Digital Twin with AI Efficiency Optimization using Semantic Knowledge Graph, BIM, BIM-AM, iBMS

I&T Wish Digital Twin with AI Efficiency Optimization using Semantic Knowledge Graph, BIM, BIM-AM, iBMS
(REF : W-0506)
Matched I&T Solution
Trial Project
Summary and Challenges
  • EMSD is providing the operation and maintenance (O&M) engineering services for Government buildings. However, it is difficult to analyze the real-time situation without the simulation of 3D spatial information to visualize the correlation in E&M assets. The assets relationship is currently avialable on the BIM-AM platform and the iBMS can provide real-time operational information. With a centralized and standalone platform, colleagues are more-effective to locate the point of failure and handle the contingency measures.
Expected Outcome
  • We propose to use Metadata from BIM and integrated Building Management System (iBMS) as the input parameter. AI algorithm will be developed to calculate the correlation between the input and energy output to build a digital twin to simulate the situation of the chiller plant.
  • It is expected to provide two deliverables, including the digital twin to visualize the real-time information and use an AI algorithm to optimize energy efficiency.
Expected Trial Duration 6-month
Contact Information
I&T Wish Proposer:Electrical and Mechanical Services Department (EMSD)
Contact Person:Karlen SHEK
Position:Electronics Engineer/Building Information Modelling/6
Tel: 9637 0093
Email: klshek@emsd.gov.hk
Upload Date 2023-10-04
Closing Date 2023-10-18
Propose I&T Solution Closed