DEVELOPMENT OF AN INTELLIGENT GREENHOUSE MONITORING AND CONTROL SYSTEM USING IOT AND CLOUD TECHNOLOGIES

Abstract

Precision agriculture demands continuous monitoring and intelligent control of environmental parameters within greenhouse structures to maximize crop yield while minimizing resource consumption. This paper presents the design and implementation of AgroAI — an intelligent IoT-based greenhouse monitoring and control system built on ESP32 microcontrollers, MQTT communication protocol, and a cloud-native SaaS backend. The system integrates five sensor modalities (temperature, humidity, soil moisture, light intensity, and CO₂ concentration) with four automated actuators (ventilation fan, soil irrigation pump, air humidification pump, and supplemental lighting) governed by a threshold-based AI control algorithm operating in real-time. The multi-tenant cloud architecture employs FastAPI with PostgreSQL for data persistence, Mosquitto MQTT broker for device communication, and a React-based dashboard for visualization. FreeRTOS dual-core task scheduling on ESP32 ensures deterministic sensor sampling at 2-second intervals while maintaining concurrent MQTT connectivity. Experimental evaluation over a 30-day deployment period demonstrates a temperature regulation accuracy within ±1.2°C of target setpoints, 34% reduction in water consumption compared to manual irrigation, and 99.2% system uptime. The system supports over-the-air (OTA) firmware updates and AI-assisted chat interface for natural language greenhouse management queries.