Risk AI

Risk AI is a real-time IoT and AI-powered dashboard designed to predict industrial hazards before they happen. It monitors environmental conditions (Temperature, Humidity, CO2, Acetone) and uses a predictive algorithm to detect gas leaks and critical trends in real-time.

(Replace this link later with a screenshot of your actual dashboard)

• Real-time Monitoring: Live updates every 2 seconds from ESP32 sensors.
• AI Risk Prediction: Algorithms analyze the rate of change (slope) to predict leaks before hazardous levels are reached.
• Critical Alerts: "Zooming" Red Alert overlay when danger is detected.
• Historical Analytics: Aggregates data by "Hour of Day" to show long-term safety trends (e.g., "Is 2 PM always dangerous?").
• Dark Mode Dashboard: Professional React-based UI with Recharts visualization.

Microcontroller: ESP32 (NodeMCU / Wemos)

Sensors:

• DHT11 (Temperature & Humidity)
• MQ-135 (Air Quality / Gas)

Actuators:

• Relay
• WaterPump
• Buzzer
• Servo motor

Wiring:

• DHT11 Data → Pin D4
• DHT11 VCC → Pin 3V3
• MQ-135 Analog → Pin D34
• Servo → Pin D27
• waterpump → red → NC , Black → VCC powersupply
• Relay "in" → Pin D26 , GND → GND ESP , VR → 5V ESP , COM → common groung , NC → Pump
• Buzzer → Pin D18 , small leg → ground

You can run this project in two ways: Docker (Recommended) or Manual Setup.

This method requires no installation of Python or Node.js. It runs the entire system in an isolated container.

• Windows: Install Docker Desktop.
• Linux:

  sudo apt install docker.io docker-compose-v2

git clone git@github.com:mohammedmokhtar2/RiskAI-IoT-System.git
cd RiskAI-IoT-System

docker compose up --build

• Frontend: http://localhost:5173
• Backend: http://localhost:5000

If you want to edit the code, run it manually.

• Python 3.9+
• Node.js 20+

# Open a terminal in the root folder
python3 -m venv venv
source venv/bin/activate  # On Windows use: venv\Scripts\activate
pip install -r requirements.txt
python app.py

# Open a NEW terminal
cd frontend
npm install
npm run dev

1. Power on the ESP32.
2. It will create a WiFi Hotspot named RiskAI_Hotspot.
3. Connect your laptop WiFi to this hotspot.
   • Password: 12345678
4. Once connected, the Python Backend will automatically start fetching live sensor data.

If testing without hardware, open app.py and set MOCK_MODE = True to simulate sensor data.

RiskAI/
├── app.py                 # Flask Backend (API & Database Logic)
├── risk_ai.db             # SQLite Database (Auto-created)
├── requirements.txt       # Python Dependencies
├── docker-compose.yml     # Docker Orchestration
├── frontend/              # React Frontend
│   ├── src/
│   │   ├── App.jsx        # Main Dashboard Logic & Charts
│   │   └── App.css        # Dark Mode Styling
│   └── Dockerfile         # Frontend Container Config
└── README.md              # Documentation

• Hardware Engineer: Hossam Mostafa
• Software Engineer: Mohammed Mokhtar , Eyad Rezk , Tarek shereen , Amr Khaled

Built with React, Flask, Recharts, and ESP32.