Application Of Sensing Technology Research Articles

Application of Sensor Technology in Wheelchair Sports for Real-Time Data Collection during Training and Competition and for Assessment of Performance Parameters: A Systematic Review and Future Directions

This review reports on the use of sensors in wheelchair sports to monitor and analyze performance during match and training time. With rapid advancements in electronics and related technologies, understanding performance metrics in wheelchair sports is essential. We reviewed nine studies using various sensor types, including electric motors, inertial measurement units, miniaturized data loggers with magnetic reed switches, and smartphones with inbuilt accelerometers and gyroscopes, operating at frequencies from 8 Hz to 1200 Hz. These studies measured parameters such as angular and translational velocities, distance, number of starts/pushes, and other performance indicators in sports such as basketball, rugby, tennis, and racing. Despite differences in sport types and methodologies, most studies found sensor-derived data effective for assessment of performance. Future developments and research in this field should focus on multi-sensor systems that could provide real-time match analysis and deeper insights into performance metrics. Overall, sensor technologies show significant potential for improving wheelchair sport performance diagnostics, contributing to better athlete training and future wheelchair design, and enhancing competitive outcomes. This review emphasizes the need for continued innovation and standardization in applying sensor technologies in wheelchair sports.

Graphene-Doped Thermoplastic Polyurethane Nanocomposite Film-Based Triboelectric Nanogenerator for Self-Powered Sport Sensor

Triboelectric nanogenerators (TENGs), as novel electronic devices for converting mechanical energy into electrical energy, are better suited as signal-testing sensors or as components within larger wearable Internet of Things (IoT) or Artificial Intelligence (AI) systems, where they handle small-device power supply and signal acquisition. Consequently, TENGs hold promising applications in self-powered sensor technology. As global energy supplies become increasingly tight, research into self-powered sensors has become critical. This study presents a self-powered sport sensor system utilizing a triboelectric nanogenerator (TENG), which incorporates a thermoplastic polyurethane (TPU) film doped with graphene and polytetrafluoroethylene (PTFE) as friction materials. The graphene-doped TPU nanocomposite film-based TENG (GT-TENG) demonstrates excellent working durability. Furthermore, the GT-TENG not only consistently powers an LED but also supplies energy to a sports timer and an electronic watch. It serves additionally as a self-powered sensor for monitoring human movement. The design of this self-powered motion sensor system effectively harnesses human kinetic energy, integrating it seamlessly with sport sensing capabilities.

Research Trends and Hot Topics of Wearable Sensors in Wound Care Over Past 18 Years: A Bibliometric Analysis

ObjectiveThis study determined the development trends, analyzed collaboration networks, and identified research hotspots in the field of wearable sensors for wound care from 2007–2024 using a rigorous bibliometric analysis approach. MethodsBibliometric and scientometric analyses were performed utilizing data sourced from the Web of Science Core Collection database. This study examined publication trends, contributions from various countries and institutions, author productivity, keyword prevalence, and citation patterns to discern research hotspots and potential future avenues in the application of wearable sensors for wound care. ResultsThis study included 1177 articles, which demonstrated a marked increase in publications since 2016 and underscores the burgeoning interest in wearable sensors for wound care. China and the United States have emerged as prominent contributors to the research field, exhibiting numerous international collaborations. An analysis of keywords and citation bursts highlighted wound healing, hydrogels, and sensors as the key research foci with recent trends shifting towards the integration of wearable technology with advanced materials and artificial intelligence for advanced wound management. The research landscape is characterized by a diverse network of international collaborations and an emphasis on interdisciplinary approaches that integrate materials science, sensor technology, and clinical applications. ConclusionThe utilization of wearable sensors in wound care constitutes a rapidly progressing area of research, garnering significant interest and promising avenues for future advances. The integration of wearable sensors with advanced materials and AI technologies presents a frontier of opportunity for innovating wound care methodologies, enhancing patient outcomes, and optimizing the allocation of healthcare resources.

Emerging Multifunctionality in 2D Ferroelectrics: A Theoretical Review of the Interplay With Magnetics, Valleytronics, Mechanics, and Optics

Abstract2D ferroelectric materials present promising applications in information storage, sensor technology, and optoelectronics through their coupling with magnetics/valleytronics, mechanics, and optics, respectively. The integration of 2D ferroelectrics with magnetism enhances data storage density in memory devices by enabling electric‐field‐controlled magnetic states. Ferroelectric‐valley coupling holds promise for high‐speed, low‐energy electronics by leveraging the electrical control of valley polarization. Ferroelectric‐strain coupling results in various polar topologies, with potential applications in high‐density data storage technologies and sensor devices. Moreover, the coupling between ferroelectrics and optics facilitates the development of nonlinear photonics based on ferroelectric materials. This review summarizes the latest theoretical progress in the coupling mechanisms, including the Dzyaloshinskii‐Moriya‐interaction‐induced magnetoelectric coupling, symmetry‐linked ferroelectric‐valley coupling, ferroelectric‐strain‐coupling‐generated polar topologies, and second‐harmonic generation through ferroelectric‐light interactions. The current challenges and future opportunities in harnessing the coupling in 2D ferroelectric materials for multifunctional applications are provided.

Secure pairing-free certificateless aggregate signcryption scheme for IoT

The widespread application of wireless sensor technology in the Internet of Things (IoT) industry significantly enhances productivity. However, the large scale deployment of IoT and the inherent vulnerabilities of wireless communication methods to attacks present significant new challenges. Consequently, there is a need to address the efficiency and security of information transfer in IoT. To effectively solve these issues, this paper presents a secure and efficient pairing-free certificateless aggregated signcryption (CL-ASC) scheme for IoT based on the elliptic curve cryptosystem. Our scheme avoids the complex certificate management issues associated with Public Key Cryptography (PKC) and the key escrow problem found in identity-based cryptography, while maintaining the storage and communication efficiency benefits of aggregated signcryption. The use of secure signcryption and aggregation techniques effectively resists a variety of potential attacks. Both formal and informal security analyses demonstrate that our scheme meets the expected security requirements. Specifically, our scheme shows significant improvements in computational and communication overheads. Compared to other state-of-the-art protocols, our scheme achieves signcryption computation cost of 0.691 ms, unsigncryption computation cost of 3.917 ms for 5 messages, and a total cost of 4.608 ms for 5 messages. Additionally, it provides a signcryption communication overhead of 128 bytes and aggregated communication overhead of 580 bytes for 5 messages.

Recent Advances in Flexible Self-Powered Sensors in Piezoelectric, Triboelectric, and Pyroelectric Fields

The rise of the Internet of things has catalyzed extensive research in the realm of flexible wearable sensors. In comparison with conventional sensor power supply methods that are reliant on external sources, self-powered sensors offer notable advantages in wearable comfort, device structure, and functional expansion. The energy-harvesting modes dominated by piezoelectric nanogenerators (PENGs), triboelectric nanogenerators (TENGs), and pyroelectric nanogenerators (PyENGs) create more possibilities for flexible self-powered sensors. This paper meticulously examines the progress in flexible self-powered devices harnessing TENG, PENG, and PyENG technologies and highlights the evolution of these sensors concerning the material selection, pioneering manufacturing techniques, and device architecture. It also focuses on the research progress of sensors with composite power generation modes. By amalgamating pivotal discoveries and emerging trends, this review not only furnishes a comprehensive portrayal of the present landscape but also accentuates avenues for future research and the application of flexible self-powered sensor technology.

Application of artificial intelligence sensor and visual image technology in the analysis of hydrophilic space landscape characteristics

With the continuous development of intelligent sensor technology and artificial intelligence, the application of artificial intelligence feature recognition at the level of intelligent sensor information acquisition to urban landscape analysis has become a current research trend and hot spot, but also brings us new research directions and challenges. In this paper, the multi-sensor collaborative filtering algorithm is optimized, and a method based on evidence theory is proposed to deal with the fuzzy and unclear information generated in the process of multi-sensor collaboration. Then, the analysis and recognition of multi-sensor fusion information using AI technology are analyzed in detail. This paper discusses the problems in multi-sensor information fusion and related solutions. Combined with the key nodes of 3D object AI feature recognition, multi-sensor collaborative Dempster Shafer evidence theory and 3D convolutional neural network waterfront space landscape feature recognition sub-model are constructed, and the waterfront space landscape recognition analysis model is tested and analyzed. The results show that the multi-sensor information collection Kalman filtering fusion algorithm effectively realizes the recognition of landscape feature information and the filtering of irrelevant interference information combined with an artificial intelligence algorithm to build a landscape feature recognition model. Among all kinds of landscape recognition, the recognition effect of beach inflow is the best, and the recognition accuracy, recall, and F1 value are all above 95. However, the identification effect of hydrophilic plank roads and underwater breakwater is relatively poor. The recognition accuracy of the hydrophilic platform is the lowest at 83.16 % among the eight landscape types, and the recall rate of underwater breakwater is the lowest at 79.96 % among the eight landscape types. In general, the multi-sensor Kalman filtering algorithm information fusion model designed in this paper has higher recognition accuracy and better classification performance for the collection and classification of the entire landscape dataset. The work of this paper provides a new idea and direction for the design and application of waterfront landscape identification and analysis systems based on intelligent sensors and artificial intelligence technology and lays a certain foundation for the intelligent design of urban waterfront landscapes.

Application of gas sensor technology to locate victims in mass disasters – a review

AbstractThe occurrence of mass disasters are increasing as a result of changing climates and the growing threat of terrorist activities/conflicts. When these tragedies strike, it is critical to locate victims. While search and rescue dogs are trained to locate the living, cadaver detection dogs are trained to locate the deceased. These dogs rely on the volatile organic compounds (VOCs) emitted from the victims to do so. Knowing which dog unit to deploy can be challenging, and the victims’ makeup is likely to change following disasters in densely inhabited places, where commingling is likely to occur. The use of electronic nose technologies in forensic science is a recent breakthrough. Due to their ability to detect differing VOCs, this technology can be used to assist in the recovery of victims in disaster events. The most popular types of accessible gas sensor technologies are briefly introduced and compared in this article for their potential use to locate missing persons, both living and deceased. The current and future market needs are articulated, and the lack of enrichment of these needs is examined in relation to the capabilities of existing gas sensors. This will inform further research areas of preference to increase victim detection capabilities.

Advancing Highway Work Zone Safety: A Comprehensive Review of Sensor Technologies for Intrusion and Proximity Hazards

Highway work zones are critical areas where accidents frequently occur, often because of the proximity of workers to heavy machinery and ongoing traffic. With technological advancements in sensor technologies and the Internet of Things, promising solutions are emerging to address these safety concerns. This paper provides a systematic review of existing studies on the application of sensor technologies in enhancing highway work zone safety, particularly in preventing intrusion and proximity hazards. Following the PRISMA (preferred reporting items for systematic reviews and meta-analyses) protocol, the review examines a broad spectrum of publications on various sensor technologies, including GPS (global positioning system), radar, laser, infrared, radio-frequency identification, Bluetooth, ultrasonic, and infrared sensors, detailing their application in reducing intrusion and proximity incidents. The review also assesses these technologies in relation to their accuracy, range, power consumption, cost, and user-friendliness, with a specific emphasis on their suitability for highway work zones. The findings highlighted the potential of sensor technologies to significantly enhance work zone safety. As there are a wide range of sensor technologies to choose from, the review also revealed that the selection of sensors for a particular application needs careful consideration of pertinent factors. Finally, although sensor technologies offer promising solutions for enhancing highway work zone safety, their effective implementation requires comprehensive consideration of various factors beyond their technological capabilities, including developing integrated, cost-effective, user-friendly, and secure systems, and creating regulatory frameworks to support the rapid development of these technologies.

Electrical Capacitors Based on Silicone Oil and Iron Oxide Microfibers: Effects of the Magnetic Field on the Electrical Susceptance and Conductance.

This paper presents the fabrication and characterization of plane capacitors utilizing magnetodielectric materials composed of magnetizable microfibers dispersed within a silicone oil matrix. The microfibers, with a mean diameter of about 0.94 μm, comprise hematite (α-Fe2O3), maghemite (γ-Fe2O3), and magnetite (Fe3O4). This study investigates the electrical behavior of these capacitors under the influence of an external magnetic field superimposed on a medium-frequency alternating electric field, across four distinct volume concentrations of microfibers. Electrical capacitance and resistance measurements were conducted every second over a 60-s interval, revealing significant dependencies on both the quantity of magnetizable phase and the applied magnetic flux density. Furthermore, the temporal stability of the capacitors' characteristics is demonstrated. The obtained data are analyzed to determine the electrical conductance and susceptance of the capacitors, elucidating their sensitivity to variations in microfiber concentration and magnetic field strength. To provide theoretical insight into the observed phenomena, a model based on dipolar approximations is proposed. This model effectively explains the underlying physical mechanisms governing the electrical properties of the capacitors. These findings offer valuable insights into the design and optimization of magnetodielectric-based capacitors for diverse applications in microelectronics and sensor technologies.

Precise measurement of chiral spectrum in the ultraviolet band using weak measurement and a deep neural network model.

Circular dichroism (CD) spectrum and optical rotation (OR) spectrum, crucial for understanding molecular properties and configurations, present challenges due to limited testing methods and equipment accuracy in the ultraviolet (UV) region. This study proposes a weak measurement system for chiral signals in varying concentrations in the ultraviolet range, optimized using a deep neural network (DNN) model. Introducing different post-selections to detect the circular dichroism spectrum and optical rotation spectrum separately, with contrast as a probe, it achieves a detection resolution of up to 10-6 rad. Moreover, the fitted value of the training data can reach 0.9989, enhancing the prediction accuracy of chiral molecule concentrations. This method exhibits considerable promise for applications in chiral measurement and sensor technologies.

Research on the technical principles and applications of massage robots

Massage robots, as innovative therapeutic devices, have garnered significant attention and application due to technological advancements and society's increasing focus on wellness. However, amidst this progress, gaps persist in fully understanding their capabilities and optimizing their functionalities, highlighting the need for further research in this domain. This paper focuses on exploring the intricate technical principles, mechanical structure, sensing technology, and intelligent control systems of massage robots, with the aim of providing both theoretical foundations and practical insights for researchers and practitioners in this field. Specific inquiries encompass the elucidation of working principles, emulation of human massage techniques, mechanical design considerations, applications of sensor technology, and implementations of intelligent control systems within massage robots. Employing a blend of literature review, comparative analysis, and experimental validation, this paper aims to not only deepen the understanding of massage robot functionality but also contribute to the advancement and refinement of this technology, fostering innovation and growth within the industry.

Strain Measurement Technology and Precision Calibration Experiment Based on Flexible Sensing Fiber.

As the basic application of fiber optic sensing technology, strain measurement accuracy as a key index needs to be further calibrated and analyzed. In this paper, accuracy calibration experiments and the related analyses of two fiber-optic sensing technologies, the fiber-optic grating (FBG) and optical frequency domain reflectometry (OFDR), are carried out using a standard beam of equal strength and a mature resistive strain gauge (ESG). The fiber-optic single-point strain data for loading and unloading changes of the beams of equal strength show good continuity and linearity, with good cyclic stability, and the error in the strain test data is less than 2% after repeated loading. At the same time, using finite element theory to analyze the data and using the measured data error within 5%, a good strain test curve linearity is achieved and R2 is better than 0.998. After repeated loading and unloading tests, it is verified that the fiber grating and the distributed optical fiber in the strain test have good stability in repeatability accuracy. The calibration experiments and data analysis in this paper further illustrate the three sensing technologies in determining the strain test accuracy and the advantages and disadvantages of the indicators, and the development of the fiber optic sensing technology application provides basic technical support.

Metallic nanostructures arrays by direct nanoimprinting of silver nanoparticles

The direct nanoimprinting of silver nanoparticles (Ag NPs) generated a plasmonic metallic nanostructure. The Ag NPs used in this study have been synthesized by a phase transfer method. The procedure comprised the utilisation of sodium borohydride to reduce silver nitrate in the presence of a stabilizing agent, which facilitated the transfer of the NPs from the aqueous phase to an organic phase, resulting in uniform and stable particles. The size and shape of the Ag NPs were characterized using electron microscopy, revealing spherical particles with an average diameter of 9 nm. The XRD examination revealed that the nanoparticles exhibit a high degree of crystallinity and possess a cubic geometric phase. The UV-visible absorption spectra demonstrate a significant level of homogeneity in the size. The silicon surface imprinted with Ag NPs exhibits hydrophobic behaviour towards water molecules. This approach allows for precise control of Ag NPs on the substrate, resulting in a robust and effective platform for future applications in sensor technology. Furthermore, the hydrophobic nature of the imprinted surface suggests potential applications in water-repellent coatings or self-cleaning materials.

Water adsorption kinetics on graphene controlled by surface modification of supporting substrates

Sensing layers with an increased affinity for water molecules are essential for the development of highly sensitive humidity sensors. Graphene possesses superior electrical properties that make it suitable for the fabrication of low-noise miniaturized sensors. However, the enhancement of water affinity by introducing surface defects such as covalently attached hydrophilic groups reduces the electrical conductivity of graphene. In this study, we exploit the wetting transparency of graphene to increase its water affinity without introducing defects. Kinetic measurements using a Kelvin probe with a large-diameter tip showed that the rate constant of water adsorption was higher for graphene deposited on a hydrophilic substrate. These findings suggest that the wetting transparency of graphene can be exploited to reduce defect introduction into the graphene sensing layer, and has potential applications in sensor technologies.

Organic thin film transistors in wearable electronics: prospects in sensor technology and healthcare

This paper critically examines Organic Thin Film Transistors (OTFTs), emphasizing their crucial role in enhancing wearable electronics. Through an in-depth exploration of OTFT fundamental principles and unique characteristics, the paper highlights their advantages, such as unparalleled mechanical flexibility and low-temperature processing capabilities, over traditional semiconductor technologies. It delves into OTFT applications in wearable sensor technologies and healthcare monitoring, illustrating the significant benefits of OTFT integration, including superior energy efficiency and augmented user comfort. Addressing the primary challenges of power consumption, environmental stability, and manufacturing scalability, the study proposes innovative solutions to improve these areas. Central to the research objectives is the enhancement of OTFT performance through strategic material selection, fabrication techniques, and integration approaches to ensure device durability and functionality. The paper concludes with a comprehensive analysis of recent advancements and future directions, underscoring the transformative potential of OTFTs in wearable electronics. This research finds that through interdisciplinary collaboration and innovative engineering, it is possible to mitigate the current limitations of OTFTs, paving the way for their widespread adoption in advanced wearable and healthcare technologies.

Simulation of performance skills teaching system based on machine vision and sensor audio signal processing

In the traditional network media education system, there is little content about skill performance, and the malleability is poor. With the combination of Internet technology, online teaching videos of performance skills began to be promoted on a large scale, and with the help of the Internet, the learning of online performance skills has been updated. The aim of this study is to develop a performance skills teaching system based on machine vision and sensor audio signal processing technology to provide a simulated performance environment and personalized instruction. In this study, multiple sensors were used to capture various movement data during the performance of students. Through the use of sensor technology, the system is able to capture information about students' posture, finger position and force in real time, and analyze posture and movement in combination with machine vision technology. The system can also process and analyze the audio signals in the students' performance to evaluate the accuracy and fluency of the playing technique. The application of sensor technology enables the system to accurately capture students' movements and provide timely feedback. The use of machine vision technology allows the system to accurately analyze the student's posture and movements to provide more targeted guidance. The application of audio signal processing algorithm enables the system to objectively evaluate the students' playing skills and help them improve the accuracy and fluency in the playing process.

Modern architectural landscape planning and design based on environmental sensors and 3D point cloud processing

With the continuous development of modern technology, the application of sensor technology in architectural landscape planning and design is becoming increasingly widespread. The combination of environmental sensors and 3D point cloud processing technology provides new possibilities for modern architectural landscape planning and design. Environmental sensors can provide accurate environmental data support for the design process by monitoring the climate conditions of the building site in real-time, better understanding the natural environmental characteristics of the building site, and making targeted planning and design. Environmental sensors can accurately measure the intensity and direction of light, helping designers arrange the layout and window design of buildings to maximize the use of natural lighting. By monitoring and analyzing temperature data, the design team can effectively optimize the energy consumption management of buildings and improve their energy efficiency performance. The combination of 3D point cloud processing technology and environmental sensor data accurately restores the real environment of the building site to a digital model, allowing designers to conduct comprehensive spatial analysis and design. This digital and intelligent design process improves the precision and efficiency of design, allowing the design team to better understand the environmental characteristics of the building site and achieve intelligent and personalized landscape design, Injecting new vitality and creativity into future architectural planning and design.

The role of big data and IoT in logistics supply chain management of e-commerce

With the rapid development of social mode virtualization and electronic component technology, the application of data science and Internet of Things (IoT) technology in the field of e-commerce is gradually increasing. This study aims to explore how these emerging technologies can enhance the advantage of Chinese e-commerce companies in international competition. By comprehensively analyzing the massive data generated by online social networking and the application of IoT sensor technology in logistics and enterprise management, this paper proposes a decision support model based on data analysis. Research methods include data collection, data analysis and case studies. The results of the study show that data analytics and IoT technologies can effectively improve the efficiency of e-commerce operations and customer experience. The conclusion is that these technologies not only contribute to the domestic development of e-commerce enterprises, but also play a non-negligible role in international competition. This research has important implications for understanding the practical applications and potential of new technologies in the field of e-commerce.

Research on design strategy of public space service of commercial complex based on internet of things

The purpose of this study is to explore the design strategy of public space service of commercial complex based on the Internet of Things. By constructing a three-tier model of environmental energy consumption monitoring and management system for commercial complex, the application of network sensor technology is analyzed, and a data access interface based on Windows Communication Foundation (WCF) service is designed to realize batch hosting of WCF services and reduce the complexity of large-scale publishing services. In addition, this paper proposes a clustering method based on probabilistic topics (PTCM), which divides the service search space into probabilistic topics and effectively narrows the service search scope. The simulation results show that the algorithm shortens the shortest distance between mobile nodes and the average network distance, and improves the perceived service quality of the Internet of Things. This study not only provides new ideas and methods for the design of public space services in commercial complexes, but also provides useful reference for the application and promotion of Internet of Things technology in the field of public services.