To address the limitations of traditional micro-landscape systems, which rely on manual maintenance and lack ecological self-regulatory capabilities, an intelligent micro-landscape control system based on the K210 chip has been designed. This system incorporates adaptive environmental regulation and human-machine affective interaction functionalities. By integrating sensors for real-time monitoring of temperature, humidity, and light intensity, it autonomously controls misting and lighting to maintain ecological equilibrium within the micro-landscape. Utilizing Wi‑Fi technology, the system enables remote transmission and storage of environmental data. Innovatively, the KPU + YOLO‑K210 model has been incorporated to achieve facial expression recognition, allowing the system to perceive user emotions and dynamically adjust the ambient atmosphere, thereby delivering personalized experiences such as stress relief, aesthetic enhancement, and anti‑fatigue effects. Experimental results demonstrate that the YOLO‑K210 model achieves a recognition accuracy of 0.874, with all system functions operating stably and reliably. These findings validate the feasibility of establishing bidirectional "environment-human" interaction in intelligent micro-landscape systems and provide a referential framework for their systematic design.