Year: 2025
Type: article
Abstract: This paper presents a comprehensive, cost-effective, and intelligent surveillance system utilizing the AI Thinker ESP32-CAM module, integrating real-time video streaming, human detection, and audible alerts for enhanced security. Designed for applications such as home monitoring, industrial safety, and especially border surveillance, the system leverages a PIR motion sensor to trigger video capture and streaming via a local network. With video frames processed through a locally hosted Flask server using YOLO and Open CV for object detection, the presence of a person activates a buzzer and enables instant alerts through IoT connectivity. By combining low-cost hardware, open-source software, and deep learning techniques, including convolutional neural networks for robust performance in low-light and complex scenarios, the project offers a scalable and autonomous security solution. Specifically addressing India’s extensive 15,106 km border with its neighboring countries, this system demonstrates significant potential for securing restricted and high-risk areas, effectively merging AI and IoT to meet modern surveillance demands.
DOI: 10.46632/jeae/4/2/56
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4411122309