Study on Smart Queue on MRT Passengers

The effectiveness of human movement is one of the main factors of “Crowd Management”. One real example is the movement of Mass Rapid Transit (MRT) passengers at the platform door who will enter to sit/stand there.

The crowd resulting from irregular queues and the movement of MRT passengers can be a medium for disease transmission in addition to system inefficiency.

Adaptive Queue Line System (AQLS) is the answer to this problem. AQLS will provide layout information for passengers to prepare them where to queue on the platform and where to sit after.

AQLS is the product of the Industrial Engineering lecturer, Sugiono, Ph.D., together with his three colleagues; Dr. Willy Satrio Nugroho and Teuku Anggara, ST., MT (Alumni of Mechanical Engineering UB), and Dr. Andi Sudjana Putra (National University of Singapore).

Sugiono explained, this product will be very useful for MRT management to obtain passenger density information in real-time.

“This information can be used to decide in managing MRT schedule, optimal service provision, and other operational management needs,” he said.

The head of the Ergonomics Laboratory continued, the system works by capturing images of chairs and identifying human presence using cloud machine learning services. The physical representation of MRT is translated into data representation using the internet of things (IoT).

The data is then streamed using the asynchronous API to the API endpoint. The endpoint is then accessed by the display computer on the destination station to provide visual information.

Aside from being used as transportation modes, this system also has the potential to be implemented in offices and sports analysis.

This AQLS has been tested on the appropriate environment and system parameters in the field and the feasibility of product studies and business documents has been carried out with the conclusion that the product is safe and low-cost.