AI-Energy Optimization Solution for HVAC System in Real Time Video Analytics

I&T Solution AI-Energy Optimization Solution for HVAC System in Real Time Video Analytics
(REF : S-0566)
Trial Project
Solution Feature
  • The objective of AI Energy Optimization Solution (“AI-EOS”) is to manage and optimize HVAC plants from a global point of view, and the re-commissioning process will be executed to search for energy saving opportunities.
  • AI-EOS is different to the traditional BMS, where its focus usually on monitoring, scheduling and optimizing set of HVAC equipment independently.
  • AI-EOS is introduced to enhance the energy efficiency and improve the user experience. Beside of responds to the real-time system load, the system reacts to real-time condition, including indoor temperature, humidity and number of people. With a global consideration of HVAC operation status, AI-EOS will select optimal set-points automatically.
  • CCTV camera with built-in people counting function can detect and tracks number of people. CCTV can observe the most stayed areas from the data of number of people and average stand time.
  • By interfaced with BMS, AI Control algorithm will be applied in HVAC System and applied with the CCTV camera with people counting function, for enhancing energy saving feature and system performance.
Trial Application and Expected Outcome
  • The effectiveness and performance of AI-EOS can be largely deviated due to different ambient environment and internal loading demand and the evaluation period is preferably be longer in order to averaging both the positive and negative effect to the AI-EOS performance.
  • A 2-week evaluation is proposed for determination the AI-EOS performance. During the evaluation period, the AI-EOS operation will be taken place by the first 7 days and the next 7 days will be using BMS operation mode.
  • During the evaluation period, all required logging data will be extracted from the BMS accordingly. The evaluation will based on the extracted data and determine the performance of the AI-EOS.
Info on I&T Solution Provider
Solution Provider:REC Green Technologies Company Limited
Address:Units A-D, 15/F., Goodman Kwai Chung Logitics Centre, 585-609 Castle Peak Road, Kwai Chung, Hong Kong
Contact Person:Ms. Carmen Wong
Position:General Manager
Tel: 26198817
Email: rgt@rec-eng.com
Webpage: www.rec-gt.com

For details of the above I&T solution, please contact the I&T solution provider.