Application and Development of Behavior Recognition Methods Based on Wireless Sensing and Image Multimodal Fusion

A groundbreaking solution in removing the shortcomings of single-mode technologies is the multimodal approach to wireless sensing and visualization data, with the essential effect of detecting human actions indoors through the use of a multimodal approach. Wireless sensing provides many benefits, like contactless working, light-interference resistance, and privacy protection, but it is vulnerable to multipath propagation. Visualization modality is characterized by high spatial resolution and works with light conditions and posing the probability of confidential information leaking. This paper reviews and analyzes the research advancements on behavior recognition through the systematic review of the foundation to integrate these two modalities, data set construction rationale, fusion architecture planning, optimization, and reliability improvement. Finally, the article mentions the possible issues in the actual implementation, namely the generalization of the environment and optimization of energy consumption, or smart homes and elder care. The work can be used both in theoretical research and in engineering practice in the area of multimodal behavior recognition.