Smart Agrocare: Automated Irrigation and Soil Nutrition Monitoring

India's agrarian sector, while central to its economic foundation, continues to grapple with inefficient water management and inadequate soil monitoring. This paper introduces Smart AgroCare, an IoT-based precision farming solution developed to address irrigation inefficiency and soil nutrient degradation in smallholder sugarcane cultivation. An ESP32 microcontroller serves as the processing core, coordinating inputs from eight heterogeneous sensors — including NPK, pH, soil moisture, temperature, float switches, and motor protection sensors — to autonomously regulate a single-phase irrigation pump. Processed readings are rendered locally on a 16×2 LCD module and remotely via a cloud-hosted React-based web interface. Data transmission is handled through MQTT messaging and HTTP REST protocols, while external integrations with OpenWeatherMap and Google Gemini AI enhance the system's predictive and advisory capabilities. A structured 21-day field evaluation conducted in October–November 2025 at Manjari (Bk), Pune, achieved water savings between 34% and 37%, a directional crop yield improvement of approximately 12%, and demonstrated full system reliability — all at a hardware cost below ₹10,000.

Precision Agriculture, IoT, ESP32, Automated Irrigation, NPK Monitoring, MQTT, Sugarcane Farming, Gemini AI, Cloud Dashboard, Water Management.

1. Government of India, Ministry of Agriculture and Farmers' Welfare, Annual Report 2023–24, New Delhi, India, 2024. [Google Scholar] [Crossref]

2. S. Patil, A. More, and R. Kulkarni, “Design of Smart Irrigation System Using ESP32,” International Journal of Engineering Trends and Technology (IJETT), vol. 71, no. 5, pp. 45–52, May 2023. [Google Scholar] [Crossref]

3. R. Bhosale and P. Kulkarni, “Arduino-Based Soil Moisture Irrigation Control System,” IJARCCE, vol. 12, no. 3, pp. 101–106, Mar. 2023. [Google Scholar] [Crossref]

4. A. Deshmukh and S. Ghorpade, “NodeMCU-Based Online Soil Data Logging for Smart Farming,” International Journal of Engineering and Technology (IJET), vol. 9, no. 1, 2023. [Google Scholar] [Crossref]

5. R. Chaudhari, P. Sharma, and M. Jain, “LoRa IoT Network for Large-Scale Irrigation Monitoring,” in Proceedings of IEEE ICIOT, 2024, pp. 211–218. [Google Scholar] [Crossref]

6. K. Joshi and D. Pandey, “Solar-Powered Smart Irrigation Using Moisture and Temperature Sensors,” International Journal of Green Energy, vol. 19, no. 8, pp. 900–910, 2022. [Google Scholar] [Crossref]

7. Espressif Systems, ESP32 Technical Reference Manual v5.1, 2023. [Online]. Available: docs.espressif.com [Google Scholar] [Crossref]

8. OpenWeatherMap, Current Weather and Forecast API Documentation, 2024. [Online]. Available: OpenWeatherMap API [Google Scholar] [Crossref]

9. Google DeepMind, Gemini AI API Documentation, 2024. [Online]. Available: Gemini API Documentation [Google Scholar] [Crossref]

10. MQTT.org, MQTT – The Standard for IoT Messaging, 2024. [Online]. Available: MQTT.org [Google Scholar] [Crossref]

11. A. Raut and K. Bhosale, “IoT for Precision Agriculture,” in Proceedings of Springer Smart Systems, pp. 211–219, 2022. [Google Scholar] [Crossref]

• NFC Data Acquisition and Visualization System