Smart Greenhouse IoT Education Platform | AI Environmental Monitoring & Automation for Smart Farming | Raspberry Pi + ESP32 Dual Control System | Python & C++ Coding for Sensor Networks | Open-Source STEM Kit for Climate & Agriculture Learning

Smart greenhouse platform combines IoT technology and AI-driven automation to teach students how modern agriculture uses data to control temperature, humidity, light, and irrigation. Sensor modules measure environmental parameters and transmit data to the Raspberry Pi controller for real-time analysis and decision-making. Python and C++ programming allow learners to develop algorithms that adjust fans, pumps, and LED lights automatically based on sensor readings.

IoT gateway integration enables students to publish data to cloud dashboards through MQTT and HTTP protocols for remote visualization and analytics. Machine-learning models predict environmental trends such as soil dryness or temperature rise to trigger automated responses. This demonstrates how AI optimizes energy use and water consumption in precision farming.

Raspberry Pi and ESP32 dual-control architecture separates high-level AI tasks from low-level device management, ensuring stable operation and real-time response. Industrial-grade power and wireless modules provide long-term field deployment capability. Students learn how IoT systems collect, analyze, and act upon data autonomously in a closed control loop.

The curriculum includes experiments on sensor calibration, cloud connection, AI data training, and mobile app integration. Project-based learning bridges electronics, agriculture, and computer science to develop real-world skills for future smart farming engineers. Open-source schematics and sample code encourage innovation and expansion with additional modules such as CO₂ sensors or camera vision.

This platform tra