Smart Fire-Detection-and-Mitigation system

This project integrates a fire detection system using a combination of sensors, a camera, and actuators. The system detects fires through both sensor data and a real-time camera feed, and responds accordingly with actuators like a fan and a submerged water motor to mitigate the detected fire.

Features

• Real-time Fire Detection: Uses a camera and computer vision (Haar Cascade) for detecting fire.
• Sensor Monitoring: Includes flame, temperature, and gas sensors to detect fire conditions.
• Automated Actuation: Controls a fan and water motor when a fire is detected.
• LabVIEW Interface: Provides real-time monitoring, control, and visualization of sensor outputs.

Sensors and Actuators

Sensors

• Flame Sensor: Detects visible flames.
• Temperature Sensor: Monitors ambient temperature to detect heat anomalies.
• MQ2 Gas Sensor: Detects the presence of flammable gases (e.g., propane, methane).
• Camera: Detects fire visually using a pre-trained Haar Cascade model.

Actuators

• Fan: Cools down the surrounding area when the temperature is high and work as a eshaust fan when gas detected.
• Submerged Water Motor: Activates to release water when a fire is detected.
• Buzzer: Alerts users when a fire or dangerous gas is detected.

Project Structure

Python Fire Detection Script (fire_detection.py)

• Performs real-time fire detection using a camera and Haar Cascade for image processing.
• Communicates over TCP/IP with the LabVIEW interface to send fire detection results.

LabVIEW Interface

• Monitors sensor outputs and controls the actuators.
• Displays real-time video feed for fire detection and graphical gauges for sensor outputs.

LabVIEW Interface

LabVIEW Interface Overview

• Live Video Feed: Shows the camera feed for real-time fire detection.
• Sensor Gauges:
  • IR sensor gauge with voltage output.
  • Temperature gauge with real-time temperature readings.
  • MQ2 gas sensor gauge indicating gas levels.
• Controls:
  • Set threshold values for the sensors (flame, temperature, gas) to trigger actuators.
• Outputs:
  • Indicator lights and gauges show whether fire or gas is detected.

Python Script (fire_detection.py)

Key Functions

• Server Setup: Acts as a TCP server, listening for commands.
• Image Processing: Processes the camera feed to detect fire using the Haar Cascade model.
• Result Communication: Sends detection results (1 for fire, 0 for no fire) back to the client (LabVIEW interface).
• Error Handling: Sends any errors encountered during image processing back to the client.

Usage

1. Run the Python Script:

   python fire_detection.py

2. Start the LabVIEW Interface: Configure the sensor thresholds and start monitoring through the VI file.

System Requirements

• Python 3.x
• OpenCV (cv2 library)
• LabVIEW
• Flame, temperature, MQ2 gas sensors, and a camera
• Fan, submerged water motor, and buzzer as actuators

Installation

1. Clone the repository:

   git clone https://github.com/ushariRanasinghe/Fire-Detection-and-Mitigation-

2. Install the required Python libraries:

   pip install opencv-python numpy

3. Run the Python Script:

   python fire_detection.py

4. Open LabVIEW VI: Configure thresholds, start the interface, and monitor the system.