Smart Greenhouse Gardening: An Intelligent Smart Greenhouse Monitoring and Automated Plant Protection System

Abstract

Smart Greenhouse Gardening: An Intelligent Smart Greenhouse Monitoring and Automated Plant Protection System, designed to improve crop growth through IoT-based sensing and AI-driven automation. The system continuously monitors temperature, humidity, soil moisture, and light using smart sensors, while AI models detect plant diseases and pest infection at an early stage. Based on real-time data, automated actions such as irrigation, ventilation, and lighting control are performed to maintain optimal growing conditions. The solution reduces manual effort, improves resources efficiency, and supports healthier plant growth in greenhouse environments.

Introduction

The document presents a comprehensive overview of a Smart Greenhouse Gardening system that integrates IoT, automation, and artificial intelligence to overcome the limitations of traditional greenhouse management. Conventional methods rely on manual monitoring, which often causes delayed responses to environmental changes, inefficient water usage, and late detection of plant diseases and pests—ultimately reducing crop yield and quality.

The proposed smart greenhouse system uses IoT sensors to continuously monitor key parameters such as temperature, humidity, soil moisture, light intensity, CO?, and pH levels. Sensor data is processed through microcontrollers to automatically control irrigation, ventilation, lighting, and climate conditions. An AI-based image processing module enables early detection of plant diseases and pest attacks, minimizing crop loss. The system also includes cloud-based dashboards and mobile access for real-time monitoring, alerts, historical analysis, and remote control.

The project aims to improve productivity, conserve water and energy, reduce labor dependency, and promote sustainable agriculture. Its scope focuses on small to medium-scale greenhouses and emphasizes intelligent automation rather than large-scale robotics. The methodology covers data collection, preprocessing, feature extraction, rule-based and predictive decision-making, automated actuation, and feedback-based optimization.

Expected outcomes include improved understanding of smart agriculture, development of a practical automation system, insights for future enhancements, and real-world benefits for farmers. However, the approach has limitations such as sensor dependency, scalability challenges, technical complexity, security risks, maintenance requirements, and reduced performance under extreme or unforeseen environmental conditions.

Conclusion

The Smart Garden Green House project impeccably presents a modern integration of technology with traditional agriculture, resulting in an efficient, sustainable, and eco-friendly cultivation system. Equipped with sensors, microcontrollers, and automated control mechanisms, it is able to observe and regulate the basic environmental variables like temperature, humidity, soil moisture, and light intensity inside the greenhouse. This ensures optimal conditions for the growth of crops at all times without necessarily requiring continuous human supervision. The project emphasizes how automation in agriculture will play a significant role in the future, amidst the problems of climate change, erratic rainfall, lack of skilled labor, and the ever-growing demand for food production. This will allow farmers to have higher yields with wasted resources minimized using IoT and smart systems for better control over crop health. The Smart Green House also allows for precision farming through delivering water, nutrients, and light just in time to improve plant growth and reduce operational costs. Similarly, the system makes real-time data and alerts available to users in order to make informed decisions. The integration of renewable energy sources, like solar panels that may be used, adds great feasibility to the system. This project thus proves that smallscale farmers and students, too, can adopt advanced technologies at low cost to improve agricultural productivity.

References

[1] Books & Journals “Internet of Things (IoT) Applications” – R. Buyya \"Embedded Systems and Automation\" - Raj Kamal “Greenhouse Technology and Management” – K. V. Peter [2] Websites www.arduino.cc - For Arduino board and sensor interfacing www.electronicsforu.com-for circuit ideas and IoT [3] concepts www.geeksforgeeks.org - For programming and technical explanations www.sciencedirect.com - Green house automation research papers. [4] YouTube Tutorials NPTEL IoT Course – Fundamentals of IoT and sensor networks Arduino Projects Hub – Smart Garden and Automation Projects [5] Other Sources Class notes and guidance provided by our faculty Practical demonstrations performed in the laboratory.

Copyright

Copyright © 2026 Shiddhi T. Vagvekar, Pranali N. Patil , Siddhi. Y. Vagvekar, Swati S. Kamat. 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.