Recent advancements in passive wireless sensor technology have significantly extended the application scope of sensing,particularly in challenging environments for monitoring industry and healthcare applications.These...Recent advancements in passive wireless sensor technology have significantly extended the application scope of sensing,particularly in challenging environments for monitoring industry and healthcare applications.These systems are equipped with battery-free operation,wireless connectivity,and are designed to be both miniaturized and lightweight.Such features enable the safe,real-time monitoring of industrial environments and support high-precision physiological measurements in confined internal body spaces and on wearable epidermal devices.Despite the exploration into diverse application environments,the development of a systematic and comprehensive research framework for system architecture remains elusive,which hampers further optimization of these systems.This review,therefore,begins with an examination of application scenarios,progresses to evaluate current system architectures,and discusses the function of each component—specifically,the passive sensor module,the wireless communication model,and the readout module—within the context of key implementations in target sensing systems.Furthermore,we present case studies that demonstrate the feasibility of proposed classified components for sensing scenarios,derived from this systematic approach.By outlining a research trajectory for the application of passive wireless systems in sensing technologies,this paper aims to establish a foundation for more advanced,user-friendly applications.展开更多
This article reports the latest development of a wireless sensing system,named Martlet,on high-g shock acceleration measurement.The Martlet sensing node design is based on a Texas Instruments Piccolo microcontroller,w...This article reports the latest development of a wireless sensing system,named Martlet,on high-g shock acceleration measurement.The Martlet sensing node design is based on a Texas Instruments Piccolo microcontroller,with clock frequency programmable up to 90 MHz.The high clock frequency of the microcontroller enables Martlet to support high-frequency data acquisition and high-speed onboard computation.In addition,the extensible design of the Martlet node conveniently allows incorporation of multiple sensor boards.In this study,a high-g accelerometer interface board is developed to allow Martlet to work with the selected microelectromechanical system(MEMS)high-g accelerometers.Besides low-pass and highpass filters,amplification gains are also implemented on the high-g accelerometer interface board.Laboratory impact experiments are conducted to validate the performance of the Martlet wireless sensing system with the high-g accelerometer board.The results of this study show that the performance of the wireless sensing system is comparable to the cabled system.展开更多
Harvesting bio-kinetic energy using a triboelectric nanogenerator(TENG) is one of the promising routes to solve the sustainable energy supply problem for wearable electronics. However, additional materials, complex fa...Harvesting bio-kinetic energy using a triboelectric nanogenerator(TENG) is one of the promising routes to solve the sustainable energy supply problem for wearable electronics. However, additional materials, complex fabricating processes or specific mechanical structures are needed for existing TENGs to harvest bio-kinetic energy. Besides, they need to be tightly attached to the human body, which may result in detachment and malfunction under tense human motion. Herein, an intrinsic epidermal electrode-based TENG(E-TENG) is proposed to harvest human walking energy. The wearing shoes and ground are used as tribo-materials, and the human epidermis is used as the back electrode of the E-TENG. Compared with the traditional TENGs,the E-TENG does not need any additional tribo-materials and complex mechanical structures. Under optimal conditions, the voltage output of E-TENG can reach 914 V. E-TENG has been used as a self-powered warning sensor and pedometer sensor for demonstration. Furthermore, E-TENG based self-powered wireless sensor system has been developed using a newly designed micro energy electronic switch(MEES). Ambient ultraviolet intensity, temperature and humidity information can be monitored and then transmitted to mobile phone every 3.5 min, demonstrating great potential for widespread wearable applications.展开更多
With the rapid development and wide deployment of wireless technology, Wi-Fi signals have no longer been confined to the Internet as a communication medium. Wi-Fi signals will be modulated again by human actions when ...With the rapid development and wide deployment of wireless technology, Wi-Fi signals have no longer been confined to the Internet as a communication medium. Wi-Fi signals will be modulated again by human actions when propagating indoors, carrying rich human body state information. Therefore, a novel wireless sensing technology is gradually emerging that can realize gesture recognition, human daily activity detection, identification,indoor localization and human body tracking, vital signs detection, imaging, and emotional recognition by extracting effective feature information about human actions from Wi-Fi signals. Researchers mainly use channel state information or frequency modulated carrier wave in their current implementation schemes of wireless sensing technology, called "Walls have eyes", and these schemes cover radio-frequency technology, signal processing technology, and machine learning. These available wireless sensing systems can be used in many applications such as smart home, medical health care, search-and-rescue, security, and with the high precision and passively device-free through-wall detection function. This paper elaborates the research actuality and summarizes each system structure and the basic principles of various wireless sensing applications in detail. Meanwhile, two popular implementation schemes are analyzed. In addition, the future diversely application prospects of wireless sensing systems are presented.展开更多
As the main health threat to the elderly living alone and performing indoor activities,falls have attracted great attention from institutions and society.Currently,fall detection systems are mainly based on wear senso...As the main health threat to the elderly living alone and performing indoor activities,falls have attracted great attention from institutions and society.Currently,fall detection systems are mainly based on wear sensors,environmental sensors,and computer vision,which need to be worn or require complex equipment construction.However,they have limitations and will interfere with the daily life of the elderly.On the basis of the indoor propagation theory of wireless signals,this paper proposes a conceptual verification module using Wi-Fi signals to identify human fall behavior.The module can detect falls without invading privacy and affecting human comfort and has the advantages of noninvasive,robustness,universality,and low price.The module combines digital signal processing technology and machine learning technology.This paper analyzes and processes the channel state information(CSI)data of wireless signals,and the local outlier factor algorithm is used to find the abnormal CSI sequence.The support vector machine and extreme gradient boosting algorithms are used for classification,recognition,and comparative research.Experimental results show that the average accuracy of fall detection based on wireless sensing is more than 90%.This work has important social significance in ensuring the safety of the elderly.展开更多
When a human body moves within the coverage range of Wi-Fi signals,the reflected Wi-Fi signals by the various parts of the human body change the propagation path,so analysis of the channel state data can achieve the p...When a human body moves within the coverage range of Wi-Fi signals,the reflected Wi-Fi signals by the various parts of the human body change the propagation path,so analysis of the channel state data can achieve the perception of the human motion.By extracting the Channel State Information(CSI)related to human motion from the Wi-Fi signals and analyzing it with the introduced machine learning classification algorithm,the human motion in the spatial environment can be perceived.On the basis of this theory,this paper proposed an algorithm of human behavior recognition based on CSI wireless sensing to realize deviceless and over-the-air slide turning.This algorithm collects the environmental information containing upward or downward wave in a conference room scene,uses the local outlier factor detection algorithm to segment the actions,and then the time domain features are extracted to train Support Vector Machine(SVM)and eXtreme Gradient Boosting(XGBoost)classification modules.The experimental results show that the average accuracy of the XGBoost module sensing slide flipping can reach 94%,and the SVM module can reach 89%,so the module could be extended to the field of smart classroom and significantly improve speech efficiency.展开更多
Nitrogen dioxide(NO_(2))is a significant air pollutant with harmful effects on human health and the environment.Timely and accurate monitoring of NO_(2)concentrations is crucial for improving air quality and protectin...Nitrogen dioxide(NO_(2))is a significant air pollutant with harmful effects on human health and the environment.Timely and accurate monitoring of NO_(2)concentrations is crucial for improving air quality and protecting public health.However,quantifying NO_(2)in the presence of other gases remains challenging.Herein,we integrate Ru onto the MoS_(2)surface to form Ru-S-Mo active sites,thereby tuning the electronic structure of MoS_(2)for enhanced NO_(2)detection.This sensor shows excellent sensitivity(29.7%at 100×10^(-6)NO_(2)and 25℃),with a linear response to NO_(2)ranging from 0.5 to 200×10^(-6),and a significantly reduced response/recovery time from 160/3636 s for pure MoS_(2)to 58/427 s for Ru@MoS_(2)at 100×10^(-6)NO_(2).Additionally,the sensor is highly selective for NO_(2),exhibiting a response 14 times higher than for other gases,and possesses strong anti-interference capabilities,accurately quantifying NO_(2)in the presence of varying H_(2)concentrations(10×10^(-6)-200×10^(-6))with a low RSD of 5.34%.A portable wireless NO_(2)monitoring system was successfully constructed using Ru@MoS_(2),enabling real-time gas leak detection(10×10^(-6)-50×10^(-6))with hazard warnings and maintaining a stable response to NO_(2)over a 4-week period.This work extends the gas sensing applications of MoS_(2)and provides a portable,wireless,and high-selectivity NO_(2)sensing method for environmental monitoring and safety assurance.展开更多
Since the outbreak of the world-wide novel coronavirus pandemic,crowd counting in public areas,such as in shopping centers and in commercial streets,has gained popularity among public health administrations for preven...Since the outbreak of the world-wide novel coronavirus pandemic,crowd counting in public areas,such as in shopping centers and in commercial streets,has gained popularity among public health administrations for preventing the crowds from gathering.In this paper,we propose a novel adaptive method for crowd counting based on Wi-Fi channel state information(CSI)by using common commercial wireless routers.Compared with previous researches on device-free crowd counting,our proposed method is more adaptive to the change of environ-ment and can achieve high accuracy of crowd count estimation.Because the dis-tance between access point(AP)and monitor point(MP)is typically non-fixed in real-world applications,the strength of received signals varies and makes the tra-ditional amplitude-related models to perform poorly in different environments.In order to achieve adaptivity of the crowd count estimation model,we used convo-lutional neural network(ConvNet)to extract features from correlation coefficient matrix of subcarriers which are insensitive to the change of received signal strength.We conducted experiments in university classroom settings and our model achieved an overall accuracy of 97.79%in estimating a variable number of participants.展开更多
In order to apply compressive sensing in wireless sensor network, inside the nodes cluster classified by the spatial correlation, we propose that a cluster head adopts free space optical communication with space divis...In order to apply compressive sensing in wireless sensor network, inside the nodes cluster classified by the spatial correlation, we propose that a cluster head adopts free space optical communication with space division multiple access, and a sensor node uses a modulating retro-reflector for communication. Thus while a random sampling matrix is used to guide the establishment of links between head cluster and sensor nodes, the random linear projection is accomplished. To establish multiple links at the same time, an optical space division multiple access antenna is designed. It works in fixed beams switching mode and consists of optic lens with a large field of view（FOV）, fiber array on the focal plane which is used to realize virtual channels segmentation, direction of arrival sensor, optical matrix switch and controller. Based on the angles of nodes＇ laser beams, by dynamically changing the route, optical matrix switch actualizes the multi-beam full duplex tracking receiving and transmission. Due to the structure of fiber array, there will be several fade zones both in the focal plane and in lens＇ FOV. In order to lower the impact of fade zones and harmonize multibeam, a fiber array adjustment is designed. By theoretical, simulated and experimental study, the antenna＇s qualitative feasibility is validated.展开更多
Sensing in wireless local area network(WLAN) gains great interests recently. In this paper we focus on the multi-user WLAN sensing problem under the existing 802.11 standards. Multiple stations perform sensing with th...Sensing in wireless local area network(WLAN) gains great interests recently. In this paper we focus on the multi-user WLAN sensing problem under the existing 802.11 standards. Multiple stations perform sensing with the access point and transmit channel state information(CSI)report simultaneously on the basis of uplink-orthogonal frequency division multiple access(OFDMA). Considering the transmission resource consumed in CSI report and the padding wastage in OFDMA based CSI report, we optimize the CSI simplification and uplink resource unit(RU)allocation jointly, aiming to balance the sensing accuracy and padding wastage performances in WLAN sensing. We propose the minimize padding maximize efficiency(MPME) algorithm to solve the problem and evaluate the performance of the proposed algorithm through extensive simulations.展开更多
The future of wireless systems is anticipated to revolutionize human connectivity through a diverse range of applications.The integration of multiple wireless functionalities into a unified system presents a critical ...The future of wireless systems is anticipated to revolutionize human connectivity through a diverse range of applications.The integration of multiple wireless functionalities into a unified system presents a critical challenge due to conflicting requirements in transceiver architecture and signal processing.Recent investigations are directing attention towards the development of systems that serve dual functions,like simultaneous wireless information and power transfer and radar-communication,aimed at boosting operational efficiency and ensuring seamless communication among different wireless capabilities.This review paper aims to discuss the architectural aspects of the integration of radar sensing,data communication,and power transfer.Firstly,the integration of radar sensing and data communication is studied for both cooperating and non-cooperating radar systems with conventional and interferometric architectures.Secondly,the power harvesting approach and internal energy recycling are discussed for the fusion of data communication and energy harvesting.Thirdly,radar sensing and power transfer integration is considered with special focus on harmonic backscattering and self-powered radars.Lastly,a roadmap for next-generation multifunction systems is outlined by considering several scenarios of multiplexing and architectures.展开更多
Device-free gesture recognition is an emerging wireless sensing technique which could recognize gestures by analyzing its influence on surrounding wireless signals,it may empower wireless networks with the augmented s...Device-free gesture recognition is an emerging wireless sensing technique which could recognize gestures by analyzing its influence on surrounding wireless signals,it may empower wireless networks with the augmented sensing ability.Researchers have made great achievements for singleperson device-free gesture recognition.However,when multiple persons conduct gestures simultaneously,the received signals will be mixed together,and thus traditional methods would not work well anymore.Moreover,the anonymity of persons and the change in the surrounding environment would cause feature shift and mismatch,and thus the recognition accuracy would degrade remarkably.To address these problems,we explore and exploit the diversity of spatial information and propose a multidimensional analysis method to separate the gesture feature of each person using a focusing sensing strategy.Meanwhile,we also present a deep-learning based robust device free gesture recognition framework,which leverages an adversarial approach to extract robust gesture feature that is insensitive to the change of persons and environment.Furthermore,we also develop a 77GHz mmWave prototype system and evaluate the proposed methods extensively.Experimental results reveal that the proposed system can achieve average accuracies of 93%and 84%when 10 gestures are conducted in Received:Jun.18,2020 Revised:Aug.06,2020 Editor:Ning Ge different environments by two and four persons simultaneously,respectively.展开更多
This paper addresses some of the problems related to direct surface temperature measurement of a salient pole synchronous generator excitation winding in rotation. Excitation winding temperature is used for determinin...This paper addresses some of the problems related to direct surface temperature measurement of a salient pole synchronous generator excitation winding in rotation. Excitation winding temperature is used for determining the dynamic limit in a PQ diagram. The paper also addresses procedures of improving the accuracy of surface temperature measurement using the contact DS 18B20 digital temperature probes. The paper also provides experimental results of direct temperature measurement of the excitation winding surface conducted in the salient pole synchronous generator in the rotation.展开更多
The integrated sensing and wireless power transfer(ISWPT)technology,in which the radar sensing and wireless power transfer functionalities are implemented using the same hardware platform,has been recently proposed.In...The integrated sensing and wireless power transfer(ISWPT)technology,in which the radar sensing and wireless power transfer functionalities are implemented using the same hardware platform,has been recently proposed.In this paper,we consider a near-field ISWPT system where one hybrid transmitter deploys extremely large-scale antenna arrays,and multiple energy receivers are located in the near-field region of the transmitter.Under such a new scenario,we study radar sensing and wireless power transfer performance trade-offs by optimizing the transmit beamforming vectors.In particular,we consider the transmit beampattern matching and max-min beampattern gain design metrics.For each radar performance metric,we aim to achieve the best performance of radar sensing,while guaranteeing the requirement of wireless power transfer.The corresponding beamforming design problems are non-convex,and the semi-definite relaxation(SDR)approach is applied to solve them globally optimally.Finally,numerical results verify the effectiveness of our proposed solutions.展开更多
Wireless smart sensing is now widely used in various applications such as health monitoring and structural monitoring.In conventional wireless sensor nodes,significant power is consumed in wirelessly transmitting the ...Wireless smart sensing is now widely used in various applications such as health monitoring and structural monitoring.In conventional wireless sensor nodes,significant power is consumed in wirelessly transmitting the raw data.Smart sensing adds local intelligence to the sensor node and reduces the amount of wireless data transmission via on-node digital signal processing.While the total power consumption is reduced compared to conventional wireless sensing,the power consumption of the digital processing becomes as dominant as wireless data transmission.This paper reviews the state-of-the-art energy-efficient digital and wireless IC design techniques for reducing the power consumption of the wireless smart sensor node to prolong battery life and enable self-powered applications.展开更多
Three-dimensional(3D)additive manufacturing techniques have been utilized to make 3D electrical components,such as resistors,capacitors,and inductors,as well as circuits and passive wireless sensors.Using the fused de...Three-dimensional(3D)additive manufacturing techniques have been utilized to make 3D electrical components,such as resistors,capacitors,and inductors,as well as circuits and passive wireless sensors.Using the fused deposition modeling technology and a multiple-nozzle system with a printing resolution of 30μm,3D structures with both supporting and sacrificial structures are constructed.After removing the sacrificial materials,suspensions with silver particles are injected subsequently solidified to form metallic elements/interconnects.The prototype results show good characteristics of fabricated 3D microelectronics components,including an inductor–capacitor-resonant tank circuitry with a resonance frequency at 0.53 GHz.A 3D“smart cap”with an embedded inductor–capacitor tank as the wireless passive sensor was demonstrated to monitor the quality of liquid food(e.g.,milk and juice)wirelessly.The result shows a 4.3%resonance frequency shift from milk stored in the room temperature environment for 36 h.This work establishes an innovative approach to construct arbitrary 3D systems with embedded electrical structures as integrated circuitry for various applications,including the demonstrated passive wireless sensors.展开更多
Being able to significantly reduce system installation time and cost,wireless sensing technology has attracted much interest in the structural health monitoring(SHM)community.This paper reports the field application o...Being able to significantly reduce system installation time and cost,wireless sensing technology has attracted much interest in the structural health monitoring(SHM)community.This paper reports the field application of a wireless sensing system on a 4-span highway bridge located in Wayne,New Jersey in the US.Bridge vibration due to traffic and ambient excitation is measured.To enhance the signal-to-noise ratio,a low-noise high-gain signal conditioning module is developed for the wireless sensing system.Nineteen wireless and nineteen cabled accelerometers are first installed along the sidewalk of two neighboring bridge spans.The performance of the wireless sensing system is compared with the high-precision cabled sensing system.In the next series of testing,16 wireless accelerometers are installed under the deck of another bridge span,forming a 4×4 array.Operating deflection analysis is successfully conducted using the wireless measurement of traffic and ambient vibrations.展开更多
Body area network has attracted extensive attention for its applications in athletics,medical,diagnosis,and rehabilitation training in the next generation personalized health care solutions.Here,a contact-separation d...Body area network has attracted extensive attention for its applications in athletics,medical,diagnosis,and rehabilitation training in the next generation personalized health care solutions.Here,a contact-separation direct current triboelectric nanogenerators(CSDC-TENGs)based selfpowered wireless body area network(SWBAN)is reported that enables multi-joint movements monitoring for human motion.The CSDC-TENG is designed as a flexible active sensor with an internal contact switch,and the flexible substrate makes the TENG-sensor stick onto skin easily.Due to the internal switch,the CSDC-TENG could generate a DC current,a large instantaneous output voltage exceeds 700 V,and an instantaneous power can reach 1.076 W,which is more than 23000 times higher than that of the traditional contact-separation mode TENG in same size and materials without the switch.By coupling with flexible coil,the fixed high-frequency radio signals can be modulated and emitted clearly ranging from 6 to 16 MHz,which can be wirelessly received and demodulated through a reader.Moreover,the SWBAN is demonstrated in a real time monitoring system for joints motion.This work has realized the wearable TENG for self-powered wireless real-time monitoring of body movements driven by low-frequency human daily activities,which may promote a tremendous development of intelligent healthcare,wireless sensing system and body area network.展开更多
Indoor localization is a fundamental requirement for future 6G Intelligent Sensing and Communication(ISAC)systems,enabling precise navigation in environments where Global Positioning System(GPS)signals are unavailable...Indoor localization is a fundamental requirement for future 6G Intelligent Sensing and Communication(ISAC)systems,enabling precise navigation in environments where Global Positioning System(GPS)signals are unavailable.Existing methods,such as map-based navigation or site-specific fingerprinting,often require intensive data collection and lack generalization capability across different buildings,thereby limiting scalability.This study proposes a cross-site,map-free indoor localization framework that uses low-frequency sub-1 GHz radio signals and a Transformer-based neural network for robust positioning without prior environmental knowledge.The Transformer’s self-attention mechanisms allow it to capture spatial correlations among anchor nodes,facilitating accurate localization in unseen environments.Evaluation across two validation sites demonstrates the framework’s effectiveness.In crosssite testing(Site-A),the Transformer achieved a mean localization error of 9.44 m,outperforming the Deep Neural Network(DNN)(10.76 m)and Convolutional Neural Network(CNN)(12.02 m)baselines.In a real-time deployment(Site-B)spanning three floors,the Transformer maintained an overall mean error of 9.81 m,compared with 13.45 m for DNN,12.88 m for CNN,and 53.08 m for conventional trilateration.For vertical positioning,the Transformer delivered a mean error of 4.52 m,exceeding the performance of DNN(4.59 m),CNN(4.87 m),and trilateration(>45 m).The results confirm that the Transformer-based framework generalizes across heterogeneous indoor environments without requiring site-specific calibration,providing stable,sub-12 m horizontal accuracy and reliable vertical estimation.This capability makes the framework suitable for real-time applications in smart buildings,emergency response,and autonomous systems.By utilizing multipath reflections as an informative structure rather than treating them as noise,this work advances artificial intelligence(AI)-native indoor localization as a scalable and efficient component of future 6G ISAC networks.展开更多
In recent years, Compressed Sensing（CS） has been a hot research topic. It has a wide range of applications, such as image processing and speech signal processing owing to its characteristic of removing redundant inf...In recent years, Compressed Sensing（CS） has been a hot research topic. It has a wide range of applications, such as image processing and speech signal processing owing to its characteristic of removing redundant information by reducing the sampling rate. The disadvantage of CS is that the number of iterations in a greedy algorithm such as Orthogonal Matching Pursuit（OMP） is fixed, thus limiting reconstruction precision.Therefore, in this study, we present a novel Reducing Iteration Orthogonal Matching Pursuit（RIOMP） algorithm that calculates the correlation of the residual value and measurement matrix to reduce the number of iterations.The conditions for successful signal reconstruction are derived on the basis of detailed mathematical analyses.When compared with the OMP algorithm, the RIOMP algorithm has a smaller reconstruction error. Moreover, the proposed algorithm can accurately reconstruct signals in a shorter running time.展开更多
基金partially supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.2018R1A6A1A03025242)by the Korea government(MIST)(RS-2023-00302751,RS-2024-00343686)the Research Grant of Kwangwoon University in 2024。
文摘Recent advancements in passive wireless sensor technology have significantly extended the application scope of sensing,particularly in challenging environments for monitoring industry and healthcare applications.These systems are equipped with battery-free operation,wireless connectivity,and are designed to be both miniaturized and lightweight.Such features enable the safe,real-time monitoring of industrial environments and support high-precision physiological measurements in confined internal body spaces and on wearable epidermal devices.Despite the exploration into diverse application environments,the development of a systematic and comprehensive research framework for system architecture remains elusive,which hampers further optimization of these systems.This review,therefore,begins with an examination of application scenarios,progresses to evaluate current system architectures,and discusses the function of each component—specifically,the passive sensor module,the wireless communication model,and the readout module—within the context of key implementations in target sensing systems.Furthermore,we present case studies that demonstrate the feasibility of proposed classified components for sensing scenarios,derived from this systematic approach.By outlining a research trajectory for the application of passive wireless systems in sensing technologies,this paper aims to establish a foundation for more advanced,user-friendly applications.
文摘This article reports the latest development of a wireless sensing system,named Martlet,on high-g shock acceleration measurement.The Martlet sensing node design is based on a Texas Instruments Piccolo microcontroller,with clock frequency programmable up to 90 MHz.The high clock frequency of the microcontroller enables Martlet to support high-frequency data acquisition and high-speed onboard computation.In addition,the extensible design of the Martlet node conveniently allows incorporation of multiple sensor boards.In this study,a high-g accelerometer interface board is developed to allow Martlet to work with the selected microelectromechanical system(MEMS)high-g accelerometers.Besides low-pass and highpass filters,amplification gains are also implemented on the high-g accelerometer interface board.Laboratory impact experiments are conducted to validate the performance of the Martlet wireless sensing system with the high-g accelerometer board.The results of this study show that the performance of the wireless sensing system is comparable to the cabled system.
基金supported by the National Natural Science Foundation of China(Grant Nos. 62274049, 61904042, 62201337)the Natural Science Foundation of Zhejiang(Grant No. LY21F040006)the Zhejiang Province Key R&D Programs(Grant Nos. 2021C05004, 2020C03039,2023C01192)。
文摘Harvesting bio-kinetic energy using a triboelectric nanogenerator(TENG) is one of the promising routes to solve the sustainable energy supply problem for wearable electronics. However, additional materials, complex fabricating processes or specific mechanical structures are needed for existing TENGs to harvest bio-kinetic energy. Besides, they need to be tightly attached to the human body, which may result in detachment and malfunction under tense human motion. Herein, an intrinsic epidermal electrode-based TENG(E-TENG) is proposed to harvest human walking energy. The wearing shoes and ground are used as tribo-materials, and the human epidermis is used as the back electrode of the E-TENG. Compared with the traditional TENGs,the E-TENG does not need any additional tribo-materials and complex mechanical structures. Under optimal conditions, the voltage output of E-TENG can reach 914 V. E-TENG has been used as a self-powered warning sensor and pedometer sensor for demonstration. Furthermore, E-TENG based self-powered wireless sensor system has been developed using a newly designed micro energy electronic switch(MEES). Ambient ultraviolet intensity, temperature and humidity information can be monitored and then transmitted to mobile phone every 3.5 min, demonstrating great potential for widespread wearable applications.
基金supported in part by the National Natural Science Foundation of China under Key Program of NSFC (No. 61332019)NSFC (Nos. 61572304 and 61272056)Shanghai Key Laboratory of Specialty Fiber Optics and Optical Access Networks (No. SKLSFO2014-06)
文摘With the rapid development and wide deployment of wireless technology, Wi-Fi signals have no longer been confined to the Internet as a communication medium. Wi-Fi signals will be modulated again by human actions when propagating indoors, carrying rich human body state information. Therefore, a novel wireless sensing technology is gradually emerging that can realize gesture recognition, human daily activity detection, identification,indoor localization and human body tracking, vital signs detection, imaging, and emotional recognition by extracting effective feature information about human actions from Wi-Fi signals. Researchers mainly use channel state information or frequency modulated carrier wave in their current implementation schemes of wireless sensing technology, called "Walls have eyes", and these schemes cover radio-frequency technology, signal processing technology, and machine learning. These available wireless sensing systems can be used in many applications such as smart home, medical health care, search-and-rescue, security, and with the high precision and passively device-free through-wall detection function. This paper elaborates the research actuality and summarizes each system structure and the basic principles of various wireless sensing applications in detail. Meanwhile, two popular implementation schemes are analyzed. In addition, the future diversely application prospects of wireless sensing systems are presented.
基金supported by Special Zone Project of National Defense Innovationthe National Natural Science Foundation of China(Nos.61572304 and 61272096)+1 种基金the Key Program of the National Natural Science Foundation of China(No.61332019)Open Research Fund of State Key Laboratory of Cryptology.
文摘As the main health threat to the elderly living alone and performing indoor activities,falls have attracted great attention from institutions and society.Currently,fall detection systems are mainly based on wear sensors,environmental sensors,and computer vision,which need to be worn or require complex equipment construction.However,they have limitations and will interfere with the daily life of the elderly.On the basis of the indoor propagation theory of wireless signals,this paper proposes a conceptual verification module using Wi-Fi signals to identify human fall behavior.The module can detect falls without invading privacy and affecting human comfort and has the advantages of noninvasive,robustness,universality,and low price.The module combines digital signal processing technology and machine learning technology.This paper analyzes and processes the channel state information(CSI)data of wireless signals,and the local outlier factor algorithm is used to find the abnormal CSI sequence.The support vector machine and extreme gradient boosting algorithms are used for classification,recognition,and comparative research.Experimental results show that the average accuracy of fall detection based on wireless sensing is more than 90%.This work has important social significance in ensuring the safety of the elderly.
基金supported by the Special Zone Project of National Defense Innovation.
文摘When a human body moves within the coverage range of Wi-Fi signals,the reflected Wi-Fi signals by the various parts of the human body change the propagation path,so analysis of the channel state data can achieve the perception of the human motion.By extracting the Channel State Information(CSI)related to human motion from the Wi-Fi signals and analyzing it with the introduced machine learning classification algorithm,the human motion in the spatial environment can be perceived.On the basis of this theory,this paper proposed an algorithm of human behavior recognition based on CSI wireless sensing to realize deviceless and over-the-air slide turning.This algorithm collects the environmental information containing upward or downward wave in a conference room scene,uses the local outlier factor detection algorithm to segment the actions,and then the time domain features are extracted to train Support Vector Machine(SVM)and eXtreme Gradient Boosting(XGBoost)classification modules.The experimental results show that the average accuracy of the XGBoost module sensing slide flipping can reach 94%,and the SVM module can reach 89%,so the module could be extended to the field of smart classroom and significantly improve speech efficiency.
基金supported by the Natural Science Foundation of Henan Province,China(No.242300421226)the scientific research program of innovation platform in State Tobacco Monopoly Administration.
文摘Nitrogen dioxide(NO_(2))is a significant air pollutant with harmful effects on human health and the environment.Timely and accurate monitoring of NO_(2)concentrations is crucial for improving air quality and protecting public health.However,quantifying NO_(2)in the presence of other gases remains challenging.Herein,we integrate Ru onto the MoS_(2)surface to form Ru-S-Mo active sites,thereby tuning the electronic structure of MoS_(2)for enhanced NO_(2)detection.This sensor shows excellent sensitivity(29.7%at 100×10^(-6)NO_(2)and 25℃),with a linear response to NO_(2)ranging from 0.5 to 200×10^(-6),and a significantly reduced response/recovery time from 160/3636 s for pure MoS_(2)to 58/427 s for Ru@MoS_(2)at 100×10^(-6)NO_(2).Additionally,the sensor is highly selective for NO_(2),exhibiting a response 14 times higher than for other gases,and possesses strong anti-interference capabilities,accurately quantifying NO_(2)in the presence of varying H_(2)concentrations(10×10^(-6)-200×10^(-6))with a low RSD of 5.34%.A portable wireless NO_(2)monitoring system was successfully constructed using Ru@MoS_(2),enabling real-time gas leak detection(10×10^(-6)-50×10^(-6))with hazard warnings and maintaining a stable response to NO_(2)over a 4-week period.This work extends the gas sensing applications of MoS_(2)and provides a portable,wireless,and high-selectivity NO_(2)sensing method for environmental monitoring and safety assurance.
基金This work was supported by the National Natural Science Foundation of China(Grant No.61802196,url:http://www.nsfc.gov.cn/)Jiangsu Provincial Government Scholarship for Studying Abroad+1 种基金The Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)NUIST Students’Platform for Innovation and Entrepreneurship Training Program(Grant No.202010300080Y,url:http://sjjx.nuist.edu.cn:81/CXCY/NUIST/).
文摘Since the outbreak of the world-wide novel coronavirus pandemic,crowd counting in public areas,such as in shopping centers and in commercial streets,has gained popularity among public health administrations for preventing the crowds from gathering.In this paper,we propose a novel adaptive method for crowd counting based on Wi-Fi channel state information(CSI)by using common commercial wireless routers.Compared with previous researches on device-free crowd counting,our proposed method is more adaptive to the change of environ-ment and can achieve high accuracy of crowd count estimation.Because the dis-tance between access point(AP)and monitor point(MP)is typically non-fixed in real-world applications,the strength of received signals varies and makes the tra-ditional amplitude-related models to perform poorly in different environments.In order to achieve adaptivity of the crowd count estimation model,we used convo-lutional neural network(ConvNet)to extract features from correlation coefficient matrix of subcarriers which are insensitive to the change of received signal strength.We conducted experiments in university classroom settings and our model achieved an overall accuracy of 97.79%in estimating a variable number of participants.
基金supported by the National Natural Science Foundation of China(61372069)and the"111"Project(B08038)
文摘In order to apply compressive sensing in wireless sensor network, inside the nodes cluster classified by the spatial correlation, we propose that a cluster head adopts free space optical communication with space division multiple access, and a sensor node uses a modulating retro-reflector for communication. Thus while a random sampling matrix is used to guide the establishment of links between head cluster and sensor nodes, the random linear projection is accomplished. To establish multiple links at the same time, an optical space division multiple access antenna is designed. It works in fixed beams switching mode and consists of optic lens with a large field of view（FOV）, fiber array on the focal plane which is used to realize virtual channels segmentation, direction of arrival sensor, optical matrix switch and controller. Based on the angles of nodes＇ laser beams, by dynamically changing the route, optical matrix switch actualizes the multi-beam full duplex tracking receiving and transmission. Due to the structure of fiber array, there will be several fade zones both in the focal plane and in lens＇ FOV. In order to lower the impact of fade zones and harmonize multibeam, a fiber array adjustment is designed. By theoretical, simulated and experimental study, the antenna＇s qualitative feasibility is validated.
基金supported in part by Sichuan Science and Technology Program (Nos. 2022NSFSC0912, 2020YJ0218,2021YFQ056 and 2022YFG0170)Fundamental Research Funds for the Central Universities (Nos. 2682021ZTPY051and 2682021CF019)+2 种基金NSFC (No. 62071393)NSFC High-Speed Rail Joint Foundation (No. U1834210)111 Project 111-2-14。
文摘Sensing in wireless local area network(WLAN) gains great interests recently. In this paper we focus on the multi-user WLAN sensing problem under the existing 802.11 standards. Multiple stations perform sensing with the access point and transmit channel state information(CSI)report simultaneously on the basis of uplink-orthogonal frequency division multiple access(OFDMA). Considering the transmission resource consumed in CSI report and the padding wastage in OFDMA based CSI report, we optimize the CSI simplification and uplink resource unit(RU)allocation jointly, aiming to balance the sensing accuracy and padding wastage performances in WLAN sensing. We propose the minimize padding maximize efficiency(MPME) algorithm to solve the problem and evaluate the performance of the proposed algorithm through extensive simulations.
文摘The future of wireless systems is anticipated to revolutionize human connectivity through a diverse range of applications.The integration of multiple wireless functionalities into a unified system presents a critical challenge due to conflicting requirements in transceiver architecture and signal processing.Recent investigations are directing attention towards the development of systems that serve dual functions,like simultaneous wireless information and power transfer and radar-communication,aimed at boosting operational efficiency and ensuring seamless communication among different wireless capabilities.This review paper aims to discuss the architectural aspects of the integration of radar sensing,data communication,and power transfer.Firstly,the integration of radar sensing and data communication is studied for both cooperating and non-cooperating radar systems with conventional and interferometric architectures.Secondly,the power harvesting approach and internal energy recycling are discussed for the fusion of data communication and energy harvesting.Thirdly,radar sensing and power transfer integration is considered with special focus on harmonic backscattering and self-powered radars.Lastly,a roadmap for next-generation multifunction systems is outlined by considering several scenarios of multiplexing and architectures.
基金This work was supported by National Natural Science Foundation of China under grants U1933104 and 62071081LiaoNing Revitalization Talents Program under grant XLYC1807019,Liaoning Province Natural Science Foundation under grants 2019-MS-058+1 种基金Dalian Science and Technology Innovation Foundation under grant 2018J12GX044Fundamental Research Funds for the Central Universities under grants DUT20LAB113 and DUT20JC07,and Cooperative Scientific Research Project of Chunhui Plan of Ministry of Education.
文摘Device-free gesture recognition is an emerging wireless sensing technique which could recognize gestures by analyzing its influence on surrounding wireless signals,it may empower wireless networks with the augmented sensing ability.Researchers have made great achievements for singleperson device-free gesture recognition.However,when multiple persons conduct gestures simultaneously,the received signals will be mixed together,and thus traditional methods would not work well anymore.Moreover,the anonymity of persons and the change in the surrounding environment would cause feature shift and mismatch,and thus the recognition accuracy would degrade remarkably.To address these problems,we explore and exploit the diversity of spatial information and propose a multidimensional analysis method to separate the gesture feature of each person using a focusing sensing strategy.Meanwhile,we also present a deep-learning based robust device free gesture recognition framework,which leverages an adversarial approach to extract robust gesture feature that is insensitive to the change of persons and environment.Furthermore,we also develop a 77GHz mmWave prototype system and evaluate the proposed methods extensively.Experimental results reveal that the proposed system can achieve average accuracies of 93%and 84%when 10 gestures are conducted in Received:Jun.18,2020 Revised:Aug.06,2020 Editor:Ning Ge different environments by two and four persons simultaneously,respectively.
文摘This paper addresses some of the problems related to direct surface temperature measurement of a salient pole synchronous generator excitation winding in rotation. Excitation winding temperature is used for determining the dynamic limit in a PQ diagram. The paper also addresses procedures of improving the accuracy of surface temperature measurement using the contact DS 18B20 digital temperature probes. The paper also provides experimental results of direct temperature measurement of the excitation winding surface conducted in the salient pole synchronous generator in the rotation.
基金supported by the National Natural Science Foundation of China(No.61971238).
文摘The integrated sensing and wireless power transfer(ISWPT)technology,in which the radar sensing and wireless power transfer functionalities are implemented using the same hardware platform,has been recently proposed.In this paper,we consider a near-field ISWPT system where one hybrid transmitter deploys extremely large-scale antenna arrays,and multiple energy receivers are located in the near-field region of the transmitter.Under such a new scenario,we study radar sensing and wireless power transfer performance trade-offs by optimizing the transmit beamforming vectors.In particular,we consider the transmit beampattern matching and max-min beampattern gain design metrics.For each radar performance metric,we aim to achieve the best performance of radar sensing,while guaranteeing the requirement of wireless power transfer.The corresponding beamforming design problems are non-convex,and the semi-definite relaxation(SDR)approach is applied to solve them globally optimally.Finally,numerical results verify the effectiveness of our proposed solutions.
文摘Wireless smart sensing is now widely used in various applications such as health monitoring and structural monitoring.In conventional wireless sensor nodes,significant power is consumed in wirelessly transmitting the raw data.Smart sensing adds local intelligence to the sensor node and reduces the amount of wireless data transmission via on-node digital signal processing.While the total power consumption is reduced compared to conventional wireless sensing,the power consumption of the digital processing becomes as dominant as wireless data transmission.This paper reviews the state-of-the-art energy-efficient digital and wireless IC design techniques for reducing the power consumption of the wireless smart sensor node to prolong battery life and enable self-powered applications.
基金Mr.Sung-Yueh Wu is supported by the“Ministry of Science and Technology of Taiwan”(Grant No.103-2917-I-009-192).
文摘Three-dimensional(3D)additive manufacturing techniques have been utilized to make 3D electrical components,such as resistors,capacitors,and inductors,as well as circuits and passive wireless sensors.Using the fused deposition modeling technology and a multiple-nozzle system with a printing resolution of 30μm,3D structures with both supporting and sacrificial structures are constructed.After removing the sacrificial materials,suspensions with silver particles are injected subsequently solidified to form metallic elements/interconnects.The prototype results show good characteristics of fabricated 3D microelectronics components,including an inductor–capacitor-resonant tank circuitry with a resonance frequency at 0.53 GHz.A 3D“smart cap”with an embedded inductor–capacitor tank as the wireless passive sensor was demonstrated to monitor the quality of liquid food(e.g.,milk and juice)wirelessly.The result shows a 4.3%resonance frequency shift from milk stored in the room temperature environment for 36 h.This work establishes an innovative approach to construct arbitrary 3D systems with embedded electrical structures as integrated circuitry for various applications,including the demonstrated passive wireless sensors.
基金This research is partially sponsored by the National Science Foundation,under grant number CMMI-0928095(Program Manager:Dr.Shih-Chi Liu).
文摘Being able to significantly reduce system installation time and cost,wireless sensing technology has attracted much interest in the structural health monitoring(SHM)community.This paper reports the field application of a wireless sensing system on a 4-span highway bridge located in Wayne,New Jersey in the US.Bridge vibration due to traffic and ambient excitation is measured.To enhance the signal-to-noise ratio,a low-noise high-gain signal conditioning module is developed for the wireless sensing system.Nineteen wireless and nineteen cabled accelerometers are first installed along the sidewalk of two neighboring bridge spans.The performance of the wireless sensing system is compared with the high-precision cabled sensing system.In the next series of testing,16 wireless accelerometers are installed under the deck of another bridge span,forming a 4×4 array.Operating deflection analysis is successfully conducted using the wireless measurement of traffic and ambient vibrations.
基金supported by the National Key R&D Project from Minister of Science and Technology(2021YFB3200301)the National Natural Science Foundation of China(Nos.52250112,51922023)Fundamental Research Funds for the Central Universities(E1EG6804).
文摘Body area network has attracted extensive attention for its applications in athletics,medical,diagnosis,and rehabilitation training in the next generation personalized health care solutions.Here,a contact-separation direct current triboelectric nanogenerators(CSDC-TENGs)based selfpowered wireless body area network(SWBAN)is reported that enables multi-joint movements monitoring for human motion.The CSDC-TENG is designed as a flexible active sensor with an internal contact switch,and the flexible substrate makes the TENG-sensor stick onto skin easily.Due to the internal switch,the CSDC-TENG could generate a DC current,a large instantaneous output voltage exceeds 700 V,and an instantaneous power can reach 1.076 W,which is more than 23000 times higher than that of the traditional contact-separation mode TENG in same size and materials without the switch.By coupling with flexible coil,the fixed high-frequency radio signals can be modulated and emitted clearly ranging from 6 to 16 MHz,which can be wirelessly received and demodulated through a reader.Moreover,the SWBAN is demonstrated in a real time monitoring system for joints motion.This work has realized the wearable TENG for self-powered wireless real-time monitoring of body movements driven by low-frequency human daily activities,which may promote a tremendous development of intelligent healthcare,wireless sensing system and body area network.
基金funded by the Ministry of Science and Technology,Taiwan,under grant number MOST 114-2224-E-A49-002was received by En-Cheng Liou.
文摘Indoor localization is a fundamental requirement for future 6G Intelligent Sensing and Communication(ISAC)systems,enabling precise navigation in environments where Global Positioning System(GPS)signals are unavailable.Existing methods,such as map-based navigation or site-specific fingerprinting,often require intensive data collection and lack generalization capability across different buildings,thereby limiting scalability.This study proposes a cross-site,map-free indoor localization framework that uses low-frequency sub-1 GHz radio signals and a Transformer-based neural network for robust positioning without prior environmental knowledge.The Transformer’s self-attention mechanisms allow it to capture spatial correlations among anchor nodes,facilitating accurate localization in unseen environments.Evaluation across two validation sites demonstrates the framework’s effectiveness.In crosssite testing(Site-A),the Transformer achieved a mean localization error of 9.44 m,outperforming the Deep Neural Network(DNN)(10.76 m)and Convolutional Neural Network(CNN)(12.02 m)baselines.In a real-time deployment(Site-B)spanning three floors,the Transformer maintained an overall mean error of 9.81 m,compared with 13.45 m for DNN,12.88 m for CNN,and 53.08 m for conventional trilateration.For vertical positioning,the Transformer delivered a mean error of 4.52 m,exceeding the performance of DNN(4.59 m),CNN(4.87 m),and trilateration(>45 m).The results confirm that the Transformer-based framework generalizes across heterogeneous indoor environments without requiring site-specific calibration,providing stable,sub-12 m horizontal accuracy and reliable vertical estimation.This capability makes the framework suitable for real-time applications in smart buildings,emergency response,and autonomous systems.By utilizing multipath reflections as an informative structure rather than treating them as noise,this work advances artificial intelligence(AI)-native indoor localization as a scalable and efficient component of future 6G ISAC networks.
基金supported in part by the National Natural Science Foundation of China(No.61379134)by Fundamental Research Funds or the Central Universities(No.06105031)
文摘In recent years, Compressed Sensing（CS） has been a hot research topic. It has a wide range of applications, such as image processing and speech signal processing owing to its characteristic of removing redundant information by reducing the sampling rate. The disadvantage of CS is that the number of iterations in a greedy algorithm such as Orthogonal Matching Pursuit（OMP） is fixed, thus limiting reconstruction precision.Therefore, in this study, we present a novel Reducing Iteration Orthogonal Matching Pursuit（RIOMP） algorithm that calculates the correlation of the residual value and measurement matrix to reduce the number of iterations.The conditions for successful signal reconstruction are derived on the basis of detailed mathematical analyses.When compared with the OMP algorithm, the RIOMP algorithm has a smaller reconstruction error. Moreover, the proposed algorithm can accurately reconstruct signals in a shorter running time.
