A critical appraisal of various implementation approaches for realtime pothole anomaly detection: Towards safer roads in developing nations

Bello-Salau, HOnumanyi, Adeiza JAdebiyi, RFAdekale, ADBello, RSAjayi, O2024-02-152024-02-152023-10Bello-Salau, H., Onumanyi, A.J., Adebiyi, R., Adekale, A., Bello, R. & Ajayi, O. 2023. A critical appraisal of various implementation approaches for realtime pothole anomaly detection: Towards safer roads in developing nations. Engineering Proceedings, 56(1). http://hdl.handle.net/10204/136032673-4591https://doi.org/10.3390/ASEC2023-15519http://hdl.handle.net/10204/13603Road infrastructure is essential to national security and growth. Potholes on the road surface causes accidents and costly automotive damage. Novel technology that detects potholes and alerts drivers in real time may address this challenge. These approaches can improve road safety and lower vehicle maintenance cost in resource-constrained developing nations. This study reviews deep learning and sensor-based pothole detection approaches. Analysis shows that deep learning computer vision-based algorithms are most accurate, but computational and economic constraints limit their use in developing nations like Nigeria. Meanwhile, the sensor-based solutions are cost-effective and can be utilized in developing nations for potholes detection.FulltextenComputer visionPothole detectionDeep learningLiDARRoad infrastructureA critical appraisal of various implementation approaches for realtime pothole anomaly detection: Towards safer roads in developing nationsArticleBello-Salau, H., Onumanyi, A. J., Adebiyi, R., Adekale, A., Bello, R., & Ajayi, O. (2023). A critical appraisal of various implementation approaches for realtime pothole anomaly detection: Towards safer roads in developing nations. Engineering Proceedings, 56(1), http://hdl.handle.net/10204/13603Bello-Salau, H, Adeiza J Onumanyi, RF Adebiyi, AD Adekale, RS Bello, and O Ajayi "A critical appraisal of various implementation approaches for realtime pothole anomaly detection: Towards safer roads in developing nations." Engineering Proceedings, 56(1) (2023) http://hdl.handle.net/10204/13603Bello-Salau H, Onumanyi AJ, Adebiyi R, Adekale A, Bello R, Ajayi O. A critical appraisal of various implementation approaches for realtime pothole anomaly detection: Towards safer roads in developing nations. Engineering Proceedings, 56(1). 2023; http://hdl.handle.net/10204/13603.TY - Article AU - Bello-Salau, H AU - Onumanyi, Adeiza J AU - Adebiyi, RF AU - Adekale, AD AU - Bello, RS AU - Ajayi, O AB - Road infrastructure is essential to national security and growth. Potholes on the road surface causes accidents and costly automotive damage. Novel technology that detects potholes and alerts drivers in real time may address this challenge. These approaches can improve road safety and lower vehicle maintenance cost in resource-constrained developing nations. This study reviews deep learning and sensor-based pothole detection approaches. Analysis shows that deep learning computer vision-based algorithms are most accurate, but computational and economic constraints limit their use in developing nations like Nigeria. Meanwhile, the sensor-based solutions are cost-effective and can be utilized in developing nations for potholes detection. DA - 2023-10 DB - ResearchSpace DP - CSIR J1 - Engineering Proceedings, 56(1) KW - Computer vision KW - Pothole detection KW - Deep learning KW - LiDAR KW - Road infrastructure LK - https://researchspace.csir.co.za PY - 2023 SM - 2673-4591 T1 - A critical appraisal of various implementation approaches for realtime pothole anomaly detection: Towards safer roads in developing nations TI - A critical appraisal of various implementation approaches for realtime pothole anomaly detection: Towards safer roads in developing nations UR - http://hdl.handle.net/10204/13603 ER -27242