“Smart Soil Health Monitoring System Using Arduino and AI-Dashboard”
Mrs.K.P.Vidhate,Shubham D. Sopnar,Rohit S. Bhoye,Piyush R. Aher,Vikas B. Mali
Department of Computer Technology
K. K. Wagh Polytechnic, Nashik, India
Abstract - Traditional agricultural practices largely depend on manual observation and farmer experience to assess soil and environmental conditions. This approach often results in inefficient irrigation, excessive water usage, delayed decision-making, and reduced crop productivity, especially in rural areas where access to advanced technology and reliable internet connectivity is limited. Although modern IoT-based agricultural systems offer automation and analytics, many of them rely heavily on cloud services, making them unsuitable for remote regions due to connectivity issues, higher costs, and data dependency on external platforms.
To address these challenges, this project presents an ESP32-based Smart Soil Health Monitoring and Decision Support System that operates entirely offline using edge computing principles. The system continuously monitors key environmental parameters such as soil moisture, temperature, and humidity through connected sensors. All data processing and analysis are performed locally on the ESP32 microcontroller using deterministic, rule-based AI logic to evaluate soil conditions and generate intelligent irrigation recommendations. The ESP32 functions as a standalone WiFi access point and hosts an embedded web server, providing a responsive and user-friendly dashboard accessible via any standard web browser without requiring internet connectivity.
The system displays real-time sensor data, soil status, historical trends, and irrigation suggestions through a multilingual (English and Marathi) and mobile-friendly interface. By eliminating manual monitoring and cloud dependency, the proposed solution reduces human error, improves water management efficiency, and supports timely decision-making for farmers. This low-cost, reliable, and scalable system offers a practical solution for smart farming in resource-constrained environments and serves as a foundation for future enhancements such as automated irrigation and renewable energy integration.
keywords:
Smart agriculture, ESP32, soil health monitoring, edge computing, offline IoT, irrigation decision support.
