As an Industrial Wireless Sensor Network(IWSN)is usually deployed in a harsh or unattended environment,the privacy security of data aggregation is facing more and more challenges.Currently,the data aggregation protoco...As an Industrial Wireless Sensor Network(IWSN)is usually deployed in a harsh or unattended environment,the privacy security of data aggregation is facing more and more challenges.Currently,the data aggregation protocols mainly focus on improving the efficiency of data transmitting and aggregating,alternately,the aim at enhancing the security of data.The performances of the secure data aggregation protocols are the trade-off of several metrics,which involves the transmission/fusion,the energy efficiency and the security in Wireless Sensor Network(WSN).Unfortunately,there is no paper in systematic analysis about the performance of the secure data aggregation protocols whether in IWSN or in WSN.In consideration of IWSN,we firstly review the security requirements and techniques in WSN data aggregation in this paper.Then,we give a holistic overview of the classical secure data aggregation protocols,which are divided into three categories:hop-by-hop encrypted data aggregation,end-to-end encrypted data aggregation and unencrypted secure data aggregation.Along this way,combining with the characteristics of industrial applications,we analyze the pros and cons of the existing security schemes in each category qualitatively,and realize that the security and the energy efficiency are suitable for IWSN.Finally,we make the conclusion about the techniques and approach in these categories,and highlight the future research directions of privacy preserving data aggregation in IWSN.展开更多
Energy efficiency is very important for the Internet of Things(IoT),especially for front-end sensed terminal or node.It not only embodies the node’s life,but also reflects the lifetime of the network.Meanwhile,it is ...Energy efficiency is very important for the Internet of Things(IoT),especially for front-end sensed terminal or node.It not only embodies the node’s life,but also reflects the lifetime of the network.Meanwhile,it is also a key indicator of green communications.Unfortunately,there is no article on systematic analysis and review for energy efficiency evaluation in IoT.In this paper,we systemically analyze the architecture of IoT,and point out its energy distribution,Furthermore,we summarized the energy consumption model in IoT,analyzed the pros and cons of improving energy efficiency,presented a state of the art the evaluation metrics of energy efficiency.Finally,we conclude the techniques and methods,and carry out a few open research issues and directions in this field.展开更多
Aiming at the defects of the traditional fire detection methods,which are caused by false positives and false negatives in large space buildings,a fire identification detection method based on video images is proposed...Aiming at the defects of the traditional fire detection methods,which are caused by false positives and false negatives in large space buildings,a fire identification detection method based on video images is proposed.The algorithm first uses the hybrid Gaussian background modeling method and the RGB color model to perform fire prejudgment on the video image,which can eliminate most non-fire interferences.Secondly,the traditional regional growth algorithm is improved and the fire image segmentation effect is effectively improved.Then,based on the segmented image,the dynamic and static features of the fire flame are further analyzed and extracted in the area of the suspected fire flame.Finally,the dynamic features of the extracted fire flame images were fused and classified by improved fruit fly optimization support vector machine,and the recognition results were obtained.The video-based fire detection method proposed in this paper greatly improves the accuracy of fire detection and is suitable for fire detection and identification in large space scenarios.展开更多
Video object tracking is an important research topic of computer vision, whichfinds a wide range of applications in video surveillance, robotics, human-computerinteraction and so on. Although many moving object tracki...Video object tracking is an important research topic of computer vision, whichfinds a wide range of applications in video surveillance, robotics, human-computerinteraction and so on. Although many moving object tracking algorithms have beenproposed, there are still many difficulties in the actual tracking process, such asillumination change, occlusion, motion blurring, scale change, self-change and so on.Therefore, the development of object tracking technology is still challenging. Theemergence of deep learning theory and method provides a new opportunity for theresearch of object tracking, and it is also the main theoretical framework for the researchof moving object tracking algorithm in this paper. In this paper, the existing deeptracking-based target tracking algorithms are classified and sorted out. Based on theprevious knowledge and my own understanding, several solutions are proposed for theexisting methods. In addition, the existing deep learning target tracking method is stilldifficult to meet the requirements of real-time, how to design the network and trackingprocess to achieve speed and effect improvement, there is still a lot of research space.展开更多
A novel non-geometrical stochastic model(NGSM)for non-wide sense station ary uncorrelated scattering(non-WSSUS)vehicle-to-vehicle(V2V)channels is proposed.This model is based on a conventional NGSM and employs a more ...A novel non-geometrical stochastic model(NGSM)for non-wide sense station ary uncorrelated scattering(non-WSSUS)vehicle-to-vehicle(V2V)channels is proposed.This model is based on a conventional NGSM and employs a more accurate method to reproduce the realistic characteristics of V2V channels,which successfully extends the existing NGSM to include the line-of-sight(LoS)component.Moreover,the statistical properties of the proposed model in different scenarios,including Doppler power spectral density(PSD),power delay profile(PDP),and the tap correlation coefficient matrix are simulated and compared with those of the existing NGSM.Furthermore,the simulation results dem onstrate not only the utility of the proposed model,but also the correctness of our theoreti cal derivations.展开更多
In a visible light communication （VLC） system, the light emitting diode （LED） is nonlinear for large signals, which limits the trans- mission power or equivalently the coverage of the VLC system. When the input si...In a visible light communication （VLC） system, the light emitting diode （LED） is nonlinear for large signals, which limits the trans- mission power or equivalently the coverage of the VLC system. When the input signal amplitude is large, the nonlinear distortion creates harmonic and intermodulation distortion, which degrades the transmission error vector magnitude （EVM）. To evaluate the impact of nonlinearity on system performance, the signal to noise and distortion ratio （SNDR） is applied, defined as the linear signal power over the thermal noise plus the front end nonlinear distortion. At a given noise level, the optimal system performance can be achieved by maximizing the SNDR, which results in high transmission rate or long transmission range for the VLC system. In this paper, we provide theoretical analysis on the optimization of SNDR with a nonlinear Hammerstein model of LED. Simulation results and lab experiments validate the theoretical analysis.展开更多
微/纳尺度压力传感器可以检测来自外部环境的压力,分析所施加力的位置,大小和方向.这种压力传感器在电子屏幕、电子皮肤、运动监测、人工触觉系统等多个领域都有很高的应用需求.本文组装了一种可实现二维映射,基于图案化铌酸钾钠纳米棒...微/纳尺度压力传感器可以检测来自外部环境的压力,分析所施加力的位置,大小和方向.这种压力传感器在电子屏幕、电子皮肤、运动监测、人工触觉系统等多个领域都有很高的应用需求.本文组装了一种可实现二维映射,基于图案化铌酸钾钠纳米棒阵列的压力传感器矩阵.水热合成的正交相铌酸钾钠纳米棒具有优异的柔性和弹性,同时具有较高的压电性能.因此在组装的压力传感器矩阵中,单个单元尺寸低至200μm,灵敏度可达0.20 V N^(-1),检测限低至20 g,且器件的稳定性高.空间分离的传感器单元能有效避免交叉干扰,使器件能准确地实现自驱动压力成像,精确地分析外部压力刺激.展开更多
基金partially supported by the National Natural Science Foundation of China(61571004)the Shanghai Natural Science Foundation(No.17ZR1429100)+1 种基金the National Science and Technology Major Project of China(No.2018ZX03001017-004)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(No.YJKYYQ20170074).
文摘As an Industrial Wireless Sensor Network(IWSN)is usually deployed in a harsh or unattended environment,the privacy security of data aggregation is facing more and more challenges.Currently,the data aggregation protocols mainly focus on improving the efficiency of data transmitting and aggregating,alternately,the aim at enhancing the security of data.The performances of the secure data aggregation protocols are the trade-off of several metrics,which involves the transmission/fusion,the energy efficiency and the security in Wireless Sensor Network(WSN).Unfortunately,there is no paper in systematic analysis about the performance of the secure data aggregation protocols whether in IWSN or in WSN.In consideration of IWSN,we firstly review the security requirements and techniques in WSN data aggregation in this paper.Then,we give a holistic overview of the classical secure data aggregation protocols,which are divided into three categories:hop-by-hop encrypted data aggregation,end-to-end encrypted data aggregation and unencrypted secure data aggregation.Along this way,combining with the characteristics of industrial applications,we analyze the pros and cons of the existing security schemes in each category qualitatively,and realize that the security and the energy efficiency are suitable for IWSN.Finally,we make the conclusion about the techniques and approach in these categories,and highlight the future research directions of privacy preserving data aggregation in IWSN.
基金This work is partially supported by the National Natural Science Foundation of China(No.61571004,No.61571303)the National Science and Technology Major Project of China(No.2018ZX03001031)+3 种基金National Key Research and Development Program of China(No.2019YFB2101602)the Science and Technology Innovation Program of Shanghai(No.17DZ2292000,No.16510711600)the Shanghai Natural Science Foundation(No.16ZR1435200)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(No.YJKYYQ20170074).
文摘Energy efficiency is very important for the Internet of Things(IoT),especially for front-end sensed terminal or node.It not only embodies the node’s life,but also reflects the lifetime of the network.Meanwhile,it is also a key indicator of green communications.Unfortunately,there is no article on systematic analysis and review for energy efficiency evaluation in IoT.In this paper,we systemically analyze the architecture of IoT,and point out its energy distribution,Furthermore,we summarized the energy consumption model in IoT,analyzed the pros and cons of improving energy efficiency,presented a state of the art the evaluation metrics of energy efficiency.Finally,we conclude the techniques and methods,and carry out a few open research issues and directions in this field.
基金This works were supported by National Natural Science Foundation of China(Grant No.51874300)the National Natural Science Foundation of China and Shanxi Provincial People’s Government Jointly Funded Project of China for Coal Base and Low Carbon(Grant No.U1510115)+1 种基金the Qing Lan Project,the China Postdoctoral Science Foundation(No.2013T60574)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(Grant No.YJKYYQ20170074).
文摘Aiming at the defects of the traditional fire detection methods,which are caused by false positives and false negatives in large space buildings,a fire identification detection method based on video images is proposed.The algorithm first uses the hybrid Gaussian background modeling method and the RGB color model to perform fire prejudgment on the video image,which can eliminate most non-fire interferences.Secondly,the traditional regional growth algorithm is improved and the fire image segmentation effect is effectively improved.Then,based on the segmented image,the dynamic and static features of the fire flame are further analyzed and extracted in the area of the suspected fire flame.Finally,the dynamic features of the extracted fire flame images were fused and classified by improved fruit fly optimization support vector machine,and the recognition results were obtained.The video-based fire detection method proposed in this paper greatly improves the accuracy of fire detection and is suitable for fire detection and identification in large space scenarios.
基金supported by National Natural Science Foundationof China (Grant No. 51874300)the National Natural Science Foundation of China andShanxi Provincial People’s Government Jointly Funded Project of China for Coal Baseand Low Carbon (Grant No. U1510115)+2 种基金National Natural Science Foundation of China(51104157)the Qing Lan Project, the China Postdoctoral Science Foundation (Grant No.2013T60574)the Scientific Instrument Developing Project of the Chinese Academy ofSciences (Grant No. YJKYYQ20170074).
文摘Video object tracking is an important research topic of computer vision, whichfinds a wide range of applications in video surveillance, robotics, human-computerinteraction and so on. Although many moving object tracking algorithms have beenproposed, there are still many difficulties in the actual tracking process, such asillumination change, occlusion, motion blurring, scale change, self-change and so on.Therefore, the development of object tracking technology is still challenging. Theemergence of deep learning theory and method provides a new opportunity for theresearch of object tracking, and it is also the main theoretical framework for the researchof moving object tracking algorithm in this paper. In this paper, the existing deeptracking-based target tracking algorithms are classified and sorted out. Based on theprevious knowledge and my own understanding, several solutions are proposed for theexisting methods. In addition, the existing deep learning target tracking method is stilldifficult to meet the requirements of real-time, how to design the network and trackingprocess to achieve speed and effect improvement, there is still a lot of research space.
基金supported by the Ministry National Key Research and Development Project under Grant No.2017YFE0121400the open research fund of Key Laboratory of Wireless Sensor Network&Communication under Grant No.2017003Shanghai Institute of Microsystem and Information Technology,and Chinese Academy of Sciences.
文摘A novel non-geometrical stochastic model(NGSM)for non-wide sense station ary uncorrelated scattering(non-WSSUS)vehicle-to-vehicle(V2V)channels is proposed.This model is based on a conventional NGSM and employs a more accurate method to reproduce the realistic characteristics of V2V channels,which successfully extends the existing NGSM to include the line-of-sight(LoS)component.Moreover,the statistical properties of the proposed model in different scenarios,including Doppler power spectral density(PSD),power delay profile(PDP),and the tap correlation coefficient matrix are simulated and compared with those of the existing NGSM.Furthermore,the simulation results dem onstrate not only the utility of the proposed model,but also the correctness of our theoreti cal derivations.
基金supported in part by the National Key Science and Technology“863”Project under Grant No.SS2015AA011303the Science and Technology Commission Foundation of Shanghai under Gant No.14511100200
文摘In a visible light communication （VLC） system, the light emitting diode （LED） is nonlinear for large signals, which limits the trans- mission power or equivalently the coverage of the VLC system. When the input signal amplitude is large, the nonlinear distortion creates harmonic and intermodulation distortion, which degrades the transmission error vector magnitude （EVM）. To evaluate the impact of nonlinearity on system performance, the signal to noise and distortion ratio （SNDR） is applied, defined as the linear signal power over the thermal noise plus the front end nonlinear distortion. At a given noise level, the optimal system performance can be achieved by maximizing the SNDR, which results in high transmission rate or long transmission range for the VLC system. In this paper, we provide theoretical analysis on the optimization of SNDR with a nonlinear Hammerstein model of LED. Simulation results and lab experiments validate the theoretical analysis.
基金financially supported by the National Natural Science Foundation of China(NSFC,52072115,51972102,and U21A20500)Wang J acknowledges the support by A*STAR,under RIE2020 AME Individual Research Grant(IRG)(A20E5c0086),for the research conducted at the National University of Singaporesupported in part by a grant from the Key Laboratory of Wireless Sensor Network&Communication,Shanghai Institute of Microsystem and Information Technology,Chinese Academy of Sciences(20190909)。
文摘微/纳尺度压力传感器可以检测来自外部环境的压力,分析所施加力的位置,大小和方向.这种压力传感器在电子屏幕、电子皮肤、运动监测、人工触觉系统等多个领域都有很高的应用需求.本文组装了一种可实现二维映射,基于图案化铌酸钾钠纳米棒阵列的压力传感器矩阵.水热合成的正交相铌酸钾钠纳米棒具有优异的柔性和弹性,同时具有较高的压电性能.因此在组装的压力传感器矩阵中,单个单元尺寸低至200μm,灵敏度可达0.20 V N^(-1),检测限低至20 g,且器件的稳定性高.空间分离的传感器单元能有效避免交叉干扰,使器件能准确地实现自驱动压力成像,精确地分析外部压力刺激.
