I&T Wish - Artificial Intelligence (AI) Based Accident Prevention System for Escalators 2019-06-10
Artificial Intelligence (AI) Based Accident Prevention System for Escalators
I&T Wish
Artificial Intelligence (AI) Based Accident Prevention System for Escalators (REF: W-0181)
Matched I&T Solution
Trial Project
Summary and Challenges
Apart from equipment failure, the occurrence of escalator accidents is mostly related to human behavior which is in turn affected by many factors, such as age and health condition of passenger, time of the day using escalator etc. This project will make use of video images captured just before the occurrence of past escalator accidents and identify their correlations with various human factors using AI technology. The developed system would be used to compare with the real-time images captured in MTR stations so that it can evaluate the chance of occurring similar escalator accidents on spot and then implement preventive measures to prevent the occurrence of similar escalator accidents. In case there is a high chance of re-occurrence of similar incident, appropriate MTR station staff will be notified immediately to provide timely assistance to passengers in need and public address system will announce caution messages to alert the concerned passengers for drawing their attention on the safe use of escalator.
Expected Outcome
To develop a AI based system to predict the chance of escalator incidents and implement preventive measures accordingly.
Expected Trial Duration
22 months (2 months for collection of historical incident data and corresponding CCTV images, 6 months for data analysis and preparation of implementation strategy, 14 months for pilot implementation and trial run)
Contact Information
I&T Wish Proposer
:
Electrical and Mechanical Services Department (EMSD)
1. To capture the video images near the time of occurrence of past escalator accidents; 2. To develop a software programme to analyze the video images and identify the correlation of accident occurrence with respective human factors; 3. To make use of the correlation and compare the real-time images captured in MTR stations; 4. To notify appropriate railway staff for appropriate action; and 5. To announce caution messages via public address system to alert the concerned passengers for drawing their attention on the safe use of escalator
