In this paper, we propose a novel gesture recognition system based on a smartphone. Due to the limitation of Channel State Information (CSI) extraction equipment, existing WiFi-based gesture recognition is limited to the microcomputer terminal equipped with Intel 5300 or Atheros 9580 network cards. Therefore, accurate gesture recognition can only be performed in an area relatively fixed to the transceiver link. The new gesture recognition system proposed by us breaks this limitation. First, we use nexmon firmware to obtain 256 CSI subcarriers from the bottom layer of the smartphone in IEEE 802.11ac mode on 80 MHz bandwidth to realize the gesture recognition system’s mobility. Second, we adopt the cross-correlation method to integrate the extracted CSI features in the time and frequency domain to reduce the influence of changes in the smartphone location. Third, we use a new improved DTW algorithm to classify and recognize gestures. We implemented vast experiments to verify the system’s recognition accuracy at different distances in different directions and environments. The results show that the system can effectively improve the recognition accuracy.

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COVID-19 is currently the biggest threat that challenges all of humankind’s health and property. One promising and effective way to control the rapid spreading of this infection is searching for primary close contacts of the confirmed cases. In response, we propose COVID-19 Tracer, a low-cost passive searching system to find COVID-19 patients’ close contacts. The main idea is utilizing ubiquitous WiFi probe requests to describe the location similarity, which is then achieved by two designed range-free judgment indicators: location similarity coefficient and close contact distance. We have carried out extensive experiments in a school office building, and the experimental results show an average accuracy of more than 98%, demonstrating our system’s effectiveness in judging close contacts. Last but not least, we have developed a prototype system for a school building to find potential close contacts.

Platinum oxide electrode, as an important part of hydrogen concentration monitoring sensor built in containment, needs to withstand extreme conditions such as high temperature, high humidity, and high irradiation and can still work normally even in the case of serious accidents, which puts forward higher requirements for its performance. In present study, platinum oxide film electrode was successfully prepared with three‐dimensional nano‐dendritic, uniform, and crack‐free on platinum substrate by reactive magnetron sputtering, and the influence of different substrate temperature and sputtering atmosphere on the composition, morphology, and electrocatalytic property of the film was investigated. The results show that platinum oxide film is composed of PtO and PtO2. As the temperature increases from room temperature (RT) to 200°C, the oxygen vacancies in the amorphous film are gradually repaired and convert to the crystalline state, which shows increasing PtO2 ratio, increasing electrochemical active area (ECSA), and improved stability. When the temperature is rising to 400°C, the film shows decreasing oxygen vacancies, increasing average grain size. Because PtO2 decomposes into PtO and Pt, and thus ECSA decreases, the stability and oxygen reduction activity of the films decreases gradually. At the same temperature, the crystalline film obtained in Ar/50%O2 has higher concentration of oxygen vacancies and smaller average grain size than that obtained in O2, resulting in larger ECSA and relatively good stability. By contrast, the platinum oxide film electrode prepared in Ar/50%O2 and 200°C has better stability and excellent electrocatalytic activity for oxygen reduction.