IoT Based Smart Border Security System
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.
Publication Details
- Journal
- Journal on Electronic and Automation Engineering
- Published
- 2025-06-07
- DOI
- https://doi.org/10.46632/jeae/4/2/56
- Primary Topic
- IoT and GPS-based Vehicle Safety Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00