International Journal of Vehicle Information and Communication Systems (33 papers in press)
Journey in vehicular ad-hoc network: a survey of message dissemination approaches and their delays
by Puja Padiya, Amarsinh Vidhate, Ramesh Vasappanavara
Abstract: Vehicular Ad-Hoc Network (VANET) is currently an active area of research and aims to improve vehicle, road safety, traffic efficiency, convenience and comfort for drivers as well as passengers. This paper provides a state of the art overview of VANET standards, architectures, channel access methods and message dissemination approaches. A detailed survey based on delays, especially those that occur in reactive message dissemination approaches, with a short survey of predictive message dissemination approaches, has been presented. We also highlight our view on some of the open issues to be addressed.
Keywords: VANET; vehicular ad-hoc network; data dissemination; road safety; routing; delays; quality of service; standards; architectures; channel access.
Wireless power transfer with tuning capacitor compensation for electric vehicle applications
by V.N. Pranathy, V. Indragandhi, Kiran Sathyan, V. Vijayakumar, Ravi Logesh, V. Subramaniyaswamy
Abstract: Nowadays, electric vehicles (EV) have a great advantage because of their environment-friendly nature. Charging of EV using wireless power transfer (WPT) releases them from annoying wires. Based on the principle of inductive power transfer, the energy transfers from the primary coil to the secondary coil through loosely coupled coils. This paper presents a prototype design of the WPT system with a source, which is the grid. An ideal topology of a 6 kW system for EV wireless charging with series-parallel (SP) compensated tuning capacitors is designed. The SP capacitor compensation consists of tuning capacitors in both the primary and secondary side of power transmission. Maximum power transfer at the high-frequency resonant condition at the compensation mode is achieved by higher efficiency. The proposed system results are obtained and validated from the numerical analysis and simulated using Matlab/Simulink. Based on the block diagram representation and by state space analysis, a more precise form of results is obtained, and the four different compensation topologies showing the most significant form of SP capacitor compensation are compared.
Keywords: wireless power transfer; energy transfer; loosely coupled coils; electric vehicle.
An overview of electric vehicle converter configurations, control methods and charging techniques
by V. Indragandhi, V. Subramaniyaswamy, R. Logesh, V. Vijayakumar, P. Manimekalai
Abstract: The prospects of Electric Vehicles (EVs) have gained momentum due to the weakening of fossil fuels and the emergence of global warming issues. Moreover, highly energy-efficient vehicles have grown in stature due to the rapid progress made by power electronic equipment. It is a fact that the transportation sector consumes a sizable chunk of energy throughout the world. EVs are the solution for this problem as it reduces the radiation of greenhouse gases. Since one-third of the EV cost is dependent on its battery, the batteries and the pricing structure have undergone several experiments. The causes and the availability of the energy sources, alternative energy sources, contemporary control methods for formulating policies of energy management, configurations of converting DC-DC in EV applications and the methods of charging EV in a smart environment are exhaustively reviewed in the present study. The study evaluates the challenges and benefits of implementing electric vehicle technology. The utility grid encompasses several alternative energy resources due to the speedy development of EV. Thus, managing and meeting the increasing demand for alternative energy resources could be achieved by using smart grid control.
Keywords: converters; electric vehicles; fuel cell; hybrid vehicle; plug-in vehicle; smart grid.
Intelligent traffic light design and control in smart cities: a survey of techniques and methodologies
by Aditi Agrawal, Rajeev Paulus
Abstract: Expanding traffic in metropolitan territories leads to significant concerns such as road blockage, transportation delays, pollution level, fuel consumption, etc. Traffic light signals at intersections, being a part of the traffic management system (TMS), play an important role in effectively controlling traffic. The conventional pre-timed controlled traffic signals are becoming a bottleneck in the clearance of intense traffic especially during rush hours. Adaptive traffic light control (ATLC) has been outlined for quick traffic clearance at convergences which could additionally be upgraded by giving right of approach to emergency methods of transport. This survey summarises ATLC systems designed by leveraging the existing technologies such as WSN, VANET and image processing techniques to gather real-time traffic statistics, and evaluating the accumulated data to alter traffic lights with the aid of intelligent controllers. Keeping in mind the benefits of fuzzy logic in traffic control, this survey provides an in-depth review of the fuzzy controllers in the context of traffic lights at isolated and multiple intersections. Popular ATLC systems implemented worldwide are also summarised.
Keywords: intelligent transportation systems; adaptive traffic light control; fuzzy logic; isolated intersections; multiple intersections; WSN; VANET.
CPAAS: an efficient conditional privacy-preservation anonymous authentication scheme using signcryption in VANET
by Meenakshi Gupta, Poonam Gera, Bharavi Mishra
Abstract: The vehicular ad-hoc network (VANET) is a tremendously promising innovation in the field of Intelligent Transportation Systems (ITS). It facilitates a vehicle to communicate on the road with infrastructure or OBU to increase road safety and driving conditions. Further, to deliver the same requires a secure network build-up through a legitimate entity. However, in an open network, any of the participating entities may be malicious. Therefore, we need a proper solution to mitigate the effects of such entities by authenticating them, and it should also preserve the privacy of entity and integrity of the message so that the impact of any malicious entity can be nullified. The existing solutions focus on any of the above aspects, but not all, and further they are not computationally efficient. Inspired by this, we propose a computationally efficient approach that achieves most of the security requirements with less communication overhead. We have used distributed pseudo_id for preserving the privacy of the vehicle and the ID-based Certificateless Signcryption scheme based on elliptic curve cryptography to provide an effective way to achieve mutual authentication, integrity, non-repudiation, and confidentiality. The security analysis of our approach demonstrates the efficiency and effectiveness of our proposed scheme.
Keywords: authentication; security; conditional privacy preservation; vehicular ad-hoc network; pseudonyms; signcryption.
Secure data aggregation scheme based on node self-adaptive monitoring for wireless sensor networks
by Shuguang Zhang, Qian Wang, Yichen Wu, Hao Wang
Abstract: Malicious nodes in a wireless sensor network will cause a great deviation in data aggregation. Such malicious nodes assigned with the aggregation task can forge and send a mass of false data. As a result, the network may consume a mass of resources and users may make wrong decisions. Concerning this problem, a secure data aggregation scheme based on node self-adaptive monitoring is proposed in this paper. According to the scheme, a master cluster head node and a vice cluster head node are selected, wherein the vice cluster head node verifies the aggregation data produced by the master cluster head, the intra-cluster monitoring nodes monitor the behaviour of the master and vice cluster head nodes in a self-adaptive manner. Besides, the confidence interval theory is introduced to evaluate and calculate the credibility of nodes and highly credible node data are selected for data aggregation. Both theoretical analysis and experimental results show that our scheme can not only effectively recognise and shield malicious nodes, enhancing the accuracy of data aggregation, but also prevent malicious master cluster head nodes from forging and sending a lot of false data.
Keywords: wireless sensor networks; secure data aggregation; self-adaptive monitoring; confidence interval; credibility.
Cloud-assisted multi-tier hierarchical safety routing strategy for collision avoidance in a vehicular ad hoc network
by Nalina V, P. Jayarekha
Abstract: The Vehicular Ad hoc network (VANET) comprises a number of moving vehicles that establish wireless communication between them directly or using fixed infrastructure. Generally, the vehicles in VANET can obtain various services such as safety and comfort by establishing cooperative communication among them or from global servers through the internet. The main intention of VANET is to protect human lives from a dangerous situation and avoid chain collisions by alerting vehicles through emergency messages. Disseminating emergency messages in a hazardous area through single hop or multi-hop is a fundamental approach for efficiently delivering the emergency alert messages to all vehicles. However, the dissemination approaches incur a high redundant rate and inefficient use of network resources. The design of safety message dissemination protocols has to ensure reliable data delivery with strict delay deadline and also use the network resources in an efficient way. Taking into account the multicriteria information in dissemination oriented decision making is an appropriate solution for critical message communication. This paper proposes a Cloud-assisted Multi-tier Hierarchical Safety Routing (CM-HSR) strategy to avoid chain collisions with efficient resource usage. Initially, the CM-HSR divides the vehicles into a logical multi-tier hierarchical structure based on multiple information retrieved from cloud and roadside infrastructure. For effectively handling an emergency situation and network dynamism, the CM-HSR dynamically changes the multi-tier structure with the help of roadside infrastructures. To ensure reliable delivery with minimum redundant rate, the CM-HSR incorporates two mechanisms that are Accident severity level based Dangerous region Formation (ADF) and Multicriteria Decision Making (MDM). Finally, the simulation results demonstrate that the proposed CM-HSR attains better performance in terms of latency, duplicate packets, number of collisions, number of transmitted data packets, reachability, overhead, and number of secondary collisions in evaluation.
Keywords: Cloud-assisted VANET; logical multi-tier hierarchical structure; multicast message dissemination; multicriteria decision making; optimal forwarder vehicle selection.
Special Issue on: Impacts of Vehicle Information and Communication Systems
Range frequency based distance computation technique for positioning in vehicular ad-hoc network
by P. Mohamed Shakeel, S. Baskar
Abstract: The intent of VANET (Vehicular Ad-hoc Network) is to allow efficient information dissemination aimed at the safety and comfort of passengers and drivers and to safeguard them from risk. Several fascinating and wide ranging potential applications that aid travellers are driver assistance, collision detection, internet access, map location and so on. The most precarious one is collision detection and avoidance. A collision happens when the distance between neighboring vehicles rapidly decreases. Thus, a precise and accurate knowledge about the distance between vehicles has to be determined to allow a robust collision avoidance service. Hence, in this paper, a Range Frequency based Distance Computation (RFDC) technique is proposed to provide distance estimation between every vehicle that approximates to the actual distance. The performance of the proposed approach is analysed in terms of delay, energy used, accuracy and received signal strength, and compared with the existing MDS (multi beacon signal).
Keywords: VANET; distance; range frequency; received signal strength.
Special Issue on: Big Data Innovation For Sustainable VANET Management
An automatic moving vehicle detection system based on hypothesis generation and verification in a traffic surveillance system
by Smitha Jolakula Asoka, N. Rajkumar
Abstract: An intelligent transportation system has a major topic called traffic surveillance. In a complex urban traffic surveillance system, booming of vehicle detection and tracking is an problematic dilemma. To overcome this, a two-stage approach for a moving vehicle detection system is proposed in this paper. The proposed system mainly consists of two stages namely, hypothesis generation and hypothesis verification. At the first step, hypotheses are generated using the concept that shadows beneath the vehicles are darker than the road region. The second step verifies whether a generated hypothesis is correct or not using an optimal artificial neural network (ANN). The weights corresponding to the ANN are optimally selected using the grasshopper optimisation algorithm. Through experimental results, it is shown that the proposed moving vehicle detection system performs with better accuracy than other methods.
Keywords: traffic surveillance system; moving vehicle detection; tracking; hypothesis generation; hypothesis verification; feedforward neural network; grasshopper optimisation algorithm.
Special Issue on: Research Challenges and Emerging Technologies in Autonomous Systems
Design and implementation of smart breaker system for electricity board using autonomous systems
by R. Vanitha
Abstract: According to the statistics of the Indian government, India loses 16.2 billion rupees owing to power theft by the people in all the states, and many of the people dont pay their bills and still use the electricity for free because of the improper existing systems in the use. The Electricity Board in India also experiences lot of troubles in various tasks such as energy auditing, billing, and regulating power in order to keep the system running smoothly. To prevent the above-mentioned problems a smart circuit breaker kit for the Electricity Board is developed with the help of Arduino Uno, Relay, GSM module, Subscribers Identity Module (SIM), and a real time clock. The major problem of power theft can also be prevented through the control over the energy meter. The controlling of energy meter will be easy as the GSM signals become part of daily life as they are available everywhere.
Keywords: automatic billing system; GSM; Arduino; smart breaker system; SIM; RTC; IoT.
Fuzzy-based local agent routing protocol for delay-conscious MANETs
by C. Venkataramanan, B. Senthilkumar
Abstract: Owing to the demand on multimedia applications, most researchers still concentrate on the area of Mobile Ad hoc NETworks (MANETs) to ensure the quality of services. MANET is an infrastructure-less network, where the devices (i.e. nodes) are self-configuring together and form the network without any central coordinator. Owing to the absence of central monitoring, MANET experiences various issues such as packet loss, topological control and delay. In order to address those problems in this paper, the enhanced version of Ad hoc On Demand Distance Vector (AODV) routing protocol is proposed. According to this proposed approach, each node in the network has to find the number of packets in the queue and calculate the weight value, which is used to predict the best routing path for ongoing transmission. The local agents are nominated for collecting and processing the information. The local agent performs the decision-based routing by using fuzzy inference model (AODV-FLA).
Keywords: AODV; energy usage; fuzzy; MANETs; routing; QoS.
An experimental analysis of quad-wheel autonomous robot location and path planning using the Borahsid algorithm with GPS and Zigbee
by Siddhanta Borah, R. Kumar, Subhradip Mukherjee, Fenil. C.Panwala, A. Prasanna Lakshmi
Abstract: This paper presents a hardware system structure and wireless navigation system for both localisation and path navigation of a mobile robot, implementing a 32-bit ARM processor (LPC2148 Board) into the design process of a mobile robot integrated with GPS and a ZigBee wireless communication device. A novel path-navigation algorithm (Borahsid algorithm), with less complexity than the existing algorithms adopted for mobile robot realistic work, uses GPS localisation as well as ZigBee communication. For simulation purpose MATLAB programming language has been used to simulate the mobile robot localisation and path navigation, and the results show the effectiveness of the model and the feasibility of the Borahsid algorithm. However, the entire control structure is executed and the experimental results were obtained in a real time system. The experimental results authenticate the performance and steadiness of the implemented control system process.
Keywords: ARM processor; GPS; ZigBee-based communication; Borahsid algorithm; MATLAB.
Low power CMOS circuit design of audio frequency shift keying for emergency alert system
by D. Haripriya, R. Vasavi
Abstract: Emergency alert systems are highly essential during natural disasters such as earthquake, flooding, volcanic eruption, landslides, and hurricanes to make the public alert. Existing emergency alert systems use siren, text alert and broadcasting, but they are slow and may not alert quickly in crucial situations. An Audio Frequency Shift Keying (AFSK) is designed to alert the public in emergency without hearing the text of the alert. It is designed with low power relaxation oscillator and voltage controlled oscillator using CMOS technology. In this work, relaxation oscillator is designed with inductor-less circuit for wideband tuning and provides huge area saving in the design. The control unit is designed to select the audio signal with two different oscillation frequencies based on input data. The public would be able to get awareness about the condition of natural disasters based on frequency of audio signal. An AFSK is designed with an operating voltage of 400 mV that consumes only 6.18
Keywords: emergency alert system; AFSK; relaxation oscillator; voltage controlled oscillator.
Secure and location privacy in geographical data with electronic codebook mode-advanced encryption standard
by Nikhil B. Khandare, Narendra S. Chaudhari
Abstract: Location based service (LBS) is considered as one of the most encouraging as well as new ways of convergence technologies in the development of numerous fields, together with database systems, mobile communication, internet technology, and positioning systems. Even though being introduced in the mid 1990s, only lately has LBS achieved an efficient intense study owing to its commercial and scientific influence. As the LBS is associated with the user's location, which can be preferred to track the actions of user, a strong privacy concern is elevated. To maintain the user's position, different intelligent works that are introduced with numerous challenges still require solutions. To solve these issues, this paper proposes an encryption technique for improving the security of the LBS system named as Electronic Codebook Mode-Advanced Encryption Standard (ECBM-AES). The key purpose of this study is to offer security in addition to location privacy against the attackers. The cryptographic approach uses two verifiers, and the claimed region could be in any intermission amongst the two verifiers. The results show that the proposed technique provides better key generation ratio and network size, packet delivery ratio, security and higher location privacy compared with the existing techniques
Keywords: ECM-AES; cryptography; LBS; security.
Special Issue on: Vehicular Networking and Communication Systems
Modelling and analysis of urban vehicle traffic congestion characteristics based on vehicle-borne network theory
by Minglei Song, Rong Rong LI, Binghua Wu, Minwo Lee
Abstract: In order to solve the problems of pollution and traffic safety caused by vehicle traffic congestion, this paper establishes an analysis model of urban vehicle traffic congestion characteristics based on vehicle network theory. Through the application of vehicular network, the extended mobility model of the vehicular network is established, and the extended motion model of the vehicular network is simulated with simulation tools and middleware tools to obtain the trajectory data of urban traffic vehicles. Based on the trajectory data, the survival analysis of urban vehicle traffic congestion is carried out. Kaplan-Meyer non-parametric regression model was used to estimate the duration of urban vehicle traffic congestion, and its distribution characteristics were quantitatively analysed. The experimental results show that the traffic congestion characteristics of urban vehicles are significantly different under different influencing factors, and the error of the trajectory data of urban traffic vehicles obtained by the proposed model is less than 1%.
Keywords: vehicle-borne network; theory; urban vehicle; traffic congestion; characteristics; analysis model; duration.
Research on self-organising control method of urban intelligent traffic signal based on vehicle networking
by Chunmei Wang
Abstract: In order to overcome the problem of poor application of traditional urban intelligent traffic signal self-organisation control, a method of urban intelligent traffic signal self-organisation control based on a vehicle network is proposed. A signal self-organising control system based on on-demand distribution is constructed, in which the fixed unit module RSU receives vehicle traffic data through sensors. RDU is used to monitor vehicle data and construct signal adaptive control strategy, which can reduce vehicle waiting time and realise urban intelligent traffic signal self-organising control. Simulation results show that the average number of stops at the intersection at the same time point is less than 0.3. The average stopping time is 8.728 s, which is lower than other methods. The average pass rate at the intersection is 98.65%, which is higher than other methods and feasible.
Keywords: vehicle networking; signal self-organising control system; urban intelligent transportation; on-demand distribution idea.
Automatic recognition of vehicle image based on monocular vision and environmental perception
by Daqin Wu, HaiYan Hu
Abstract: Aiming at the problems of low recognition accuracy and long time-consuming in current automobile recognition research, an automobile image recognition method based on monocular vision and environmental perception is proposed. A hybrid filter is composed of median filter and mean filter to suppress image noise and preserve the edge features of the signal. The non-target background is removed by environmental perception, and the target area is obtained with the geometric information in the vehicle shadow as the constraint condition. According to the result of image processing and the determination of target area, HAAR-like feature vectors of targets are extracted and dimensionality reduction is processed. The training classifier is constructed by using the obtained eigenvectors to recognize the current frame vehicles. The experimental results show that the method has the advantages of high recognition accuracy and less time-consuming.
Keywords: environment perception; monocular vision; vehicle image; recognition.
Design of recognition and compensation system for vehicle communication signal based on vehicle networking
by Min Yang
Abstract: A vehicle communication signal recognition and compensation system based on vehicle network is proposed to overcome the problems of the traditional vehicle communication signal recognition systems, such as poor anti-interference and signal recognition accuracy. The hardware part of the system consists of three modules. The software USES inverse operator and Wiener filter compensates the vehicle communication signal and improves the precision of signal recognition. The MFCC parameters are extracted as the main parameters of signal recognition, and the distance measurement between the unknown communication signal and each template is obtained by using the nonlinear registration mode DTW, so as to realise the optimal registration mode of signal pattern recognition. Experimental results show that the anti-interference performance of the system is about 110 dB, and the recognition rate of different types of signal is more than 85%, which proves that the system has high recognition accuracy and strong anti-interference ability.
Keywords: vehicle networking; vehicle-borne; communication signal; signal recognition; compensation system.
Anti-jamming method for vehicle communication network based on internet of vehicles technology
by Xiangjun Tian
Abstract: In order to solve the problems of poor signal anti-interference ability, high error rate and low network coverage in traditional vehicle communication network and to improve the communication quality of vehicle communication network, an anti-interference method of vehicle communication network based on vehicle internet technology is proposed. The maximum cellular rate resource reuse algorithm (MCRRA) is used to optimise the link resources of vehicle communication network, so as to realise the optimal allocation of vehicle communication network resources. Then, the wavelet denoising method is used to filter the signal noise after resource allocation in the vehicle communication network. Finally, the improved threshold function method of wavelet transform is used to compensate the pseudo-Gibbs phenomenon and signal loss in vehicle communication network. Experiments show that this method can effectively suppress the interference of the vehicle communication network. The error rate of the vehicle communication network using this method is only 10%, and the coverage rate is as high as 98.7%.
Keywords: internet of vehicles; vehicle communication; communication network; anti-jamming; cellular link.
Binocular vision vehicle environment collision early warning method based on machine learning
by Hong Mi, Ying Zheng
Abstract: Because the existing early warning methods do not assign weights, it is easy to cause collisions in the vehicle driving process, and the prediction accuracy is low. Therefore, this paper proposes a binocular vision vehicle environment collision early warning method based on machine learning. The comparison of experiments on high-speed sections shows that the number of vehicle collisions decreases by about six times when the proposed method is used, which is significantly less than that of the existing methods. Moreover, the distance error between the target vehicle and the running vehicle measured by the method in this paper is small. The error rate is between 0.005 and 0.041. Therefore, it can accurately warn of the occurrence of vehicle collisions, and its application advantages are obvious.
Keywords: machine learning; binocular vision; vehicle environment; camera; classifier; threshold value.
Design of intelligent traffic guidance display system based on internet of vehicles
by Chunling Liu
Abstract: In order to solve the problem of inaccurate detection of road space occupation, an intelligent traffic guidance and display system based on vehicle network is designed. Firstly, the real-time acquisition and prediction of vehicle and path environment data are realised by using a navigation information data acquisition module. Secondly, the traffic guidance information is used to publish the model, edit the data, and send the traffic guidance information display module. Then the set theory method is used to detect the traffic volume of RFID readers set up on the road. Finally, the average space speed, space occupation rate and road delay time are calculated to complete the traffic guidance. The experimental results show that the system can quickly balance the delay in road network and shows powerful guidance display performance with instantaneity larger than 95% and dynamics as high as 0.97 in ten kinds of traffic congestion in different roads.
Keywords: internet of vehicles; intelligent transportation; guidance; display system; traffic volume; speed.
Research on abnormal monitoring of vehicle traffic network data based on support vector machine
by Dahui Li, Jianzhao Cui, Qi Fan
Abstract: In order to solve the problems of low accuracy and long delay in traditional data monitoring methods of vehicle-mounted traffic network, an anomaly monitoring method based on support vector machine (SVM) is proposed. The data of acceleration sensor, gyroscope and magnetic field sensor are collected and filtered. The online analysis method of driving behaviour based on SVM is introduced to identify various driving behaviours. By simulating the normal behaviour and abnormal behaviour based on HTTP protocol, the obtained data is analysed to construct the HTTP protocol behaviour. The neural network based on radial basis function was trained to monitor the abnormal data in driving behaviours by simulating the behaviour records generated by experiments for many times. The experimental results show that the proposed method can accurately monitor the abnormal data in driving behaviour, and the delay is short, which provides a favorable basis for relevant studies.
Keywords: driving behaviour recognition; traffic network; data anomaly monitoring.
Special Issue on: ICBCC-2019 Intelligent Transportation Systems for Smart Cities
Improved coverage measurements through machine learning algorithms in a situational aware channel condition for indoor distributed massive MIMO mm-wave system
by Vankayala Chethan Prakash, G. Nagarajan, V. Subramaniyaswamy, Logesh Ravi
Abstract: In a massive MIMO (Multiple Input Multiple output) mm (millimetre)-wave system, the channel conditions are measured and analysed for a better placement of reflectors or antennas. In order to increase the coverage area and to reduce interference among users factors such as pathloss and power delay profile are extracted from the channel impulse response (CIR) i.e. from the received signal with respect to transmitter and receiver channel propagation conditions. In a distributed indoor massive MIMO mm-wave system, pathloss and power delay profile are evaluated for line of sight (LoS) and non-line of sight (NLoS) environments at frequencies such as 28 and 39 GHz. Based on these factors, a dataset is constructed for 28 GHz. Algorithms such as Support Vector Machine (SVM), KNN and Fine Tree are considered. These algorithms are trained with a set of datasets and are tested for performance metrics such as Mean Absolute Error, Correlation Coefficient, Root Mean Squared Error, Relative Absolute Error, and Root Relative Squared Error, which are evaluated. Simulation results show an accuracy of 94% and 95% using SVM, 93.8% and 94.5% using KNN, and 93.2% and 93.8% using Fine Tree algorithm for pathloss and power delay profile respectively.
Keywords: Fine Tree; KNN; massive MIMO; mm-wave; pathloss; power delay profile; support vector machine.
Effect of feature and sampling ratio on tool wear classification during boring operation using tree-based algorithms
by Surendar Selvasubramaniam, Elangovan Mahadevan, Akshay Elangovan, Vijayakumar Varadarajan
Abstract: The tool condition monitoring (TCM) system is used to predict the tool wear during the machining process. The predominant wear is the flank wear which has its impact on the surface roughness of the workpiece that is being machined. The quantum of flank wear is to be ascertained so that a decision could be made whether the time has come for the insert to be replaced. Although since the wear is continuous, it may be divided into three stages and may be classified as to which stage the tool wear falls into. Wear prediction may be carried out by extracting information from the vibration signals acquired during machining and interpreting them using machine learning. This paper confers on monitoring the uncoated carbide tooltip during boring operation using tree-based classifier algorithms such as random forest, J48, logistic model tree and gradient-boosted tree, in order to study the effect of feature and sampling ratio on tool wear classification when tree-based algorithms are used. Also, the statistical features and histogram features were compared for various cutting tool conditions to explore a better classifierfeature combine.
Keywords: J48; random forest tree; gradient-boosted tree; logistic model tree; Knime analytics platform.
Multivariate short-term traffic flow prediction based on real-time expressway toll plaza data using non-parametric techniques
by Annu Mor, Mukesh Kumar
Abstract: Accurate real-time traffic flow prediction is a vital component of an Intelligent Transportation System (ITS).The real-time traffic flow prediction helps transportation authorities as well as travellers for better route guidance. In this study, a novel approach is proposed for accurate toll plaza traffic prediction by introducing heterogeneous data sources other than traffic volume data. Toll data is analysed with exogenous factors, such as weather conditions and holidays. Here, ten non-parametric techniques is applied for traffic prediction on a real-time multivariate dataset. The proposed approach is validated using data collected from Pinjore-Kalka Toll Plaza, Chandigarh, India. The performances of the non-parametric models are compared on the basis of mean square error, absolute mean square error, coefficient of determination and correlation. The experimental results revealed that the random forest regression technique outperforms other techniques, achieving an accuracy of 90%. The proposed approach can be used for further proxy measure of level-of-service to design the existing infrastructure more efficiently for application in smart cities.
Keywords: traffic flow; intelligent transportation system; non-parametric technique; multivariate time series data; proxy measure.
Special Issue on: Advanced Intelligent Computing Techniques in Vehicular Communication, Computing and Applications
Optimised design of LCC-S compensation topologies for wireless power transfer with dynamic load for electric vehicles
by Ning Wang, Qingxin Yang
Abstract: This paper proposes a LCC-S compensation network structure to solve the problem of dynamic load changing that generally exists in wireless power transfer systems. Transmitter current, phase angle, power factor, output power, and efficiency are also analysed when the load changes. By preparing an experimental platform and taking a three-phase permanent magnet synchronous motor as equivalent load, we study the relationship between output power of the motor and output current of the transmitter under different motor speeds and torques. We find that the output current is stable at 1.87 A with resonant frequency at 20 kHz. Finally, system parameters are optimised by changing the ratio of each compensation element parameter, which improves the output efficiency by 7.69%.
Keywords: wireless power transfer; dynamic load; constant current output; compensation network; electric vehicles.
Research on map matching of lidar/vision sensor for automatic driving aided positioning
by Qing An, Xijiang Chen, Yuhua OuYang
Abstract: Aiming at the technical difficulties of map matching aided positioning based on lidar/vision sensor, the joint calibration of lidar/vision sensor and point cloud/image registration technology, as well as the dynamic environment interference removal method based on depth learning are studied in this paper. A lightweight coding-decoding architecture is introduced. We use deep separable convolution technology to extract urban environment features and generate semantic-level feature descriptors. The similarity measurement criteria that contain semantic information and geometric state are built. Then, we perform robust feature matching. Finally, a map matching location model based on recursive Bayesian filtering optimisation framework and an estimation method of location confidence are proposed. This realises the map assistant positioning under the complex environment of the city. In typical urban environments, the speed of feature extraction and matching is better than 0.1 s, the success rate of matching is more than 95%, and the positioning accuracy of high-precision map matching is better than 20 cm.
Keywords: laser radar; visual sensor; point cloud; depth learning; map matching.
Study on intelligent traffic search method based on driver facial feature analysis
by Kaidi Chen, Libing Hu, Miaobo Yao, Ledan Qian, Yongchun Zhang
Abstract: With the rapid development of internet technology and biometrics technology in China, artificial intelligence has gradually entered into every aspect of people's life. Big data is used to upgrade intelligent traffic search for people, which improves the efficiency and accuracy of people search for people. Intelligent traffic search is a hotspot in the field of biometric identification and plays an important role in social stability. As an important feature, driver's face image can not only provide great help to the detection of illegal vehicles, but also help to carry out the tracing of missing people, so as to maintain social harmony and stability. Therefore, the intelligent traffic search method based on the analysis of driver's facial features has a broad application prospect and research value. This paper investigates the current international top facial recognition algorithm technology level, and proposes a face image illumination invariant feature extraction algorithm and face feature detection ASM algorithm. The experimental results show that the intelligent traffic search method in this paper has a good recognition rate, and the study also has a certain guiding significance for the application of image processing in the field of intelligent traffic.
Keywords: driver facial features; artificial intelligence; intelligent traffic search; face feature detection.
Special Issue on: Emerging Digitalisation Technologies and Future Trends for Intelligent Transportation Systems
A scheduling heuristic in mobile distributed real-time database systems
by Prakash Kumar Singh
Abstract: A major research challenge has been addressed by real-time database systems to assign priority to transactions. Further, in the mobile environment, several wireless limitations are identified to execute transactions, which make it difficult to perform concurrent transactions within time-constraint situations. The role of a mobile distributed real-time system is to perform transaction executions and complete the concurrent transaction without damaging the consistency of data items at various stages. The transaction scheduling mechanism manages the correct order of execution of transactions to enhance concurrency and ultimately improve the database system and cloud computing system. In the last few decades, transaction scheduling policies have been introduced to enhance concurrency in a distributed real-time environment. Recently, various heuristic approaches have been developed in the course to assign priority precedence. Heuristic approaches have used to maximise the rate of successful completion of executing transactions. In this paper, the developed heuristic approaches are discussed and three heuristic strategies are proposed, which show improved results over the DHP-2PL concurrency control algorithm. The ENT approach is proposed, which is based on the exact requirement of the number of locks. Further, the DENT approach is discussed, which integrates the concept of similarity with the ENT approach. The DENT approach is proposed, which considers the transaction deadline with the present data items priority level. It added characteristics such as deadline and data item size to evaluate the priority of data item which is used in assigning priority in the DENT heuristic approach. The transaction scheduler applies various heuristic approaches that increase concurrency without affecting data consistency. The proposed heuristic policies are tested with Distributed High priority two-phase locking (DHP-2PL) concurrency control protocol for different transaction parameters. A series of simulation experiments are compared with earlier developed heuristic approaches and the results show that these heuristic strategies improve the system performance.
Keywords: transaction; deadline; distributed real-time database system; priority; wireless; scheduling; concurrency control.
Efficient transportation: future aspects of the internet of vehicles
by Ajay Dureja, Dr Suman
Abstract: Nowadays, the term Internet of Vehicles (IoV) has gained popularity among researchers. We are in the era of smart things, smart cities, smart homes, smart transport and smart home appliances, which has been realised owing to the Internet of Things (IoT).With the advent of smart cars and emerging communication technologies among vehicles, IoV has become a popular field of research and thereby attracted several vehicle industries and researchers. IoV is an amalgamation of VANET with IoT. Several research challenges need to be addressed for the development of an efficient transportation system using IoV. This paper presents the architecture of the IoV with five layers and a simple network model of IoV. Recent trends of IoV are discussed in this paper and are tabulated to present state of the art advancements and future trends in IoV.
Keywords: internet transportation system; internet of vehicles; network model; internet of things; VANET.
Collaboration of UAV & HetNet for better QoS: a comparative study
by Akshita Gupta, Shriya Sundhan, Sachin Kumar Gupta, S.H. Alsamhi, Mamoon Rashid
Abstract: To boost network performance in terms of QoS, the main approach to be considered is Heterogeneous Networks (HetNet) deployment. The deployment of random HetNet supports users with a better Quality of Service (QoS) by providing an efficient mechanism for proper data dissemination. Furthermore, UAVs can be used to deliver services for provisioning high QoS effectively and efficiently, because of their characteristics such as easy to deploy, line of sight, low propagation delay, immediate availability, and reliability. The combination of UAV and dynamic Ground Users (GU), where GU is connected through random HetNet, is one of the examples of UAVs assisted network. This paper shows the comparative performance evaluation of random HetNet for a real communication scenario: with and without UAVs assisted. Here, work is presented into two parts: The first one explains the concept of random HetNet and Random Waypoint Mobility Model (RWPM) for simulating the network for better QoS. The second part investigates the comparison of QoS parameters for the GUs connected in a random HetNet assisted by UAVs versus without UAVs. After comparison, results purely describe the betterment in terms of higher throughput, lower end-to-end delay, and reduced jitter as justified with simulation results and evaluations. The article concludes that the collaboration between UAV and random HetNet increases performance and supports better QoS.
Keywords: HetNet; UAVs; RWPM; GU; QoS.
Clone detection using fuzzy logic in a static wireless sensor network
by Sachin Lalar, Shashi Bhushan, A. Surender
Abstract: The wireless sensor networks have operated in various applications in which sensor nodes operated in hostile and open environments. The attacker can originate different types of attack in the open environment. The clone node attack is one of the gravest attacks on WSN since the clone node is deliberated as a legitimate node and can initiate different attacks within the network. The paper proposes a fuzzy-logic based clone detection scheme (FULCD) to detect replica nodes in the static wireless sensor network. The proposed scheme has three segments. In first segment of FULCD, sensor node determines whether any adjacent node is missing from the network. When any missed node again comes alive then there is a probability that node has been cloned. The second segment of FULCD checks whether the missed node is activated again or not. The network maintains a suspect list in which information of reactivated nodes is entered. The third segment of proposed method identifies the clone node with the help of fuzzy logic. The performance of FULCD has been evaluated using three different scenarios in the NS2 simulator. The proposed method reduces end-to-end delay, packet loss, and energy consumption, and increases PDR as shown by simulation results. FULCD has been compared with existing methods, i.e. ERCD, RED, LSM and RAWL. The proposed method FULCD diminishes energy consumption by 45% and increases the clone detection rate by 46% compared with ERCD, RED, LSM and RAWL.
Keywords: wireless sensor network; clone node attack; static sensor network; clone node detection method; NS-2 simulator; detection rate.
Special Issue on: ICBCC-2019 Intelligent Transportation Systems for Smart Cities
Collaborative decision making system in intelligent transportation system using distributed blockchain technology
by Bhabendu Kumar Mohanta, Debasish Jena, Utkalika Satapathy, Somula Ramasubbareddy
Abstract: Intelligent Transportation System (ITS) is one of the promising
applications of the Internet of Things(IoT) as the IoT system provides an easy
way to collect and monitor the system. One of the critical components to make
a city smart is by managing the traffic. The modes of transportation in the city are
different, such as bike, car, bus, auto, and rickshaw. Most of the vehicles are integrated with Information Communication Technology (ICT). As the vehicles share and
access information from the ITS infrastructure, some security issues exist, including trust management, privacy, data linking, and computational problems. This paper identifies the security issues present in the ITS model, then proposes a distributed architecture of the ITS system using blockchain. Then the Consensus algorithm is used to perform computations in a distributed platform. The Ethereum platform used to create a distributed network. The implementation and security analysis are given at the end.
Keywords: secure decision making; blockchain; IoT; intelligent transportation system; Ethereum.