5G-enabled Smart Buildings for Energy and Space Management

This project aims to propose a novel fifth generation (5G)-enabled machine learning based edge computing solution for the optimal energy and space management of smart buildings and implement it in hardware to validate its performance. The proposed solution exploits the energy and space management databases, enriched by the emerging advanced sensor technologies and 5G wireless communication networks in smart buildings. The proposed solution combines machine learning technologies with the edge computing paradigm to improve the proposed solution’s scalability, reliability, and efficiency while preserving end-user’s privacy. By leveraging the advanced 5G-enabled sensors and data analytics technologies, advanced control and 5G mobile edge computing (MEC) systems provided by the partner organization, the proposed solution will be implemented in hardware to evaluate its performance in practice. The expected outcome also includes a software monitoring platform, which can be utilized by the partner organization for their commercial building management systems.

Faculty Supervisor:

Bhushan Gopaluni;Yu (Christine) Chen;Vincent Wong


Peng Zhuang



Engineering - computer / electrical


Information and cultural industries


University of British Columbia


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