Intense human motion, such as hitting, kicking, and falling, in some particular scenes indicates the occurrence of abnormal events like violence and school bullying. Camera-based human motion detection is an effective way to analyze human behavior and detect intense human motion. However, even if the camera is properly deployed, it will still generate blind spots. Moreover, camera-based methods cannot be used in places such as restrooms and dressing rooms due to privacy issues. In this paper, we propose a multi-target intense human motion detection scheme using commercial Wi-Fi infrastructures. Compared with human daily activities, intense human motion usually has the characteristics of intensity, rapid change, irregularity, large amplitude, and continuity. We studied the changing pattern of Channel State Information (CSI) influenced by intense human motion, and extracted features in the pattern by conducting a large number of experiments. Considering occlusion exists in some complex scenarios, we distinguished the Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) conditions in the case of obstacles appearing between the transmitter and the receiver, which further improves the overall performance. We implemented the intense human motion detection system using single commercial Wi-Fi devices, and evaluated it in real indoor environments. The experimental results show that our system can achieve intense human motion detection rate of 90%.

MU-MIMO proposed in 802.11ac is to achieve higher data rate, with transmitting to multiple users concurrently. However, the overhead cost by collecting channel state information (CSI) sometimes even overwhelm real data transmission when quantity of user is large, which leads the network and unscalable. In this work, we address the problem with adaptive location-based CSI feedback compression (LFC), LFC utilizes location, the most influential factor of beamforming, and enables users in a group with correlative location sharing the CSI feedback matrix, which makes the MU-MIMO system energy sufficient and scalable. The simulation result shows that LFC could achieve higher throughput than traditional scheme and latest works.