Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on co...Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.展开更多
Nowadays,spatiotemporal information,positioning,and navigation services have become critical components of new infrastructure.Precise positioning technology is indispensable for determining spatiotemporal information ...Nowadays,spatiotemporal information,positioning,and navigation services have become critical components of new infrastructure.Precise positioning technology is indispensable for determining spatiotemporal information and providing navigation services.展开更多
This paper focuses on the key issues of tool wear condition monitoring in the field of machining,and deeply discusses the application of digital twin technology in this aspect.This paper expounds the principle and arc...This paper focuses on the key issues of tool wear condition monitoring in the field of machining,and deeply discusses the application of digital twin technology in this aspect.This paper expounds the principle and architecture of digital twin technology,analyzes its specific methods in tool wear data acquisition,modeling,simulation,and real-time monitoring,and shows the significant advantages of this technology in improving the accuracy of tool wear monitoring and realizing predictive maintenance.At the same time,the challenges faced by digital twin technology in tool wear condition monitoring are discussed,and the corresponding development direction is put forward,aiming to provide theoretical reference and practical guidance for optimizing tool management by digital twin technology in the machining industry.展开更多
This article focuses on the current computer monitoring and control as the research direction,studying the application strategies of artificial intelligence and big data technology in this field.It includes an introdu...This article focuses on the current computer monitoring and control as the research direction,studying the application strategies of artificial intelligence and big data technology in this field.It includes an introduction to artificial intelligence and big data technology,the application strategies of artificial intelligence and big data technology in computer hardware,software,and network monitoring,as well as the application strategies of artificial intelligence and big data technology in computer process,access,and network control.This analysis aims to serve as a reference for the application of artificial intelligence and big data technology in computer monitoring and control,ultimately enhancing the security of computer systems.展开更多
Marine environmental monitoring and data platform technology plays a pivotal role in advancing marine scientific research,sustainable resource development,ecological conservation,and the effective utilization of ocean...Marine environmental monitoring and data platform technology plays a pivotal role in advancing marine scientific research,sustainable resource development,ecological conservation,and the effective utilization of ocean resources.Despite its growing importance in addressing global environmental and economic challenges,a comprehensive and systematic review of recent advancements in this field remains lacking.To address this gap,this paper synthesizes and analyzes academic literature published between 2021 and 2025,sourced from reputable databases including Scopus and Web of Science,while adhering to the PRISMA systematic review standards.It delineates core technologies employed in marine environmental monitoring,such as advanced sensor systems,robust data acquisition and transmission methods,and innovative data processing and analysis techniques.Furthermore,the study examines the architectural functionalities,data sharing mechanisms,and interoperability standards that underpin modern marine data platforms.The paper also addresses critical technical challenges encountered in deep-water monitoring operations,including equipment durability under extreme conditions,significant economic constraints,data management complexities,and emerging privacy and security concerns.Finally,future development trajectories are outlined,emphasizing the transformative potential of novel materials and artificial intelligence(AI)in enhancing deep-water monitoring capabilities,alongside the urgent need for strengthened global collaboration to improve data sharing protocols and management frameworks.Collectively,the continuous evolution of marine monitoring technologies promises to provide increasingly intelligent,integrated,and systematic support for global marine protection efforts and sustainable resource stewardship.展开更多
The Internet of Things technology provides a comprehensive solution for the real-time monitoring of cold chain logistics by integrating sensors,wireless communication,cloud computing,and big data analysis.Based on thi...The Internet of Things technology provides a comprehensive solution for the real-time monitoring of cold chain logistics by integrating sensors,wireless communication,cloud computing,and big data analysis.Based on this,this paper deeply explores the overview and characteristics of the Internet of Things technology,the feasibility analysis of the Internet of Things technology in the cold chain logistics monitoring,the application analysis of the Internet of Things technology in the cold chain logistics real-time monitoring to better improve the management level and operational efficiency of the cold chain logistics,to provide consumers with safer and fresh products.展开更多
With the advancement of the rural revitalization strategy,preventing poverty recurrence among previously impoverished populations has become a crucial social concern.The application of big data technology in poverty r...With the advancement of the rural revitalization strategy,preventing poverty recurrence among previously impoverished populations has become a crucial social concern.The application of big data technology in poverty recurrence monitoring and agricultural product sales systems can effectively enhance precise identification and early warning capabilities,promoting the sustainable development of rural economies.This paper explores the application of big data technology in poverty recurrence monitoring,analyzes its innovative integration with agricultural product sales systems,and proposes an intelligent monitoring and sales platform model based on big data,aiming to provide a reference for relevant policy formulation.展开更多
With China’s rapidly aging population and the growing preference for aging in place,digital monitoring technologies have emerged as potential tools to support older adults in managing their activities of daily living...With China’s rapidly aging population and the growing preference for aging in place,digital monitoring technologies have emerged as potential tools to support older adults in managing their activities of daily living(ADLs).This study explores the perceptions and acceptance of these technologies among elderly individuals living alone and their informal caregivers(ICs)in Nanshan District,Shenzhen.Grounded in the Unified Theory of Acceptance and Use of Technology(UTAUT),the study employed semi-structured and photo-elicitation interviews to analyze how performance expectancy,effort expectancy,social influence,and facilitating conditions shape technology adoption.The findings reveal clear intergenerational differences:caregivers show higher acceptance and a better understanding of the benefits and functionalities of wearable and environmental monitoring devices,while older adults often express skepticism due to concerns over privacy,usability,and cost.Many elderly participants also cite discomfort,technical complexity,and lack of training as barriers to adoption.Despite these obstacles,both groups acknowledge the potential safety and health benefits of such technologies.The study highlights the need for privacy-by-design features,customized user interfaces,and enhanced digital literacy programs tailored to both elderly users and their caregivers.The research contributes to a sociotechnical understanding of aging-in-place technologies in China and provides actionable insights for developers,policymakers,and healthcare practitioners aiming to enhance home-based elder care.展开更多
A low-power environmental monitoring system based on WSN technology is proposed to effectively monitor the environmental status and ensure the healthy growth of greenhouse crops in the greenhouse. The system performs ...A low-power environmental monitoring system based on WSN technology is proposed to effectively monitor the environmental status and ensure the healthy growth of greenhouse crops in the greenhouse. The system performs dynamic mon- itoring on the environmental data of temperature, humidity, illumination, soil tempera- ture and humidity of the greenhouse, and it reduces the energy consumption by us- ing solar energy and lithium battery as the power supply mode and dynamic power management algorithm combined with improved routing protocol. Stable and reliable, the system could effectively monitor the key environmental factors in the green- house, making it of certain promotion value.展开更多
Using 3S technology, relying on earth-space three-dimensional agriculture disaster monitoring network, remote sensing monitoring model for agricultural disaster in Henan Province was established, and agricultural disa...Using 3S technology, relying on earth-space three-dimensional agriculture disaster monitoring network, remote sensing monitoring model for agricultural disaster in Henan Province was established, and agricultural disaster monitoring system plat- form of Henan Province based on multi-souroe satellite data was further constructed, which realizes dynamic monitoring of agricultural disasters in Henan Province （drought, flood, snow cover and straw burning）.展开更多
Real-time health monitoring and ongoing evaluation of physiological conditions are becoming increasingly vital for the advancement of future medical diagnostics and personalized healthcare solutions.Given that certain...Real-time health monitoring and ongoing evaluation of physiological conditions are becoming increasingly vital for the advancement of future medical diagnostics and personalized healthcare solutions.Given that certain illnesses necessitate prompt and accessible detection methods,wearable chemical sensors have garnered considerable interest for their capability to monitor health through physiological signals and chemical indicators.This review delivers a thorough examination of recent developments in four primary categories of wearable chemical sensors:biosensors,humidity sensors,gas sensors,and ion sensors.We explore the representative materials,device structures,operating mechanisms,and various application scenarios for each type of sensor.By investigating the latest innovations in these technologies,we aim to provide a detailed overview of the current research landscape,highlight existing challenges,and present potential future directions of wearable chemical sensors in healthcare monitoring.展开更多
With the widespread application of lithium batteries in electric vehicles and energy storage systems,battery-related safety and reliability issues have become increasingly prominent.Conventional monitoring methods oft...With the widespread application of lithium batteries in electric vehicles and energy storage systems,battery-related safety and reliability issues have become increasingly prominent.Conventional monitoring methods often struggle to address dynamic changes under complex operando.In recent years,flexible sensing technology has emerged as a promising solution for battery health monitoring due to its high adaptability and conformability to complex structures.Meanwhile,empowered by artificial intelligence(AI)for data analysis,the collected data enables efficient and accurate state assessment,offering robust support for accident prevention.Against this background,this paper first explores the integrated applications of flexible sensors in battery health monitoring and their unique advantages in addressing complex battery operating conditions,while analyzing the potential of AI in battery state analysis.Subsequently,it systematically reviews mainstream flexible sensing technologies(e.g.,film sensors,thermocouples,and optical fiber sensors),elucidating their mechanisms for revealing intricate internal battery processes during operation.Finally,the paper discusses AI’s role in enhancing monitoring efficiency and accuracy,and envisions future research directions and application prospects.This work aims to provide technical references for the battery health monitoring field as well as promote the application of flexible sensing technologies in improving battery system safety and reliability.展开更多
Structural deformation monitoring of flight vehicles based on optical fiber sensing(OFS)technology has been a focus of research in the field of aerospace.After nearly 30 years of research and development,Chinese and i...Structural deformation monitoring of flight vehicles based on optical fiber sensing(OFS)technology has been a focus of research in the field of aerospace.After nearly 30 years of research and development,Chinese and international researchers have made significant advances in the areas of theory and methods,technology and systems,and ground experiments and flight tests.These advances have led to the development of OFS technology from the laboratory research stage to the engineering application stage.However,a few problems encountered in practical applications limit the wider application and further development of this technology,and thus urgently require solutions.This paper reviews the history of research on the deformation monitoring of flight vehicles.It examines various aspects of OFS-based deformation monitoring including the main varieties of OFS technology,technical advantages and disadvantages,suitability in aerospace applications,deformation reconstruction algorithms,and typical applications.This paper points out the key unresolved problems and the main evolution paradigms of engineering applications.It further discusses future development directions from the perspectives of an evolution paradigm,standardization,new materials,intelligentization,and collaboration.展开更多
On the basis of the massive amount of published literature and the long-term practice of our research group in the field of prevention and control of rockburst,the research progress and shortcomings in understanding t...On the basis of the massive amount of published literature and the long-term practice of our research group in the field of prevention and control of rockburst,the research progress and shortcomings in understanding the rockburst phenomenon have been comprehensively in-vestigated.This study focuses on the occurrence mechanism and monitoring and early warning technology for rockburst in coal mines.Results showed that the prevention and control of rockburst had made significant progress.However,with the increasing mining depth,several unre-solved concerns remain challenging.From the in-depth research and analysis,it can be inferred that rockburst disasters involve three main problems,i.e.,the induction factors are complicated,the mechanism is still unclear,and the accuracy of the monitoring equipment and multi-source stereo monitoring technology is insufficient.The monitoring and warning standards of rockburst need to be further clarified and im-proved.Combined with the Internet of Things,cloud computing,and big data,a study of the trend of rockburst needs to be conducted.Further-more,the mechanism of multiphase and multi-field coupling induced by rockburst on a large scale needs to be explored.A multisystem and multiparameter integrated monitoring and early warning system and remote monitoring cloud platform for rockburst should be explored and developed.High-reliability sensing technology and equipment and perfect monitoring and early warning standards are considered to be the de-velopment direction of rockburst in the future.This research will help experts and technicians adopt effective measures for controlling rock-burst disasters.展开更多
Crack monitoring plays a great role in modern structural health monitoring, however, most of the conventional crack inspections have disadvantages in terms of the accuracy, expense, reliability, durability and level o...Crack monitoring plays a great role in modern structural health monitoring, however, most of the conventional crack inspections have disadvantages in terms of the accuracy, expense, reliability, durability and level of instrumentation required. Thus, development of a simple and reliable crack inspection technique that allows continuous monitoring has been desired. In this paper, electrical potential technique and modern surface technology are employed together to develop a new structural surface crack monitoring method. A special crack monitoring coating sensor based on electrical potential technique was deposited on the hot spot of the structure by modern surface technology. The sensor consists of three layers： the isolated layer, the sensing layer and the protective layer. The isolated layer is prepared by anodic oxidation technology, the sensing layer is made of ion plated copper, and the protective layer is made of silicone. The thickness of each layer is at micrometer magnitude. The electrical conductivity of the sensor is very stable, and the fatigue performance of the specimen with or without coating sensor is nearly unchanged. The crack monitoring experiment result shows that there are two sudden rises of the coating sensor electrical potential values, corresponding to different stages of the crack initiation and propagation. Since the width of the surface coating sensor is only 0.5 mm, this crack monitoring sensor can detect the propagation of cracks less than 0.5 mm long. The method proposed takes the simplicity of electrical potential technique and can monitor surface crack of nearly all kinds of structures precisely. The results of this paper may form the basis of a new crack monitoring system.展开更多
The health monitoring for large-scale structures need to resolve a large number of difficulties,such as the data transmission and distributing information handling.To solve these problems,the technology of multi-agent...The health monitoring for large-scale structures need to resolve a large number of difficulties,such as the data transmission and distributing information handling.To solve these problems,the technology of multi-agent is a good candidate to be used in the field of structural health monitoring.A structural health monitoring system architecture based on multi-agent technology is proposed.The measurement system for aircraft airfoil is designed with FBG,strain gage,and corresponding signal processing circuit.The experiment to determine the location of the concentrate loading on the structure is carried on with the system combined with technologies of pattern recognition and multi-agent.The results show that the system can locate the concentrate loading of the aircraft airfoil at the accuracy of 91.2%.展开更多
Emissions from mobile sources and stationary sources contribute to atmospheric pollution in China,and its components,which include ultrafine particles(UFPs),volatile organic compounds(VOCs),and other reactive gases,su...Emissions from mobile sources and stationary sources contribute to atmospheric pollution in China,and its components,which include ultrafine particles(UFPs),volatile organic compounds(VOCs),and other reactive gases,such as NH3and NOx,are the most harmful to human health.China has released various regulations and standards to address pollution from mobile and stationary sources.Thus,it is urgent to develop online monitoring technology for atmospheric pollution source emissions.This study provides an overview of the main progress in mobile and stationary source monitoring technology in China and describes the comprehensive application of some typical instruments in vital areas in recent years.These instruments have been applied to monitor emissions from motor vehicles,ships,airports,the chemical industry,and electric power generation.Not only has the level of atmospheric environment monitoring technology and equipment been improving,but relevant regulations and standards have also been constantly updated.Meanwhile,the developed instruments can provide scientific assistance for the successful implementation of regulations.According to the potential problem areas in atmospheric pollution in China,some research hotspots and future trends of atmospheric online monitoring technology are summarized.Furthermore,more advanced atmospheric online monitoring technology will contribute to a comprehensive understanding of atmospheric pollution and improve environmental monitoring capacity.展开更多
A procedure to recognize individual discontinuities in rock mass from measurement while drilling(MWD)technology is developed,using the binary pattern of structural rock characteristics obtained from in-hole images for...A procedure to recognize individual discontinuities in rock mass from measurement while drilling(MWD)technology is developed,using the binary pattern of structural rock characteristics obtained from in-hole images for calibration.Data from two underground operations with different drilling technology and different rock mass characteristics are considered,which generalizes the application of the methodology to different sites and ensures the full operational integration of MWD data analysis.Two approaches are followed for site-specific structural model building:a discontinuity index(DI)built from variations in MWD parameters,and a machine learning(ML)classifier as function of the drilling parameters and their variability.The prediction ability of the models is quantitatively assessed as the rate of recognition of discontinuities observed in borehole logs.Differences between the parameters involved in the models for each site,and differences in their weights,highlight the site-dependence of the resulting models.The ML approach offers better performance than the classical DI,with recognition rates in the range 89%to 96%.However,the simpler DI still yields fairly accurate results,with recognition rates 70%to 90%.These results validate the adaptive MWD-based methodology as an engineering solution to predict rock structural condition in underground mining operations.展开更多
Attempted to conduct a dynamic monitoring research on coal mining subsidence in western mining areas by using the method of combining D-InSAR and GPS technology. The observation points were installed on the main secti...Attempted to conduct a dynamic monitoring research on coal mining subsidence in western mining areas by using the method of combining D-InSAR and GPS technology. The observation points were installed on the main section and the three-dimensional coordinates of the points were measured by using the method of dynamic differential GPS. Meanwhile, the radar images of this subsidence area were processed by using the method of interferometry with daris software, and the interferogram of the subsidence area was obtained. Through this study, the GPS monitoring data and the InSAR deformation data were integrated and the dynamic subsidence contours of the experimental area were obtained. GPS/InSAR fusion technology provides a new technological means for large-scale dynamic monitoring of coal mining subsidence in western mountainous mining areas and shows good application prospects in coal mining subsidence monitoring and disaster warning.展开更多
Hydraulic fracturing technology is an important means of shale gas development,and microseismic monitoring is the key technology of fracturing effect evaluation.In this study,hydraulic fracturing and microseismic moni...Hydraulic fracturing technology is an important means of shale gas development,and microseismic monitoring is the key technology of fracturing effect evaluation.In this study,hydraulic fracturing and microseismic monitoring were simultaneously conducted in the Eyangye 2HF well(hereinafter referred to as EYY2HF well).The target stratum of this well is the second member of the Doushantuo Formation of the Sinian System,which is the oldest stratum of horizontal shale gas wells in the world.A total of 4341 microseismic fracturing events were identified,and 23 fracturing stages of the well were defined.The fluctuation of the number of events showed a repeating“high-low”pattern,and the average energy of these events showed minimal differences.These findings indicate that the water pressure required for the reconstruction of the EYY2HF well is appropriate.The main body of the fracture network extended from northwest to southeast,consistent with the interpretation of regional geological and seismic data.The stimulated rock volumes showed a linear increase with the increase of the fracturing stage.Some technological measures,such as quick lift displacement,quick lift sand ratio,and pump stop for secondary sand addition,were adopted during fracturing to increase the complexity of the fracture network.Microseismic fracture monitoring of the well achieved expected eff ects and guided real-time fracturing operations and fracturing eff ect evaluation.展开更多
基金supported by the Sichuan Science and Technology Program(Nos.2024JDRC0100 and 2023YFQ0091)the National Natural Science Foundation of China(Nos.U21A20167 and 52475138)the Scientific Research Foundation of the State Key Laboratory of Rail Transit Vehicle System(No.2024RVL-T08).
文摘Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.
文摘Nowadays,spatiotemporal information,positioning,and navigation services have become critical components of new infrastructure.Precise positioning technology is indispensable for determining spatiotemporal information and providing navigation services.
文摘This paper focuses on the key issues of tool wear condition monitoring in the field of machining,and deeply discusses the application of digital twin technology in this aspect.This paper expounds the principle and architecture of digital twin technology,analyzes its specific methods in tool wear data acquisition,modeling,simulation,and real-time monitoring,and shows the significant advantages of this technology in improving the accuracy of tool wear monitoring and realizing predictive maintenance.At the same time,the challenges faced by digital twin technology in tool wear condition monitoring are discussed,and the corresponding development direction is put forward,aiming to provide theoretical reference and practical guidance for optimizing tool management by digital twin technology in the machining industry.
文摘This article focuses on the current computer monitoring and control as the research direction,studying the application strategies of artificial intelligence and big data technology in this field.It includes an introduction to artificial intelligence and big data technology,the application strategies of artificial intelligence and big data technology in computer hardware,software,and network monitoring,as well as the application strategies of artificial intelligence and big data technology in computer process,access,and network control.This analysis aims to serve as a reference for the application of artificial intelligence and big data technology in computer monitoring and control,ultimately enhancing the security of computer systems.
文摘Marine environmental monitoring and data platform technology plays a pivotal role in advancing marine scientific research,sustainable resource development,ecological conservation,and the effective utilization of ocean resources.Despite its growing importance in addressing global environmental and economic challenges,a comprehensive and systematic review of recent advancements in this field remains lacking.To address this gap,this paper synthesizes and analyzes academic literature published between 2021 and 2025,sourced from reputable databases including Scopus and Web of Science,while adhering to the PRISMA systematic review standards.It delineates core technologies employed in marine environmental monitoring,such as advanced sensor systems,robust data acquisition and transmission methods,and innovative data processing and analysis techniques.Furthermore,the study examines the architectural functionalities,data sharing mechanisms,and interoperability standards that underpin modern marine data platforms.The paper also addresses critical technical challenges encountered in deep-water monitoring operations,including equipment durability under extreme conditions,significant economic constraints,data management complexities,and emerging privacy and security concerns.Finally,future development trajectories are outlined,emphasizing the transformative potential of novel materials and artificial intelligence(AI)in enhancing deep-water monitoring capabilities,alongside the urgent need for strengthened global collaboration to improve data sharing protocols and management frameworks.Collectively,the continuous evolution of marine monitoring technologies promises to provide increasingly intelligent,integrated,and systematic support for global marine protection efforts and sustainable resource stewardship.
文摘The Internet of Things technology provides a comprehensive solution for the real-time monitoring of cold chain logistics by integrating sensors,wireless communication,cloud computing,and big data analysis.Based on this,this paper deeply explores the overview and characteristics of the Internet of Things technology,the feasibility analysis of the Internet of Things technology in the cold chain logistics monitoring,the application analysis of the Internet of Things technology in the cold chain logistics real-time monitoring to better improve the management level and operational efficiency of the cold chain logistics,to provide consumers with safer and fresh products.
基金2025 College Students’Innovation Training Program“Return to Poverty Monitoring and Agricultural Products Sales System”2024 College Students’Innovation Training Program“Promoting Straw Recycling to Accelerate the Sustainable Development of Agriculture”(202413207010)。
文摘With the advancement of the rural revitalization strategy,preventing poverty recurrence among previously impoverished populations has become a crucial social concern.The application of big data technology in poverty recurrence monitoring and agricultural product sales systems can effectively enhance precise identification and early warning capabilities,promoting the sustainable development of rural economies.This paper explores the application of big data technology in poverty recurrence monitoring,analyzes its innovative integration with agricultural product sales systems,and proposes an intelligent monitoring and sales platform model based on big data,aiming to provide a reference for relevant policy formulation.
文摘With China’s rapidly aging population and the growing preference for aging in place,digital monitoring technologies have emerged as potential tools to support older adults in managing their activities of daily living(ADLs).This study explores the perceptions and acceptance of these technologies among elderly individuals living alone and their informal caregivers(ICs)in Nanshan District,Shenzhen.Grounded in the Unified Theory of Acceptance and Use of Technology(UTAUT),the study employed semi-structured and photo-elicitation interviews to analyze how performance expectancy,effort expectancy,social influence,and facilitating conditions shape technology adoption.The findings reveal clear intergenerational differences:caregivers show higher acceptance and a better understanding of the benefits and functionalities of wearable and environmental monitoring devices,while older adults often express skepticism due to concerns over privacy,usability,and cost.Many elderly participants also cite discomfort,technical complexity,and lack of training as barriers to adoption.Despite these obstacles,both groups acknowledge the potential safety and health benefits of such technologies.The study highlights the need for privacy-by-design features,customized user interfaces,and enhanced digital literacy programs tailored to both elderly users and their caregivers.The research contributes to a sociotechnical understanding of aging-in-place technologies in China and provides actionable insights for developers,policymakers,and healthcare practitioners aiming to enhance home-based elder care.
基金Supported by the Fund for Independent Innovation of Agricultural Sciences in Jiangsu Province(CX(14)2108&CX(13)5066)~~
文摘A low-power environmental monitoring system based on WSN technology is proposed to effectively monitor the environmental status and ensure the healthy growth of greenhouse crops in the greenhouse. The system performs dynamic mon- itoring on the environmental data of temperature, humidity, illumination, soil tempera- ture and humidity of the greenhouse, and it reduces the energy consumption by us- ing solar energy and lithium battery as the power supply mode and dynamic power management algorithm combined with improved routing protocol. Stable and reliable, the system could effectively monitor the key environmental factors in the green- house, making it of certain promotion value.
基金Supported by Key Scientific and Technological Project of Henan Province(082102140009)~~
文摘Using 3S technology, relying on earth-space three-dimensional agriculture disaster monitoring network, remote sensing monitoring model for agricultural disaster in Henan Province was established, and agricultural disaster monitoring system plat- form of Henan Province based on multi-souroe satellite data was further constructed, which realizes dynamic monitoring of agricultural disasters in Henan Province （drought, flood, snow cover and straw burning）.
基金supported by the Shandong Excellent Young Scientists Fund Program(Overseas)(2023HWYQ-035)the Taishan Scholar Program of Shandong Province(tsqn202306078)+2 种基金the Guangdong Basic and Applied Basic Research Foundation(2024A1515011635)the Natural Science Foundation of Shandong Province(ZR2023MF108)the Jinan Central Hospital(1190022050)。
文摘Real-time health monitoring and ongoing evaluation of physiological conditions are becoming increasingly vital for the advancement of future medical diagnostics and personalized healthcare solutions.Given that certain illnesses necessitate prompt and accessible detection methods,wearable chemical sensors have garnered considerable interest for their capability to monitor health through physiological signals and chemical indicators.This review delivers a thorough examination of recent developments in four primary categories of wearable chemical sensors:biosensors,humidity sensors,gas sensors,and ion sensors.We explore the representative materials,device structures,operating mechanisms,and various application scenarios for each type of sensor.By investigating the latest innovations in these technologies,we aim to provide a detailed overview of the current research landscape,highlight existing challenges,and present potential future directions of wearable chemical sensors in healthcare monitoring.
基金supported by the grant of State Key Laboratory of Space Environment Interaction with Matters,the Science and Technology on Vacuum Technology and Physics Laboratory Fund(HTKJ2023KL510008)Key Program of the National Natural Science Foundation of China(No.62433017)+6 种基金the National Natural Science Foundation of China(No.62274140)the Fundamental Research Funds for the Central Universities(20720230030)the Xiaomi Young Talents Program/Xiaomi Foundation,Shenzhen Science and Technology Program(JCYJ20230807091401003)the Young Elite Scientist Sponsorship Program by Cast(No.YESS20230523)the State Key Laboratory of Space Environment Interaction with Matters(WDZC-HGD-2022-08)the Gansu Provincial Science and Technology Major Project(2244ZZDD1133GGAA000077)the China Aerospace Science and Technology Group Corporation Young Top Talents.
文摘With the widespread application of lithium batteries in electric vehicles and energy storage systems,battery-related safety and reliability issues have become increasingly prominent.Conventional monitoring methods often struggle to address dynamic changes under complex operando.In recent years,flexible sensing technology has emerged as a promising solution for battery health monitoring due to its high adaptability and conformability to complex structures.Meanwhile,empowered by artificial intelligence(AI)for data analysis,the collected data enables efficient and accurate state assessment,offering robust support for accident prevention.Against this background,this paper first explores the integrated applications of flexible sensors in battery health monitoring and their unique advantages in addressing complex battery operating conditions,while analyzing the potential of AI in battery state analysis.Subsequently,it systematically reviews mainstream flexible sensing technologies(e.g.,film sensors,thermocouples,and optical fiber sensors),elucidating their mechanisms for revealing intricate internal battery processes during operation.Finally,the paper discusses AI’s role in enhancing monitoring efficiency and accuracy,and envisions future research directions and application prospects.This work aims to provide technical references for the battery health monitoring field as well as promote the application of flexible sensing technologies in improving battery system safety and reliability.
基金funded by the National Natural Science Foundation of China(51705024,51535002,51675053,61903041,61903042,and 61903041)the National Key Research and Development Program of China(2016YFF0101801)+4 种基金the National Hightech Research and Development Program of China(2015AA042308)the Innovative Equipment Pre-Research Key Fund Project(6140414030101)the Manned Space Pre-Research Project(20184112043)the Beijing Municipal Natural Science Foundation(F7202017 and 4204101)the Beijing Nova Program of Science and Technology(Z191100001119052)。
文摘Structural deformation monitoring of flight vehicles based on optical fiber sensing(OFS)technology has been a focus of research in the field of aerospace.After nearly 30 years of research and development,Chinese and international researchers have made significant advances in the areas of theory and methods,technology and systems,and ground experiments and flight tests.These advances have led to the development of OFS technology from the laboratory research stage to the engineering application stage.However,a few problems encountered in practical applications limit the wider application and further development of this technology,and thus urgently require solutions.This paper reviews the history of research on the deformation monitoring of flight vehicles.It examines various aspects of OFS-based deformation monitoring including the main varieties of OFS technology,technical advantages and disadvantages,suitability in aerospace applications,deformation reconstruction algorithms,and typical applications.This paper points out the key unresolved problems and the main evolution paradigms of engineering applications.It further discusses future development directions from the perspectives of an evolution paradigm,standardization,new materials,intelligentization,and collaboration.
基金This work was financially supported by the National Nat-ural Science Foundation of China(Nos.51634001,51774023,and 51904019).
文摘On the basis of the massive amount of published literature and the long-term practice of our research group in the field of prevention and control of rockburst,the research progress and shortcomings in understanding the rockburst phenomenon have been comprehensively in-vestigated.This study focuses on the occurrence mechanism and monitoring and early warning technology for rockburst in coal mines.Results showed that the prevention and control of rockburst had made significant progress.However,with the increasing mining depth,several unre-solved concerns remain challenging.From the in-depth research and analysis,it can be inferred that rockburst disasters involve three main problems,i.e.,the induction factors are complicated,the mechanism is still unclear,and the accuracy of the monitoring equipment and multi-source stereo monitoring technology is insufficient.The monitoring and warning standards of rockburst need to be further clarified and im-proved.Combined with the Internet of Things,cloud computing,and big data,a study of the trend of rockburst needs to be conducted.Further-more,the mechanism of multiphase and multi-field coupling induced by rockburst on a large scale needs to be explored.A multisystem and multiparameter integrated monitoring and early warning system and remote monitoring cloud platform for rockburst should be explored and developed.High-reliability sensing technology and equipment and perfect monitoring and early warning standards are considered to be the de-velopment direction of rockburst in the future.This research will help experts and technicians adopt effective measures for controlling rock-burst disasters.
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2009AA03Z103)Scientific Research Foundation for the Returned Overseas Chinese Scholars of Ministry of Education of China (Grant No. [2006]331)
文摘Crack monitoring plays a great role in modern structural health monitoring, however, most of the conventional crack inspections have disadvantages in terms of the accuracy, expense, reliability, durability and level of instrumentation required. Thus, development of a simple and reliable crack inspection technique that allows continuous monitoring has been desired. In this paper, electrical potential technique and modern surface technology are employed together to develop a new structural surface crack monitoring method. A special crack monitoring coating sensor based on electrical potential technique was deposited on the hot spot of the structure by modern surface technology. The sensor consists of three layers： the isolated layer, the sensing layer and the protective layer. The isolated layer is prepared by anodic oxidation technology, the sensing layer is made of ion plated copper, and the protective layer is made of silicone. The thickness of each layer is at micrometer magnitude. The electrical conductivity of the sensor is very stable, and the fatigue performance of the specimen with or without coating sensor is nearly unchanged. The crack monitoring experiment result shows that there are two sudden rises of the coating sensor electrical potential values, corresponding to different stages of the crack initiation and propagation. Since the width of the surface coating sensor is only 0.5 mm, this crack monitoring sensor can detect the propagation of cracks less than 0.5 mm long. The method proposed takes the simplicity of electrical potential technique and can monitor surface crack of nearly all kinds of structures precisely. The results of this paper may form the basis of a new crack monitoring system.
基金supported by the Key Program of the National Science Foundation of China(50830201)Aviation Research Foundation(20060952)+1 种基金the National High Technology Research and Development of China(2007AA03Z117)the Natural Science Foundation of Jiansu Province(08kjd560009)
文摘The health monitoring for large-scale structures need to resolve a large number of difficulties,such as the data transmission and distributing information handling.To solve these problems,the technology of multi-agent is a good candidate to be used in the field of structural health monitoring.A structural health monitoring system architecture based on multi-agent technology is proposed.The measurement system for aircraft airfoil is designed with FBG,strain gage,and corresponding signal processing circuit.The experiment to determine the location of the concentrate loading on the structure is carried on with the system combined with technologies of pattern recognition and multi-agent.The results show that the system can locate the concentrate loading of the aircraft airfoil at the accuracy of 91.2%.
基金supported by the National Key Research and Development Program of China(Nos.2016YFC0201000 and 2016YFC0201100)the Plan for Anhui Major Provincial Science&Technology Project(Nos.202203a07020004 and 202003a07020005)+1 种基金the National Natural Science Foundation of China(Nos.U2133212 and 42005108)the Science and Technological Fund of Anhui Province for Outstanding Youth(No.1808085J19)。
文摘Emissions from mobile sources and stationary sources contribute to atmospheric pollution in China,and its components,which include ultrafine particles(UFPs),volatile organic compounds(VOCs),and other reactive gases,such as NH3and NOx,are the most harmful to human health.China has released various regulations and standards to address pollution from mobile and stationary sources.Thus,it is urgent to develop online monitoring technology for atmospheric pollution source emissions.This study provides an overview of the main progress in mobile and stationary source monitoring technology in China and describes the comprehensive application of some typical instruments in vital areas in recent years.These instruments have been applied to monitor emissions from motor vehicles,ships,airports,the chemical industry,and electric power generation.Not only has the level of atmospheric environment monitoring technology and equipment been improving,but relevant regulations and standards have also been constantly updated.Meanwhile,the developed instruments can provide scientific assistance for the successful implementation of regulations.According to the potential problem areas in atmospheric pollution in China,some research hotspots and future trends of atmospheric online monitoring technology are summarized.Furthermore,more advanced atmospheric online monitoring technology will contribute to a comprehensive understanding of atmospheric pollution and improve environmental monitoring capacity.
基金conducted under the illu MINEation project, funded by the European Union’s Horizon 2020 research and innovation program under grant agreement (No. 869379)supported by the China Scholarship Council (No. 202006370006)
文摘A procedure to recognize individual discontinuities in rock mass from measurement while drilling(MWD)technology is developed,using the binary pattern of structural rock characteristics obtained from in-hole images for calibration.Data from two underground operations with different drilling technology and different rock mass characteristics are considered,which generalizes the application of the methodology to different sites and ensures the full operational integration of MWD data analysis.Two approaches are followed for site-specific structural model building:a discontinuity index(DI)built from variations in MWD parameters,and a machine learning(ML)classifier as function of the drilling parameters and their variability.The prediction ability of the models is quantitatively assessed as the rate of recognition of discontinuities observed in borehole logs.Differences between the parameters involved in the models for each site,and differences in their weights,highlight the site-dependence of the resulting models.The ML approach offers better performance than the classical DI,with recognition rates in the range 89%to 96%.However,the simpler DI still yields fairly accurate results,with recognition rates 70%to 90%.These results validate the adaptive MWD-based methodology as an engineering solution to predict rock structural condition in underground mining operations.
基金Supported by the Natural Science Foundation of Shannxi Province
文摘Attempted to conduct a dynamic monitoring research on coal mining subsidence in western mining areas by using the method of combining D-InSAR and GPS technology. The observation points were installed on the main section and the three-dimensional coordinates of the points were measured by using the method of dynamic differential GPS. Meanwhile, the radar images of this subsidence area were processed by using the method of interferometry with daris software, and the interferogram of the subsidence area was obtained. Through this study, the GPS monitoring data and the InSAR deformation data were integrated and the dynamic subsidence contours of the experimental area were obtained. GPS/InSAR fusion technology provides a new technological means for large-scale dynamic monitoring of coal mining subsidence in western mountainous mining areas and shows good application prospects in coal mining subsidence monitoring and disaster warning.
基金National key R&D plan(2016YFC060110605)National major projects(2016ZX05034004-005)。
文摘Hydraulic fracturing technology is an important means of shale gas development,and microseismic monitoring is the key technology of fracturing effect evaluation.In this study,hydraulic fracturing and microseismic monitoring were simultaneously conducted in the Eyangye 2HF well(hereinafter referred to as EYY2HF well).The target stratum of this well is the second member of the Doushantuo Formation of the Sinian System,which is the oldest stratum of horizontal shale gas wells in the world.A total of 4341 microseismic fracturing events were identified,and 23 fracturing stages of the well were defined.The fluctuation of the number of events showed a repeating“high-low”pattern,and the average energy of these events showed minimal differences.These findings indicate that the water pressure required for the reconstruction of the EYY2HF well is appropriate.The main body of the fracture network extended from northwest to southeast,consistent with the interpretation of regional geological and seismic data.The stimulated rock volumes showed a linear increase with the increase of the fracturing stage.Some technological measures,such as quick lift displacement,quick lift sand ratio,and pump stop for secondary sand addition,were adopted during fracturing to increase the complexity of the fracture network.Microseismic fracture monitoring of the well achieved expected eff ects and guided real-time fracturing operations and fracturing eff ect evaluation.
