Aegis Architect is a high-performance, real-time industrial monitoring and security system. It features a C++ Core for high-speed telemetry and a Python Intelligence Layer that provides real-time web visualization, SQLite persistence, and predictive anomaly detection with an automated "Kill Switch" mechanism.

• High-Speed Emitter (C++): Simulates industrial sensor data (Voltage & Current) with low-latency UDP broadcasting.
• AI Intelligence (Python): Uses Scikit-Learn trained models to predict anomalies in real-time based on historical power surge patterns.
• Web Dashboard: A responsive, dark-themed Flask-SocketIO interface for live monitoring without page refreshes.
• Automated Defense: Integrated "Kill Switch" that sends a /SHUTDOWN command back to the C++ core upon anomaly detection.
• Reliable Logging: Persistent data storage using SQLite, ensuring all telemetry is recorded for post-incident analysis.
• Bi-Directional Communication: Full-duplex communication between C++ and Python using UDP protocols.

Aegis doesn't just watch; it thinks. The Python "Mind" uses a pre-trained classification model to analyze every incoming packet.

1. Data Ingestion: Receives voltage/current data via UDP.
2. Inference: AI model evaluates the risk level.
3. Action: If an anomaly (surge) is detected, Aegis automatically triggers a remote shutdown of the C++ Core to prevent hardware damage.

TheArchitect/
├── aegis_app.py # Main Python Entry (AI, Flask & SocketIO)
├── core/ # C++ Source files (The Emitter & Listener)
├── templates/ # Web Dashboard HTML
├── data/ # SQLite Database (aegis_records.db)
└── models/ # Pre-trained AI Models (aegis_brain.pkl)
## How to Run
1. Requirements
 MSYS2 (UCRT64) with GCC/G++
 Python 3.12+
 Required Python Packages:
 Bash
 pip install flask flask-socketio scikit-learn joblib
2. Execution
 Start the Intelligence Layer:
 Bash
python aegis_app.py
Ignite the Core: Run your compiled aegis_core.exe from the terminal.
Access the Dashboard: Open your browser and navigate to http://127.0.0.1:5000