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Automatic Tagging of a Commercial Building System's Meta Data for Energy-Saving and Operational Efficiency Applications.

Team members

Wang Zihao (ESD), Wu Tong (ESD), Lu Yidan (ISTD), Li Tiantian (ESD), Gou Yuanyuan (ISTD), Liu Xiangyu (ESD), Zhang Siyao (ESD)


Cyrille Pierre Joseph Jegourel, Stefano Galelli, Ying Xu

Writing Instructors:

Nurul Wahidah Binte Mohd Tambee

Industry Partner

Technovator International Ltd is a leading building energy-saving solution provider within the building management systems market. It designs, manufactures, and distributes integrated building automation and energy management systems to system integrators and distributors


Project Background and Objective

The operational data collected from sensors installed in buildings are unstructured and difficult to comprehend, and a manual and labor-intensive process is required to tag the data with standardized and readable tags before potential energy-saving opportunities can be identified in building management systems(BMS).

This project aims to develop an automated solution for tagging and analysis of IoT devices' data in order to identify potential energy-saving opportunities for BMS.


Syetem Architecture


Tagging Model

屏幕快照 2020 08 12 上午12 08 45

Machine learning models were used to learn the tagging convention in sample data. The model is used to create tags correspond to the file name.


Data Analysis

Based on the tags on each raw data file, data analysis is carried out generate insights and discover potential energy saving opportunities.

data analysis


The visualization of insights and other findings are presented in the form of a webpage














student Wang Zihao Engineering Systems and Design
student Wu Tong Engineering Systems and Design
student Lu Yidan Information Systems Technology and Design
student Li Tiantian Engineering Systems and Design
student Gou Yuanyuan Information Systems Technology and Design
student Liu Xiangyu Engineering Systems and Design
student Zhang Siyao Engineering Systems and Design
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