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Protecting Agricultural Fields from Fire: A Scilab-Based Data Logger Solution

Agricultural fields are at constant risk from threats like fire, which can cause significant damage to crops and livelihoods. This article introduces an innovative Scilab-based data logger system designed to detect fires early and protect your fields. Using simple, readily available components, this system helps safeguard crops by monitoring environmental data such as temperature, light, and gas levels. Here’s how you can implement this fire-protection system and understand its workings.

Protecting Agricultural Fields from Fire: A Scilab-Based Data Logger Solution

Components Needed for the Fire Detection System

This fire-detection system is centered around a combination of sensors and the Scilab platform. Below is a breakdown of the essential components:

ComponentQuantity
Power supply (12V/1.5Amp)1
Arduino UNO1
Jumper wire M-M20
Jumper wire M-F20
Jumper wire F-F20
Power supply extension1
MQ135 (Air quality sensor)1
MQ6 (Gas sensor)1
Light sensor1
Temperature sensor1
Touch sensor1

All these components can be sourced from specialized electronics suppliers, and they are quite affordable. You can find most of these at websites like NuttyEngineer.com.


Circuit Setup: Step-by-Step Guide

To build the system, follow these connection steps for each sensor:

  1. Air Quality (MQ135) Sensor: Connect the output pin to pin A1 of the Arduino and the +Vcc and GND pins to a 5V power supply.
  2. Gas Sensor (MQ6): Connect the output pin to pin A2 of the Arduino, and the power pins to the 5V supply.
  3. Light Sensor: Attach the output to pin A0 of the Arduino, with +Vcc and GND connected to the 5V supply.
  4. Temperature Sensor: Connect the sensor output to pin A3 of the Arduino and supply power similarly.
  5. IR Fire Sensor: Attach the output pin to pin 6 of the Arduino.
  6. Touch Sensor: Connect the output to pin 7, with power going to 5V.
  7. Indicator LEDs: Connect two LEDs to pins 5 and 4 to indicate sensor status, using 330-ohm resistors.

The system uses Scilab to process the data from the sensors, making the process automated and efficient.


Using Scilab for Fire Detection

Once your hardware is in place, the next step is setting up Scilab to communicate with the Arduino. Here’s how you do it:

  1. Download and Install Arduino I/O for Scilab: This is the software package that allows Scilab to interface with the Arduino.
  2. Upload the Program: Upload the “toolbox_arduino_v3_ino” code to your Arduino board, which will allow it to read sensor data.
  3. Connect Scilab to Arduino: Use Scilab’s GUI to establish a connection with the Arduino for real-time data collection.

Protecting Agricultural Fields from Fire: A Scilab-Based Data Logger Solution

Building the XCOS Model in Scilab

XCOS is a graphical tool in Scilab used for modeling dynamic systems. Follow these steps to create the XCOS model for this fire-detection system:

  1. Open Scilab and launch the XCOS window.
  2. Navigate to the “Palette Browser” from the view menu.
  3. Add necessary blocks from the block window into the blank workspace.
  4. Complete the model as per the system’s requirements and run it to start receiving sensor data.

This XCOS model will help in real-time visualization of the data collected from the field sensors. The system creates waveforms (as shown in Fig. 10.4 and Fig. 10.5) to monitor environmental changes in real-time.


Tips for Implementation:

  • Ensure Proper Placement: Place the sensors across critical areas in your field for comprehensive coverage.
  • Regular Maintenance: Keep the sensors clean and in working condition to avoid false alarms or missed detections.
  • Test the System: Before relying entirely on the system, run it multiple times in a controlled environment to ensure accurate detection.

Summary for Instagram Reels or Canva Infographics:

  • Introduction: Highlight the importance of fire protection in agriculture.
  • Component List: Display the necessary components for the data logger system.
  • Circuit Setup: Simplify the process with a quick overview of sensor connections.
  • Scilab Integration: Mention the steps to integrate Scilab for real-time monitoring.
  • Actionable Tips: Share insights on sensor placement and maintenance.
  • Conclusion: Reinforce the importance of early fire detection using affordable technology.

By following this guide, you can create a simple yet effective fire detection system to protect your agricultural fields from disaster.

Protecting Agricultural Fields from Fire: A Scilab-Based Data Logger Solution

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