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Concealed Wireless Warning Sensor Based on Triboelectrification and Human-Plant Interactive Induction

With the continuous development of artificial intelligence, the demand for sensors with simple preparation and strong concealment continues to increase. However, most of the high-sensitivity sensors have complex manufacturing methods, high costs, and single functions. In this paper, a sensitive moti...

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Detalles Bibliográficos
Autores principales: Feng, Yange, Benassi, Enrico, Zhang, Liqiang, Li, Xiaojuan, Wang, Daoai, Zhou, Feng, Liu, Weimin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AAAS 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8106444/
https://www.ncbi.nlm.nih.gov/pubmed/34013208
http://dx.doi.org/10.34133/2021/9870936
Descripción
Sumario:With the continuous development of artificial intelligence, the demand for sensors with simple preparation and strong concealment continues to increase. However, most of the high-sensitivity sensors have complex manufacturing methods, high costs, and single functions. In this paper, a sensitive motion sensor based on the triboelectric interaction between a living plant and the human body was designed to detect the real-time movements of human beings and provide danger warning. A certain relationship exists between the triboelectric signal and the distance between the plant and the human body, with effective signals being detected in the range of 1.8 m. In addition, the triboelectric signal generated by each person is unique like a fingerprint, which can be used for biometrics. On the basis of the triboelectric signal, a wireless character entry warning system is designed. This sensor can not only send out a wireless warning signal at a specific distance but also allow one to receive the warning information synchronously on a mobile phone in real time. The wireless movement sensor receives signals through a living plant, and it has the characteristics of convenient use, strong concealment, and shielding difficulty. This sensor has the potential to be widely used in person recognition, danger warning, and motion monitoring.