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This paper reviews our work on the development of microwave carbon nanotube resonator sensors for gas detection. The sensor consists of a radio frequency resonator coated with a layer of carbon nanotubes. Upon exposure to gasses, the resonant frequency of the sensor shifts to indicate the presence of gasses. Our experimental results demonstrate that the microwave carbon nanotube resonator sensor achieves a sensitivity of 4000 Hz/ppm upon exposure to ammonia and the resonant frequency is recovered when ammonia is evacuated. The sensing mechanism is dependent on electron transfer from the ammonia to the nanotubes. This sensor platform has great potential for wireless sensing network applications.

Presently, the design process of the AI remote server can enable the user to evaluate whether an authorized user can gain emotional responses when they establish an emotional product interface in the approach of the interaction with the device. Therefore, it is necessary for user experience and the ability to address the user’s emotional expectations. This paper proposes an artificial intelligence-based user face recognition response system (AI-UFRRS) to monitor users’ emotions in real life continually and provide new insights into their emotional responses and transitions. The user face recognition response system design is analyzed based on device intelligence. Eventually, the response system is improved and strategy based on an intelligent device. The proposed AI-UFRRS utilizes reinforcement learning technologies to maintain emotional processing in substantial information relating to the user’s identity. This paper offers AI remote strategies to reduce identification information and maximize information on emotions formed by reinforcement learning. The results suggest that the system provided can perform a convolute transformation to maintain user recognition accuracy and reduce face identity recognition. Thus, the experimental results of AI-UFRRS show the improved accuracy ratio of 95.6%, the recognition rate of 93.4%, emotion ratio of 95.5%, high response system ratio of 96.3%, and to increase user identification ratio of 91.8% and reduced false acceptance rate of 19.2%, the false rejection rate of 19.5% compared to other methods.

We used calibrated 2D images uploaded by patients to an online platform to generate a 3D digital model of the limb. This was used to 3D print a splint. This method of 3D printing of splints was used for two patients who were not able to visit the hospital in person due to restrictions placed by the COVID-19 pandemic. Both patients were satisfied with the splint. We feel that this technology could be used to offer additional options to conventional splinting that allows contactless splint fitting.

Level of Evidence: Level V (Therapeutic)

This paper reviews our work on the development of microwave carbon nanotube resonator sensors for gas detection. The sensor consists of a radio frequency resonator coated with a layer of carbon nanotubes. Upon exposure to gasses, the resonant frequency of the sensor shifts to indicate the presence of gasses. Our experimental results demonstrate that the microwave carbon nanotube resonator sensor achieves a sensitivity of 4000 Hz/ppm upon exposure to ammonia and the resonant frequency is recovered when ammonia is evacuated. The sensing mechanism is dependent on electron transfer from the ammonia to the nanotubes. This sensor platform has great potential for wireless sensing network applications.

A multi-functional crop intelligent monitoring system, including internet and Arduino micro-controllers, function to upload humiture, soil moisture, light intensity, PM2.5, harmful gas and other real time data. The system's other functions include automatic watering of crops when the humidity data exceeds warning levels, broadcasting the condition of crops by Microblog, remotely controlling the watering and lighting by web and WeChat and remote video monitoring. Data collection of sensor data is conducted by Arduino UNO micro-controller and the data is uploaded real time into the internet by HLK-RM04 WiFi module. Software functions of the system include real time charts by Websocket, JavaScript in PC and mobile internet, and concurrently, the implementation of WeChat control and Microblog broadcast through Tencent micro channel public platform and Sina Microblog.