intelligent Systems, Technologies and Applications. Advances in Intelligent Systems and Computing, vol 1353. Springer, Singapore. https://doi.org/10.1007/978-981-16-0730-1_27
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