Design and Experimental Evaluation of an STM32-Based Smart Agriculture Monitoring and Adaptive Control System

Abstract

This paper proposes an STM32-based smart agriculture environmental monitoring and adaptive control system integrating multi-sensor acquisition, wireless communication, and automatic actuator control. The system collects soil moisture, temperature, and light intensity data through multiple sensors, while an ESP8266 WiFi module and Message Queuing Telemetry Transport (MQTT) protocol are used for remote monitoring and control command interaction. An adaptive control strategy based on dynamic threshold adjustment and hysteresis control is proposed to improve environmental adaptability and reduce unnecessary actuator switching under changing conditions. The system controls irrigation, cooling, and supplementary lighting according to environmental variations. Experimental results demonstrate that the proposed system achieves stable sensing, communication, and control performance in an indoor simulated agricultural environment. The MQTT transmission success rate reaches 98.7% with an average delay of 146 ms, and the actuator response time remains within approximately one second. Compared with fixed-threshold control, the proposed strategy reduces actuator switching frequency by 59.1%. The results demonstrate the preliminary feasibility of the proposed embedded IoT system for smart agriculture monitoring and adaptive environmental control.