IoT-Driven Smart Greenhouse System for Real-Time Environmental Monitoring

Aim/Background: The rising challenges of climate change, resource constraints, and labor shortages have accelerated the need for automated and sustainable agricultural practices. This project aims to design and implement a Smart Greenhouse Monitoring System using Internet of Things (IoT) technology to optimize environmental conditions for plant growth. Methods: A Raspberry Pi was employed as the main controller, integrated with key sensors and actuators including a soil moisture sensor, DHT11 temperature and humidity sensor, LDR, DC water pump, cooling fan, and electric bulb. The system automatically adjusts irrigation, temperature, and lighting based on real-time data. Sensor readings were transmitted to the ThingSpeak cloud platform for visualization and remote monitoring. Threshold-based logic controlled the actuators for efficient environmental management. Results: The system achieved a fast actuator response time of under two seconds and demonstrated an uptime exceeding 98%. Sensor accuracy was measured within ±5% for soil moisture and ±2°C for temperature. Cloud connectivity via ThingSpeak ensured over 99% successful data transmission. The system effectively automated greenhouse functions while reducing manual intervention, water consumption, and energy usage. Conclusion: The Smart Greenhouse Monitoring System offers a scalable, low-cost, and efficient alternative to traditional greenhouse models. It enhances plant productivity through real-time automation and remote monitoring. Future improvements such as AI-based predictive control and mobile app integration could further advance the system for precision agriculture in both small and commercial settings.