|I&T Wish||AI Predictive Monitoring System for E&M Equipment
(REF : W-0148)
|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 Trial Duration||6 months|
Development of an AI monitoring system for E&M equipment
|Propose I&T Solution||Closed|