I&T Wish - Development of Artificial Intelligence Lift and Escalator Automatic Inspection Planning System 2024-06-6
Development of Artificial Intelligence Lift and Escalator Automatic Inspection Planning System
I&T Wish
Development of Artificial Intelligence Lift and Escalator Automatic Inspection Planning System (REF: W-0536)
Matched I&T Solution
Trial Project
Summary and Challenges
In this project, we aim to develop an Artificial Intelligence lift and escalator inspection planning system to optimize the efficiency and effectiveness of lift and escalator inspection work, and thus, related law enforcement and regulatory work by lift and escalator inspection ranking with risk-based approach.
The system shall predict and forecast the most effective L&E inspection ranking based on big data to maintain maximized effectiveness of L&E inspections and sustain safety of lifts and escalators in Hong Kong without substantial increasing in manpower in future.
Project Challenges:
To process EMSD’s big data from various existing platforms and formats; the majority of provided data include the specifications of L&Es, relations between L&Es and registered lift/escalator contractors("RCs"), registered lift/escalator engineers ("REs"), registered lift/escalator workers ("RWs"), etc and the respective parties' past performance data; please note NO SENSOR DATA will be applied to this project;
Limited historical data for AI model to learn the rules;
To assist EMSD user to conduct the feature selection, risk level labelling and validate the risk ranking.
Expected Outcome
A recommender engine that can accurately ranking the riskiest L/E based on the big data;
Pipe line and transformation framework for conveying the updated big data to the recommender engine;
The engine shall able to refine the ranking according to the executed inspection result and various big data such as the incident database, issued warning letters and etc.
The engine shall able to export the ranking to other system for further processing;
95% or above accuracy preferred.
Expected Trial Duration
9-month
Contact Information
I&T Wish Proposer
:
Electrical and Mechanical Services Department (EMSD)