🛡️ Getfund Watch — AI-Powered Security & Threat Detection System

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🚀 Overview

Getfund Watch is a real-time, AI-powered surveillance and threat detection system designed for campuses, hostels, and secure environments.

It transforms traditional CCTV systems into an intelligent monitoring platform capable of:

• Identifying individuals in real time
• Detecting human activity using AI
• Capturing unknown or suspicious faces
• Logging and tracking events for analysis

Built to simulate modern surveillance systems used in high-security environments.

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🎯 Problem

Most surveillance systems:

• Only record footage (no intelligence)
• Cannot identify individuals
• Require manual monitoring

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💡 Solution

Getfund Watch introduces:

• Real-time AI detection
• Automated recognition system
• Smart alerting + logging
• Multi-camera integration

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🔥 Core Features

• 🤖 AI Face Recognition Engine
• 👁️ YOLOv5 Person Detection
• 📸 Automatic Threat Snapshots
• 🎥 Multi-Camera Support (USB, ONVIF, IP, Bluetooth)
• 🚨 Real-Time Alerts
• 🖥️ Advanced Monitoring Dashboard
• 🗄️ MySQL Storage System

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📸 System Demonstration (Real Output)

🎥 Real-Time Detection Engine

• Detects humans in real time
• Draws bounding boxes
• Runs continuously on live feed

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🧠 Face Recognition System

• Identifies known individuals
• Displays confidence scores
• Tracks identity across frames

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📸 Security Snapshot Logging

• Captures unknown individuals
• Stores timestamped evidence
• Supports quick actions (search/delete)

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🔍 Live Person Search

• Upload image → search in live feed
• Real-time matching
• Useful for investigations

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⚙️ Detection Control Panel

• Adjust detection thresholds
• Control recognition sensitivity
• Switch performance modes

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📴 No Camera / Idle State

• Clean fallback UI
• Prevents system errors
• Production-ready UX

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🧠 System Architecture

Camera Sources (USB / IP / ONVIF)
            ↓
   Frame Capture Layer
            ↓
   AI Processing Engine
   (YOLOv5 + Face Recognition)
            ↓
   Threat Detection Logic
            ↓
   Logging & Alert System
            ↓
   MySQL Database
            ↓
   PyQt5 Dashboard

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🔄 Workflow

1. Camera feed is captured
2. AI processes frames
3. Faces are recognized or flagged
4. Unknown persons trigger alerts
5. Snapshots stored in database
6. Dashboard updates in real time

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🛠️ Tech Stack

Core

• Python 3.11
• PyQt5

AI / Vision

• YOLOv5
• Mediapipe
• ONNX Runtime

Storage

• MySQL

Media

• OpenCV
• Pygame

Protocols

• ONVIF
• RTSP / HTTP

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⚙️ Installation

git clone https://github.com/qwame2/GetfundWatch.git
cd GetfundWatch
pip install -r requirements.txt

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Configure Database

Edit credentials in:

run.py

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Run

python run.py

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🔐 Security Design

• Facial data stored securely
• Event logs for auditing
• Real-time monitoring capability
• Designed for controlled environments

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📈 Use Cases

• 🏫 Campus Security
• 🏨 Hostel Monitoring
• 🏢 Office Surveillance
• 🚔 Restricted Areas

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🔮 Future Improvements

• Multi-camera synchronization
• Edge AI deployment
• Distributed monitoring system
• Advanced anomaly detection

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👨‍💻 Author

Adomako Emmanuel AI Systems Developer | Cybersecurity Focused