Smart Irrigation and Environmental Monitoring System using IoT

Abstract

The Smart Irrigation and Environmental Monitoring System using IoT is designed to improve water management and plant monitoring in agriculture. The system uses ESP32, soil moisture, temperature-humidity, and water level sensors to collect real-time environmental data. Based on soil moisture levels, the irrigation process is automatically controlled using a relay and water pump. Users can also manually start irrigation through a web application, while the system automatically stops watering at the desired threshold level. Sensor data is continuously displayed and stored on a customized website for monitoring and analysis. Additionally, the ESP32-CAM module enables plant image monitoring and supports AI-assisted plant disease detection. The proposed system provides a low-cost, efficient, and scalable solution for smart farming applications.

Introduction

The document presents an IoT-based Smart Irrigation and Environmental Monitoring System designed to improve agricultural efficiency, reduce water wastage, and minimize manual labor. Traditional irrigation methods are inefficient and lack real-time monitoring of key factors like soil moisture, temperature, humidity, and water levels, which negatively affects crop productivity.

The proposed system uses ESP32 along with ESP32-CAM and various sensors to continuously monitor environmental conditions. Based on soil moisture levels, the system automatically controls irrigation using a relay and motor, while also allowing manual control through a web interface.

The system follows a full IoT architecture where sensor data is collected, processed by ESP32, transmitted via Wi-Fi, and displayed on a real-time web dashboard. Data is also stored for analysis, and the ESP32-CAM enables remote plant monitoring with AI-based plant health analysis using machine learning models.

The technology stack includes React.js for the frontend, Node.js for backend processing, MongoDB for storage, and Python-based AI models for plant analysis. The system improves decision-making by integrating automation, real-time monitoring, and predictive insights.

Future enhancements include solar power integration, mobile application development, improved AI-based disease detection, and weather forecasting integration.

Conclusion

The Smart Irrigation and Environmental Monitoring System using IoT provides an efficient and cost-effective solution for modern agriculture. The system automates irrigation based on real-time environmental conditions, reducing water wastage and manual effort. By integrating real-time monitoring, data storage, and ESP32-CAM-based plant observation, the system improves plant health monitoring and agricultural productivity. The proposed solution demonstrates the effective use of IoT and AI technologies in supporting smart and sustainable farming practices.

References

[1] Pereira, G. P., Chaari, M. Z., & Daroge, F., “IoT-Enabled Smart Drip Irrigation System Using ESP32,” IoT, vol. 4, no. 3, pp. 221–243, 2023. DOI: 10.3390/iot4030012. [2] Kumar, R., Harpal, Prakash, O., Lohiya, N. K., & Kumar, S., “IoT Based Smart Irrigation System Using Sensors: A Revolutionary Idea in the Field of Agriculture in India,” Recent Developments in Electronics and Communication Systems, 2023. DOI: 10.3233/ATDE221261. [3] Mehta, K. R., Naidu, K. J., Baheti, M., Parmar, D., & Sharmila, A., “Internet of Things Based Smart Irrigation System Using ESP WROOM 32,” Journal on Internet of Things, vol. 5, pp. 45–55, 2023. DOI: 10.32604/jiot.2023.043102. [4] Zheng, Y., Jiang, Z., Kozlov, O. V., & Kondratenko, Y. P., “Fuzzy Automatic Control of the Irrigation Process for the IoT-Based Smart Farming Systems,” Artificial Intelligence for Sustainable Agriculture, vol. 16, no. 3, 2024. DOI: 10.3233/AIS-230403. [5] Kunt, Y. E., “Development of a Smart Autonomous Irrigation System Using IoT and AI,” arXiv preprint arXiv:2506.11835, 2025.

Copyright

Copyright © 2026 Prof. Ashatai Bhure, Srushti Dhananjay Khedkar, Shraddha Kantilal Bhavsar, Mansi Sunil Borse. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.