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@article{203019,
        author = {LALITHA BODDEDA and A. RAMANA BABU and M.LALITHA and S. PRAKASH and K. VINAY and N. KARTHIK},
        title = {OBJECT DETECTION USING ESP32 CAM IN REALTIME},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {9723-9730},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=203019},
        abstract = {The ESP32-CAM based Real-Time Object Detection System is a low-cost embedded vision solution designed for smart surveillance and monitoring applications. The system utilizes the ESP32-CAM module, which integrates a Wi-Fi enabled microcontroller with an OV2640 camera. It captures real-time images and streams video over a wireless network. The device processes visual data using embedded programming and supports integration with machine learning models. Lightweight object detection algorithms are implemented to identify objects in real time. The system is programmed using Arduino IDE and C/C++ language. It can transmit captured data to a web server or cloud platform for remote monitoring. The compact design makes it suitable for IoT-based applications. It consumes low power and operates efficiently in real-time environments. The system supports image capture, video streaming, and motion detection features. It can be applied in security systems, smart homes, and industrial monitoring [2] [1]
The wireless capability eliminates the need for complex wiring. The project demonstrates the integration of embedded systems with artificial intelligence. It provides a scalable and cost-effective smart vision solution. Overall, the ESP32-CAM enables real-time intelligent monitoring in modern IoT applications [2]},
        keywords = {ESP32-CAM, Object Detection, Internet of Things (IoT), Deep Learning, Tensor Flow, Computer Vision, CNN, Real-Time Monitoring, Embedded Systems, Edge Computing, Smart Surveillance. [7]},
        month = {May},
        }