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Smart-Learning Networked Controllers for Centralized Air-Conditioning Systems Using Model-View-Controller Model

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Part of the Lecture Notes in Computer Science book series (LNIP,volume 10645)


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.


  • Machine learning
  • M5P algorithm
  • Internet-of-things system
  • Heating Venting and Air-Conditioning (HVAC)
  • Smart-Learning system and model-view-controller

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  • DOI: 10.1007/978-3-319-70010-6_68
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Special thanks to our client, Blue Snow Energy Sendirian Berhad (Shn Bhd) who shares the project idea and provides experiments testing point and hardware support. I also would like to thank my friend – Thanh C. Ngo, Rutgers University – who supported me on designing the app. This paper is presented based on a G52GRP group project with Tran Phuong Dung, Ahmad Kamal Kamariza, Wong Wei Thong, and Lim Jyy Bing from the University of Nottingham, Malaysia Campus.

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Correspondence to Tran Trong Tin .

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Tin, T.T., Yuan, C.Z., Selvaraj, K.R. (2017). Smart-Learning Networked Controllers for Centralized Air-Conditioning Systems Using Model-View-Controller Model. In: , et al. Advances in Visual Informatics. IVIC 2017. Lecture Notes in Computer Science(), vol 10645. Springer, Cham.

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  • Print ISBN: 978-3-319-70009-0

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