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@article{195888,
        author = {RAYAVARAPU YAMINI and K. VANDHANA and J. SANTHOSHI KUMARI and T. CHARAN and Y. SAI VARDHAN and S. SRINIVAS and M. KARTHIKEYA},
        title = {Smart Lot: Adaptive Parking Management System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {912-924},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195888},
        abstract = {Urban parking management remains a persistent challenge in modern cities due to inefficient space utilization, increasing vehicle density, and reliance on costly infrastructure-based solutions. Traditional smart parking systems predominantly depend on Internet of Things (IoT) sensors, which require extensive hardware deployment and maintenance, limiting scalability and cost-effectiveness.
The proposed solution presents SMART LOT: Adaptive Parking Management System, a software-defined, vision-based approach that transforms conventional CCTV and IP camera feeds into an intelligent parking management framework. The system constructs a dynamic digital twin of the parking environment using a custom-trained object detection model based on YOLOv8, optimized for high-angle and real-world parking scenarios. 
A novel spatial mapping technique is employed to determine parking occupancy through geometric intersection analysis between detected vehicle regions and predefined parking slot areas. The system integrates a FastAPI-based backend for real-time processing and a graph-based routing mechanism utilizing Dijkstra’s algorithm to guide users efficiently to available parking spaces.
Experimental evaluation demonstrates that the proposed system significantly reduces deployment costs by eliminating the need for physical sensors while maintaining high detection accuracy and real-time responsiveness. The SMART LOT system provides a scalable, cloud-ready solution for smart city infrastructure, contributing to reduced traffic congestion and improved urban mobility.},
        keywords = {Smart Parking System, Computer Vision, YOLOv8, Parking Occupancy Detection, Digital Twin, Intelligent Transportation Systems},
        month = {April},
        }