About This Architecture

ESP32-based plant health monitoring system integrates soil moisture, temperature, humidity sensors, and computer vision to detect plant diseases in real time. The system reads sensor data, captures plant images, and sends collected information via Wi-Fi to cloud-based AI for analysis and disease detection. When disease is detected, the system sends alerts; otherwise it displays healthy status and updates the Blynk Dashboard for remote monitoring. This architecture demonstrates practical IoT sensor fusion with edge computing and cloud AI integration for agricultural automation. Fork and customize this diagram to adapt sensor types, add additional environmental parameters, or integrate alternative cloud platforms and alerting mechanisms.

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How do I build an IoT plant monitoring system using ESP32 with disease detection?

This diagram shows a complete ESP32 plant monitoring workflow: initialize sensors for soil moisture and temperature/humidity, capture plant images, send data via Wi-Fi to cloud AI for analysis, detect diseases, and update a Blynk Dashboard with alerts or healthy status. The system loops continuously, enabling real-time remote monitoring and automated disease detection for smart agriculture applica