Big Data Analysis Technology for Electric Vehicle Networks in Smart Cities

Lv, Zhihan; Qiao, Lei; Cai, Ken; Wang, Qingjun

doi:10.1109/tits.2020.3008884

Cited by 82 publications

(43 citation statements)

References 38 publications

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“…In this study, VR technology and Internet of Vehicles are combined to build a theoretical model of road network traffic state information accident prediction perception, and real-time detection of road network traffic state information can minimize the occurrence of accidents. Through the combined impact of VR technology and IoV technology, the car will be tested in all directions, and the safety performance and sensitivity performance will be evaluated in real-time [7].…”

Section: Innovation and Contentmentioning

confidence: 99%

Retracted: VR Technology and the Theoretical Model and Method of Road Network Traffic State Information Accident Prediction and Perception under the Environment of Internet of Vehicles

et al. 2024

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With the rapid increase in the number of private cars and buses in the country, the living standard has gradually improved, and vehicles as a means of transportation commonly used by people have caused more traffic accidents. The present study mainly discusses the theoretical models and methods of VR technology and road network traffic status information accident prediction perception on the Internet of Vehicles (IoV) environment. Use of VR technology to simulate the experimental environment. The main techniques of VR real-time rendering are the visualization and roaming of large-area spatial data and the simulation of things that currently exist in computer vision simulation methods. Use VR technology to simulate ordinary highways, and use VR technology to simulate six sets of virtual cars. Use the real-time positioning function and data transmission function of the IoV technology to systematically collect driving data in the VR environment and advance collisions in advance to perceive and control the speed of the cars. Experimental data shows that when the time level is 2, the brake response sensitivity in the data is 88.9%, and the brake sensitivity value is relatively high. When the distance level is 1, the car safety factor value is 97.5%, and the data value is the highest. The research results show that when the time level is 2, the brake sensitivity value is relatively high, indicating that the VR technology and the traffic network information environment accident prediction effect on the Internet of Vehicles environment are better. When the distance level is 1, the performance of road network traffic status information accident perception based on VR technology and IoV environment is the best. Through the real-time sharing of the image recognition performance of VR technology and the geographic location of the Internet of Vehicles technology, the real-time prediction and perception of road network traffic status information accidents can minimize the chances of accidents.

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Section: Innovation and Contentmentioning

confidence: 99%

Retracted: VR Technology and the Theoretical Model and Method of Road Network Traffic State Information Accident Prediction and Perception under the Environment of Internet of Vehicles

et al. 2024

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“…At present, the video data analysis systems in sports and competitions include Hawkeye system applied in tennis competitions and Sport Vu system applied in Western professional basketball competitions. These systems not only collect a large number of relevant data during the competition but also provide reliable visual data analysis and daily training data analysis for athletes and coaches [ 25 ]. At the same time, these data analysis systems improve the visibility of live broadcast technology review and greatly improve the audience's viewing experience.…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Automatic Detection Method of Technical and Tactical Indicators for Table Tennis Based on Trajectory Prediction Using Compensation Fuzzy Neural Network

Zhang

2021

Computational Intelligence and Neuroscience

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In the system design of table tennis robot, the important influencing factors of automatic detection of technical and tactical indicators for table tennis are table tennis rotation state, trajectory, and rebound force. But the general prediction algorithm cannot process the time series data and give the corresponding rotation state. Therefore, this paper studies the automatic detection method of technical and tactical indicators for table tennis based on the trajectory prediction using the compensation fuzzy neural network. In this paper, the compensation fuzzy neural network algorithm which combines the compensation fuzzy algorithm and recurrent neural network is selected to construct the automatic detection of technical and tactical indicators for table tennis. The experimental results show that the convergence time of the compensation fuzzy neural network is shorter, the training time is shortened, and the prediction accuracy is improved. At the same time, in terms of performance testing, the model can accurately distinguish the influence of table tennis rotation state and rebound on table tennis motion estimation, so as to improve the accuracy of motion trajectory prediction. In addition, the accuracy of trajectory prediction will be improved with the increase of input data. When the number of data reaches 30, the trajectory prediction error is within the actual acceptable error range.

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“…Artificial intelligence is difficult to define precisely. Many human activities, such as solving problems, guessing, discussing, making plans, writing computer programs, and even driving cars and bicycles [15], require "intelligence." If the machine can complete this task, it can be considered that the machine has some kind of "artificial intelligence.…”

Section: Definition Of Artificial Intelligencementioning

confidence: 99%

Research and Application of Combined Algorithm Based on Sustainable Computing and Artificial Intelligence

2021

Mathematical Problems in Engineering

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The Internet is a popular form of information technology development in the new century, and it organizes and analyzes big data by taking effective measures to find useful information. With manpower, it is obviously not enough to be in such a huge information system, so the emergence of sustainable computing and artificial intelligence has become the core of large-scale data processing at this stage. This paper studies the application of the combined algorithm based on sustainable computing and artificial intelligence. In this paper, a new combined intelligent search algorithm is proposed by combining sustainable computing with artificial intelligence. The combination algorithm firstly analyzes the value from the aspects of ecological environment and economic benefits and studies the overall evaluation of sustainable development ability. Secondly, the energy analysis method is used to establish a reasonable comprehensive ecosystem and evaluate its impact on the sustainable development of environment and economy. Finally, the impact of resource consumption, wind speed detection, waste discharge, and utilization of renewable resources in a certain area is analyzed by simulation. Through the experimental results, on the one hand, it is proved that the data obtained by the combined algorithm are more accurate than the single algorithm; on the other hand, the combined algorithm can be further sublimated and widely used for other data detection. The combination algorithm proposed in this paper can effectively detect the required data and has high applicability.

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Big Data Analysis Technology for Electric Vehicle Networks in Smart Cities

Cited by 82 publications

References 38 publications

Retracted: VR Technology and the Theoretical Model and Method of Road Network Traffic State Information Accident Prediction and Perception under the Environment of Internet of Vehicles

Retracted: VR Technology and the Theoretical Model and Method of Road Network Traffic State Information Accident Prediction and Perception under the Environment of Internet of Vehicles

[Retracted] Automatic Detection Method of Technical and Tactical Indicators for Table Tennis Based on Trajectory Prediction Using Compensation Fuzzy Neural Network

Research and Application of Combined Algorithm Based on Sustainable Computing and Artificial Intelligence

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