The integration of cloud computing into traditional industrial control systems is accelerating the evolution of Industrial Cyber-Physical System(ICPS),enhancing intelligence and autonomy.However,this transition also e...The integration of cloud computing into traditional industrial control systems is accelerating the evolution of Industrial Cyber-Physical System(ICPS),enhancing intelligence and autonomy.However,this transition also expands the attack surface,introducing critical security vulnerabilities.To address these challenges,this article proposes a hybrid intrusion detection scheme for securing ICPSs that combines system state anomaly and network traffic anomaly detection.Specifically,an improved variation-Bayesian-based noise covariance-adaptive nonlinear Kalman filtering(IVB-NCA-NLKF)method is developed to model nonlinear system dynamics,enabling optimal state estimation in multi-sensor ICPS environments.Intrusions within the physical sensing system are identified by analyzing residual discrepancies between predicted and observed system states.Simultaneously,an adaptive network traffic anomaly detection mechanism is introduced,leveraging learned traffic patterns to detect node-and network-level anomalies through pattern matching.Extensive experiments on a simulated network control system demonstrate that the proposed framework achieves higher detection accuracy(92.14%)with a reduced false alarm rate(0.81%).Moreover,it not only detects known attacks and vulnerabilities but also uncovers stealthy attacks that induce system state deviations,providing a robust and comprehensive security solution for the safety protection of ICPS.展开更多
To investigate the response of Roadside Monitoring Stations(RSs)to traffic-related air pollution,traffic and pollutant characteristics,influencing factors,and potential source characterization in Tianjin,China were de...To investigate the response of Roadside Monitoring Stations(RSs)to traffic-related air pollution,traffic and pollutant characteristics,influencing factors,and potential source characterization in Tianjin,China were determined based on roadside monitoring of real-world data conducted at RSs in 2022.The diurnal variation trend of pollutants at RSs was consistent with that at the National Monitoring Station(NM),with notably higher pollutant fluctuations during the morning and evening peak traffic times at RSs,where the average diurnal concentration was 41.46%higher than that at the NM.The generalized additive model(GAM)for nitrogen oxides(NO_(x))and carbon monoxide(CO),responding to themultiple influencing factors,performed well at RSs,with deviance explained by 86.6%and 61.4%,respectively.The synergistic effects of wind direction and speed contributed to most of the variations in NO_(x) and CO,which were 14.74%and 12.87%,respectively.Pollutant concentrations were highest under windless conditions,with pollutants originating primarily from local vehicle emissions.The model results indicated that medium-duty truck(MDT)traffic flow predominantly contributed to the variability in NO_(x) emissions,whereas passenger car(PC)traffic flow was the primary source of CO emissions from traffic variables.MDTs should be the focus of urban NO_(x) traffic emissions control.Potential-source analysis validated the results obtained from the GAM,and both analyses showed that RSs can better characterize traffic-related air pollutants.Furthermore,more stringent emission standards have effectively mitigated the release of pollutants from motor vehicles and contributed to the modernization of vehicle fleet composition,effectively decreasing CO concentrations.展开更多
Towards line speed and accurateness on-line content popularity monitoring on Content Centric Networking(CCN) routers, we propose a three-stage scheme based on Bloom filters and hash tables for differentiated traffic. ...Towards line speed and accurateness on-line content popularity monitoring on Content Centric Networking(CCN) routers, we propose a three-stage scheme based on Bloom filters and hash tables for differentiated traffic. At the first stage, we decide whether to deliver the content to the next stage depending on traffic types. The second stage consisting of Standard Bloom filters(SBF) and Counting Bloom filters(CBF) identifies the popular content. Meanwhile, a scalable sliding time window based monitoring scheme for different traffic types is proposed to implement frequent and real-time updates by the change of popularities. Hash tables according with sliding window are used to record the popularity at the third stage. Simulation results reveal that this method reaches a 40 Gbps processing speed at lower error probability with less memory, and it is more sensitive to the change of popularity. Additionally, the architecture which can be implemented in CCN router is flexible and scalable.展开更多
Real traffic information was analyzed in the statistical characteristics and approximated as a Gaussian time series. A data source model, called two states constant bit rate (TSCBR), was proposed in dynamic traffic mo...Real traffic information was analyzed in the statistical characteristics and approximated as a Gaussian time series. A data source model, called two states constant bit rate (TSCBR), was proposed in dynamic traffic monitoring sensor networks. Analysis of autocorrelation of the models shows that the proposed TSCBR model matches with the statistical characteristics of real data source closely. To further verify the validity of the TSCBR data source model, the performance metrics of power consumption and network lifetime was studied in the evaluation of sensor media access control (SMAC) algorithm. The simulation results show that compared with traditional data source models, TSCBR model can significantly improve accuracy of the algorithm evaluation.展开更多
A real-time vehicle tracking method is proposed for trattlC monitoring system at roau mte^cc- tions, and the vehicle tracking module consists of an initialization stage and a tracking stage. Li- cense plate location b...A real-time vehicle tracking method is proposed for trattlC monitoring system at roau mte^cc- tions, and the vehicle tracking module consists of an initialization stage and a tracking stage. Li- cense plate location based on edge density and color analysis is used to detect the license plate re- gion for tracking initialization. In the tracking stage, covariance matching is employed to track the license plate. Genetic algorithm is used to reduce the computational cost. Real-time image tracking of multi-lane vehicles is achieved. In the experiment, test videos are recorded in advance by record- ers of actual E-police systems erage false detection rate and at several different city intersections. In the tracking module, the av- missed plates rate are 1.19%, and 1.72%, respectively.展开更多
Wind speed,temperature,relative humidity and TSP concentration at three intersections in Binzhou City were monitored,and the relationships of TSP concentration with wind speed,temperature,relative humidity and traffic...Wind speed,temperature,relative humidity and TSP concentration at three intersections in Binzhou City were monitored,and the relationships of TSP concentration with wind speed,temperature,relative humidity and traffic flow at the three intersections in Binzhou City were analyzed by using SPSS.The results show that traffic flow was the main factor affecting TSP concentration of road traffic in Binzhou City.展开更多
Road Traffic monitoring involves the collection of data describing the characteristic of vehicles and their movement through road networks. Such data may be used for one of these purposes such as law enforcement, cong...Road Traffic monitoring involves the collection of data describing the characteristic of vehicles and their movement through road networks. Such data may be used for one of these purposes such as law enforcement, congestion and incident detection and increasing road capacity. Transportation is a requirement for every nation regardless of its economy, political stability, population size and technological development. Movement of goods and people from one place to another is crucial to maintain strong economic and political ties between the various components of any given nation among nations. However, there are different modes of transportation and the most paramount one to human beings is road transportation. Due to increase in the modes of transportation, road users encounter different problems such as road blockage and incidents. Therefore there is need to monitor users incidents and to know the causes. Road traffic monitoring can be done manually or using ICT devices. This paper focuses on how the use of ICT devices can enhance road traffic monitoring. It traces the brief history of transportation;it equally discussed road traffic and safety, tools for monitoring road traffic, Intelligent Transportation Systems (ITS) use for traffic monitoring and their benefits. The result shows that the use of ICT devices in road traffic monitoring should be a Millennium Goal for all developed and developing countries because of its numerous advantages in the reduction of the intensity of traffic and other road incidents.展开更多
To process the traffic monitoring image, a local Histogram Equalization method based on fuzzy mathematics was proposed in this paper. In this paper, firstly, we define a function to measure the similarity degree of tw...To process the traffic monitoring image, a local Histogram Equalization method based on fuzzy mathematics was proposed in this paper. In this paper, firstly, we define a function to measure the similarity degree of two images. Then, a suitable Gaussian fuzzy distribution function was chose to generate a 3 × 3 matrix of influential factors. In order to reduce the artificial boundaries, we combined the 3 × 3 influential matrix with a 3 × 3 smooth filter matrix to get the final smooth-influ- ence matrix. Finally, the smooth-influence matrix was used to process the center block image. The simulation results demonstrated that the proposed method can reduce time consumption while improving the image contrast and can get satisfactory results.展开更多
The lack of current network dynamics studies that evaluate the effects of new application and protocol deployment or long-term studies that observe the effect of incremental changes on the Internet, and the change in ...The lack of current network dynamics studies that evaluate the effects of new application and protocol deployment or long-term studies that observe the effect of incremental changes on the Internet, and the change in the overall stability of the Internet under various conditions and threats has made network monitoring challenging. A good understanding of the nature and type of network traffic is the key to solving congestion problems. In this paper we describe the architecture and implementation of a scalable network traffic moni-toring and analysis system. The gigabit interface on the monitoring system was configured to capture network traffic and the Multi Router Traffic Grapher (MRTG) and Webalizer produces graphical and detailed traffic analysis. This system is in use at the Obafemi Awolowo University, IleIfe, Nigeria;we describe how this system can be replicated in another environment.展开更多
Determining trip purpose is an important link to explore travel rules. In this paper,we takea utomobile users in urban areas as the research object,combine unsupervised learning and supervised learningm ethods to anal...Determining trip purpose is an important link to explore travel rules. In this paper,we takea utomobile users in urban areas as the research object,combine unsupervised learning and supervised learningm ethods to analyze their travel characteristics,and focus on the classification and prediction of automobileu sers’trip purposes. However,previous studies on trip purposes mainly focused on questionnaires and GPSd ata,which cannot well reflect the characteristics of automobile travel. In order to avoid the multi-dayb ehavior variability and unobservable heterogeneity of individual characteristics ignored in traditional traffic questionnaires,traffic monitoring data from the Northern District of Qingdao are used,and the K-meansc lustering method is applied to estimate the trip purposes of automobile users. Then,Adaptive Boosting(AdaBoost)and Random Forest(RF)methods are used to classify and predict trip purposes. Finally,ther esult shows:(1)the purpose of automobile users can be mainly divided into four clusters,which includeC ommuting trips,Flexible life demand travel in daytime,Evening entertainment and leisure shopping,andT axi-based trips for the first three types of purposes,respectively;(2)the Random Forest method performss ignificantly better than AdaBoost in trip purpose prediction for higher accuracy;(3)the average predictiona ccuracy of Random Forest under hyper-parameters optimization reaches96.25%,which proves the feasibilitya nd rationality of the above clustering results.展开更多
This paper focuses on the key technologies of P2P technology and network traffic monitoring, which focuses on AC automaton and bypass interference control technology, and on based of it, we design a new P2P traffic mo...This paper focuses on the key technologies of P2P technology and network traffic monitoring, which focuses on AC automaton and bypass interference control technology, and on based of it, we design a new P2P traffic monitoring system. The system uses DPI and DFI recognition technology, as well as straight loss and bypass interference control technology, basically meet the recognition and control of P2P traffic. Finally, the test results show that this system recognition accuracy of P2P traffic is high, good control effect, function and performance meet the design requirements.展开更多
This paper focuses on the key technologies of P2P and network traffic monitoring, research and analyze the traditional P2P flow control technology and the working principle of deployment, discuss on the straight loss ...This paper focuses on the key technologies of P2P and network traffic monitoring, research and analyze the traditional P2P flow control technology and the working principle of deployment, discuss on the straight loss and bypass interference control technology, and the reasonable combination of two kinds of technology to design straight bypass joint deployment. On basis of it, we design a new P2P traffic monitoring system. Through the design and implementation of computer network traffic monitoring system based on C/S mode to achieve automatic control, maintenance, and monitor network traffic, which is suitable for the current engineering software to monitor a network application environment. From the network users and network operator＇ s perspective, monitoring of network traffic is scientific, reasonable that improve network management and it has important research value.展开更多
The piezoelectric effect is used in sensing applications such as in force and displacement sensors.However,the brittleness and low performance of piezoceramic lead zirconate titanate(PZT) often impede its applicabilit...The piezoelectric effect is used in sensing applications such as in force and displacement sensors.However,the brittleness and low performance of piezoceramic lead zirconate titanate(PZT) often impede its applicability in civil structures which are subjected to large loads.The concept of a piezocomposite electricity generating element(PCGE) has been proposed for improving the electricity generation performance and overcoming the brittleness of piezoceramic wafers.The post-curing residual stress in the PZT layer constitutes a main reason for the PCGE's enhanced performance,and the outer epoxy-based composites protect the brittle PZT layer.A d33-mode PCGE designed for bridge monitoring application was inserted in a bridge bearing to provide a permanent and simple weigh-in-motion system.The designed PCGEs were tested through a series of tests including fatigue and dynamic tests to verify their applicability for monitoring purposes in a bridge structure.A simple beam example was presented to show the applicability of the proposed bridge bearing equipped with the PCGE for adequately measuring the traffic loads.展开更多
The present paper aims to describe the conceptual idea to use cars as sensors to measure and acquire data related road environment. The parameters are collected using only standard equipment commonly installed and ope...The present paper aims to describe the conceptual idea to use cars as sensors to measure and acquire data related road environment. The parameters are collected using only standard equipment commonly installed and operative on commercial cars. Real sensors and car sub-systems (e.g. thermometers, accelerometers, ABS, ESP, and GPS) together with other “implicit” sensors (e.g. fog lights, windscreen wipers) acquire and contain information. They are shared inside an in-vehicle communication network using mainly the standard CAN bus and can be collected by a simple central node. This node can also be available on the market without too expensive costs thanks to some companies which business is devoted to car fleet monitoring. All the collected data are then geolocalized using a standard GPS receiver and sent to a remote elaboration unit, exploiting mobile network technologies such as GPRS or UMTS. A large number of cars, connected together in a diffuse Wireless Sensor Network, allow the elaboration unit to realize some info-layers put at the disposal of a car driver. Traffic, state of the road and other information about the weather can be received by car drivers using an ad hoc developed mobile application for smartphone which can give punctual information related to a specific route, previously set on the mobile phone navigator. The description of some experimental activities is presented, some technical points will be addressed and some examples of applications of the network of cars “as sensors” will be given.展开更多
Unmanned Aerial Vehicles(UAVs)are enabled to be fast and flexible in managing traffic compared to the conventional methods.However,in emergencies,this system takes more time to identify and clear the traffic because o...Unmanned Aerial Vehicles(UAVs)are enabled to be fast and flexible in managing traffic compared to the conventional methods.However,in emergencies,this system takes more time to identify and clear the traffic because of fixed time control.To overcome this problem,an automated intelligent traffic monitoring and controlling system is designed using YOLO V3 neural architecture and implemented to detect the emergency vehicles from video stream data from UAVs using deep Convolution Neural Network(CNN)along with rerouting algorithm to provide the safest alternate route from current position to destination,in a heavy traffic environment.The real-time visual data collected through UAV video cameras are trained using machine learning algorithms to produce statistical profiles that are used continuously as updated inputs to the existing traffic simulation models for improving predictions.The proposed automated system performs exemplary in recognizing emergency vehicles and diverting them to an alternate route for quick transportation in various scenarios.展开更多
In network traffic classification,it is important to understand the correlation between network traffic and its causal application,protocol,or service group,for example,in facilitating lawful interception,ensuring the...In network traffic classification,it is important to understand the correlation between network traffic and its causal application,protocol,or service group,for example,in facilitating lawful interception,ensuring the quality of service,preventing application choke points,and facilitating malicious behavior identification.In this paper,we review existing network classification techniques,such as port-based identification and those based on deep packet inspection,statistical features in conjunction with machine learning,and deep learning algorithms.We also explain the implementations,advantages,and limitations associated with these techniques.Our review also extends to publicly available datasets used in the literature.Finally,we discuss existing and emerging challenges,as well as future research directions.展开更多
Based on the massive data collected with a passive network monitoring equipment placed in China＇s backbone, we present a deep insight into the network backbone traffic and evaluate various ways for inproving traffic ...Based on the massive data collected with a passive network monitoring equipment placed in China＇s backbone, we present a deep insight into the network backbone traffic and evaluate various ways for inproving traffic classifying efficiency in this pa- per. In particular, the study has scrutinized the net- work traffic in terms of protocol types and signatures, flow length, and port distffoution, from which mean- ingful and interesting insights on the current Intemet of China from the perspective of both the packet and flow levels are derived. We show that the classifica- tion efficiency can be greatly irrproved by using the information of preferred ports of the network applica- tions. Quantitatively, we find two traffic duration thresholds, with which 40% of TCP flows and 70% of UDP flows can be excluded from classification pro- cessing while the in^act on classification accuracy is trivial, i.e., the classification accuracy can still reach a high level by saving 85% of the resources.展开更多
In this work,the primary focus is to identify potential technical risks of Artificial Intel-ligence(AI)-driven operations for the safety monitoring of the air traffic from the perspective of speech communication by st...In this work,the primary focus is to identify potential technical risks of Artificial Intel-ligence(AI)-driven operations for the safety monitoring of the air traffic from the perspective of speech communication by studying the representative case and evaluating user experience.The case study is performed to evaluate the AI-driven techniques and applications using objective metrics,in which several risks and technical facts are obtained to direct future research.Considering the safety–critical specificities of the air traffic control system,a comprehensive subjective evaluation is conducted to collect user experience by a well-designed anonymous questionnaire and a face-to-face interview.In this procedure,the potential risks obtained from the case study are confirmed,and the impacts on human working are considered.Both the case study and the evaluation of user experience provide compatible results and conclusions:(A)the proposed solution is promising to improve the traffic safety and reduce the workload by detecting potential risks in advance;(B)the AI-driven techniques and whole diagram are suggested to be enhanced to eliminate the possible distraction to the attention of air traffic controllers.Finally,a variety of strategies and approaches are discussed to explore their capability to advance the proposed solution to industrial practices.展开更多
A three-year sampling campaign was conducted at a roadside air pollution monitoring station in the urban area of Kanazawa, Japan. Due to a new emission regulation, PAHs levels decreased over the sampling campaign, exh...A three-year sampling campaign was conducted at a roadside air pollution monitoring station in the urban area of Kanazawa, Japan. Due to a new emission regulation, PAHs levels decreased over the sampling campaign, exhibiting values of 706 ± 413 pg/m^(3) in 2017, 559 ±384 pg/m^(3) in 2018, and 473 ± 234 pg/m^(3) in 2019. In each year, similar seasonal variations in PAHs levels were observed, with higher levels observed in winter and lower levels in summer. Among the PAHs isomer ratios, we observed that the ratio of benzo[b]fluoranthene(BbF) and benzo[k]fluoranthene(BkF), [Bb F]/([BbF] + [BkF]), and the ratio of indeno[1,2,3-cd]pyrene(IDP) and benzo[ghi]perylene(BgPe), [IDP]/([BgPe] + [IDP]), showed stability over the sampling campaign and were less affected by the new emission regulation, seasonal variations, and regional characteristics. When using the combined ratio ranges of 0.66-0.80([Bb F]/[BbF] + [BkF]) and 0.26-0.49([IDP]/[Bg Pe] + [IDP]), traffic emissions were clearly distinguished from other PAHs emission sources. Principal component analysis(PCA) and positive matrix factorization(PMF) were also performed to further analyse the characteristics of traffic-related PAHs. Overall, this study affirmed the effectiveness of the new emission regulation in the reduction of PAHs emissions and provided a combined range for identifying PAHs traffic emission sources.展开更多
Recently, there have been many mo- bile value-added services in the Chinese mo- bile telecommunication market nowadays. Am- ong them, the characteristics of Multimedia Mes- saging Service （MMS） have not yet been ful...Recently, there have been many mo- bile value-added services in the Chinese mo- bile telecommunication market nowadays. Am- ong them, the characteristics of Multimedia Mes- saging Service （MMS） have not yet been fully understood. In this paper, with the help of a cloud computing platform, we investigated the flow-level charactefistcs of Chinese MMS. All of the experimental data were collected by the TMS equipment deployed in a major node in Sou- them China. The collection time spanned six mo- nths. We performed high-level analysis to show the basic distributions of MMS characteristics. Then, by analysing the detailed MMS features, we determined the distribution of personal MMS, and made a comprehensive comparison between 2G and 3G MMS. Finally, we tried to build a model on the personal MMS inter-arrival time, and we found that the Weibull distribution was optimum.展开更多
基金supported by the National Natural Science Foundation of China(NSFC)under grant No.62371187the Hunan Provincial Natural Science Foundation of China under Grant Nos.2024JJ8309 and 2023JJ50495.
文摘The integration of cloud computing into traditional industrial control systems is accelerating the evolution of Industrial Cyber-Physical System(ICPS),enhancing intelligence and autonomy.However,this transition also expands the attack surface,introducing critical security vulnerabilities.To address these challenges,this article proposes a hybrid intrusion detection scheme for securing ICPSs that combines system state anomaly and network traffic anomaly detection.Specifically,an improved variation-Bayesian-based noise covariance-adaptive nonlinear Kalman filtering(IVB-NCA-NLKF)method is developed to model nonlinear system dynamics,enabling optimal state estimation in multi-sensor ICPS environments.Intrusions within the physical sensing system are identified by analyzing residual discrepancies between predicted and observed system states.Simultaneously,an adaptive network traffic anomaly detection mechanism is introduced,leveraging learned traffic patterns to detect node-and network-level anomalies through pattern matching.Extensive experiments on a simulated network control system demonstrate that the proposed framework achieves higher detection accuracy(92.14%)with a reduced false alarm rate(0.81%).Moreover,it not only detects known attacks and vulnerabilities but also uncovers stealthy attacks that induce system state deviations,providing a robust and comprehensive security solution for the safety protection of ICPS.
基金supported by the National Key Research and Development Program of China(Nos.2023YFC3707301 and 2023YFC3705400)the Fundamental Research Funds for the Central Universities(Nos.ZB23003425 and 63211075)。
文摘To investigate the response of Roadside Monitoring Stations(RSs)to traffic-related air pollution,traffic and pollutant characteristics,influencing factors,and potential source characterization in Tianjin,China were determined based on roadside monitoring of real-world data conducted at RSs in 2022.The diurnal variation trend of pollutants at RSs was consistent with that at the National Monitoring Station(NM),with notably higher pollutant fluctuations during the morning and evening peak traffic times at RSs,where the average diurnal concentration was 41.46%higher than that at the NM.The generalized additive model(GAM)for nitrogen oxides(NO_(x))and carbon monoxide(CO),responding to themultiple influencing factors,performed well at RSs,with deviance explained by 86.6%and 61.4%,respectively.The synergistic effects of wind direction and speed contributed to most of the variations in NO_(x) and CO,which were 14.74%and 12.87%,respectively.Pollutant concentrations were highest under windless conditions,with pollutants originating primarily from local vehicle emissions.The model results indicated that medium-duty truck(MDT)traffic flow predominantly contributed to the variability in NO_(x) emissions,whereas passenger car(PC)traffic flow was the primary source of CO emissions from traffic variables.MDTs should be the focus of urban NO_(x) traffic emissions control.Potential-source analysis validated the results obtained from the GAM,and both analyses showed that RSs can better characterize traffic-related air pollutants.Furthermore,more stringent emission standards have effectively mitigated the release of pollutants from motor vehicles and contributed to the modernization of vehicle fleet composition,effectively decreasing CO concentrations.
基金supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No.61521003)the National Basic Research Program of China (2012CB315901, 2013CB329104)+1 种基金the National Natural Science Foundation of China (Grant No. 61372121, 61309019, 61309020)the National HighTech Research & Development Program of China (Grant No. 2015AA016102, 2013AA013505)
文摘Towards line speed and accurateness on-line content popularity monitoring on Content Centric Networking(CCN) routers, we propose a three-stage scheme based on Bloom filters and hash tables for differentiated traffic. At the first stage, we decide whether to deliver the content to the next stage depending on traffic types. The second stage consisting of Standard Bloom filters(SBF) and Counting Bloom filters(CBF) identifies the popular content. Meanwhile, a scalable sliding time window based monitoring scheme for different traffic types is proposed to implement frequent and real-time updates by the change of popularities. Hash tables according with sliding window are used to record the popularity at the third stage. Simulation results reveal that this method reaches a 40 Gbps processing speed at lower error probability with less memory, and it is more sensitive to the change of popularity. Additionally, the architecture which can be implemented in CCN router is flexible and scalable.
基金The National Natural Science Foundation ofChia(No60372076)The Important cienceand Technology Key Item of Shanghai Science and Technology Bureau ( No05dz15004)
文摘Real traffic information was analyzed in the statistical characteristics and approximated as a Gaussian time series. A data source model, called two states constant bit rate (TSCBR), was proposed in dynamic traffic monitoring sensor networks. Analysis of autocorrelation of the models shows that the proposed TSCBR model matches with the statistical characteristics of real data source closely. To further verify the validity of the TSCBR data source model, the performance metrics of power consumption and network lifetime was studied in the evaluation of sensor media access control (SMAC) algorithm. The simulation results show that compared with traditional data source models, TSCBR model can significantly improve accuracy of the algorithm evaluation.
基金Supported by the National Natural Science Foundation of China(No.61005034)China Postdoctoral Science Foundation and under Grant(No.2012M510768)the Science Foundation of Hebei Province under Grant(No.F2012203182)
文摘A real-time vehicle tracking method is proposed for trattlC monitoring system at roau mte^cc- tions, and the vehicle tracking module consists of an initialization stage and a tracking stage. Li- cense plate location based on edge density and color analysis is used to detect the license plate re- gion for tracking initialization. In the tracking stage, covariance matching is employed to track the license plate. Genetic algorithm is used to reduce the computational cost. Real-time image tracking of multi-lane vehicles is achieved. In the experiment, test videos are recorded in advance by record- ers of actual E-police systems erage false detection rate and at several different city intersections. In the tracking module, the av- missed plates rate are 1.19%, and 1.72%, respectively.
基金Supported by the Science and Technology Development Planning Project of Binzhou City,Shandong Province(2014ZC0331)
文摘Wind speed,temperature,relative humidity and TSP concentration at three intersections in Binzhou City were monitored,and the relationships of TSP concentration with wind speed,temperature,relative humidity and traffic flow at the three intersections in Binzhou City were analyzed by using SPSS.The results show that traffic flow was the main factor affecting TSP concentration of road traffic in Binzhou City.
文摘Road Traffic monitoring involves the collection of data describing the characteristic of vehicles and their movement through road networks. Such data may be used for one of these purposes such as law enforcement, congestion and incident detection and increasing road capacity. Transportation is a requirement for every nation regardless of its economy, political stability, population size and technological development. Movement of goods and people from one place to another is crucial to maintain strong economic and political ties between the various components of any given nation among nations. However, there are different modes of transportation and the most paramount one to human beings is road transportation. Due to increase in the modes of transportation, road users encounter different problems such as road blockage and incidents. Therefore there is need to monitor users incidents and to know the causes. Road traffic monitoring can be done manually or using ICT devices. This paper focuses on how the use of ICT devices can enhance road traffic monitoring. It traces the brief history of transportation;it equally discussed road traffic and safety, tools for monitoring road traffic, Intelligent Transportation Systems (ITS) use for traffic monitoring and their benefits. The result shows that the use of ICT devices in road traffic monitoring should be a Millennium Goal for all developed and developing countries because of its numerous advantages in the reduction of the intensity of traffic and other road incidents.
文摘To process the traffic monitoring image, a local Histogram Equalization method based on fuzzy mathematics was proposed in this paper. In this paper, firstly, we define a function to measure the similarity degree of two images. Then, a suitable Gaussian fuzzy distribution function was chose to generate a 3 × 3 matrix of influential factors. In order to reduce the artificial boundaries, we combined the 3 × 3 influential matrix with a 3 × 3 smooth filter matrix to get the final smooth-influ- ence matrix. Finally, the smooth-influence matrix was used to process the center block image. The simulation results demonstrated that the proposed method can reduce time consumption while improving the image contrast and can get satisfactory results.
文摘The lack of current network dynamics studies that evaluate the effects of new application and protocol deployment or long-term studies that observe the effect of incremental changes on the Internet, and the change in the overall stability of the Internet under various conditions and threats has made network monitoring challenging. A good understanding of the nature and type of network traffic is the key to solving congestion problems. In this paper we describe the architecture and implementation of a scalable network traffic moni-toring and analysis system. The gigabit interface on the monitoring system was configured to capture network traffic and the Multi Router Traffic Grapher (MRTG) and Webalizer produces graphical and detailed traffic analysis. This system is in use at the Obafemi Awolowo University, IleIfe, Nigeria;we describe how this system can be replicated in another environment.
基金Sponsored by the National Key R&D Program of China(Grant No.2020YFB1600500)the National Natural Science Foundation of China(GrantN o.52272319)。
文摘Determining trip purpose is an important link to explore travel rules. In this paper,we takea utomobile users in urban areas as the research object,combine unsupervised learning and supervised learningm ethods to analyze their travel characteristics,and focus on the classification and prediction of automobileu sers’trip purposes. However,previous studies on trip purposes mainly focused on questionnaires and GPSd ata,which cannot well reflect the characteristics of automobile travel. In order to avoid the multi-dayb ehavior variability and unobservable heterogeneity of individual characteristics ignored in traditional traffic questionnaires,traffic monitoring data from the Northern District of Qingdao are used,and the K-meansc lustering method is applied to estimate the trip purposes of automobile users. Then,Adaptive Boosting(AdaBoost)and Random Forest(RF)methods are used to classify and predict trip purposes. Finally,ther esult shows:(1)the purpose of automobile users can be mainly divided into four clusters,which includeC ommuting trips,Flexible life demand travel in daytime,Evening entertainment and leisure shopping,andT axi-based trips for the first three types of purposes,respectively;(2)the Random Forest method performss ignificantly better than AdaBoost in trip purpose prediction for higher accuracy;(3)the average predictiona ccuracy of Random Forest under hyper-parameters optimization reaches96.25%,which proves the feasibilitya nd rationality of the above clustering results.
文摘This paper focuses on the key technologies of P2P technology and network traffic monitoring, which focuses on AC automaton and bypass interference control technology, and on based of it, we design a new P2P traffic monitoring system. The system uses DPI and DFI recognition technology, as well as straight loss and bypass interference control technology, basically meet the recognition and control of P2P traffic. Finally, the test results show that this system recognition accuracy of P2P traffic is high, good control effect, function and performance meet the design requirements.
文摘This paper focuses on the key technologies of P2P and network traffic monitoring, research and analyze the traditional P2P flow control technology and the working principle of deployment, discuss on the straight loss and bypass interference control technology, and the reasonable combination of two kinds of technology to design straight bypass joint deployment. On basis of it, we design a new P2P traffic monitoring system. Through the design and implementation of computer network traffic monitoring system based on C/S mode to achieve automatic control, maintenance, and monitor network traffic, which is suitable for the current engineering software to monitor a network application environment. From the network users and network operator＇ s perspective, monitoring of network traffic is scientific, reasonable that improve network management and it has important research value.
基金Project supported by Konkuk University,Korea,in 2014
文摘The piezoelectric effect is used in sensing applications such as in force and displacement sensors.However,the brittleness and low performance of piezoceramic lead zirconate titanate(PZT) often impede its applicability in civil structures which are subjected to large loads.The concept of a piezocomposite electricity generating element(PCGE) has been proposed for improving the electricity generation performance and overcoming the brittleness of piezoceramic wafers.The post-curing residual stress in the PZT layer constitutes a main reason for the PCGE's enhanced performance,and the outer epoxy-based composites protect the brittle PZT layer.A d33-mode PCGE designed for bridge monitoring application was inserted in a bridge bearing to provide a permanent and simple weigh-in-motion system.The designed PCGEs were tested through a series of tests including fatigue and dynamic tests to verify their applicability for monitoring purposes in a bridge structure.A simple beam example was presented to show the applicability of the proposed bridge bearing equipped with the PCGE for adequately measuring the traffic loads.
文摘The present paper aims to describe the conceptual idea to use cars as sensors to measure and acquire data related road environment. The parameters are collected using only standard equipment commonly installed and operative on commercial cars. Real sensors and car sub-systems (e.g. thermometers, accelerometers, ABS, ESP, and GPS) together with other “implicit” sensors (e.g. fog lights, windscreen wipers) acquire and contain information. They are shared inside an in-vehicle communication network using mainly the standard CAN bus and can be collected by a simple central node. This node can also be available on the market without too expensive costs thanks to some companies which business is devoted to car fleet monitoring. All the collected data are then geolocalized using a standard GPS receiver and sent to a remote elaboration unit, exploiting mobile network technologies such as GPRS or UMTS. A large number of cars, connected together in a diffuse Wireless Sensor Network, allow the elaboration unit to realize some info-layers put at the disposal of a car driver. Traffic, state of the road and other information about the weather can be received by car drivers using an ad hoc developed mobile application for smartphone which can give punctual information related to a specific route, previously set on the mobile phone navigator. The description of some experimental activities is presented, some technical points will be addressed and some examples of applications of the network of cars “as sensors” will be given.
文摘Unmanned Aerial Vehicles(UAVs)are enabled to be fast and flexible in managing traffic compared to the conventional methods.However,in emergencies,this system takes more time to identify and clear the traffic because of fixed time control.To overcome this problem,an automated intelligent traffic monitoring and controlling system is designed using YOLO V3 neural architecture and implemented to detect the emergency vehicles from video stream data from UAVs using deep Convolution Neural Network(CNN)along with rerouting algorithm to provide the safest alternate route from current position to destination,in a heavy traffic environment.The real-time visual data collected through UAV video cameras are trained using machine learning algorithms to produce statistical profiles that are used continuously as updated inputs to the existing traffic simulation models for improving predictions.The proposed automated system performs exemplary in recognizing emergency vehicles and diverting them to an alternate route for quick transportation in various scenarios.
文摘In network traffic classification,it is important to understand the correlation between network traffic and its causal application,protocol,or service group,for example,in facilitating lawful interception,ensuring the quality of service,preventing application choke points,and facilitating malicious behavior identification.In this paper,we review existing network classification techniques,such as port-based identification and those based on deep packet inspection,statistical features in conjunction with machine learning,and deep learning algorithms.We also explain the implementations,advantages,and limitations associated with these techniques.Our review also extends to publicly available datasets used in the literature.Finally,we discuss existing and emerging challenges,as well as future research directions.
基金This paper was partially supported by the National Natural Science Foundation of China under Crant No. 61072061111 Project of China under Crant No. B08004 the Fundamental Research Funds for the Central Universities under Grant No. 2009RC0122. References
文摘Based on the massive data collected with a passive network monitoring equipment placed in China＇s backbone, we present a deep insight into the network backbone traffic and evaluate various ways for inproving traffic classifying efficiency in this pa- per. In particular, the study has scrutinized the net- work traffic in terms of protocol types and signatures, flow length, and port distffoution, from which mean- ingful and interesting insights on the current Intemet of China from the perspective of both the packet and flow levels are derived. We show that the classifica- tion efficiency can be greatly irrproved by using the information of preferred ports of the network applica- tions. Quantitatively, we find two traffic duration thresholds, with which 40% of TCP flows and 70% of UDP flows can be excluded from classification pro- cessing while the in^act on classification accuracy is trivial, i.e., the classification accuracy can still reach a high level by saving 85% of the resources.
基金supported by the National Natural Science Foundation of China(Nos.62001315,71971150,U20A20161)the Open Fund of Key Laboratory of Flight Techniques and Flight Safety,Civil Aviation Administration of China(No.FZ2021KF04)Fundamental Research Funds for the Central Universities of China(No.2021SCU12050).
文摘In this work,the primary focus is to identify potential technical risks of Artificial Intel-ligence(AI)-driven operations for the safety monitoring of the air traffic from the perspective of speech communication by studying the representative case and evaluating user experience.The case study is performed to evaluate the AI-driven techniques and applications using objective metrics,in which several risks and technical facts are obtained to direct future research.Considering the safety–critical specificities of the air traffic control system,a comprehensive subjective evaluation is conducted to collect user experience by a well-designed anonymous questionnaire and a face-to-face interview.In this procedure,the potential risks obtained from the case study are confirmed,and the impacts on human working are considered.Both the case study and the evaluation of user experience provide compatible results and conclusions:(A)the proposed solution is promising to improve the traffic safety and reduce the workload by detecting potential risks in advance;(B)the AI-driven techniques and whole diagram are suggested to be enhanced to eliminate the possible distraction to the attention of air traffic controllers.Finally,a variety of strategies and approaches are discussed to explore their capability to advance the proposed solution to industrial practices.
基金supported by the Bilateral Open Partnership Joint Research Projects of the Japan Society for the Promotion of Science, Japan (JPJSBP120219914)the Environment Research and Technology Development Fund (5-1951) of the Environmental Restoration and Conservation Agency of Japan+1 种基金the CHOZEN Project of Kanazawa University, Japanthe cooperative research programs of Institute of Nature and Environmental Technology, Kanazawa University, Japan (21001)。
文摘A three-year sampling campaign was conducted at a roadside air pollution monitoring station in the urban area of Kanazawa, Japan. Due to a new emission regulation, PAHs levels decreased over the sampling campaign, exhibiting values of 706 ± 413 pg/m^(3) in 2017, 559 ±384 pg/m^(3) in 2018, and 473 ± 234 pg/m^(3) in 2019. In each year, similar seasonal variations in PAHs levels were observed, with higher levels observed in winter and lower levels in summer. Among the PAHs isomer ratios, we observed that the ratio of benzo[b]fluoranthene(BbF) and benzo[k]fluoranthene(BkF), [Bb F]/([BbF] + [BkF]), and the ratio of indeno[1,2,3-cd]pyrene(IDP) and benzo[ghi]perylene(BgPe), [IDP]/([BgPe] + [IDP]), showed stability over the sampling campaign and were less affected by the new emission regulation, seasonal variations, and regional characteristics. When using the combined ratio ranges of 0.66-0.80([Bb F]/[BbF] + [BkF]) and 0.26-0.49([IDP]/[Bg Pe] + [IDP]), traffic emissions were clearly distinguished from other PAHs emission sources. Principal component analysis(PCA) and positive matrix factorization(PMF) were also performed to further analyse the characteristics of traffic-related PAHs. Overall, this study affirmed the effectiveness of the new emission regulation in the reduction of PAHs emissions and provided a combined range for identifying PAHs traffic emission sources.
基金supported in part by the National Science and Technology Major Project under Grant No.2012ZX03002008the National Natural Science Foundation of China under Grant No.61072061the National "111" Project of China’s Higher Education under Grant No.B08004
文摘Recently, there have been many mo- bile value-added services in the Chinese mo- bile telecommunication market nowadays. Am- ong them, the characteristics of Multimedia Mes- saging Service （MMS） have not yet been fully understood. In this paper, with the help of a cloud computing platform, we investigated the flow-level charactefistcs of Chinese MMS. All of the experimental data were collected by the TMS equipment deployed in a major node in Sou- them China. The collection time spanned six mo- nths. We performed high-level analysis to show the basic distributions of MMS characteristics. Then, by analysing the detailed MMS features, we determined the distribution of personal MMS, and made a comprehensive comparison between 2G and 3G MMS. Finally, we tried to build a model on the personal MMS inter-arrival time, and we found that the Weibull distribution was optimum.
