Currently, the EMSD processes over 500 type approval applications for lifts and escalators each year, involving approximately 7,000 safety component models. These approval records are stored in a database in EMSD’s backend system. As the approval process involved a huge amount of technical data, the current approval process is facing several challenges including
increasing number of applications,
lack of automated workflow,
difficulty in on-site verification of compliance with respect to the type approval document, and
lack of transparency of approval data and status.
The Smart Lifts & Escalators Design Approval Platform shall be designed, developed and implemented with Optical Character Recognition (OCR), Artificial Intelligence (AI), and Big Data technologies. OCR technology shall be used to facilitate specific data extraction from the submitted design documents, mostly in the form of scanned images of documents. While AI and Big Data technologies shall be used to enhance the accuracy of the OCR function of the platform, the platform shall also provide an automatic approval function for vetting of the submitted technical documents.
The platform shall also be well integrated and developed to facilitate e-submission of type approval application such as receiving documents for equipment details and specifications, comparing data, verifying compliance, issuing approval, and up-keeping records.
It is expected when the platform development finished, its OCR function and automatic approval function could achieve an accuracy of 90% or better.
Expected Trial Duration
I&T Wish Proposer
Electrical and Mechanical Services Department (EMSD)