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@article{203913,
        author = {Ms. Renuka Ashok Mallade and Prof.Vijay.J.Patil},
        title = {Smart EV Parking Bay with Automatic EV Identification and Occupancy Monitoring using IoT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {1204-1212},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=203913},
        abstract = {The accelerating adoption of electric vehicles (EVs) has created a critical demand for intelligent and policy-compliant parking infrastructure. However, existing parking systems lack automated mechanisms to enforce EV-only parking regulations, resulting in misuse by non-electric vehicles and inefficient resource utilization. This paper presents a smart EV parking bay with automatic EV identification and occupancy monitoring using IoT that integrates Radio Frequency Identification (RFID), Internet of Things (IoT), and embedded systems to enable automated vehicle authentication, real-time occupancy monitoring, violation detection, and time-based billing. The system employs an ESP32 microcontroller for local processing, ultrasonic sensors for occupancy detection, and cloud connectivity for centralized monitoring and analytics. Authorized EV users are identified using RFID tags, enabling automated billing based on parking duration, while unauthorized vehicles trigger violation alerts. A web-based dashboard provides real-time visibility into parking status, billing records, and usage patterns. The proposed system offers a scalable, cost-effective, and reliable solution for deployment in smart cities, commercial spaces, and public EV charging infrastructures. It significantly enhances operational efficiency, ensures policy enforcement, and contributes to sustainable urban mobility.},
        keywords = {Smart Parking, Electric Vehicles, RFID Authentication, IoT, Automated Billing, Violation Detection},
        month = {June},
        }