AI Predictive Monitoring System for E&M Equipment

Title of I&T Wish AI Predictive Monitoring System for E&M Equipment
(REF : W-0148)
Project Summary and Challenges

This project calls for an innovative solution to monitor the operation status of various E&M equipment with the use of LoRaWAN sensors with edge-based artificial intelligence (AI).

With learning ability itself, the sensor node would learn about the operation pattern and thus deduce the need to take necessary maintenance. The sensor node would monitor various E&M equipment, including but not limited to: (i) Air compressor; (ii) Engine; (iii) Cold Group Air Conditioner; (iv) Transformer; (v) Power Generator; (vi) Pump; and (vii) Power Supply.

Operation status and data patterns would be reflected in back-end web-based applications with a user-friendly graphical user interface. Such information could serve as performance indicators for the maintenance parties to take predictive and preventive maintenance.

 

Expected Outcome This project aims to quantify the operation status of the E&M equipment as the performance indicator for the maintenance parties to undertake predictive and preventive maintenance.
Expected Project Duration 6 months
Contact Information

Contact Person: Ms. Karen Cheung Pui Yi

Position: Electronics Engineer

Tel: 3757 6193

Email: inno@emsd.gov.hk

Project Deliverables

Development of an AI monitoring system for E&M equipment