Implementation of non-pharmaceutical intervention of COVID-19 in MRT through engineering controlled queue line using participatory ergonomics approach

The viral transmission in public places and transportations can be minimized by following the world health organization (WHO) guideline. However, the uncertainty in a dynamic system complicates the social engagement to the physical distancing regulation. This study aims to overcome this obstacle in MRT stations and train by developing an adaptive queue line system. The system was developed using low-cost hardware and open-source software to guide passengers using visual information. The system works by capturing seat images and identify the presence of humans using a cloud machine learning service. The physical representation of MRT was translated to data representation using the internet of things (IoT). The data then streamed using an asynchronous API with a representative endpoint. The endpoint is then accessed by a display computer in the destination station platform to provide visual information. The visual information was ergonomically designed with visual display principles, including the minimum content load, layout, color combination, and dimension of contents. The design of the system was evaluated by Markov simulation of virus transmission in train and usability testing of the visual design. The implementation of the system has balanced the queue line capacity in station and crowd spots distribution in MRT. The system was effective due to the visual cortex manipulation by visual information. Consequently, the aerosol and falling droplets' viral transmission radius can be reduced. Accordingly, the chance for airborne transmission can be lowered. Therefore, the adaptive queue line system is a non-pharmaceutical intervention of viral transmission diseases in public transportatio

Impact of elevated outdoor MRT station towards passenger thermal comfort: A case study in Jakarta MRT

Comfort of the train passengers is the main priority of modern mass rapid transit (MRT) management. Objective of this paper is to investigate the thermal comfort of the elevated MRT station in tropical climate. The first step of this study was to conduct literature review on human thermal comfort, environment ergonomics, computational fluid dynamic (CFD), computational aeroacoustics (CAA), and predicted mean vote (PMV). Air quality in elevated MRT station was measured based on several parameters: relative humidity, wind speed, temperature, and wind direction. A 3D model of MRT designed was used to describe existing condition prior to simulations with CFD and CAA softwares. Predicted mean vote is arranged based on the value of metabolism, wind speed, ambient temperature, mean radiant temperature, amount of insulation from clothing, and relative humidity. Whereas predicted percentage of dissatisfi ed (PPD) can be derived from PMV calculations. The analysis shows that the average PMV of existing condition for elevated outdoor MRT station is 3.6 (extremely hot) with PPD is 100% (all passengers felt discomfort). Some recommendations to reduce heat stress were addressed such as: adding plant, changing materials of the MRT station, and change the design of the elevated MRT station. Modifying open elevated MRT station into indoor elevated MRT station with installing six units of AC (2pk, ±23°C) can improve air quality and maintain the thermal comfort scale of PMV to be –0.04 (comfort) with PPD of < 8%. Based on the analysis, it can be concluded that the most suitable design for elevated MRT station in tropical climate (hot and humid) is indoor MRT station with pay attention to both direct and indirect heat exposure that hit the station