Drauig BMS (Border Monitoring System)

Project Overview

Drauig BMS is an AI-powered border monitoring system designed to support national security and trade compliance. The system integrates real-time surveillance, facial recognition, and AI-based threat detection to monitor cross-border movement and identify suspicious activities.

Key Features

• Real-time camera feeds and motion detection
• Facial recognition and anomaly alerts
• Trade analytics and compliance reporting
• Role-based access controls and audit logs

Technical Implementation

The system was built using OpenCV for video processing, TensorFlow for facial recognition models, and AWS for scalable infrastructure:

def detect_faces(frame):
    face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    
    for (x,y,w,h) in faces:
        cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)
        face = frame[y:y+h, x:x+w]
        features = extract_features(face)
        match = compare_with_database(features)
        
        if match['confidence'] > 0.9:
            alert_security(match['identity'])
    
    return frame

Results

• Streamlined border patrol operations
• Reduced manual inspection by 50%
• Improved accuracy in identifying persons of interest
• Enhanced trade compliance monitoring