🏠 AI-Powered Home Security System Using Deep Learning & OpenCV

📌 Project Description:


This project develops a real-time AI home security system that detects intruders, unknown faces, and suspicious activities using Deep Learning (CNNs) & OpenCV. The system can send alerts when an unrecognized person is detected.

🔹 Key Phases of the Project:

✔ Dataset Collection & Preprocessing

  • Use pre-existing face datasets (CelebA, LFW) or collect images of household members.
  • Apply OpenCV for face detection & feature extraction.
  • Perform image augmentation for better model accuracy.

✔ Face Recognition Model

  • Train a CNN-based model (ResNet, FaceNet, or MobileNet) to classify known vs. unknown faces.
  • Use OpenCV’s Haar Cascades or Dlib’s HOG for real-time face tracking.

✔ Intruder Detection & Alerts

  • Detect unknown faces using OpenCV & Deep Learning.
  • Send email or SMS alerts when an unrecognized face is detected.

✔ Deployment

  • Use Flask/Gradio for a simple web interface.
  • Allow users to view live surveillance and check alerts.
  • Optionally, integrate with Raspberry Pi for an IoT setup.

📂 Project Deliverables:

✅ 📊 Professional PPT – Covers face detection, deep learning model & security features.
✅ 📁 Dataset & Source Code –

  • Face dataset for training.
  • OpenCV-based real-time detection script.
  • Alert system (email/SMS integration).
  • 💰 Project Price: ₹7,500/-

A simple yet powerful AI project for home security using Deep Learning & OpenCV! 🚀