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PDA-Ag/TiO2 Nanoparticles-Loaded Electrospun Nylon Composite Nanofibrous Film-Based Triboelectric Nanogenerators for Wearable Biomechanical Energy Harvesting and Multifunctional sensors

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advanced FUNCTIONAL MATERIALS 2025年第9期35卷

作者： Manchi, Punnarao Paranjape, Mandar Vasant Kurakula, Anand Graham, Sontyana Adonijah Kavarthapu, Venkata Siva Yu, Jae Su Kyung Hee Univ Inst Wearable Convergence Elect Dept Elect & Informat Convergence Engn 1732 Deogyeong Daero Yongin 17104 Gyeonggi Do South Korea

Although the adoption of self-powered energy harvesting technologies is rapidly increasing, the fabrication of flexible, easy-to-assemble, highly sensitive, and energy-efficient devices continues to pose a significant challenge. Electrospun nanofibrous film-based triboelectric nanogenerators (TENGs) show great promise for mechanical energy harvesting and self-powered sensor applications due to their flexibility, wearability, lightweight, and high electrical output. Herein, a polydopamine (PDA)-treated silver (Ag) nanoparticles (NPs)-decorated titanium dioxide (PDA-Ag/TiO2 NPs) is innovatively incorporated into an electrospun Nylon 66 polymer to construct PDA-Ag/TiO2 nylon composite nanofibrous film (NCNF)-based TENGs (PAT@NCNF TENGs). The prepared nanofibrous films display high dielectric and conductive properties, improving the output electrical performance of the TENG. The electrical output performance of the PAT@NCNF TENG is systematically studied by varying the filler material embedded in the Nylon 66 polymer. The assembled PAT@NCNF TENG exhibits an electrical output of approximate to 370 V, approximate to 15 mu A, and approximate to 5.4 W m(-2) with an excellent pressure sensitivity of approximate to 7.88 V kPa(-1). The proposed PAT@NCNF TENG is used to harvest various forms of biomechanical energy and to power electronic gadgets. Finally, PAT@NCNF TENG is effectively employed for multifunctional sensing systems to monitor biomechanical actions, detect the pressure and impact of objects, and facilitate Morse code transmission and human gait monitoring applications.

关键词： biomechanical sensor mechanical energy harvesting multifunctional sensing system PAT@NCNF TENG PDA-Ag/TiO2 nylon electrospun nanofibrous film

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6th IEEE International conference on Image Processing, applications and systems, IPAS 2025 - Proceedings

6th IEEE International Conference on Image Processing, Appli...

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6th IEEE International conference on Image Processing, applications and systems, IPAS 2025

ISBN: (纸本)9798331506520

The proceedings contain 86 papers. The topics discussed include: robust real-time monitoring of complex human activities using multi modal video analytics;a robust approach for classifying laparoscopic video distortions using ResNet-50;enhancing x-ray image classification through neural architecture;revolutionary MRI imaging for Alzheimer’s: cutting-edge GANs and vision transformer solutions;advanced deep learning strategies for breast cancer image analysis;identifying surgical instruments in pedagogical cataract surgery videos through an optimized aggregation network;enhancing auxiliary cancer classification task for multi-task breast ultrasound diagnosis network;and bioinspired computer vision for effective extended reality applications.

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An Antifreeze Gel as Strain sensors and Machine Learning Assisted Intelligent Motion Monitoring of Triboelectric Nanogenerators in Extreme Environments

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advanced FUNCTIONAL MATERIALS 2025年

作者： Han, Delong Cai, Yuting Wang, xinze Zhang, Weining Li, xusheng Hou, Zhaoru Liu, Jiahui Song, Dengke xu, Wenlong Ludong Univ Sch Chem & Mat Sci Yantai 264025 Peoples R China

Traditional hydrogels tend to freeze and lose performance at low temperatures, limiting their applications. Additionally, hydrogels need to exhibit low hysteresis, excellent cycling stability, and self-adhesion to ensure high-quality signal acquisition in complex environments. To address this challenge, this study designed a dual-network gel in a glycerol (Gly)/H2O solvent system. Due to the combination of chemical and physical crosslinking (hydrogen bonding and electrostatic interactions), the resulting gel exhibits skin-adaptive modulus, high cycling stability, anti-freezing ability, body temperature-induced adhesion, and excellent electrical performance, making it suitable for wearable sensors at low temperatures. Based on this gel, a single-electrode triboelectric nanogenerator (gel-TENG) is developed, achieving efficient conversion of mechanical energy into electrical energy. Further applied to a smart insole, it successfully enabled real-time visualization of plantar pressure distribution and skiing motion recognition. Using a random forest machine learning algorithm, the system accurately classified 11 basic skiing motions, achieving a classification accuracy of 97.1%. This study advances flexible sensors and self-powered systems, supporting intelligent materials research in extreme environments.

关键词： antifreeze gel machine learning self-power sensor

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Quality and Trust Indicators of Digital Road Infrastructure Data Are Essential to Improve Its Usability: An Intelligent Speed Assist (ISA) Study 11

Quality and Trust Indicators of Digital Road Infrastructure ...

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11th International conference on Vehicle Technology and Intelligent Transport systems, VEHITS 2025

作者： van de Sluis, Jacco Altgassen, Daniel Schackmann, Peter-Paul Networks Department TNO - ICT The Hague Netherlands Integrated Vehicle Safety Department TNO - Mobility & Build Environment Helmond Netherlands

ISBN: (纸本)9789897587450

The promise of a Digital Road Infrastructure (DRI) is to improve both road and vehicle safety. ADAS/ADS with DRI support, can help vehicles in overcoming certain sensor limitations, handle more complex operational situations and offer additional situational awareness. An effective DRI must be trusted and must offer the required data quality, both are currently lacking. Intelligent Speed Assist (ISA) is an interesting show case for the added value of DRI. In our approach camera-based traffic sign detections and map-based speed limit information, both occasionally wrong, are augmented with actual speed limit and road layout information coming from DRI. A Misbehaviour Detection and Reporting (MBD&R) concept tailored to the ISA sources is deployed in the vehicle to detect and report ISA related misbehaviour. Trust and quality indicators are calculated for data coming from camera, map and DRI, which are used to verify and compare theses sources and make improved ISA speed limit decisions. The vehicle implementation is tested under real-life traffic conditions. Our work is a first step in realizing a trusted DRI. The long-term goal is collaboration among all stakeholders to implement mechanisms that improve trust and the quality of shared data sources for use in traffic safety applications. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： advanced driver assistance systems

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Smart Steering Wheel: Design of IoMT-Based Non-Invasive Driver Health Monitoring System to Enhance Road Safety

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IET INTELLIGENT TRANSPORT systems 2025年第1期19卷

作者： Khan, Muhammad Adil Chen, Mu Nawaz, Tahir Sedky, Mohamed Sheikh, Muhammad Bashir, Ali Kashif Hassan, Sohail Changan Univ Dept Comp Sci & Technol Xian Peoples R China Natl Univ Sci & Technol Dept Mechatron Engn Islamabad Pakistan Natl Ctr Robot & Automat NCRA Islamabad Pakistan Staffordshire Univ Fac Comp Engn & Sci Stoke On Trent England Univ Warwick Warwick Mfg Grp WMG Coventry England Manchester Metropolitan Univ Dept Comp & Math Manchester England Ascens St John Hosp Dept Cardiac Electrophysiol Detroit MI USA

The integration of Internet of Things (IoT) technology and medical devices in healthcare is termed the Internet of Medical Things (IoMT). This advancement holds promise for numerous applications aimed at mitigating the risk of loss of life through physiological signal monitoring. As the number of road accidents is rapidly increasing, a substantial number of car crashes occur due to medical conditions. Therefore, the need remains to develop an effective solution to enable the prevention of such accidents for enhanced road safety. Unlike existing approaches, this paper proposes a holistic IoMT-based non-invasive driver health monitoring system (DHMS) to monitor important vital signs for detecting abnormal health conditions. The proposed system consists of an embedded system, edge computing, cloud computing, and a mobile application with an alert system, to offer an end-to-end unified solution for driver physiological signal monitoring to detect abnormal health conditions that might lead to a road accident. The system is particularly suited to aid (elderly) people with medical conditions and can also be used for public transport to ensure passenger safety. A detailed experimental evaluation of the proposed system has been performed and its performance accuracy compared with standard medical devices, along with quality factors including usability, portability, and effective sensor placement.

关键词： advanced driver assistance systems health care internet of things road safety

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Soft Micropneumatic Touchpad

ADVANCED INTELLIGENT SYSTEMS

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advanced INTELLIGENT systems 2025年第2期7卷

作者： Lampinen, Vilma Pihlajamaki, Mika Koivikko, Anastasia Sariola, Veikko Tampere Univ Fac Med & Hlth Technol Korkeakoulunkatu 3 PL 692 Tampere 33014 Finland

Soft tactile sensors outputting fluidic signals have many potential applications in soft microfluidic devices and soft robots. However, existing systems have been limited to a single or a few sensors in parallel, so they are not comparable to the state-of-the-art electrical resistive and capacitive touchpads, which can detect rich tactile information, including touch location, pressure, area, and even multiple touches simultaneously. This work reports a soft micropneumatic touchpad. The touchpad consists of 32 pneumatic channels inside soft elastomer, with 16 channels aligned row-wise and 16 column-wise. The flow resistance of each channel is measured using a pressure divider. When the pad is touched, the cross-sectional area of the channels close to the contact location deforms, which changes the flow resistance of those channels. With 32 sensing channels, the location, depth, area of the contact, and even two simultaneous touches can be detected. Letters hand-written on the touchpad can be reconstructed from the measured data. With the assumption of sparsity, a tactile pressure map, with a value at each 16 x 16 grid point, can also be reconstructed. This work opens a path to replace electronic tactile sensors in soft devices with all-fluidic alternatives. sensors outputting fluidic signals would allow replacing electrical or optical sensors in soft devices with their fluidic alternatives. This work reports a soft elastomeric touchpad consisting of 32 pneumatic microchannels. When touched, the cross-sectional area and flow resistance of the channels near the contact location change, allowing the touchpad to detect contact location, depth, area, and even multiple simultaneous *** (c) 2024 WILEY-VCH GmbH

关键词： microfluidics pneumatics sensor array soft sensors soft touchpad

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Visualization Detection of Ultralow Temperature Based on Flexible Cross-linked Polymer systems

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advanced FUNCTIONAL MATERIALS 2025年第10期35卷

作者： Guo, Fengling Chen, Yuanjin Li, Chen Wang, xiaojuan Li, Qiankun He, Meiyi Hou, Hui Yang, Chaolong Chongqing Univ Technol Sch Mat Sci & Engn Chongqing 400054 Peoples R China South China Univ Technol Guangdong Prov Key Lab Luminescence Mol Aggregates Guangzhou 510640 Peoples R China

Ultralow temperature storage has sparked considerable attention with the development of the economy, showing promising applications ranging from biomedical to national defense and other fields. However, the development of ultralow temperature detection is constrained by the brittleness of current materials at low temperatures and the complexity of detection techniques. Consequently, the challenge exists in finding efficient solutions to material tolerance issues and achieving rapid detection of ultralow temperature. Herein, a novel flexible cross-linked polymer TPTA@PU film with long afterglow, high phosphorescence quantum efficiency, and excellent mechanical properties are successfully fabricated. Interestingly, the obtained TPTA@PU films demonstrate a notable thermoresponsive behavior, with the afterglow color shifting rapidly from blue to green within the temperature ranges from 80 to 280 K. Additionally, there is a positive linear correlation between the RGB values of the afterglow color and the corresponding temperature. Based on these prominent features, an ultralow temperature sensor is realized by utilizing TPTA@PU films as thermoresponsive elements. This work can be expected to provide more inspiration and possibilities for using RTP materials in a more cutting-edge field.

关键词： flexible materials room temperature phosphorescence temperature monitoring thermoresponsive ultralow temperature

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In-depth development of temperature insensitive refractive index Fabry-Perot optical sensor 2

In-depth development of temperature insensitive refractive i...

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2nd International conference on Optical Communication and Optical Information Processing, OCOIP 2024

作者： Gao, Yuda Luo, Yanhua Institute of Fiber Optics Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai200444 China

ISBN: (数字)9781510688995

ISBN: (纸本)9781510688988

sensors based on optical fiber interference structures offer benefits such as high sensitivity, simple fabrication and good compatibility, and are widely used in fields like biological monitoring, chemical engineering, and environmental monitoring. However, these sensors often face unavoidable cross-sensitivity issues between temperature and refractive index. Therefore, developing a new optical fiber refractive index sensor that is insensitive to temperature and has a broad refractive index measurement range remains a significant research issue. In this work, proposing a temperature-insensitive refractive index sensor featuring a two-stage Fabry-Perot (F-P) cavity made from single-mode fiber (SMF), capillary fiber (CF), and no core fiber (NCF) based on the principle of mode interference. The research experimentally investigates the sensor's sensitivity to temperature and refractive index. Results indicate that the sensor's amplitude correlates linearly with the refractive index in both optical and Fourier domains, covering a refractive index range of 1.3164 to 1.4215. In the Fourier domains, sensitivities of - 0.7184/refractive index unit (RIU) and - 0.2672/RIU are recorded at two distinct positions, respectively. A direct relationship between the amplitude and the refractive index is established. Additionally, the proposed sensor is almost insensitive to temperature in both the wavelength and Fourier domains. At the same time, experimental validation using water, ethanol, isopropanol, and glycerin solutions with varying refractive indexes, yielding results that align well with the established refractive index relationship. © 2025 SPIE.

关键词： Fabry-Perot interferometers

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A Comprehensive Survey on Traffic Light Detection sensors for Vehicle Safety and Automatic Emergency Braking systems Using Deep Learning Techniques 3rd

A Comprehensive Survey on Traffic Light Detection Sensors fo...

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3rd International conference on Intelligent systems and Sustainable Computing, ICISSC 2023

作者： Gowri, B. Shyamala Priya, G. Vishnu Anjana, S. Arjun, V. Kodal, Devendraa Department of Computer Science and Engineering Easwari Engineering College Tamil Nadu Chennai India

ISBN: (纸本)9789819783540

The integration of Traffic Light Detection (TLD) systems with advanced Emergency Braking systems (AEBS) marks a critical milestone in enhancing road safety and paving the way for advanced autonomous driving. This survey paper provides a panoramic and extensive overview of the state-of-the-art TLD solutions leveraging sensors and deep learning techniques. With an increasing emphasis on accident prevention and traffic management, the intersection of TLD and AEBS has become a focal point of research and development. This survey begins by elucidating the fundamental challenges associated with TLD, including varying environmental conditions, occlusions, and complex traffic scenarios. We explore the pivotal role of sensors such as cameras, LiDAR, and radar in providing the requisite data for TLD, and delve into the intricacies of sensor fusion techniques for enhanced perception. Deep Learning has emerged as a cornerstone technology in TLD, enabling robust object detection, classification, and real-time decision-making. We meticulously analyze a spectrum of deep learning architectures including Single-Shot Detectors (SSD), Faster R-CNN, YOLO, and custom-designed networks tailored for TLD applications. Furthermore, the survey examines critical components of the TLD pipeline, encompassing data collection, preprocessing, model training, real-time inference, and integration with AEBS. Emphasis is placed on real-time constraints, multi-modal sensor fusion, and adaptability to diverse traffic light configurations. The paper also delves into the significance of accurate traffic light state prediction, going beyond mere detection to anticipate traffic light changes and optimize vehicle control actions. Human-centric interaction and privacy concerns are addressed, encompassing driver warnings, user interfaces, and data anonymization strategies. Moreover, the survey discusses the importance of safety, validation, and collaboration within the TLD and AEBS ecosystem, emphasizing compl

关键词： Road and street markings

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Research on the development and application of an interactive AI-based power supply system 2

Research on the development and application of an interactiv...

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2nd International conference on Big Data, Computational Intelligence, and applications, BDCIA 2024

作者： Gao, Jinming Zhu, Pingfei xiong, Genxin Wang, Yukun Liu, Lei Shu, Yanfei Beijing China-power Information Technology Co. Ltd. Changping District Beijing102206 China

ISBN: (纸本)9781510689053

With the rapid evolution of digital technologies, the application of artificial intelligence (AI) in power systems has become increasingly critical to addressing the growing complexity and dynamic demands of modern energy markets. Traditional power marketing models are no longer sufficient to meet the need for real-time interaction, intelligent service delivery, and seamless collaboration among stakeholders. This study aims to develop an AI-powered, interactive power supply system to transform marketing processes and enhance service capabilities. Leveraging a co-innovation strategy-"AI + power marketing"-the proposed system integrates multimodal interaction, real-time voice communication, and intelligent solution generation, enabling dynamic engagement between users and service providers. The research employs advanced AI algorithms to optimize interaction design, improve solution accuracy, and streamline digital marketing workflows. Results from simulations and real-world applications demonstrate significant improvements in user-centric service quality, operational efficiency, and the digitalization of power marketing. These findings highlight the effectiveness of AI-based approaches in fostering intelligent transformation within the energy sector, offering a scalable framework for future advancements in power system marketing and services. © 2025 SPIE.

关键词： Artificial intelligence Power supplies Intelligence systems Industry Human computer interaction Industrial applications Inspection Design Power consumption systems modeling

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