AI-EOS designed to optimize the energy consumption of the central air-conditioning system, it responds to the real-time system load and changes in the external weather condition to continually monitor and control different system components. With big data analysis, the optimal set points can be calculated to reach the lowest energy consumption of the system while maintaining the thermal comfort of the occupants. The effects of the equipment degradation are also taken into consideration by the software solution. The first application project of AI-EOS, Holiday Inn Express Hong Kong SoHo, reaches 30% in system energy saving performance.

AI-EOS has been implemented in other public projects, and the results are significant. Besides EOS, we plan to apply the BIG Data Analysis to other applications, such as the control of sewage plant pumping station.


Applications:

AI-EOS is not only applicable in new buildings. With the high level interface, it is able to implement the control algorithms to communicate with existing iBMS.

• Existing Building
  • EOS can be integrated to the new BMS platform directly.
• New Building
  • Communicates with the existing BMS via high level interface e.g. Open Protocol (BACnet/Lonworks).
  • The operation data of HVAC system will be shared to EOS through high level interface.
• Requirements
  • Chiller with high-level interface
  • High-level interface with BMS by Open Protocol. (e.g., BACnet, Lonworks, Modbus, etc.)