Smart data processing for energy harvesting systems using artificial intelligence

Power metaverse and smart grids are the future of power systems, with a focus on intelligence, digitization, and informatization. Their foundation is electricity data acquisition by massive distributed sensors with features such as multi-parameter, miniaturization, high precision, self-powered, wireless transmission, and high reliability. The significant advances in high-performance, self-powered, micro sensors are achieved over recent years through the interdisciplinary convergence of nanotechnologies, MEMS technologies, and electronics. Although there have been several summaries of self-powered sensors in areas such as medical health, smart cities, and smart agriculture, there is currently no relevant review paper for power grids. Therefore, this paper first reviews the recent progress and practical applications of self-powered, multi-parameter and micro sensor technologies for power metaverse and smart grids. The review systematically presents the milestone progress in micro electrical and environmental sensing technologies, discusses energy harvesting methods suitable for power grids, elaborates on the applications of self-powered micro sensor systems in the power grids, and puts forward the challenges and future perspectives to construct smart grids based on self-powered multi-parameter sensors. 

Progress in self-powered, multi-parameter, micro sensor technologies for power metaverse and smart grids

Triboelectric Nanogenerator-based smart biomedical sensors for healthcare

The application of wearable intelligent systems toward human-computer interaction has received widespread attention. It is still desirable to conveniently promote health and monitor sports skills for disabled people. Here, a wireless intelligent sensing system (WISS) has been developed, which includes two ports of wearable flexible triboelectric nanogenerator (WF-TENG) sensing and an upper computer digital signal receiving intelligent processing. The WF-TENG sensing port is connected by the WF-TENG sensor and flexible printed circuit (FPC). Due to its flexibility, the WF-TENG sensing port can be freely adhered on the surface of human skin. The WISS can be applied to entertainment reaction training based on human-computer interaction, and to the technical judgment and analysis on wheelchair curling sport. This work provides new application opportunities for wearable devices in the fields of sports skills monitoring, sports assistive devices and health promotion for disabled people. 

Flexible Wearable Intelligent Sensing System for Wheelchair Sports Monitoring

A comprehensive review on triboelectric sensors and AI-integrated systems

Multi-Functional Triboelectric Nanogenerators on Printed Circuit Board for Metaverse Sport Interactive System

Gait is the information that can reflect the state index of the human body, and at the same time, the leg is the organ with the maximum output power of the human body. Effective collection of maximum mechanical power output and gait information can play an important role in sustainable energy acquisition and human health monitoring. In this paper, a 3D printing triboelectric nanogenerator (3D printed TENG) is fabricated by 3D printing technology, it is composited of Poly tetra fluoroethylene (PTFE) film, Nylon film, and 3D printing substrate. Based on the principle of friction electrification and electrostatic induction, it can be used as the equipment for human sustainable mechanical energy collection and gait monitoring. In order to solve the problems of energy collection, gait monitoring, and immersion experience, we conducted the following experiments. Firstly, the problem of sustainable energy recovery and reuse of the human body was solved. Three-dimensionally printed TENG was used to collect human mechanical energy and convert it into electric energy. The capacitor of 2 μF can be charged to 1.92 V in 20 s. Therefore, 3D printed TENG can be used as a miniature sustainable power supply for microelectronic devices. Then, the gait monitoring software is used to monitor human gait, including the number of steps, the frequency of steps, and the establishment of a personal gait password. This gait password can only identify a specific individual through machine learning. Through remote wireless transmission means, remote real-time information monitoring can be achieved. Finally, we use the Internet of Things to control virtual games through electrical signals and achieve the effect of human–computer interaction. The peak search algorithm is mainly used to detect the extreme points whose amplitude is greater than a certain threshold and the distance is more than 0.1 s. Therefore, this study proposed a 3D printed TENG method to collect human mechanical energy, monitor gait information, and then conduct human–computer interaction, which opened up a multi-dimensional channel for human energy and information interaction.

/pdf/a-3d-printing-triboelectric-sensor-for-gait-analysis-and-132ezah6.pdf

A 3D Printing Triboelectric Sensor for Gait Analysis and Virtual Control Based on Human–Computer Interaction and the Internet of Things

Multiple Functions Printed Circuit Triboelectric Nanogenerators-Based Metauniverse Sport Interactive System

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Multi-Functional Triboelectric Nanogenerators on Printed Circuit Board for Metaverse Sport Interactive System

A 3D Printing Triboelectric Sensor for Gait Analysis and Virtual Control Based on Human–Computer Interaction and the Internet of Things

Multiple Functions Printed Circuit Triboelectric Nanogenerators-Based Metauniverse Sport Interactive System