Smart-Learning Networked Controllers for Centralized Air-Conditioning Systems

What is it about?

This paper presents a smart system iBeam which is a smart learning and networked air conditioning system designing by using a Model – View – Controller (MVC) model. This is a learning and networked Internet of Thing (IoT) system that can predict the thermal comfort of the occupants and regulate the air-conditioning temperature using Machine Learning algorithm in order to give an ideal thermal comfort and indoor air quality with the most minimal vitality cost. This system consists of an Android app to collect user’s input, a server to run Machine Learning algorithm and to associate with a database that stores values from sensors such as temperature or humidity level. The app and the server communicate to each other through a Representational State Transfer web-service.

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Photo by Dewi Karuniasih on Unsplash

Photo by Dewi Karuniasih on Unsplash

Why is it important?

The use and cost of energy affects each of us every day in our lives. Many issues arise from the use of energy such as in gas emissions, climate change, and dependency on deleting supplies of fossil fuels, which is the main resource to generate electricity and it is limited. Buildings in Malaysia consume more than industry and transport combined, in which cooling system accounts for 65%, triples as much as lighting. With the threat of global warming and increasing energy cost, keeping the room cool with less energy will become increasingly important in the future.

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