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As a widely used security device, the electronic passworded locker is designed to protect personal property and space. However, once the password is leaked to an unauthorized person, its security is lost. Here, with the assistance of triboelectric nanogenerators (TENGs), we present an intelligent electronic passworded locker (IEPL) based on unique and personalized security barriers, which can accurately extract users’ habits of entering passwords through integrated deep learning. The key of the IEPL adopts the single electrode mode of TENG that accurately recognizes the input behavior of a person based on machine learning, which serves as a reliable, unique, and unreproducible gate, with advantages of thin thickness, diversified structure, and simple preparation method. Finally, the proposed IEPL offers a reliable solution for improving the overall security of passworded lockers and extending the application of TENG-based sensors in the smart home.

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Publication history
Copyright
Acknowledgements

Publication history

Received: 23 September 2022
Revised: 10 November 2022
Accepted: 13 November 2022
Published: 21 December 2022
Issue date: May 2023

Copyright

© Tsinghua University Press 2022

Acknowledgements

Acknowledgements

This research was supported by the National Natural Science Foundation of China (No. 61503051).

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