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11th international conference on Vehicle Technology and intelligent Transport systems, VEHITS 2025

作者： Ma, Bocheng Zhu, Yang Su, Hongye College of Control Science and Engineering Zhejiang University Zhejiang Hangzhou China

ISBN: (纸本)9789897587450

This paper presents a longitudinal and lateral coupling control model for platoons on roads with varying curvature. The model integrates a 3-DOF vehicle dynamic model with lateral distance errors using the Frenet coordinate system and employs a distributed predictive controller. This approach ensures that vehicles within the platoon maintain ideal inter-vehicle distances, follow the leader’s speed, and remain within their lanes, effectively addressing the "cutting-corner" issue. Joint simulations using Carsim and Matlab demonstrate that the model effectively maintains ideal inter-vehicle distances and tracks the leader’s speed, even with changes in the leader’s velocity. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Predictive control systems

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UDS for Data Communication in Temperature Monitoring 3rd

UDS for Data Communication in Temperature Monitoring

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3rd international conference on intelligent computing Techniques for Smart Energy systems, ICTSES 2023

作者： Mallikarjun, B.C. Prathima, H.S. Department of ETE Siddaganga Institute of Technology Karnataka Tumkur India

ISBN: (纸本)9789819784288

Electronic control units (ECUs) are computer systems which are capable to process this data and send signals to the various systems in the vehicle to modify their behavior in order to optimize performance and ensure safety. Maintaining appropriate operating temperatures within ECUs is essential for preventing overheating, which can lead to system malfunction or failure. Overheating can cause the components of an ECU to degrade over time, leading to decreased performance, increased energy consumption, and potential system failure. This proposed work provides a temperature monitoring solution, i.e., Unified Diagnostic Service (UDS), that enhances the overall functionality of ECUs and contributes to vehicle safety and performance. The temperature monitoring solution would enable the ECUs to measure and monitor the temperature of the vehicles components and systems, which would help to reduce the risk of malfunctions and overheating, which can lead to catastrophic failures and safety risks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Catastrophic Electronic control units Temperature monitoring

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Integrating 5G into VANETs: Methodological Approaches and Performance Evaluation Through Simulation 11

Integrating 5G into VANETs: Methodological Approaches and Pe...

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11th international conference on Vehicle Technology and intelligent Transport systems, VEHITS 2025

作者： Omheni, Nouri Sboui, Mazen Zarai, Faouzi NTS’Com Research Unit National School of Electronics and Telecommunications of Sfax University of Sfax Tunisia

ISBN: (纸本)9789897587450

The integration of 5G technology with Vehicular Ad-hoc Networks (VANETs) represents a significant advancement in the field of intelligent Transportation systems (ITS). This paper explores the potential of 5G to enhance real-time communication between vehicles and infrastructure, aiming to improve road safety and traffic management. Using simulation tools such as OMNeT++ and SUMO, various traffic scenarios were modeled to assess the performance of the integrated 5G-VANET system. Key performance indicators including end to end latency, packet loss, and node acceleration behaviour were evaluated. The results indicate that the integration of 5G reduces communication latency to below 10 milliseconds and achieves packet delivery rates exceeding 95% in high-density traffic situations. This study demonstrates the feasibility of 5G-enhanced VANETs, highlighting their potential to contribute to safer and smarter transportation systems. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Highway traffic control

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Real-Time Object Detection for an intelligent Retail Checkout System 3

Real-Time Object Detection for an Intelligent Retail Checkou...

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3rd international conference on intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Vaneeta, M. Mugada, Swathi Patil, Prachi Bhausaheb Preethi, V.J. Deeksha, K. M.S.Ramaiah Institute of Technology Department of Artificial Intelligence & Data Science Bangalore India

ISBN: (纸本)9798331515911

Customers are made to wait for extended hours in busy shopping settings as traditional limits of barcode and RFID-based billing systems have a predisposition towards errors and inefficiencies in scanning untagged or weighted items. The methods that are in use today can't keep up with the demand and lead to queues at check-out counters causing customer discontentment. This paper presents an idea of a novel Smart Billing Counter, based on Object Detection using advanced deep learning, YOLOv8, and OCR technologies for smooth billing processes. It captures the image of items placed at the counter, identifies what it is with minimal error, extracts necessary information from labels concerning weighted items, and generates a bill automatically. The unique capability of this solution is to recognize identical items in one frame with total cost by quantity to optimize checkout times and minimize the possibility of errors or fraud. At an inference speed of 37.2ms per image with 93.6% accuracy, this significantly enhances operational efficiency and ensures that grocery retailers provide their customers with smooth, error-free, and swift checkout processes. This innovation is likely, therefore, to bring about a transformation in retail billing systems. It will enhance customer satisfaction and operations efficiency quite highly. © 2025 IEEE.

关键词： Sales

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IoT - Enabled intelligent Power Monitoring and control for Grid-Integrated Solar Power in Domestic Load

IoT - Enabled Intelligent Power Monitoring and Control for G...

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2025 international conference on intelligent control, computing and Communications, IC3 2025

作者： Yogasathiyan, S. Vinoth, M. Kishore, S. Aravindan, P. Tiruchengode637 215 India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527495

IoT Power Monitoring System for Grid-connected Solar Power systems is designed to improve the performance and reliability of solar panels used in residential homes. The system records the daily energy consumption of the grid by monitoring the energy produced by solar panels, allowing a better understanding of energy production and consumption. A key innovation of the system is the integration of a temperature sensor and an automatic water spraying mechanism to solve the problem of reduced efficiency due to an increase in temperature. When the thermometer detects an increase in temperature above the threshold, the sprinkler is activated to cool the panels, thus maintaining the efficiency of the panels. In addition, to ensure that the system is effective and efficient, a potentiometer is included to measure the actual current produced by the solar panel;this allows real-time monitoring and reporting of power measurements on the Internet of Things. The monitoring system allows home users to track energy production, monitor performance and understand their daily energy usage, enabling management that controls efficiency and electricity quality. Using IoT technology, users can access information about energy production, grid usage and battery panels via online platforms, perform remote monitoring and data analysis. The integration of temperature control now allows solar panels to perform at their best, providing an efficient way to use the sun for home energy needs. © 2025 IEEE.

关键词： Battery management systems

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Two-Stage Deep Energy Optimization in IRS-Assisted UAV-Based Edge computing systems

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IEEE TRANSACTIONS ON MOBILE computing 2025年第1期24卷 449-465页

作者： Wu, Jianqiu Yu, Zhongyi Guo, Jianxiong Tang, Zhiqing Wang, Tian Jia, Weijia BNU HKBU United Int Coll Dept Comp Sci Guangdong Key Lab AI & Multimodal Data Proc Zhuhai 519087 Peoples R China Beijing Normal Univ Adv Inst Nat Sci Zhuhai 519087 Peoples R China

Integrating wireless-powered Mobile Edge computing (MEC) with Unmanned Aerial Vehicles (UAVs) leverages computation offloading services for mobile devices, significantly enhancing the mobility and control of MEC networks. However, current research has not focused on customizing system designs for Terahertz (THz) communication networks. When dealing with THz communication, one must account for blockage vulnerability due to severe THz wave propagation attenuation and insufficient diffraction. The intelligent Reflecting Surface (IRS) can effectively address these limitations in the model, enhancing spectrum efficiency and coverage capabilities while reducing blockage vulnerability in THz networks. In this paper, we introduce an upgraded MEC system that integrates IRS and UAVs into THz communication networks, focusing on a binary offloading policy for studying the computation offloading problem. Our primary objective is to optimize the energy consumption of both UAVs and User Electronic Devices, alongside refining the phase shift of the IRS reflector. The problem is a Mixed Integer Non-Linear Programming problem known as NP-hard. To tackle this challenge, we propose a two-stage deep learning-based optimization framework named Iterative Order-Preserving Policy Optimization (IOPO). Unlike exhaustive search methods, IOPO continually updates offloading decisions through an order-preserving quantization method, thereby accelerating convergence and reducing computational complexity, especially when handling complex problems with extensive solution spaces. The numerical results demonstrate that the proposed algorithm significantly improves energy efficiency and achieves near-optimal performance compared to benchmark methods.

关键词： Terahertz communications Autonomous aerial vehicles Optimization Resource management Servers Computational modeling Costs Mobile edge computing deep learning unmanned aerial vehicles intelligent reflective surface terahertz communications

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Cloud Based Automated control System Workshops and Rooms for controlling Parameters 1

Cloud Based Automated Control System Workshops and Rooms for...

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1st international conference on Advances in Computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Kumar, Dinesh Kuntal, Ravinder Singh Deep, Pragya Chamoli, Anup Shekhar Singh, Pinki Mandal, Rishabh SRM Institute of Science & Technology Department of Computer Science and Engineering UP Ghaziabad India Nitte Meenakshi Institute of Technology Department of Mathematics Karnataka Bangalore India IIMT College of Engineering Department of AI & DS Greater Noida India Uttaranchal School of Computing Sciences Uttaranchal University Dehradun248001 India Accurate College of Engineering & Management Department of Computer Science and Engineering Greator Noida India Tula's Institute Department of Computer Science and Engineering UK Dehradun India

ISBN: (纸本)9798331518578

Across all industries, cloud-based automated control systems have completely changed how operational and environmental parameters are tracked and controlled. With cloud-integrated systems for real-time data collection, processing, and control, this concept presents intelligent, remote-controlled workshops and control rooms. To guarantee accurate control of crucial variables like temperature, humidity, pressure, and equipment efficiency, these systems make use of IoT devices, AI techniques, and big data analytics. Through sophisticated data perspectives, the cloud-based strategy enables predictive maintenance, improves flexibility, and lowers operating expenses. Stakeholders may make prompt, data-driven choices from anywhere with remote access to control rooms. These seminars provide practical experience with cloud-controlled settings and function as training and development centres. The system's flexibility to meet a range of industrial demands is further enhanced by its compatibility with external tools and equipment. The design, deployment, and possible uses of cloud-based control systems are covered in this paper, with an emphasis on how they might promote operational excellence, energy efficiency, and smart manufacturing. © 2025 IEEE.

关键词： Smart manufacturing

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Research on Low Carbon Energy Integration and intelligent Heating control in Urban Heating Networks

Research on Low Carbon Energy Integration and Intelligent He...

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2024 international conference on Mechatronics and intelligent control, ICMIC 2024

作者： Wang, Guangming School of Management Wuhan University of Technology Wuhan430070 China School of Politics and Public Administration Zhengzhou University Zhengzhou450001 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Energy security, environmental issues, and economic issues are the driving factors for studying the reduction of energy consumption and greenhouse gas emissions. To solve the problems of urban centralized heating systems, this article designs and implements an intelligent monitoring system based on the current mainstream Internet of Things communication technology NB IoT. The monitoring system can maintain device information in the cloud platform and monitor energy consumption in real-time. Management personnel can issue device control instructions through the monitoring system. On this basis, we designed an RBF neural network prediction model to predict the water supply temperature of the secondary network, achieving closed-loop control of the water supply temperature of the secondary network. Through simulation experiments on the established predictive model and control algorithm, the results show that the adopted control algorithm can effectively control the system model due to changes in amplification factor and time constant compared to conventional PID control, verifying the feasibility and effectiveness of the adopted control method. © 2025 SPIE.

关键词： Photons

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Secure Intelligence Development Lifecycle (SIDL) Model for Vulnerability Detection 4th

Secure Intelligence Development Lifecycle (SIDL) Model for V...

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4th international conference on Advanced Network Technologies and intelligent computing-ANTIC-Annual

作者： Dhanush, V. Chandra, T. Sarath Divakarla, Usha Chandrasekaran, K. Natl Inst Technol Karnataka Surathkal CSE Dept Mangalore India NITTE NMAMIT ISE Dept Mangalore India

ISBN: (纸本)9783031837890;9783031837906

This paper presents the Secure Intelligence Development Life-Cycle, a Software Development Life-Cycle created to address the need for advanced security and intelligent technologies, such as artificial intelligence and machine learning, at the development level. It differs from standard software development models that usually involve security measures only in the later stages of development;this one integrates security measures right from the early stage of requirements gathering through design, development, and deployment. The embedding of security from the onset allows real-time vulnerability detection and response with adaptability to emerging threats. It has also improved threat detection, made better decisions, and enhanced system resilience with intelligent processes. It is most effective with sectors like healthcare, finance, and critical infrastructure for secure and complex software systems.

关键词： Secure Intelligence Development Lifecycle (SIDL) SDLC intelligent systems AI Security Vulnerability Detection

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19th international conference on Soft computing Models in Industrial and Environmental Applications, SOCO 2024

19th International Conference on Soft Computing Models in In...

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19th international conference on Soft computing Models in Industrial and Environmental Applications, SOCO 2024

ISBN: (纸本)9783031750090

The proceedings contain 61 papers. The special focus in this conference is on Soft computing Models in Industrial and Environmental Applications. The topics include: Improving the Efficiency of Production Processes by Reducing Human Errors Using intelligent Methods;automated Semantic Labelling of Images Generated with Deep Diffusion Probabilistic Models;wastewater Quality Indicator Estimation Using Machine Learning and Data Augmentation Techniques;a Virtual Avatar for Sign Language Signing;comparison of D-Wave Quantum computing Environment Solvers for a Two-Machine Jobs Scheduling Problem;hybrid Fuzzy-Based Method for Optimally Selecting Aircraft for Low-Cost Carriers Operating Medium-Haul Flights;two Way Ranging Positioning Methods Analysis Under Optimized Sensor Deployments;human Acoustic Events Detection as Anomalies in Industrial Environments Using Shallow Unsupervised Techniques;Machine Learning in the Last-Mile Delivery: Modified Q-Learning for the TSP;IoT and AI Based Security System – Design and Implementation;characterization of Cattle Behavior Based on Dimensional Reduction Techniques;time Series Forecasting in Agriculture: Explainable Deep Learning with Lagged Feature Selection;artificial Intelligence Methodology for Run-to-Target Manufacturing;multi-robot Path Planning Problem Applied to Real World Enviroment;an Approach of Optimization in Capacitated Vehicle Routing Problem in Logistics Distribution;bayesian Generation of Synthetic Data;learning-Based Models for intelligent control Over Air Conditioning Units in a Smart Building;predicting Power Generation from Photovoltaic Energy System;photovoltaic Generation Forecasting for intelligent Management in Energy Communities;application of Neural Models in Solar Radiation Measurements for a Better Data Gathering Quality;caravels: A Decentralized Container-Based Infrastructure for Sustainable Human-Centric intelligent Energy Communities;Production Scheduling for Energy Cost Optimization with Constraints: Com

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