Research On Adaptive Environment Control System Based on Image Recognition

Bowen Zhao

doi:10.54097/xpn5cn52

Authors

Bowen Zhao

DOI:

https://doi.org/10.54097/xpn5cn52

Keywords:

Image Recognition; Adaptive Environmental Control; Computer Vision; Deep Learning; Internet of Things (IoT); Indoor Environment Regulation; Multimodal Sensing.

Abstract

This review paper investigates the current research status of adaptive environmental control systems driven by image recognition technology. By analyzing and summarizing recent studies, This paper outline key methods and frameworks for dynamically regulating indoor environments using computer vision, including control of humidity, temperature, and lighting. Current technologies mainly meet requirements for monitoring temperature and humidity and manually adjusting these conditions, but do not achieve full autonomy in adaptively modifying environmental parameters for human comfort. So, I made this system in the hope of providing people with better living conditions and a more intelligent living experience. Existing methods have improved user comfort and energy efficiency; however, challenges remain in robustness, real-time performance, privacy protection, and adaptability to different environments. This paper highlights these limitations and presents future directions, including integration of multimodal sensor data, development of inference models for lightweight devices, and establishment of standardized evaluation benchmarks. It aims to provide a comprehensive foundation for the further development of vision-based intelligent environmental control systems and inspire more intelligent adaptive solutions.

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