The IoT-based granary monitoring system is designed to track real-time storage conditions with temperature, humidity, and gas sensors like (ds18b20, HS1101, MQ-135, MiCS-5526, MH-Z19B). Data is sent over the MQTT protocol to MongoDB a cloud-based platform and displayed in an interactive web interface for real-time insights using ReactJS. Users will be automatically alerted when predefined thresholds are breached so that they can intervene in real time to prevent spoilage. Comparable IoT-based agricultural monitoring systems are available, though they tend to be limited by scalability and real-time monitoring. This is a scalable, automated, real-time monitoring and energy-efficient system as compared to conventional storage systems. Performance evaluation comprises the high accuracy of sensor response, rapid response time, and reduced rates of spoilage. The experimental results achieved an accuracy of 85% in tracking the environmental condition; the notification response time is under 5 s outpacing traditional system. Its efficiency in storage management is better than the existing ones. The future enhancements concern AI predictive analytics with blockchain integration for better security and decision-making for agricultural storage. This solution seeks to enhance food security and minimize waste in farm storage.

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Iot-Based Automated Smart Granary Monitoring System for Real-Time Monitoring

  • G. Karthick Kumar,
  • B. Nantha Kumar,
  • R. Nishanthan,
  • R. Ranjith,
  • S. Dhanasekar,
  • D. Sathish Kumar

摘要

The IoT-based granary monitoring system is designed to track real-time storage conditions with temperature, humidity, and gas sensors like (ds18b20, HS1101, MQ-135, MiCS-5526, MH-Z19B). Data is sent over the MQTT protocol to MongoDB a cloud-based platform and displayed in an interactive web interface for real-time insights using ReactJS. Users will be automatically alerted when predefined thresholds are breached so that they can intervene in real time to prevent spoilage. Comparable IoT-based agricultural monitoring systems are available, though they tend to be limited by scalability and real-time monitoring. This is a scalable, automated, real-time monitoring and energy-efficient system as compared to conventional storage systems. Performance evaluation comprises the high accuracy of sensor response, rapid response time, and reduced rates of spoilage. The experimental results achieved an accuracy of 85% in tracking the environmental condition; the notification response time is under 5 s outpacing traditional system. Its efficiency in storage management is better than the existing ones. The future enhancements concern AI predictive analytics with blockchain integration for better security and decision-making for agricultural storage. This solution seeks to enhance food security and minimize waste in farm storage.