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@article{203896,
        author = {Harsh Amit Jagota and DR. A.R Kulkarni},
        title = {Pothole Volume Estimation Using LiDar-Based 3D Reconstruction},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {1521-1525},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=203896},
        abstract = {Potholes on road surfaces present significant safety hazards and demand reliable methods for detection and quantification. This study introduces a LiDAR enabled, smartphone-based approach for estimating pothole volume through three-dimensional reconstruction. Depth data captured via LiDAR sensors is processed into a point cloud representation of the road surface, which is subsequently converted into a continuous mesh using Poisson surface reconstruction. The pothole volume is determined by comparing the reconstructed mesh against a reference road plane, enabling precise volumetric assessment. The proposed framework offers a low-cost, scalable, and automated solution for road condition monitoring, making it well-suited for real world infrastructure management and maintenance applications.},
        keywords = {Pothole Volume Estimation, LiDAR Sensing, Three-Dimensional Reconstruction, Point Cloud Processing, Poisson Surface Reconstruction, Road Surface Condition Assessment, Infrastructure Monitoring.},
        month = {June},
        }