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@article{171932,
        author = {Avish Dinesh Kumar and Ashik A J and Nagprasanna Hebri and Nidhish D S and Dr. Shivananda V. Seeri},
        title = {Park-Insight: Parking Vacancy Detection System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {1327-1330},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=171932},
        abstract = {“Park-Insight” applies the technology deep learning, combined with computer vision, in building efficient scalable solutions for parking space management, making a Convolutional Neural Network which can be used in a model that categorizes occupied versus free parking in a given video feed input based in real-time; it's based on open processing of video data using OpenCV and has given power in this system web interface through Flask so that access for users would become user-friendly. This automated system saves time searching, reduces the rate of traffic congestion, and optimizes the efficiency of parking. It will benefit operators, ensuring that space usage is optimized to deliver valuable insights with a modern and intelligent solution in managing urban parking.},
        keywords = {Parking management, Deep learning, CNN, Real-time detection, Smart city, OpenCV, Flask, VGG16, Sustainability},
        month = {January},
        }