Analysis of Lift and Escalator Reportable Incidents

I&T Wish Analysis of Lift and Escalator Reportable Incidents
(REF : W-0299)
Matched I&T Solution
Trial Project
Summary and Challenges

In order to improve efficiency, this project aims to develop an Artificial Intelligence (AI) system that automate the data extraction and data analysis of lift and escalator reportable incidents from the following forms "Notification of Incident Involving a Lift(s) or an Escalator(s)" (LE27), "Full Investigation Report for Lift / Escalator Incident" (LE29) and "Preliminary Investigation Report for Lift / Escalator Incident" (LE28).

The project is required to use AI Natural Language Processing (NLP) technology to recognize handwriting and typewriting characters from the forms, in Traditional Chinese, Simplified Chinese and English, or a mixture of the three. The recognized data should be stored in Excel file and the existing Lift and Escalator Ordinance System through API call. After data extraction, the system should perform data classification and data analysis. It should create reports and dashboard to visualize the analyzed data, and a summary report that describe the trend of incidents in words.

Project Challenges:

  1. Need to perform image tuning on the scanned forms.
  2. Need to adopt AI NLP to analyse the semantic meaning so as to aid the recognition of handwriting characters and the data classification.
  3. Need to generate summary report which describe the trend in words.
Expected Outcome
  • AI NLP aided data extraction and user-friendly User Interface for manual cross-checking and correction.
  • Comprehensive Excel with all the fields of the forms and indicate any outstanding and late submission.
  • API calls to the existing system for storing the forms information.
  • Data classification, data analysis, generate reports and followed by a dashboard that show the analyzed data with statistics by graphs and charts.
  • Summary report to describe analyzed data and correlation between incidents quarterly or yearly in words in detail.
Expected Trial Duration 5 months
Contact Information
I&T Wish Proposer:Electrical and Mechanical Services Department (EMSD)
Contact Person:Mr YIU Yung Ngai
Position:Engineer/General Legislation 3/2
Tel: 28083540
Upload Date 2020-08-12
Closing Date 2020-08-26