City Transit AI: Intelligent Transport Monitoring System
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Abstract
This paper presents the design and implementation of CityTransit AI, an intelligent public transportation monitoring system based on Internet of Things (IoT) technology. The proposed system aims to reduce passenger waiting time and improve public transportation efficiency by providing real-time bus tracking and arrival time prediction. The system uses a GPS module and ESP32 microcontroller to collect real-time bus location data such as latitude, longitude, and speed. The collected data is transmitted to the cloud server using Wi-Fi connectivity and displayed to users through a mobile application.
The system calculates the distance between the bus and passengers using the Haversine formula and estimates the arrival time based on average speed. The proposed system was implemented and tested in real-time conditions, and the results show acceptable accuracy and reliable performance. The system is low-cost, easy to deploy, and suitable for smart city transportation applications
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