AI-Driven Smart Road Monitoring: A Case Study of Bilaspur Chhattisgarh
Author(s): Nazya Parveen 1, Anchal Sondhiya2, Abhay Singh Dahariya 3, Ramendra Kumar Mishra 4, Anjali Sharma5
Affiliation: 1Nazya Parveen PhD Scholar in Kalinga University, 2 Anchal Sondhiya M.Tech Civil engineering Vishwavidyalaya Engineering College Ambikapur CSVTU Bhilai Chhattisgarh, 3 Abhay Singh Dahariya M.Tech Civil engineering Vishwavidyalaya Engineering College Ambikapur CSVTU Chhattisgarh , 4 Dr. Ramendra Kumar Mishra Civil Engineering JK institute of Engineeering, 5Anjali Sharma M.tech Civil Engineering BIT Durg
Page No: 26-29-
Volume issue & Publishing Year: Volume 2 Issue 4,April-2025
Journal: International Journal of Modern Engineering and Management | IJMEM
ISSN NO: 3048-8230
DOI:
Abstract:
India’s rapid urbanization has significantly increased the strain on road infrastructure, leading to traffic congestion, poor road conditions, and higher accident rates. Bilaspur, Chhattisgarh, a growing commercial and transportation hub, faces similar challenges. This study explores the implementation of Smart Road Sensing Techniques (SRST) in Bilaspur to enhance real-time monitoring and road management. The proposed system integrates IoT sensors, Artificial Intelligence (AI), GPS tracking, and cloud computing to monitor traffic density, road deterioration, and accident-prone areas. A lab-based experimental analysis was conducted to validate the efficiency of smart road sensors in detecting potholes, road surface friction, and traffic load impact. The results demonstrated that accelerometer-based sensors could detect potholes with 95% accuracy, while friction analysis showed that asphalt roads degrade faster than concrete roads under heavy traffic loads. Field surveys on NH-130 and urban intersections like Satyam Chowk indicate that peak-hour congestion, potholes, and lack of predictive maintenance are major issues affecting commuters. The research highlights how SRST can improve traffic flow, reduce accidents, and provide cost-effective road maintenance solutions by integrating technology-driven interventions. By implementing real-time data analysis, local authorities can make better policy decisions and improve urban mobility and economic productivity. The lab experiments validate that smart road sensing can increase road lifespan, reduce maintenance costs by 20%, and improve road safety by 15-20%.
Keywords:
Smart roads, IoT-based monitoring, traffic congestion, real-time road sensing, Bilaspur infrastructure, AI-driven road maintenance.
Reference:
[1] Bianchini, F., Rossi, L., & Conti, G. (2023). Big data clustering for road maintenance. Journal of Transportation Engineering.
[2] Bilaspur Traffic Police. (2024). Traffic congestion and road safety report.
[3] Chhattisgarh Public Works Department (PWD). (2024). Annual Road Infrastructure Report.
[4] Liu, X., & He, L. (2021). AI integration for next-generation smart highways. Journal of Smart Transportation, 5(4), 212–225.
[5] Mateen, M., Kumar, R., & Sharma, P. (2022). AI-based accident detection systems. Sensors, 22(6), 2077.