Semantic AI on Predictive Maintenance of Permanent Way of Railway System

I&T Wish Semantic AI on Predictive Maintenance of Permanent Way of Railway System
(REF : W-0387)
Matched I&T Solution
Trial Project
Summary and Challenges This project aims to develop a proof of concept (PoC) on predictive maintenance of Permanent Way (PWay) by applying AI semantic model to analyze PWay data including incident data, asset data, maintenance data, real-time condition data and other information in the public domain.

Remarks: The solution provider should provide a I&T solution proposal to EMSD on or before the closing date. It should include a preliminary design idea with block diagram, workflow and budgetary ballpark cost estimate. EMSD may invite the proposer to conduct a presentation on its proposal.
Expected Outcome
  • To perform data analysis of the PWay data provided by EMSD, to generate insights for predictive maintenance;
  • To develop AI models to identify relationships within the PWay data and provide predictive results;
  • To design and implement a system to demonstrate proof of concept of the proposed AI analytic;
  • To build a clustered database including columnized database and graph-based database;
  • To integrate the different database clusters in the PWay data to perform data analytic and predictive functions. The system should also provide visualization tools using a knowledge graph and user interface to display the analytic results; and
  • To submit a report on the proposed system architecture, results of data integration and findings/insights for predictive maintenance.
Expected Trial Duration 3-month
Contact Information
I&T Wish Proposer:Electrical and Mechanical Services Department (EMSD)
Contact Person:Mr Kinson LAM
Position:Senior Engineer/Railways 9
Tel: 3912 0612
Upload Date 2021-10-22
Closing Date 2021-11-05