I&T Wish - Using AI Recognition for Equipment Gauge Reading 2023-12-20
Using AI Recognition for Equipment Gauge Reading
I&T Wish
Using AI Recognition for Equipment Gauge Reading (REF: W-0521)
Matched I&T Solution
Trial Project
Summary and Challenges
In the hospital plant rooms, there are numerous traditional equipment gauges (~400), such as rotary meters and seven segment digital meters, that lack automated reading functionality. Consequently, technicians are required to manually record all the readings from these gauges on a daily basis using paper forms to identify any abnormalities. To streamline this workflow and automate the recording process, we are seeking a solution that utilizes AI meter recognition.
Expected Outcome
Develop an AI training model and algorithm capable of recognizing and reading various types of equipment gauges, including analog gauges, rotary meters with needles, digital meters with LCD displays, and seven segment displays.
The solution should include a mobile application that enables technicians to scan images of the gauges and retrieve the current readings mentioned in item (1).
The system should be able to recognize the gauge readings accurately by utilizing the developed AI training set.
The system should assign a systematic numbering system to differentiate between different meters in different plant rooms and store all the gauge readings in a centralized database. Additionally, it should facilitate the report generation and migration to existing electronic records.
The solution should comprise a web portal, report generation functionality, and a notification system to alert users if any of the meters exceed the normal operational range.
The AI training set of the system should be scalable and capable of learning new types of meters in the future.
Expected Trial Duration
9-month
Contact Information
I&T Wish Proposer
:
Electrical and Mechanical Services Department (EMSD)
