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#EHD127 AI Based Smart Farming

AI Based Smart Farming

Project Fee:Negotiable

Project Discount:0

Project Duration:One Month

AI Based Smart Farming.

1. Introduction

The AI-Based Smart Farming project uses artificial intelligence, sensors, and automation to improve agricultural productivity and resource management. The system collects data about soil moisture, temperature, humidity, and crop conditions to support intelligent farming decisions. By integrating AI-based analysis with automated irrigation and crop monitoring, the project aims to reduce resource wastage and promote sustainable agriculture.

2. Objectives

  • Improve farming efficiency using AI.

  • Monitor soil and environmental conditions.

  • Automate irrigation based on soil moisture.

  • Identify potential crop diseases.

  • Reduce water and resource wastage.

  • Support data-driven agricultural decisions.

3. Methodology

  • Integrate sensors to collect soil and environmental data.

  • Connect sensors to an ESP32 or Raspberry Pi.

  • Develop an AI model to analyze collected data.

  • Use soil moisture readings to control irrigation.

  • Apply image processing for crop disease detection.

  • Display sensor readings and AI predictions through a monitoring interface.

  • Test system performance under different farming conditions.

4. Instrument List

  • ESP32 or Raspberry Pi

  • Soil moisture sensor

  • Temperature and humidity sensor

  • Camera module

  • Water pump and relay module

  • AI model and Python software

  • Irrigation pipes

  • Power supply and connecting wires

  • Monitoring display or IoT dashboard

5. Working Principle

  • Sensors collect data about soil and environmental conditions.

  • The controller transfers the collected data for processing.

  • The AI model analyzes the data to identify patterns and predict potential crop problems.

  • Soil moisture readings help determine when irrigation is required.

  • The controller operates the water pump according to programmed conditions.

  • The monitoring interface displays sensor data, irrigation status, and AI-based results.

6. Advantages

  • Intelligent crop monitoring

  • Automated irrigation management

  • Efficient water utilization

  • Early identification of crop problems

  • Reduced manual effort

  • Improved resource management

  • Supports sustainable agriculture

7. Conclusion

The AI-Based Smart Farming project demonstrates how artificial intelligence, sensors, and automation can improve agricultural management. By monitoring crop conditions, supporting irrigation decisions, and identifying potential plant diseases, the system can help farmers use resources more efficiently. Further development can improve prediction accuracy, crop monitoring, and practical field performance.

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𝐂𝐨𝐧𝐭𝐚𝐜𝐭 𝐃𝐞𝐭𝐚đĸđĨđŦ:

📞 01894-801150, 01886-180101

📧Email: projects.zeronebd@gmail.com

🌐Web: https://www.projects.zeronebd.com 

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