RISAR: RIS-assisted Human Activity Recognition with Commercial Wi-Fi Devices
Human activity recognition (HAR) holds significant importance in smart homes, security, and healthcare. Existing systems face limitations because of the insufficient spatial diversity provided by a limited number of antennas. Furthermore, inefficiencies in noise reduction and feature extraction from sensing data pose challenges to recognition performance. This study presents a reconfigurable intelligent surface (RIS)-assisted passive human activity recognition (RISAR) method, compatible with commercial Wi-Fi devices. RISAR leverages a RIS to enhance the spatial diversity of Wi-Fi signals, effectively capturing a wider range of information distributed across the spatial domain. A novel high-dimensional factor model based on random matrix theory is proposed to address noise reduction and feature extraction in the temporal domain. A dual-stream spatial-temporal attention network model is developed to assign variable weights to different characteristics and sequences, mimicking human cognitive processes in prioritizing essential information. Experimental analysis shows that RISAR significantly outperforms existing HAR methods in accuracy and efficiency, achieving an average accuracy of 97.26%. These findings underscore RISAR's adaptability and potential as a robust activity recognition solution in real environments.
Code (0)
등록된 구현이 없습니다.
Tasks
Activity RecognitionDenoisingDiversityHuman Activity RecognitionSimilar Papers 제목 키워드 기반
HAPRec: Hybrid Activity and Plan Recognizer
Computer-based assistants have recently attracted much interest due to its applicability to ambient assisted living. Such assistants have to detect and recognize the high-level activities and goals performed by the assis…
Action RecognitionActivity RecognitionSimultaneous Learning from Human Pose and Object Cues for Real-Time Activity Recognition
Real-time human activity recognition plays an essential role in real-world human-centered robotics applications, such as assisted living and human-robot collaboration. Although previous methods based on skeletal data to …
Activity RecognitionHuman Activity RecognitionTRIS-HAR: Transmissive Reconfigurable Intelligent Surfaces-assisted Cognitive Wireless Human Activity Recognition Using State Space Models
Human activity recognition (HAR) using radio frequency (RF) signals has garnered considerable attention for its applications in smart environments. However, traditional systems often struggle with limited independent cha…
Activity RecognitionHuman Activity RecognitionMambaState Space ModelsTRTAR: Transmissive RIS-assisted Through-the-wall Human Activity Recognition
Device-free human activity recognition plays a pivotal role in wireless sensing. However, current systems often fail to accommodate signal transmission through walls or necessitate dedicated noise removal algorithms. To …
Activity RecognitionHuman Activity RecognitionHuman Activity Recognition using Recurrent Neural Networks
Human activity recognition using smart home sensors is one of the bases of ubiquitous computing in smart environments and a topic undergoing intense research in the field of ambient assisted living. The increasingly larg…
Activity RecognitionBIG-bench Machine LearningHuman Activity Recognition