🛡️ AI-Powered Border Surveillance System | Real-Time Anomaly Detection + YOLOv8 Object Detection + Azure Cloud + Streamlit Dashboard | GTU Internship Project 2026

This project develops a real-time terrain classification system for defense using deep learning, multispectral aerial imaging, and LiDAR data. A CNN with decision-level fusion enhances accuracy in near-border surveillance, classifying sandy, rocky, marshy, and grassy terrains from a 45,000-image dataset.

This project aims to detect drones in border surveillance settings using deep learning models. It classifies images into `Drone` vs `Non-Drone`.

AI-Driven-Border-Security-and-Strategic-Management-System In this project we introduced an AI-Driven Border Security System designed to enhance real-time surveillance and threat detection. The system integrates cutting-edge deep learning models and classical computer vision techniques to ensure robust performance in complex border environments.

In this project we introduced an AI-Driven Border Security System designed to enhance real-time surveillance and threat detection. The system integrates cutting-edge deep learning models and classical computer vision techniques to ensure robust performance in complex border environments.

This project develops a surveillance robot for border and space regions, enhancing safety with an ESP32-CAM for real-time video streaming and night vision. It features manual and autonomous control via IoT, a metal detector for threat identification, and an air quality monitoring system with Arduino. Data is displayed and stored for analysis.

🛡️ AI-Powered Border Surveillance System | Real-Time Anomaly Detection + YOLOv8 Object Detection + Azure Cloud + Streamlit Dashboard | GTU Internship Project 2026

Developed a real time application i.e. Surveillance System which monitor 24/7 on the restricted area like Border, Bank Locker etc. By using this application we protect a Restricted area more safer, smarter and self sufficient.

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Defense sector project :- Intelligent Border Surveillance System for Threat Automated Detection

Defence & Border Surveillance Decision Dashboard — Web Programming Project, Semester [4], [VIT CHENNAI]

This is a research based project emphasising mainly on border surveillance using UAVs

Agentic AI-based human detection and alert system for Border Surveillance (BSF project)

It is a page that displays photos and videos related to the project "Border Surveillance UAV with Face Recognition".

The project aims to leverage artificial intelligence (AI) techniques to enhance border security measures. By automating various aspects of border surveillance and control, the system aims to improve efficiency, accuracy, and responsiveness in monitoring and managing border activities.

This project develops an AI-based Border Defence and Surveillance System using Machine Learning and Deep Learning to automate monitoring, detect threats, and improve response efficiency. It reduces reliance on manual observation, enabling faster, more accurate, and reliable surveillance.

Project: Border Defence & Surveillance – AI-Powered System This project is an AI-based security system designed to automatically monitor and protect India's border areas. Instead of relying on human guards to watch camera feeds 24/7, this system uses artificial intelligence to do it automatically.

This is a work, which is a part of project that I am currently working upon named"Border Surveillance" in which I have to perform object detection using Deep Learning and this repo contains annotated images converted into videos

This project leverages deep learning techniques to detect changes in satellite imagery for enhancing surveillance and security across India's borders. It focuses on automated analysis to identify potential threats, intrusions, or environmental shifts using state-of-the-art image processing and neural networks.

A real-time surveillance and inventory monitoring system for cross-border defense. This project leverages deep learning (UNet++), computer vision, and cloud integration to detect, classify, and track weapons, vehicles, and infrastructure using satellite and field images. Equipped with a React.js dashboard, Firebase backend, and MongoDB Atlas.

The EO/IR (Electro-Optical / Infrared) Project is a real-time vision-based surveillance and tracking system designed to capture, detect, and track targets using both visible (EO) and infrared (IR) sensors. This system is useful in applications such as defense, border security, drone vision, search and rescue, and wildlife monitoring.