Smart Bicycle Speed and Location Monitor
Authors
Rodriguez Institute of Science and Technology Nagtahan Street (Philippines)
Rodriguez Institute of Science and Technology Nagtahan Street (Philippines)
Rodriguez Institute of Science and Technology Nagtahan Street (Philippines)
Rodriguez Institute of Science and Technology Nagtahan Street (Philippines)
Rodriguez Institute of Science and Technology Nagtahan Street (Philippines)
Rodriguez Institute of Science and Technology Nagtahan Street (Philippines)
Article Information
DOI: 10.51244/IJRSI.2026.13010138
Subject Category: COMPUTER ENGINEERING
Volume/Issue: 13/1 | Page No: 1600-1609
Publication Timeline
Submitted: 2026-01-19
Accepted: 2026-01-24
Published: 2026-02-07
Abstract
This study presents the design, development, and evaluation of a Smart Bicycle Speed and Location Monitoring System aimed at enhancing the safety of young cyclists through real-time monitoring and parental notification. The system integrates a Hall Effect sensor for accurate speed detection and a GPS/GSM module for continuous location tracking. Speed and location data are transmitted via GSM short message service (SMS) to a parent’s mobile device, including automated alerts when predefined overspeed thresholds are exceeded. Field testing conducted in urban and suburban environments demonstrated a mean speed measurement accuracy of 98% with a maximum deviation of ±0.3 km/h, and GPS positional accuracy within ±5–10 meters. The results indicate that the proposed system provides a reliable, low-cost, and practical IoT-based solution for improving youth cycling safety and parental supervision.
Keywords
Smart Bicycle, GPS Tracking, Hall Effect Sensor, GSM Communication
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References
1. System Using Hall Effect Sensor. Journal of Physics: Conference Series, 1339(1), 012018. https://doi.org/10.1088/1742-6596/1339/1/012018 [Google Scholar] [Crossref]
2. Devi, L., Bindushree, Deekshitha, & Likhith, M. (2016). Helmet Using GSM and GPS Technology for Accident Detection and Reporting System. International Journal on Recent and Innovation Trends in Computing and Communication. https://core.ac.uk/download/pdf/539906066.pdf [Google Scholar] [Crossref]
3. Fajar Hadi Hidayatullah, Maman Abdurohman, & Aji Gautama Putrada. (2021). Accident Detection System for Bicycle Athletes Using GPS/IMU Integration and Kalman Filtered AHRS Method. *2021 [Google Scholar] [Crossref]
4. International Conference Advancement in Data Science, E-Learning and Information Systems [Google Scholar] [Crossref]
5. (ICADEIS)*, 1–6. https://doi.org/10.1109/ICADEIS52521.2021.9702085 [Google Scholar] [Crossref]
6. Kiefer, C., & Behrendt, F. (2016). Smart e-bike monitoring system: real-time open source and open hardware GPS assistance and sensor data for electrically-assisted bicycles. IET Intelligent Transport Systems, 10(2), 79–88. https://doi.org/10.1049/iet-its.2014.0251 [Google Scholar] [Crossref]
7. Sodaq. (2023). Solar-Powered Asset Tracking: The Next Generation of IoT Sensors. https://sodaq.com/solar-powered-asset-tracking-the-next-generation-of-iot-sensors/? [Google Scholar] [Crossref]
8. Audette, R. (2023). Bicycle Dashcam. Hackaday.io https://hackaday.io/project/167941-bicycle-dashcam [Google Scholar] [Crossref]