International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Intelligent Road Maintenance Robot |
|---|---|
| ABSTRACT | The rapid degradation of urban and highway infrastructure presents a critical challenge for global transportation safe-ty and economic efficiency. Conventional road maintenance strategies are often hampered by high operational costs, human error, and significant safety risks to maintenance crews. This paper proposes the design and implementation of an Intelligent Road Maintenance Robot, an autonomous system engineered to detect, analyze, and remediate pave-ment defects without human intervention. Traditional road repair methods are often labor-intensive, hazardous for workers, and result in significant traffic disrup-tions. This paper presents the design and development of an Intelligent Road Maintenance Robot (IRMR) capable of autonomous distress detection and localized repair. By integrating computer vision algorithms with an automated dispensing system, the robot can identify asphalt cracks and potholes in real-time without human intervention. The system utilizes a high-resolution camera sensor to feed visual data into a deep-learning model, which classifies the severity of road damage. Once a defect is localized, the robot’s onboard processing unit coordinates a precise filling mechanism to apply repair materials. Preliminary testing indicates that the robot significantly improves the consisten-cy of surface treatments while reducing operational costs and human exposure to roadside risks. Experimental results demonstrate that the robotic platform significantly reduces the time required for surface assess-ment compared to manual methods, while maintaining a lower margin of error in material usage. By transitioning from reactive labor to proactive automation, this research provides a scalable solution for sustainable infrastructure man-agement, contributing to the development of smart city frameworks and safer transit networks. |
| AUTHOR | ANKITA MAHENDRA BANDIVADEKAR, AARYA ASHOK BOLKE, JANHAVI PRASHANT CHAVAN, RICHA KISHOR CHAVAN, SAKSHI LAXMAN CHAVAN, ARYA SOMA GAONKAR, S.S. KOLAPATE Student, Yashwantrao Bhonsale Institute of Technology, Sawantwadi, Maharashtra, India Faculty, Yashwantrao Bhonsale Institute of Technology, Sawantwadi, Maharashtra, India |
| VOLUME | 180 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1401067 |
| pdf/67_Intelligent Road Maintenance Robot.pdf | |
| KEYWORDS | |
| References | 1. F. Samadzadegan, F. D. Javan, and F. Nex," Automatic Road Pavement Distress Recognition Using Deep Learning Networks from Unmanned Aerial Imagery". 2. M. Ahmad and S. Suthar," Automated Pothole Discovery and Filling Robot with IoT Integration," International Journal of Research in Engineering and Technology. R. Kumar and S. Tung," Pavement torments covering on a stretch of NH- 44( India) using DCNN," Innovative structure results,. A. Adeniran- Bakare et al.," Civil engineering smart me-tropolises road conservation with a data- driven approach of machine literacy and IOT," Discover Internet of effects. 3. L. Zhao and Y. Wu," Vision- Grounded Automated Pavement torture examination A Comprehensive Review of Cur-rent State- of- the- art," IEEE Xplore. K. Singh and D. Kapoor," Computer- Vision Grounded Object Discovery and Recognition for Service Robots in Urban surroundings," Computers, Accoutrements & Continua |
