The Intelligent Disaster Management System with Alternative Energy and AI-Powered

Objective

The objective of our project is to transition from human-based observation to a camera-based system. Cameras have a much longer viewing distance than humans, and our system provides notifications much faster than manual methods, helping to avoid danger more effectively.

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How Does It Work?

Our project has three main components:

1. Wildfire Detection Pole: This pole is set up in the forest to detect fires.
2. Data Center: It receives information from the Wildfire Detection Pole and sends it to the internet, allowing users to monitor the temperature and other data around the pole.
3. Application: A mobile app that provides essential wildfire-related features and notifications.

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Application Features

Our application includes five key features:

1. Wildfire Location

   • The app displays the locations of active wildfires. For example, if there are wildfires in three places, it lists those locations for easy reference.

2. Hotline Call

   • Users can directly call emergency hotlines from within the app.

3. Location Sharing

   • Users can share their current location with others. For instance, if someone is in the forest during a wildfire, they can send their location to request help.

4. Environmental Data

   • The app provides real-time data, including temperature, humidity, and gas levels around the pole.

5. Alert System

   • If a wildfire is detected, a red circle appears on the map to indicate the affected area. Users within this red circle receive a notification sound, prompting them to evacuate the danger zone.

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The Wildfire Detection Pole

The Wildfire Detection Pole integrates the following components:

• Raspberry Pi Pico Board: Handles environmental sensors and initial data processing.
• Raspberry Pi 5 Board: Controls the camera and processes image data for object detection.
• Camera System: Rotates back and forth to scan the environment and detect wildfires.

How It Works

1. The Raspberry Pi 5 connects to the Raspberry Pi Pico and the camera, controlling the camera's rotation.
2. The camera uses an object detection system to identify wildfires. When a wildfire is detected:
   • The camera stops rotating and captures images of the wildfire.
   • These images, along with temperature and humidity data, are sent to the Data Center.
3. If no wildfires are detected:
   • The camera continues rotating and pauses for 30 seconds after completing a full rotation.
   • Temperature and humidity data are sent every 30 minutes.

Data Transmission

• Data is encoded in two stages for efficiency
  1. Run-Length Encoding (RLE): Compresses the data to reduce size.
  2. Alphabet Replacement Encoding: Further compresses the RLE data for transmission.
• The encoded data is sent to the Data Center via the NRF module.