Transforming urban mobility with internet of things: public bus fleet tracking using proximity-based bluetooth beacons - Elijah, Olakunle; Keoh, Sye Loong; bin Abdul Rahim, Sharul Kamal; Seow, Chee Kiat; Cao, Qi; bin Sarijari, Mohammad Adib; Ibrahim, Noor Farizah; Basuki, Achmad (Frontiers in the Internet of Things, 2023)
In today’s fast-paced world, efficient and reliable public transportation systems are crucial for optimising time and reducing carbon dioxide emissions. However, developing countries face numerous challenges in their public transportation networks, including infrequent services, delays, inaccurate and unreliable arrival times, long waiting time, and limited real-time information available to the users. GPS-based systems have been widely used for fleet management, but they can be a significant infrastructure investment for smaller operators in developing countries. The accuracy of the GPS location can be easily affected by the weather condition and GPS signals are susceptible to spoofing attacks. When the GPS device is faulty, the entire location traces will be unavailable. This paper proposes the use of Internet-of-Things (IoT)-enabled Bluetooth Low Energy (BLE) systems as an alternative approach to fleet tracking for public bus service. The proposed approach offers simplicity and easy implementation for bus operators by deploying BLE proximity beacons on buses to track their journeys, with detection devices using Raspberry Pi (RPi) Zero strategically placed at terminals and selected stops. When the bus approaches and stops at the bus stops, the BLE advertisements emitted by the proximity beacons can be reliably detected by the RPi Zero. Experiment results show that the BLE signals can be detected up to 20 m in range when the RPi Zero is placed inside a metal enclosure. The location of the bus is then sent to the cloud to estimate the arrival times. A field trial of the proposed IoT-based BLE proximity sensing system involving two public bus services in southern Malaysian cities, namely, Johor Bahru, Iskandar Puteri and Kulai is presented. Based on the data collected, a bus arrival time estimation algorithm is designed. Our analysis shows that there was a 5–10 min reduction in journey time on public holidays as compared to a normal day. Overall, the paper emphasises the importance of addressing public transportation challenges. It also describes the challenges, experience, and mitigation drawn from the deployment of this real-world use case, demonstrating the feasibility and reliability of IoT-based proximity sensing as an alternative approach to tracking public bus services.