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Smart Strawberry Farming Using Edge Computing and IoT.

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This study introduces an IoT platform for strawberry farming, using AI and computer vision to detect diseases and monitor environmental conditions, improving crop management and reducing pesticide use.

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Area of Science:

  • Agricultural Technology
  • Plant Pathology
  • Environmental Monitoring

Background:

  • Strawberry farming faces significant challenges from pests, diseases, and environmental factors like extreme temperatures and humidity.
  • Intensive use of agrochemicals and pesticides is common due to crop sensitivity, posing environmental and health concerns.
  • Existing farming monitoring systems are often fragmented, lacking integrated data analysis and real-time detection capabilities.

Purpose of the Study:

  • To develop an integrated edge technology platform for comprehensive data management in strawberry farming.
  • To enhance disease detection accuracy and environmental monitoring for improved crop yield and quality.
  • To provide a reliable, unified digital farming solution mitigating disease and environmental impacts.

Main Methods:

  • Development of an Internet of Things (IoT) platform integrating data collection, analysis, prediction, and detection services.
  • Implementation of a computer vision model (Yolo v5) for real-time detection of seven common strawberry diseases with high accuracy.
  • Integration of machine learning for outlier detection in collected data and LoRa communication for long-distance data transmission.

Main Results:

  • The developed IoT platform successfully integrates diverse monitoring services for digital strawberry farming.
  • The computer vision model achieved 92% accuracy in real-time detection of common strawberry diseases.
  • The system demonstrated effective data management, environmental monitoring, and disease mitigation capabilities during on-farm testing.

Conclusions:

  • The proposed IoT edge technology offers a robust solution for precision agriculture in strawberry farming.
  • The integrated system effectively addresses challenges related to disease, environmental stress, and data management.
  • This technology has the potential to reduce agrochemical dependency and improve the sustainability of strawberry production.