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共 34963 条记录，以下是161-170 订阅

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TrackNCount - intelligent Vehicle Tracking, Counting, and Speed Estimation using YOLOv8 and DeepSORT Algorithms 6

TrackNCount - Intelligent Vehicle Tracking, Counting, and Sp...

引用

6th international conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Sathiyaprasad, B. Reddy, Paluru Ambareesh Ram Venkatesh, Digumalla Manisri Department of Computer Science and Engineering Sathyabama institute of science and technology Chennai India

ISBN: (纸本)9798331522667

For effective city planning and traffic control, it is now crucial to develop some effective monitoring systems for vehicle traffic in order to address this quickly growing tendency within a city. As a result, the TrackNCount project combines DeepSORT with YOLOv8 for object identification to create a smart system for tracking, counting, and speed estimation of vehicles. The idea behind this design is to use sophisticated computer vision techniques in conjunction with efficient algorithms to handle real-world scenarios. Setting up a reliable procedure that recognizes cars, gives them distinct IDs, and records their movements through video frames is our first priority. The system computes vehicle speeds using the Euclidean distance formula, manages item trajectories using double-ended queues, and detects entering and outgoing vehicles based on directional thresholds. Motion trails and bounding boxes are two further visual aids that improve the results' readability. With the added benefit of simple speed estimation feature integration, the model provides exceptional accuracy in real-time vehicle monitoring and counting. Experiments conducted on a variety of traffic scenarios consistently showed that this system can deliver precise vehicle counts in designated directions and speed calculations with a small margin of error. The findings show that TrackNCount is a viable and scalable solution for data-driven city planning and intelligent traffic management. © 2025 ieee.

关键词： Street traffic control

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Delay-Tolerant for Stablity Second-Order Stochastic systems with Multiplicative Noises

Delay-Tolerant for Stablity Second-Order Stochastic Systems ...

引用

ieee international conference on Industrial technology (ICIT)

作者： Dongyuan Yu Xiaofeng Zong School of Automation China University of Geosciences Wuhan China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

In this paper, a second-order stochastic multiagents system is investigated, a consensus control strategy is proposed, and a stable delay tolerance range for distributed system is established. The control strategy consider the multiplicative noises associated with the measurement information between the agents as well as the communication delay. First, the communication information between the agents with multiplicative noises and their internal topology are analyzed, and a consensus controller is designed. Then by Lyapunov direction method and Ito formula, we get the consensus condition of multi-intelligent system. And based on this condition, we study the delay tolerance problem of this system and find a stable delay bound to realize almost sure and mean square exponential stability within the delay tolerance.

关键词： Asymptotic stability Stochastic systems Noise Stability analysis Delays control theory Topology Noise measurement Nonlinear systems Multi-agent systems

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intelligent Robotic Assistance in Precision Surgery: Vision, automation, and Human-Robot Collaboration

Intelligent Robotic Assistance in Precision Surgery: Vision,...

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international conference on Computational cybernetics (ICCC)

作者： Chee-Kong Chui Department of Mechanical Engineering National University of Singapore

ISBN: (数字)9798331502461

ISBN: (纸本)9798331502478

Surgical robotics has revolutionized modern medicine, enhancing precision, safety, and efficiency in complex procedures. However, many surgical fields, including ophthalmology, continue to rely heavily on manual techniques, demanding exceptional dexterity, coordination, and sustained focus from surgeons. The next frontier in robotic surgery lies in intelligent systems that integrate real-time perception, automation, and human-robot collaboration to enhance surgical outcomes while reducing surgeon workload. This talk presents an overview of our research on intelligent robotic assistance for precision surgery, with a focus on vision-based robotic systems for ophthalmic and microsurgical procedures. One of our key innovations is an intelligent vision-based robotic-assisted system for vitreoretinal surgery, which enhances intraoperative safety through real-time scene understanding, automates surgical lighting to improve visualization, and records surgical actions for skill assessment and training. Beyond ophthalmology, our work extends to developing AI-driven robotic systems for other surgical applications, enabling autonomous assistance in delicate operations where precision and real-time decision-making are critical. By integrating computer vision, machine learning, and robotic automation, our research aims to push the boundaries of robotic surgery, making procedures safer, more efficient, and accessible to a broader range of surgeons. This talk will explore the challenges and breakthroughs in intelligent surgical robotics, the role of AI in enhancing human dexterity, and the future of robotic-assisted surgery in various medical domains.

关键词： Visualization automation Medical robotics Robot kinematics Surgery Human-robot interaction Real-time systems Safety Ophthalmology Robots

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Delay-Tolerant for Stablity Second-Order Stochastic systems with Multiplicative Noises

Delay-Tolerant for Stablity Second-Order Stochastic Systems ...

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26th international conference on Industrial technology, ICIT 2025

作者： Yu, Dongyuan Zong, Xiaofeng School of Automation China University of Geosciences Wuhan430074 China

ISBN: (纸本)9798331521950

关键词： Distributed parameter control systems

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PID controller Design for a Mechatronic System using Lion Optimization Algorithm 5

PID Controller Design for a Mechatronic System using Lion Op...

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5th National and the 1st international conference on Applied Research in Electrical Engineering, AREE 2025

作者： Safdari, Amirhossein Mansouri, Amirhosein Fazli, Mohammad Javad Zarafshan, Payam Alipour, Khalil Tarvirdizadeh, Bahram College of Interdisciplinary Science and Technology University of Tehran School of Intelligent Systems Department of Mechatronics Engineering Tehran Iran Shahid Beheshti University Faculty of Mechanical and Energy Engineering Department of Renewable Energy Engineering Tehran Iran University of Tehran School of Mechanical Engineering College of Engineering Tehran Iran Western Sydney University School of Engineering Design and Built Environment Sydney Australia

ISBN: (纸本)9798350377170

controllers act as a bridge between the operator and the system, allowing the operator to communicate with the system as if it were a human. In other words, the controller is like the thinking brain of an industrial process. A controller communicates all the commands that an expert wants to apply to the system to follow its standard flow process and ultimately achieve the desired response. When industrial processes are left alone and without a controller in the control loop, they typically do not give satisfactory responses in terms of transient or steady-state characteristics. Therefore, the selection and programming of an appropriate controller is one of the most important steps in an industrial process. One of the most widely used and well-known controllers is the PID controller, whose gains are often determined experimentally or through trial and error. However, finding the optimal gains is always a challenge. In this study, for the first time, the optimal gains of the PID controller are determined using Lion Optimization Algorithm (LOA). This research has introduced a systematic and efficient approach to achieving optimal control of mechatronic systems. © 2025 ieee.

关键词： Three term control systems

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Improving Traffic Sign Recognition with the YOLOv9 Algorithm 2

Improving Traffic Sign Recognition with the YOLOv9 Algorithm

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2nd international conference on Computational Intelligence, Communication technology and Networking, CICTN 2025

作者： Anand, Ketan Dwivedi, Shyam Shankar Department of Computer Science and Engineering Rameshwaram Institute of Technology & Management AKTU Lucknow India

ISBN: (纸本)9798331530389

Modern intelligent transportation systems and autonomous driving technologies are quite helpful in light of the population's increasing growth, and they work particularly well when used in conjunction with traffic sign monitoring. By giving drivers accurate and exact traffic signals, such as speed limits, warnings, and directional assistance, this makes transportation much safer. Autonomous vehicles must correctly understand these indicators in order to make wise driving judgments. Accurately identifying and classifying a wide variety of traffic signs in a range of environmental circumstances is a difficulty. A cutting-edge deep learning model created specifically for object recognition tasks is called YOLOv9 (You Only Look Once version 9).In addition to offering respectable speed and accuracy, YOLOv9 expands on the advantages of its predecessors by implementing cutting-edge strategies such as PGI and *** of these improvements, YOLOv9 is especially ideal for real-time applications like recognition of traffic signs, where more accuracy and quick and accurate object identification are essential. With an increased accuracy the results demonstrate the model's stability and dependability and show that it is appropriate for real-world uses in autonomous driving and traffic control. Subsequent investigations will concentrate on improving resilience in various situations, utilizing semi-supervised learning, creating more resource-efficient models, broadening the range of datasets, and combining traffic sign recognition with additional autonomous driving tasks. The development of dependable and effective traffic sign detection systems is furthered by this work. © 2025 ieee.

关键词： Traffic signs

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Real-Time Environmental Monitoring and control Using cyber-Physical systems: A Case Study in Agriculture

Real-Time Environmental Monitoring and Control Using Cyber-P...

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3rd ieee international conference on automation and Computation, AUTOCOM 2025

作者： Yadav, Dhananjay Kumar Kumar, Amit Devi, Suprava Mishra, Abhinav Venkadeshwaran, K. Reddy, V. Venkata Ramesh Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Punjab Rajpura140417 India Department of Computer Science and Engineering Odisha Bhubaneswar India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh Baddi174103 India Karnataka Bangalore India Presidency University Sponsored Research Karnataka Bangalore India

ISBN: (纸本)9798331542375

Due to its nature, real-time environmental monitoring and control is an indispensable part of modern agriculture. At its core, it is the ongoing collection, analysis, and application of ecological data to improve crop yields while conserving resources and minimizing expenditures. This article proposes that cyber-physical systems are an effective organization that provides a building structure where real-time monitoring and control can be provided across different processes within agriculture. Here, we report on a detailed case study of the application of CPS as discussed for environmental monitoring and control in agriculture. This paper reviews the dominant components of CPS sensors, actuators, and communication systems and data analytics. Together, these elements help us to gather real-time data on critical environmental variables like temperature, humidity, soil moisture and nutrient levels. The algorithm analyzes the data and provides farmers with insights. With the help of CPS, farmers can automate and remotely monitor essential processes like watering, fertilization, pest control, etc., increasing efficiency while decreasing labor costs. Another benefit of CPS is that it makes accurate decisions in a timely manner using real-time data, which can yield better crops and be more effective in resource utilization. © 2025 ieee.

关键词： Crops

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intelligent IoT System for Irrigation and Water Management 5th

Intelligent IoT System for Irrigation and Water Management

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5th international conference on Computing, Communications, and cyber Security, IC4S 2023

作者： Chaudhari, Swapnil Warke, Rutuja Pungaonkar, Shreya Shivudkar, Atharvaraj Gurav, Uma Chanchal, Amit KIT’s College of Engineering Kolhapur India

ISBN: (纸本)9789819773701

Water is one of the most crucial aspects of one’s life and as the population is increasing drastically, the need for water is also increasing. However freshwater resources are scarce, and freshwater is the main component for irrigation. As the technology is growing rapidly the agriculture sector needs to use advanced irrigation systems. This study addresses the water control project by exploring the combination of Artificial Intelligence, Machine Learning, and the Internet of Things. Drip irrigation, a key generation in water conservation, ensures managed water release to plant roots. However, traditional methods fall short in optimizing water use, necessitating the utility of device studying for sensible irrigation. By the use of the Kaggle dataset Irrigation *** comprising soil moisture, temperature, altitude, etc. The observations of this paper employ four ML models—LR, Naive Bayes, SVM, and XGBoost. This model is evaluated based on accuracy scores;results exhibit the effectiveness of XGBoost which emerges as the top-performing model with a perfect accuracy of 0.9979. This comparative evaluation presents treasured insights, setting up a basis for the mixing of devices and gaining knowledge of enhancing irrigation structures. The research contributes to sustainable water useful resource control in agriculture, important for addressing the worldwide project of water shortage. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Soil moisture

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From Legacy to intelligent IIoT systems: automation, Scalability and Elasticity

From Legacy to Intelligent IIoT Systems: Automation, Scalabi...

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Working ieee/IFIP conference on Software Architecture

作者： Gianluca Caiazza Teodors Lisovenko Pietro Ferrara Fabio Berti Francesca Ferrari Alessandro Zaupa Guangzheng Zhang Ca’ Foscari University Venice Italy Zamperla Vicenza Italy

ISBN: (数字)9798331520908

ISBN: (纸本)9798331520915

The Internet of Things (IoT) revolution is reshaping how physical devices embedded with software connect to the Internet, facilitating seamless data exchange and driving automation. Industrial IoT (IIoT) extends these capabilities to industrial devices and cyber-Physical systems (CPS), driving intelligent Manufacturing. This integration supports advanced applications like remote monitoring, predictive maintenance, machine learning (ML), and artificial intelligence (AI) optimization, enhancing production efficiency, adaptability, and decisionmaking. However, managing the vast amounts of data generated requires scalable, automated software architectures. Many small and medium-sized enterprises (SME) face challenges in building such systems due to limited resources and expertise, often starting with manual data collection and basic *** paper presents a solution: a fully automated, configurable, and scalable software architecture for intelligent Manufacturing. Our system has been operational for almost one and a half years on 21 plants, processing about 17K tasks, amounting to more than three months of computations. The experimental results show that automation and elasticity have been needed by such systems since the beginning, while scalability is not required during an initial experimentation phase.

关键词： automation Software architecture Scalability Computer architecture Production Manuals Elasticity Software Manufacturing Industrial Internet of Things

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VibeGait: Enhancing Structural-Vibration based Gait Recognition using Vision

VibeGait: Enhancing Structural-Vibration based Gait Recognit...

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2025 ieee international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Chakraborty, Mainak Chandan Mukhopadhyay, Bodhibrata Anchal, Sahil Kar, Subrat Indian Institute of Technology Delhi Delhi India Indian Institute of Technology Roorkee Roorkee India

ISBN: (纸本)9798350368741

Structural vibration-based gait recognition has emerged as a promising soft-biometric modality, particularly for privacy-sensitive monitoring and access control. Despite its potential, current research is largely limited to proof-of-concept studies that rely on hand-crafted features, with minimal exploration of deep learning methodologies. This gap reduces the potential for integrating structural vibration-based gait recognition with existing modalities, such as camera-based systems. In this study, we propose a multi-modal gait recognition system that integrates both vision and structural vibration modalities. We address two key challenges: (a) lack of studies exploring outdoor gait recognition using both vision and structural vibration, and (b) absence of a multi-modal training scheme that combines these two modalities. To tackle the first challenge, we curated a dataset comprising five minutes of walking data from ten individuals captured simultaneously by two cameras and a geophone sensor. To address the second challenge, we developed a joint training framework that uses data from both modalities. Our methods achieve an accuracy of 96.03% (±1.12) using structural vibration signals alone, and this improves to 98.27% (±0.06) when both modalities are combined. © 2025 ieee.

关键词： Multi-Modal Person Identification Soft-biometrics Structural Vibration

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