Smart Plant Monitoring System

Abstract

The Smart Plant Monitoring System is designed to improve the health, growth, and safety of plants using modern IoT and artificial intelligence technologies. The system provides real-time monitoring of soil moisture, temperature, humidity, and light intensity using sensor hardware, combined with AI-based plant disease detection through image processing. It helps farmers, plant enthusiasts, and agricultural researchers monitor plant conditions continuously and receive intelligent recommendations for better crop management. The system is developed using a Python Flask backend, PyTorch-based deep learning for disease detection, ESP32-CAM hardware, Claude AI integration, SQLite database, and a glassmorphism HTML/CSS/JS frontend with Chart.js visualizations. Overall, it improves plant health management, reduces manual monitoring effort, and provides a reliable intelligent solution for modern precision agriculture.

Plant phenotyping relevance

植物の状態をセンサーと画像処理で継続的に取得し、AIによる病害検出を中核機能とする監視プラットフォームであり、単なる生物学的実験のルーチン測定ではない。

Code and data availability

The paper describes a Smart Plant Monitoring System (ESP32-CAM sensors, PyTorch model trained on PlantVillage, Flask/SQLite/Chart.js) but provides no public dataset, images, code repository, or trained model checkpoint of its own. PlantVillage is a cited third-party dataset, and all other URLs are generic documentation

No evidence-backed public reproduction asset is currently recorded.