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
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article

IoT Based Smart Border Security System

Journal on Electronic and Automation Engineering
IoT and GPS-based Vehicle Safety Systems
article

IoT Based Smart Border Security System

article en

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.

Journal on Electronic and Automation EngineeringVol. 4(2 June 2025)
Openalex Percentile: Top 87%
IoT and GPS-based Vehicle Safety Systems
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