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Revolutionizing Traffic Law Enforcement: IoT-Enabled Vehicle control systems for Smart Cities

Revolutionizing Traffic Law Enforcement: IoT-Enabled Vehicle...

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2024 IEEE international conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

作者： Mehta, Shiva Singh, Manpreet Chitkara University Institute of Engineering and Technology Chitkara University Centre for Research Impact & Outcome Punjab Rajpura140401 India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India

ISBN: (纸本)9798350379525

This article presents an enhanced Internet of Things-based vehicle management system for traffic law enforcement to improve road safety and compliance with the law. The designed system will integrate real-time data collection from various IoT devices such as cameras, speed sensors, and RFID readers and incorporate complex machine learning algorithms to detect offences on the road and control the traffic patterns accordingly. In a three-month prototype application in a small metropolitan area, the system demonstrated a traffic violation detection rate of 92.3% - including speeding and red-light running - with a reduction of false positives compared to traditional methods of 28%. Upon putting the system to use, releases in traffic violations were cut by 30%, and the punctuality of the traffic flow during rush hour was given a 15% boost with evidence of the reduction of average waiting time at major junctions. Furthermore, it enhanced the response time via technology, with responders achieving an 18% cut in the average response time of emergency vehicles compared to the original method. Nevertheless, some problems were observed: first, high dependence on the Internet - the data processing of objectives was slowed down by 12% of regions with a weak Internet connection. In addition, 14 % of users reported concerns about data privacy, showing the necessity of taking steps to improve data protection. The results reveal that while the IoT -based vehicular control system yields benefits for enforcing traffic laws, key challenges relating to connectivity, the privacy of information, and system adaptability must be addressed if it is to be first applied and then effectively implemented in extensive urban environments. © 2024 IEEE.

关键词： Data privacy

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Traffic Light control Using Reinforcement Learning 2

Traffic Light Control Using Reinforcement Learning

引用

2nd IEEE international conference on Integrated Circuits and Communication systems, ICICACS 2024

作者： Masfequier Rahman Swapno, S.M. Nuruzzaman Nobel, S.M. Ramachandra, A.C. Islam, Md Babul Haque, Rezaul Rahman, Mohammad Mominur Bangladesh University of Business and Technology Dept of CSE Dhaka Bangladesh Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India UNICAL Dept. of Computer Modeling Electronic and System Engineering Rende Italy East West University Dept of CSE Dhaka1212 Bangladesh Hamad Bin Khalifa University College of Science and Engineering Qatar

ISBN: (纸本)9798350317558

Nowadays, one of the biggest issues in urban areas is traffic. This problem wastes important time and contributes to air and sound pollution. This affects people's general quality of life in addition to posing health dangers. Our study attempts to mitigate these problems, effectively cutting down on wait times and delays. Our Reinforcement Learning method creates intelligent agents that can adjust traffic lights at crossings instantly. Our objective is to minimize delays, reduce congestion, reduce travel times, improve safety, and improve traffic flow. We implemented the Deep Q Learning algorithm which activities yield the greatest benefits under various traffic scenarios. Our model can the sequence time since the Green signal (GS) lasts 10 seconds and the Red signal (RS) lasts 5 seconds. The waiting period is shortened by 50% as a result. This study suggests reinforcement learning may improve traffic signal controller synchronization and urban traffic congestion. This novel method may improve transport efficiency and sustainability. © 2024 IEEE.

关键词： Action Deep Q Learning GS Model Q Value Rewards RS State Traffic signal vehicles Waiting Time

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22nd international conference on Computational Mechanics and Modern Applied Software systems, CMMASS 2021

22nd International Conference on Computational Mechanics and...

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22nd international conference on Computational Mechanics and Modern Applied Software systems, CMMASS 2021

The proceedings contain 16 papers. The topics discussed include: mathematical modeling of the gettering process for a cylindrical region;comparative analysis of optimization strategies by software complex ‘metaheuristic nature-inspired methods of global optimization’;computer simulation of the physical neutralization of drones in a smart city;reinforcement learning reward function in unmanned aerial vehicle control tasks;stabilization of a pendulum on an elastic foundation using a multilayer perceptron;theoretical basis, concept and methodology of control and correction of turbojet engines thrust asymmetry;the use of modern computer technologies in the study of the geometric modeling course;fractal feedback control for elastic computing based on the container–component model;utilization of parallel computing for mathematical modeling of high-enthalpy flows;and numerical investigation of rotor-dynamic system on taking into account gas in labyrinth seals clearances.

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Methods for Developing Effective Models of Biomedical Processes in MATLAB

Methods for Developing Effective Models of Biomedical Proces...

引用

international conference on Modern problems of Radio Engineering, Telecommunications and Computer Science

作者： Kostyantyn Kolisnyk Viktoriia Kolisnyk Torsten Wik Dept. Industrial and Biomedical Electronics National Technical University “Kharkiv Polytechnic Institute” Kharkov Ukraine Dept. Media Engineering and Information Radioelectronic Systems Kharkiv National University of Radio Electronics Kharkiv Ukraine Dept. Systems and Control Technology Electrical Technology Institutionen for elektroteknik Chalmers tekniska hogskola Gothenburg Sweden

ISBN: (数字)9798331520564

ISBN: (纸本)9798331520571

Mathematical modeling in the study of dynamic processes in biomedicine is currently widely used. The use of mathematical statistics and formal logic methods in the analysis of complex biomedical processes is especially important for increasing the efficiency of biomedical research. Taking into account the established growth of the technical base of research, the development of new technologies and technical means for obtaining and processing statistical biomedical information, the use of mathematical modeling methods is a fairly promising direction in scientific and practical work. In this paper the authors studies the possibility of improving the quality of biomedical process modeling using the MATLAB software environment. The research was carried out on real statistical material obtained by the authors during a full-scale experiment to study the impact of a complex of external factors on patients. The results obtained in this work can be used in the implementation of scientific and applied research of biomedical processes.

关键词： Process modeling Biological system modeling Market research Mathematical models Data models Software Telecommunications Logic MATLAB Medical diagnostic imaging

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MLP-Based Adaptive Sampling and Optimization of Laser-Ion Acceleration with Ultra-Short Laser Pulses 15th

MLP-Based Adaptive Sampling and Optimization of Laser-Ion ...

引用

15th international conference on Parallel Processing and Applied Mathematics, PPAM 2024

作者： Miethlinger, Thomas Bussmann, Michael Schramm, Ulrich Kluge, Thomas Helmholtz -Zentrum Dresden-Rossendorf Dresden01328 Germany Technische Universität Dresden Dresden01069 Germany

ISBN: (纸本)9783031857027

The field of laser-ion acceleration faces significant challenges in handling high-dimensional, computationally intensive problems, often constrained by budgets and available computational power. Reliably achieving high ion energies with current laser technologies through ultra-high intensity pulses in near-critical to overdense plasmas remains difficult, necessitating detailed, costly simulations to explore various acceleration mechanisms and optimize outcomes. Due to the high computational cost of these simulations, there is a need for precise, scalable, and efficient adaptive sampling methods that balance exploring new mechanisms while exploiting known parameter dependencies and that can operate in high-performance computing environments. In this work, we propose and investigate a scalable adaptive sampling approach that intrinsically supports parallel processing. We apply this method to data obtained from particle-in-cell simulations using multilayer perceptrons (MLPs), chosen for their flexibility in modeling complex dependencies. We benchmark our results against Bayesian optimization, and we highlight the limitations of MLPs when accounting for the intrinsic uncertainty present in the acceleration process. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Budget control

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Extension of Delphi Method to Z-Environment 15th

Extension of Delphi Method to Z-Environment

引用

15th international conference on Application of Fuzzy systems, Soft Computing and Artificial Intelligence Tools, ICAFS 2022

作者： Aliyev, Rafig R. Huseynov, O.H. Zeynalov, E.R. Azerbaijan State Oil and Industry University Azadlyg Avenue 20 BakuAZ1010 Azerbaijan Ministry of Agriculture Baku Azerbaijan Research Laboratory of Intelligent Control and Decision Making Systems in Industry and Economics Azerbaijan State Oil and Industry University 20 Azadlig Baku1010 Azerbaijan

ISBN: (纸本)9783031252518

Delphi method is very frequently used heuristic methods in forecasting and decision making in complex real-world problems, such as economics, business, engineering etc. Main drawback of existing Delphi methods is that they consider experts knowledge as absolutely reliable. In real-life problems experts’ opinions may be partially reliable. In this paper extension of classical Delphi method to bimodal information environment by using Z-number theory is suggested. Main advantage of proposed Z-Delphi method is fact that is based on direct Z-arithmetic to avoid loss of information. Z-Delphi method is illustrated by numerical example. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Number theory

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Fast Parametric Fourier Transform

Fast Parametric Fourier Transform

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2022 international conference on Dynamics and Vibroacoustics of Machines, DVM 2022

作者： Alexey, Ponomarev Olga, Ponomareva Natalia, Smirnova Kalashnikov Izhevsk State Technical University Language Training in Professional Sphere Izhevsk Russia Kalashnikov Izhevsk State Technical University Instruments and Methods of Measurements Control Diagnostics Izhevsk Russia Sevastopol State University Power Systems of Nuclear Power Plants Sevastopol Russia

ISBN: (数字)9781665463140

ISBN: (纸本)9781665463140

The purpose of the study is to the develop new discrete Fourier transform, by generalizing the classical discrete Fourier transform (DFT) in the form of a parametric discrete Fourier transform (DFT-P) and the development of fast algorithms for implementing this type of transform - the fast parametric discrete Fourier transform (FFT-P). The classical Fourier processing of complex vibroacoustic finite discrete signals (VFD signals), based on DFT and fast Fourier transform (FFT) algorithm, is the most powerful method of digital analysis, modeling, optimization, improvement of control and decision making in solving problems of machine dynamics and vibroacoustic. The theoretical basis of the classical Fourier processing of VFD signals is the discrete Fourier transform. The practical base of the classical Fourier processing of VFD signals is the fast Fourier transform algorithms. However, the practice of applying the classical Fourier processing of VFD signals of a complex structure containing both deterministic periodic and random signals, on the one hand, confirming the effectiveness of the classical Fourier processing, on the other hand revealed a number of negative effects inherent in this type of digital signal processing (DSP). The aliasing effect, the scalloping effect, the picket fence effect, significantly negatively affect the effectiveness of analysis, modeling, optimization, improvement of control and decision-making in the study. To improve the efficiency and effectiveness of the Fourier processing of VFD signals, authors of this work developed a generalization of the theoretical basis of the classical Fourier processing - DFT in the form of a parametric DFT (DFT-P). Since the direct application of the parametric Fourier processing of VFD signals (as well as the use of the classical Fourier processing of VFD signals) requires complex multiplications, fast procedures are needed for the practical implementation of this type of VFD signals. We have developed fas

关键词： Discrete Fourier transforms

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A Digital Twin-Driven Guidance Method for Human-Machine Collaborative Assembly Operations Based on Machine Learning and Computer Vision 21

A Digital Twin-Driven Guidance Method for Human-Machine Coll...

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21st international conference on Networking, Sensing and control, ICNSC 2024

作者： Cheng, Dinghao Hu, Bingtao Feng, Yixiong Song, Junjie Wang, Bin Tan, Jianrong Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou China Guizhou University State Keyaboratory of Public Big Data Guiyang China

ISBN: (纸本)9798350365221

Ruman-machine collaborative assembly is commonly used in industrial assembly processes, while the existing assembly guidance methods have fixed processes, complex guidance procedures and low guidance accuracy. Based on this, in order to improve the success rate and quality of assembly, a digital twin-driven human-machine collaborative assembly guidance method system is proposed, and an inverse guidance mechanism for the assembly process is established, which realizes the on-line accurate identification of the parts to be assembled through the improved lightweight YOLO model with Biformer attention mechanism and CARAFE lightweight upsampling operator, and generates the geometric reference features of the parts for the assembly through OpenCV. The effectiveness of the proposed method is verified by taking the assembly process of a bipolar expansion helical cylindrical gear reducer as an example, and the advancement of the proposed method is verified by comparing it with the algorithms of the same type. The experimental results show that the proposed assembly guidance method is easy to implement, low-cost and high accurate, which is of great significance for improving the accuracy and flexibility of the human-machine collaborative assembly process. © 2024 IEEE.

关键词： Inverse problems

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Model-Free H∞Optimal control of Multi-Agent systems with Intermittent Exploration Noise via Adaptive Dynamic Programming

Model-Free H∞Optimal Control of Multi-Agent Systems with In...

引用

complex systems and Intelligent Science (CSIS-IAC), international Annual conference on

作者： Shunwei Hu Yanhong Luo Juan Zhang Fanghua Tang College of Information Science and Engineering Northeastern University Shenyang China

ISBN: (数字)9798331504755

ISBN: (纸本)9798331504762

In this paper, the $H$ ∞ optimal control problem for linear multi-agent systems is studied, and a hierarchical control scheme is designed to reduce the computational complexity. By introducing an additional compensating input indicator, the expected performance indicators are met. The designed output feedback control protocol introduces relaxation parameters, which relax the design requirements of the performance indicators. In addition, by using the idea of adaptive dynamic programming (ADP) at the local level and designing the data set at the collaborative level, the model-free control of the multi-agent system is realized. In the data acquisition phase, intermittent noise detection is used to suppress the system oscillation caused by the introduced external noise. Finally, the effectiveness of the proposed control protocol and algorithm is verified by simulation on the F-16 aircraft model.

关键词： Adaptation models Protocols Heuristic algorithms Computational modeling Atmospheric modeling Noise Dynamic programming Output feedback Oscillators Multi-agent systems

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Anti-interference model of intelligent control for high-precision regulation of pressure in industrial low pressure area based on neural network

Anti-interference model of intelligent control for high-prec...

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2024 international conference on Computer Application and Information Security, ICCAIS 2024

作者： Ren, Yan Wang, Yunjiang Department of Information and Control Engineering Shenyang Institute of Science and Technology Liaoning Shenyang110167 China School of Mechatronics Engineering Shenyang Aerospace University Liaoning Shenyang110136 China

ISBN: (纸本)9781510689312

As science and technology progress, the traditional pressure regulation system is being phased out, and researchers today are focusing on the study of higher precision regulation systems as a crucial task. However, there are still problems with pressure regulation in low pressure areas. In this regard, a high-precision regulation model for low-pressure zone pressure based on neural networks is proposed, which applies the neural system to pressure regulation in low-pressure zones to achieve the purpose of high-precision regulation. Neural network is a computing model that imitates the structure and function of the human brain. It can achieve complex nonlinear mapping and intelligent processing by learning large amounts of data. Applying the nervous system to the field of pressure regulation can adaptively learn the load characteristics of the pressure system, thereby improving the accuracy and stability of load prediction. Real-time monitoring and fault diagnosis can also be performed on the operating status of the pressure system, thereby improving the reliability and safety of the system. And optimize and adjust the control strategy of the pressure system, so as to improve the efficiency and energy saving of the system. Based on this, this paper proposes to combine BP algorithm and particle swarm optimization algorithm to obtain PSOB model. stability. And it can adaptively adjust network parameters and control strategies, adapt to different working conditions and environmental disturbances, and improve control flexibility and intelligence. Historical data and real-time data can also be used for learning and updating to improve control accuracy and prediction capabilities. © The Authors.

关键词： Particle swarm optimization (PSO)

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