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Smart city article details
| Title | Empowering The Capabilities And Service Optimization For Location Tracking And Management Of School Bus Passenger Density In Jakarta Through The Integration Of Cv-Ai |
|---|---|
| ID_Doc | 22951 |
| Authors | Nugroho R.I.R.; Panjaitan J.G.H.; Taloputri R.H.; Soepeno R.A.A.P.; Jatmiko N.W.; Arisandi E.D. |
| Year | 2024 |
| Published | 2024 Beyond Technology Summit on Informatics International Conference, BTS-I2C 2024 |
| DOI | http://dx.doi.org/10.1109/BTS-I2C63534.2024.10942085 |
| Abstract | The school public transportation mobile application is a mobile application that creates safe and secure school bus transportation. It has a real-time bus tracking location and notification to the parents while the student boards the bus. However, the lack of appropriate information in the mobile application leads to significant challenges for students in crowded cities, such as prolonged waiting times due to the absence of real-time information about bus capacity and bus arrivals at transit stations. This research proposed a system to empower the capabilities of the School Bus Information System and optimize services in Jakarta through the integration of Computer Vision Artificial Intelligence (AI) for location tracking and passenger density management. This research uses a GPS module for the bus location, a smartphone location sensor for the student location, a webcam for passenger counting, the Raspberry Pi 4 to process the data, a WIFI modem, and a Firebase Cloud server. This system provides real-time location tracking and also the real-time capacity of the bus, whether it is full or not. The information is then transmitted to a server, where students can access it with the smartphone app. It's also accessed by the bus operator and management in Jakarta to make a fast response decision whether they will add an extra bus to the specific location that is crowded with students. The result of this research significantly contributes to Jakarta's Smart Cities Mission by empowering the capabilities of the School Bus Information System, specifically enhancing the daily travel experience for students. By leveraging GPS technology for accurate location tracking and AI-based sensors for monitoring passenger count, the system effectively addresses key challenges in urban mobility, such as prolonged waiting times and overcrowding, which are particularly critical for young passengers. Overall, the experiment result showed that the system works as expected. © 2024 IEEE. |
| Author Keywords | Artificial Intelligence (AI); Computer Vision; Location Tracking; Passenger Density Management; Public Transport; Raspberry Pi; School Bus System |
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