Accelerate processor, efficient software and pervasive connections provide sensor nodes with more powerful computation and storage ability, which can offer various services to user. Based on these atomic services, dif...Accelerate processor, efficient software and pervasive connections provide sensor nodes with more powerful computation and storage ability, which can offer various services to user. Based on these atomic services, different sensor nodes can cooperate and compose with each other to complete more complicated tasks for user. However, because of the regional characteristic of sensor nodes, merging data with different sensitivities become a primary requirement to the composite services, and information flow security should be intensively considered during service composition. In order to mitigate the great cost caused by the complexity of modeling and the heavy load of single-node verification to the energy-limited sensor node, in this paper, we propose a new distributed verification framework to enforce information flow security on composite services of smart sensor network. We analyze the information flows in composite services and specify security constraints for each service participant. Then we propose an algorithm over the distributed verification framework involving each sensor node to participate in the composite service verification based on the security constraints. The experimental results indicate that our approach can reduce the cost of verification and provide a better load balance.展开更多
Wireless smart sensors(WSS)process field data and inform inspectors about the infrastructure health and safety.In bridge engineering,inspectors need reliable data about changes in displacements under loads to make cor...Wireless smart sensors(WSS)process field data and inform inspectors about the infrastructure health and safety.In bridge engineering,inspectors need reliable data about changes in displacements under loads to make correct decisions about repairs and replacements.Access to displacement information in the field and in real-time remains a challenge as inspectors do not see the data in real time.Displacement data from WSS in the field undergoes additional processing and is seen at a different location.If inspectors were able to see structural displacements in real-time at the locations of interest,they could conduct additional observations,creating a new,information-based,decision-making reality in the field.This paper develops a new,human-centered interface that provides inspectors with real-time access to actionable structural data during inspection and monitoring enhanced by augmented reality(AR).It summarizes and evaluates the development and validation of the new human-infrastructure interface in laboratory experiments.The experiments demonstrate that the interface that processes all calculations in the AR device accurately estimates dynamic displacements in comparison with the laser.Using this new AR interface tool,inspectors can observe and compare displacement data,share it across space and time,visualize displacements in time history,and understand structural deflection more accurately through a displacement time history visualization.展开更多
The recent resurgence of pneumoconiosis among coal miners in the United States has been linked to their exposure to excessive levels of coal dust.PDM3700 monitors are used in the mining industry to measure each miner&...The recent resurgence of pneumoconiosis among coal miners in the United States has been linked to their exposure to excessive levels of coal dust.PDM3700 monitors are used in the mining industry to measure each miner's coal dust exposure levels and control overexposure.However,the high cost of the PDM3700 hinders its use in measuring the exposure levels of all miners.Plantower PMS5003 low-cost particulate matter(PM)sensors can measure coal dust concentrations with high spatial resolution in real-time owing to their low cost and small size.However,these sensors require extensive calibration to ensure a high accuracy over long deployment periods.Because they have only been calibrated for mining-induced PM monitoring using linear regression models,the objective of this study was to leverage machine learning algorithms for calibration of coal-dust-monitoring sensors.Laboratory collocation tests were performed using the PDM3700 and aerodynamic particle sizer as reference monitors in a wind tunnel at a wide range of concentrations(0-3mg/m^(3)),temperatures(20-32℃),and relative humidities(23%-43%).The results revealed that nonlinear machine learning techniques significantly outperformed traditional linear regression models for low-cost sensor calibration.With the artificial neural network(ANN)being the strongest calibration model,Pearson's correlation of the PMS5003 sensors reached 0.98 and 0.97,those of the Airtrek sensors reached of 0.89 and 0.91,and those of the GasLab sensors reached 0.93 and 0.92.This shows a 2%-11%improvement in model performance over the linear regression model using ANN calibration.The success of the machine learning algorithms used in this study demonstrates the feasibility of deploying low-cost PM sensors for coal dust monitoring in mines.展开更多
Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,etc.With the development of sensor technology,wireless communication,smart...Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,etc.With the development of sensor technology,wireless communication,smart monitoring terminal,cloud storage/computing technology,and artificial intelligence,smart gas sensors represent the future of gassensing due to their merits of real-time multifunctional monitoring,earlywarning function,and intelligent and automated feature.Various electronicand optoelectronic gas sensors have been developed for high-performancesmart gas analysis.With the development of smart terminals and the maturityof integrated technology,flexible and wearable gas sensors play an increasingrole in gas analysis.This review highlights recent advances of smart gassensors in diverse applications.The structural components and fundamentalprinciples of electronic and optoelectronic gas sensors are described,andflexible and wearable gas sensor devices are highlighted.Moreover,sensorarray with artificial intelligence algorithms and smart gas sensors in“Internet of Things”paradigm are introduced.Finally,the challengesand perspectives of smart gas sensors are discussed regarding the future need of gas sensors for smart city and healthy living.展开更多
We discuss blending sensor scheduling strategies with particle filtering (PF) methods to deal with the prob-lem of tracking a ‘smart’ target, that is, a target being able to be aware it is being tracked and act in a...We discuss blending sensor scheduling strategies with particle filtering (PF) methods to deal with the prob-lem of tracking a ‘smart’ target, that is, a target being able to be aware it is being tracked and act in a manner that makes the future track more difficult. We concern here how to accurately track the target with a care on concealing the observer to a possible extent. We propose a PF method, which is tailored to mix a sensor scheduling technique, called covariance control, within its framework. A Rao-blackwellised unscented Kal-man filter (UKF) is used to produce proposal distributions for the PF method, making it more robust and computationally efficient. We show that the proposed method can balance the tracking filter performance with the observer’s concealment.展开更多
The wireless sensor network （WSN） consists of sensor nodes that interact with each other to collectively monitor environmental or physical conditions at different locations for the intended users. One of its potenti...The wireless sensor network （WSN） consists of sensor nodes that interact with each other to collectively monitor environmental or physical conditions at different locations for the intended users. One of its potential deployments is in the form of smart home and ambient assisted living （SHAAL）to measure patients or elderly physiological signals, control home appliances, and monitor home. This paper focuses on the development of a wireless sensor node platform for SHAAL application over WSN which complies with the IEEE 802.15.4 standard and operates in 2.4 GHz ISM （industrial, scientific, and medical） band. The initial stage of SHAAL application development is the design of the wireless sensor node named TelG mote. The main features of TelG mote contributing to the green communications include low power consumption, wearable, flexible, user-friendly, and small sizes. It is then embedded with a self-built operating system named WiseOS to support customized operation. The node can achieve a packet reception rate （PRR） above 80% for a distance of up to 8 m. The designed TelG mote is also comparable with the existing wireless sensor nodes available in the market.展开更多
Based on the advantages of the fiber Bragg grating sensing technology,this paper presents a principle of a novel smart concrete with fiber optical Bragg grating sensor,analyses the theory and characteristics,illustrat...Based on the advantages of the fiber Bragg grating sensing technology,this paper presents a principle of a novel smart concrete with fiber optical Bragg grating sensor,analyses the theory and characteristics,illustrates the key technology and method to make the fiber Bragg grating sensor for the smart concrete,and proves the feasibility with experiments.The results indicate that the smart concrete with fiber Bragg grating sensors is feasible in the structure monitoring and damage diagnosing in the long run.展开更多
The discovery of laser-induced graphene(LIG) from polymers in 2014 has aroused much attention in recent years.A broad range of applications,including batteries,catalysis,sterilization,and separation,have been explored...The discovery of laser-induced graphene(LIG) from polymers in 2014 has aroused much attention in recent years.A broad range of applications,including batteries,catalysis,sterilization,and separation,have been explored.The advantages of LIG technology over conventional graphene synthesis methods are conspicuous,which include designable patterning,environmental friendliness,tunable compositions,and controllable morphologies.In addition,LIG possesses high porosity,great flexibility,and mechanical robustness,and excellent electric and thermal conductivity.The patternable and printable manufacturing process and the advantageous properties of LIG illuminate a new pathway for developing miniaturized graphene devices.Its use in sensing applications has grown swiftly from a single detection component to an integrated smart detection system.In this minireview,we start with the introduction of synthetic efforts related to the fabrication of LIG sensors.Then,we highlight the achievement of LIG sensors for the detection of a diversity of stimuli with a focus on the design principle and working mechanism.Future development of the techniques toward in situ and smart detection of multiple stimuli in widespread applications will be discussed.展开更多
Nowadays,healthcare applications necessitate maximum volume of medical data to be fed to help the physicians,academicians,pathologists,doctors and other healthcare professionals.Advancements in the domain of Wireless ...Nowadays,healthcare applications necessitate maximum volume of medical data to be fed to help the physicians,academicians,pathologists,doctors and other healthcare professionals.Advancements in the domain of Wireless Sensor Networks(WSN)andMultimediaWireless Sensor Networks(MWSN)are tremendous.M-WMSN is an advanced form of conventional Wireless Sensor Networks(WSN)to networks that use multimedia devices.When compared with traditional WSN,the quantity of data transmission in M-WMSN is significantly high due to the presence of multimedia content.Hence,clustering techniques are deployed to achieve low amount of energy utilization.The current research work aims at introducing a new Density Based Clustering(DBC)technique to achieve energy efficiency inWMSN.The DBC technique is mainly employed for data collection in healthcare environment which primarily depends on three input parameters namely remaining energy level,distance,and node centrality.In addition,two static data collector points called Super Cluster Head(SCH)are placed,which collects the data from normal CHs and forwards it to the Base Station(BS)directly.SCH supports multi-hop data transmission that assists in effectively balancing the available energy.Adetailed simulation analysiswas conducted to showcase the superior performance of DBC technique and the results were examined under diverse aspects.The simulation outcomes concluded that the proposed DBC technique improved the network lifetime to a maximum of 16,500 rounds,which is significantly higher compared to existing methods.展开更多
基金supported in part by National Natural Science Foundation of China(61502368,61303033,U1135002 and U1405255)the National High Technology Research and Development Program(863 Program)of China(No.2015AA017203)+1 种基金the Fundamental Research Funds for the Central Universities(XJS14072,JB150308)the Aviation Science Foundation of China(No.2013ZC31003,20141931001)
文摘Accelerate processor, efficient software and pervasive connections provide sensor nodes with more powerful computation and storage ability, which can offer various services to user. Based on these atomic services, different sensor nodes can cooperate and compose with each other to complete more complicated tasks for user. However, because of the regional characteristic of sensor nodes, merging data with different sensitivities become a primary requirement to the composite services, and information flow security should be intensively considered during service composition. In order to mitigate the great cost caused by the complexity of modeling and the heavy load of single-node verification to the energy-limited sensor node, in this paper, we propose a new distributed verification framework to enforce information flow security on composite services of smart sensor network. We analyze the information flows in composite services and specify security constraints for each service participant. Then we propose an algorithm over the distributed verification framework involving each sensor node to participate in the composite service verification based on the security constraints. The experimental results indicate that our approach can reduce the cost of verification and provide a better load balance.
基金Air Force Research Laboratory(AFRL,Grant No.FA9453-18-2-0022)the New Mexico Consortium(NMC,Grant No.2RNA6)the US Department of Transportation Center:Transportation Consortium of South-Central States(TRANSET)Project 19STUNM02(TRANSET,Grant No.8-18-060ST)。
文摘Wireless smart sensors(WSS)process field data and inform inspectors about the infrastructure health and safety.In bridge engineering,inspectors need reliable data about changes in displacements under loads to make correct decisions about repairs and replacements.Access to displacement information in the field and in real-time remains a challenge as inspectors do not see the data in real time.Displacement data from WSS in the field undergoes additional processing and is seen at a different location.If inspectors were able to see structural displacements in real-time at the locations of interest,they could conduct additional observations,creating a new,information-based,decision-making reality in the field.This paper develops a new,human-centered interface that provides inspectors with real-time access to actionable structural data during inspection and monitoring enhanced by augmented reality(AR).It summarizes and evaluates the development and validation of the new human-infrastructure interface in laboratory experiments.The experiments demonstrate that the interface that processes all calculations in the AR device accurately estimates dynamic displacements in comparison with the laser.Using this new AR interface tool,inspectors can observe and compare displacement data,share it across space and time,visualize displacements in time history,and understand structural deflection more accurately through a displacement time history visualization.
基金funded by the National Science Foundation(No.2034198)the National Institute for Occupational Safety and Health(NIOSH)(No.75D30123C17714)
文摘The recent resurgence of pneumoconiosis among coal miners in the United States has been linked to their exposure to excessive levels of coal dust.PDM3700 monitors are used in the mining industry to measure each miner's coal dust exposure levels and control overexposure.However,the high cost of the PDM3700 hinders its use in measuring the exposure levels of all miners.Plantower PMS5003 low-cost particulate matter(PM)sensors can measure coal dust concentrations with high spatial resolution in real-time owing to their low cost and small size.However,these sensors require extensive calibration to ensure a high accuracy over long deployment periods.Because they have only been calibrated for mining-induced PM monitoring using linear regression models,the objective of this study was to leverage machine learning algorithms for calibration of coal-dust-monitoring sensors.Laboratory collocation tests were performed using the PDM3700 and aerodynamic particle sizer as reference monitors in a wind tunnel at a wide range of concentrations(0-3mg/m^(3)),temperatures(20-32℃),and relative humidities(23%-43%).The results revealed that nonlinear machine learning techniques significantly outperformed traditional linear regression models for low-cost sensor calibration.With the artificial neural network(ANN)being the strongest calibration model,Pearson's correlation of the PMS5003 sensors reached 0.98 and 0.97,those of the Airtrek sensors reached of 0.89 and 0.91,and those of the GasLab sensors reached 0.93 and 0.92.This shows a 2%-11%improvement in model performance over the linear regression model using ANN calibration.The success of the machine learning algorithms used in this study demonstrates the feasibility of deploying low-cost PM sensors for coal dust monitoring in mines.
基金supported by the National Natural Science Foundation of China(No.22376159)the Fundamental Research Funds for the Central Universities.
文摘Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,etc.With the development of sensor technology,wireless communication,smart monitoring terminal,cloud storage/computing technology,and artificial intelligence,smart gas sensors represent the future of gassensing due to their merits of real-time multifunctional monitoring,earlywarning function,and intelligent and automated feature.Various electronicand optoelectronic gas sensors have been developed for high-performancesmart gas analysis.With the development of smart terminals and the maturityof integrated technology,flexible and wearable gas sensors play an increasingrole in gas analysis.This review highlights recent advances of smart gassensors in diverse applications.The structural components and fundamentalprinciples of electronic and optoelectronic gas sensors are described,andflexible and wearable gas sensor devices are highlighted.Moreover,sensorarray with artificial intelligence algorithms and smart gas sensors in“Internet of Things”paradigm are introduced.Finally,the challengesand perspectives of smart gas sensors are discussed regarding the future need of gas sensors for smart city and healthy living.
文摘We discuss blending sensor scheduling strategies with particle filtering (PF) methods to deal with the prob-lem of tracking a ‘smart’ target, that is, a target being able to be aware it is being tracked and act in a manner that makes the future track more difficult. We concern here how to accurately track the target with a care on concealing the observer to a possible extent. We propose a PF method, which is tailored to mix a sensor scheduling technique, called covariance control, within its framework. A Rao-blackwellised unscented Kal-man filter (UKF) is used to produce proposal distributions for the PF method, making it more robust and computationally efficient. We show that the proposed method can balance the tracking filter performance with the observer’s concealment.
基金supported by the Ministry of Higher Education,Malaysia under Grant No.R.J130000.7823.4L626
文摘The wireless sensor network （WSN） consists of sensor nodes that interact with each other to collectively monitor environmental or physical conditions at different locations for the intended users. One of its potential deployments is in the form of smart home and ambient assisted living （SHAAL）to measure patients or elderly physiological signals, control home appliances, and monitor home. This paper focuses on the development of a wireless sensor node platform for SHAAL application over WSN which complies with the IEEE 802.15.4 standard and operates in 2.4 GHz ISM （industrial, scientific, and medical） band. The initial stage of SHAAL application development is the design of the wireless sensor node named TelG mote. The main features of TelG mote contributing to the green communications include low power consumption, wearable, flexible, user-friendly, and small sizes. It is then embedded with a self-built operating system named WiseOS to support customized operation. The node can achieve a packet reception rate （PRR） above 80% for a distance of up to 8 m. The designed TelG mote is also comparable with the existing wireless sensor nodes available in the market.
文摘Based on the advantages of the fiber Bragg grating sensing technology,this paper presents a principle of a novel smart concrete with fiber optical Bragg grating sensor,analyses the theory and characteristics,illustrates the key technology and method to make the fiber Bragg grating sensor for the smart concrete,and proves the feasibility with experiments.The results indicate that the smart concrete with fiber Bragg grating sensors is feasible in the structure monitoring and damage diagnosing in the long run.
基金the funding support from the CityU New Research Initiatives/Infrastructure Support from Central under Grant APRC-9610426the State Key Laboratory of Marine Pollution (SKLMP) Seed Collaborative Research Fund under SKLMP/SCRF/0021。
文摘The discovery of laser-induced graphene(LIG) from polymers in 2014 has aroused much attention in recent years.A broad range of applications,including batteries,catalysis,sterilization,and separation,have been explored.The advantages of LIG technology over conventional graphene synthesis methods are conspicuous,which include designable patterning,environmental friendliness,tunable compositions,and controllable morphologies.In addition,LIG possesses high porosity,great flexibility,and mechanical robustness,and excellent electric and thermal conductivity.The patternable and printable manufacturing process and the advantageous properties of LIG illuminate a new pathway for developing miniaturized graphene devices.Its use in sensing applications has grown swiftly from a single detection component to an integrated smart detection system.In this minireview,we start with the introduction of synthetic efforts related to the fabrication of LIG sensors.Then,we highlight the achievement of LIG sensors for the detection of a diversity of stimuli with a focus on the design principle and working mechanism.Future development of the techniques toward in situ and smart detection of multiple stimuli in widespread applications will be discussed.
文摘Nowadays,healthcare applications necessitate maximum volume of medical data to be fed to help the physicians,academicians,pathologists,doctors and other healthcare professionals.Advancements in the domain of Wireless Sensor Networks(WSN)andMultimediaWireless Sensor Networks(MWSN)are tremendous.M-WMSN is an advanced form of conventional Wireless Sensor Networks(WSN)to networks that use multimedia devices.When compared with traditional WSN,the quantity of data transmission in M-WMSN is significantly high due to the presence of multimedia content.Hence,clustering techniques are deployed to achieve low amount of energy utilization.The current research work aims at introducing a new Density Based Clustering(DBC)technique to achieve energy efficiency inWMSN.The DBC technique is mainly employed for data collection in healthcare environment which primarily depends on three input parameters namely remaining energy level,distance,and node centrality.In addition,two static data collector points called Super Cluster Head(SCH)are placed,which collects the data from normal CHs and forwards it to the Base Station(BS)directly.SCH supports multi-hop data transmission that assists in effectively balancing the available energy.Adetailed simulation analysiswas conducted to showcase the superior performance of DBC technique and the results were examined under diverse aspects.The simulation outcomes concluded that the proposed DBC technique improved the network lifetime to a maximum of 16,500 rounds,which is significantly higher compared to existing methods.
