Tomato planting environment monitoring and pest warning system based on Internet of Things and Huawei ModelArts

In the course of global agricultural modernization, smart agricultural systems have markedly enhanced crop production efficiency, minimized resource consumption, and advanced the development of environmentally friendly sustainable agriculture through precision perception, intelligent control, and remote management. This paper introduces a monitoring and early warning system for the tomato planting environment based on Internet of Things (IoT) technology and visual recognition technology. The system employs STM32 as the control core, integrates the ESP8266 communication module, OV7725 camera, and Huawei Cloud platform, and leverages deep learning technologies to achieve real-time monitoring of the tomato growing environment and intelligent early warning of insect pests. The system collects key parameters such as air temperature and humidity, light intensity, and soil moisture in real time via sensors, utilizes the Huawei ModelArts platform to train disease identification models, and provides remote data interaction and early warning services through WeChat mini programs. As a result, the system is capable of significantly mitigating yield losses caused by insect pests, thereby enhancing the productivity of tomato cultivation.