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An Ontology-Based Framework for Building Energy Management with IoT

Engineering Product Development, Singapore University of Technology and Design (SUTD), 8 Somapah Road, Singapore 487372, Singapore
Electrical Engineering Department, Lahore University of Management Sciences (LUMS), Lahore 54792, Pakistan
School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD 4072, Australia
School of Software & Microelectronics, Peking University, Beijing 102600, China
Author to whom correspondence should be addressed.
Electronics 2019, 8(5), 485;
Received: 30 March 2019 / Revised: 26 April 2019 / Accepted: 27 April 2019 / Published: 30 April 2019
(This article belongs to the Special Issue Green Communications in Smart City)
PDF [2287 KB, uploaded 30 April 2019]


In this paper, we develop an ontology-based framework for energy management in buildings. We divide the functional architecture of a building energy management system into three interconnected modules that include building management system (BMS), benchmarking (BMK), and evaluation & control (ENC) modules. The BMS module is responsible for measuring several useful environmental parameters, as well as real-time energy consumption of the building. The BMK module provides the necessary information required to understand the context and cause of building energy efficiency or inefficiency, and also the information which can further differentiate normal and abnormal energy consumption in different scenarios. The ENC module evaluates all the information coming from BMS and BMK modules, the information is contextualized, and finally the cause of energy inefficiency/abnormality and mitigating control actions are determined. Methodology to design appropriate ontology and inference rules for various modules is also discussed. With the help of actual data obtained from three different rooms in a commercial building in Singapore, a case study is developed to demonstrate the application and advantages of the proposed framework. By mitigating the appropriate cause of abnormal inefficiency, we can achieve 5.7%, 11.8% and 8.7% energy savings in Room 1, Room 2, and Room 3 respectively, while creating minimum inconvenience for the users. View Full-Text
Keywords: energy management; building energy management systems; ontology and inference rule based framework; building benchmarking energy management; building energy management systems; ontology and inference rule based framework; building benchmarking

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Lork, C.; Choudhary, V.; Hassan, N.U.; Tushar, W.; Yuen, C.; Ng, B.K.K.; Wang, X.; Liu, X. An Ontology-Based Framework for Building Energy Management with IoT. Electronics 2019, 8, 485.

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