
iScience, Год журнала: 2024, Номер 27(12), С. 111480 - 111480
Опубликована: Ноя. 26, 2024
Язык: Английский
iScience, Год журнала: 2024, Номер 27(12), С. 111480 - 111480
Опубликована: Ноя. 26, 2024
Язык: Английский
Nano Energy, Год журнала: 2025, Номер unknown, С. 110663 - 110663
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
2IEEE Access, Год журнала: 2023, Номер 11, С. 145869 - 145896
Опубликована: Янв. 1, 2023
The Healthcare Internet-of-Things (H-IoT), commonly known as Digital Healthcare, is a data-driven infrastructure that highly relies on smart sensing devices (i.e., blood pressure monitors, temperature sensors, etc.) for faster response time, treatments, and diagnosis. However, with the evolving cyber threat landscape, IoT have become more vulnerable to broader risk surface (e.g., risks associated generative AI, 5G-IoT, etc.), which, if exploited, may lead data breaches, unauthorized access, lack of command control potential harm. This paper reviews fundamentals healthcare IoT, its privacy, security challenges machine learning H-IoT devices. further emphasizes importance monitoring layers such perception, network, cloud, application. Detecting responding anomalies involves various cyber-attacks protocols Wi-Fi 6, Narrowband Internet Things (NB-IoT), Bluetooth, ZigBee, LoRa, 5G New Radio (5G NR). A robust authentication mechanism based deep techniques required protect mitigate from increasing cybersecurity vulnerabilities. Hence, in this review paper, privacy mitigation strategies building resilience are explored reported.
Язык: Английский
Процитировано
23Chemical Engineering Journal, Год журнала: 2024, Номер unknown, С. 158184 - 158184
Опубликована: Ноя. 1, 2024
Язык: Английский
Процитировано
9Nano Energy, Год журнала: 2024, Номер 128, С. 109878 - 109878
Опубликована: Июнь 13, 2024
Язык: Английский
Процитировано
7Device, Год журнала: 2025, Номер unknown, С. 100707 - 100707
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
1Advanced Functional Materials, Год журнала: 2025, Номер unknown
Опубликована: Фев. 16, 2025
Abstract Interfacial gel compliance is essential for the stable monitoring of physiological electrical signals. Current materials often fail to maintain operation at skin interface, which subject constant change, due an inadequate balance viscoelastic properties. In this study, a dynamic adaptive network involving metal coordination with hierarchical hydrogen bonding developed. The multilayered supramolecular structure has enabled polymer chains generate new physical entanglements upon dissociation. This cross‐linking allows eutectogel sustain viscosity and elasticity across broad frequency range (10 −7 –340 Hz). Furthermore, metal‐based exhibits enhanced stretchability (1800%), good conductivity (125 mS m −1 ), wide operating temperature (−70–100 °C), strong interfacial adhesion. offers superior stability in acquisition signals when compared standard commercial gels. Viable application resultant strain sensors demonstrated human–machine interaction (HMI) virtual reality (VR) haptic interaction. addition, convolutional neural (CNN) algorithm employed develop intelligent system evaluating motion states using surface electromyography (sEMG) signals, achieving accuracy 94.1%.
Язык: Английский
Процитировано
1Nanomaterials, Год журнала: 2025, Номер 15(4), С. 298 - 298
Опубликована: Фев. 15, 2025
Flexible sensors are revolutionizing our lives as a key component of intelligent wearables. Their pliability, stretchability, and diverse designs enable foldable portable devices while enhancing comfort convenience. Advances in materials science have provided numerous options for creating flexible sensors. The core their application areas like electronic skin, health medical monitoring, motion human-computer interaction is selecting that optimize sensor performance weight, elasticity, comfort, flexibility. This article focuses on sensors, analyzing "sensing mechanisms-materials-applications" framework. It explores development trajectory, material characteristics, contributions various domains such interaction. concludes by summarizing current research achievements discussing future challenges opportunities. expected to continue expanding into new fields, driving the evolution smart wearables contributing society.
Язык: Английский
Процитировано
1Chemical Engineering Journal, Год журнала: 2025, Номер unknown, С. 161618 - 161618
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
1Advanced Science, Год журнала: 2025, Номер 12(20)
Опубликована: Апрель 25, 2025
Triboelectric nanogenerators (TENGs) are emerging as transformative technologies for sustainable energy harvesting and precision sensing, offering eco-friendly power generation from mechanical motion. They harness while enabling self-sustaining sensing self-powered devices. However, challenges such material optimization, fabrication techniques, design strategies, output stability must be addressed to fully realize their practical potential. Artificial intelligence (AI), with its capabilities in advanced data analysis, pattern recognition, adaptive responses, is revolutionizing fields like healthcare, industrial automation, smart infrastructure. When integrated TENGs, AI can overcome current limitations by enhancing output, stability, adaptability. This review explores the synergistic potential of AI-driven TENG systems, optimizing materials embedding machine learning deep algorithms intelligent real-time sensing. These advancements enable improved harvesting, predictive maintenance, dynamic performance making TENGs more across industries. The also identifies key future research directions, including development low-power algorithms, materials, hybrid robust security protocols AI-enhanced solutions.
Язык: Английский
Процитировано
1Materials Today Sustainability, Год журнала: 2024, Номер 26, С. 100692 - 100692
Опубликована: Фев. 13, 2024
Язык: Английский
Процитировано
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