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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68829 条记录，以下是821-830 订阅

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Partial-Node-Based State Estimation for Complex Networks With Energy Harvesting Sensors 28

Partial-Node-Based State Estimation for Complex Networks Wit...

引用

28th international conference on automation and Computing, ICAC 2023

作者： Wang, Yu-Ang Wang, Zidong Wang, Fan Zou, Lei College of Information Science and Technology Donghua University Shanghai201620 China Brunel University London Department of Computer Science Middlesex UxbridgeUB8 3PH United Kingdom University of Duisburg-Essen Duisburg47057 Germany

ISBN: (纸本)9798350335859

In this paper, the recursive partial-node-based (PN-B) state estimation problem is investigated for a class of time-varying complex networks (CNs) with energy harvesting sensors (EHSs). Measurements are transmitted to the remote state estimator by the EHSs only when the current energy level can compensate for the energy consumption. Only a part of the network nodes' measurements, which are available to the users, are utilized to estimate the network states. The objective of this problem is to design a recursive state estimator for CNs with EHSs based on available measurements observed from partial nodes. The upper bound of the estimation error covariance is first established with the help of intensive scholastic techniques and induction approach. Then, the required estimator gain is determined by minimizing such an upper bound. Finally, an illustrative example is presented to verify the effectiveness of the proposed PNB state estimation method. © 2023 IEEE.

关键词： State estimation

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A Survey on Green IoT and Its Opportunities for Future Directions

A Survey on Green IoT and Its Opportunities for Future Direc...

引用

2023 international conference on Advanced Computing and Communication Technologies, ICACCTech 2023

作者： Upadhye, Sachin Shelke, Nilesh Thakur, Uma Patel Shri Ramdeobaba College of Engineering and Management Department of Computer Application Nagpur India Symbiosis Institute of Technology Nagpur Campus Symbiosis International Deemed University Pune India Jhulelal Institute of Technology Department of Computer Science and Engineering Nagpur India

ISBN: (纸本)9798350380880

The Internet of Things (IoT) has changed the way technology has evolved, integrating it with other aspects such as home appliances for home automation, smart city projects, e-waste management, and many more. But with the increase in the usage of IoT, there are several challenges that come along, like an increase in energy consumption. Due to this, the Green IoT comes into play. It looks for alternative solutions to the present style of implementing IoT technology, which leads to eco-friendly, sustainable, and cost-effective solutions. This survey points towards effective ways of implementing the IoT for eco-friendly, sustainable, and cost-effective management. The Internet of Things (IoT) has transformed the way technology is integrated into various aspects of life, including home automation, smart city projects, and e-waste management. However, the increasing usage of IoT technology has led to challenges, such as higher energy consumption. This has given rise to Green IoT, which seeks alternative solutions for implementing eco-friendly, sustainable, and cost-effective IoT technology. This survey focuses on effective ways to implement IoT technology for sustainable and eco-friendly cost management. It also explores the potential of IoT technology in new areas, its future sustainability, and its challenges. The adoption of green IoT practices can reduce pollution hazards, traffic waste, and energy consumption while enhancing public safety and quality of life. To create sustainable and eco-friendly cities, researchers, policymakers, and industry leaders must collaborate to address IoT implementation challenges. The survey concludes by highlighting opportunities for future research and innovation in this field. © 2023 IEEE.

关键词： Internet of things

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Cofee Quality Prediction Using Machine Learning

Cofee Quality Prediction Using Machine Learning

引用

2023 international conference on System, Computation, automation and Networking, ICSCAN 2023

作者： Rajbharath, R. Vijayamalaiya, S. Aabid, M. Salilan, Amal Manakula Vinayagar Institute of Technology Department of Computer Science Puducherry605107 India Manakula Vinayagar Institute of Technology Final Year Department of Computer Science and Engineering Puducherry605107 India

ISBN: (纸本)9798350315127

The analysis and modeling of a dataset related to sensory evaluations of coffee quality scores is presented in this report. The report explores various features related to aroma, flavor, aftertaste, acidity, body, balance, uniformity, cleanliness, sweetness, and overall quality of coffee. The report starts with data preprocessing, including handling missing values and encoding categorical variables. The report then drops irrelevant columns and extracts useful information from date columns. For the modeling phase, the report splits the data into training and testing sets and applies feature scaling using the MinMaxScaler to normalize the numeric features. The report then trains a Linear Regression model and evaluates its performance using mean squared error (MAE) and R- squared score. The model achieved a low MAE of 0.2567 and a high R-squared score of 0. 9476, indicating a good fit to the data. Furthermore, the report compares the performance of various regression models using cross-validation. The models included Linear Regression, Ridge, Lasso, ElasticNet, Decision Tree Regressor, Random Forest Regressor, Gradient Boosting Regressor, Support Vector Regressor (SVR), and MLP Regressor. Finally, the report recommends the best coffee combination based on the analysis. The recommended coffee combination is from Coffee Quality Union, with the variety of Castillo, the country of origin of Colombia, the farm name of Finca El Paraiso, and the processing method of Double Anaerobic Washed. © 2023 IEEE.

关键词： Decision trees

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Real-Time Fire Detection in Unmanned Ground Vehicles Integrating YoloV5 and AWS IoT

Real-Time Fire Detection in Unmanned Ground Vehicles Integra...

引用

2023 international conference on System, Computation, automation and Networking, ICSCAN 2023

作者： Banerjee, Saptajit Das, Ronodeep Rathinam, Rajesh Dhanalakshmi, R. School of Computer Science and Engineering Vellore Institute of Technology Chennai India Centre for Cyber Physical Systems School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350315127

This paper aimed at the development of a remotely controllable 4-wheeled unmanned ground vehicle (UGV) capable of transmitting realtime sensor data and live video feeds over the internet. The central innovation lies in the utilization of an advanced object detection model, to detect fires within the live video feed. By leveraging a Raspberry Pi 4 with 2GB RAM, AWS IoT Core, MQTT, HTTP, and TCP protocols, the UGV achieves seamless data exchange. AWS IoT Core serves as both MQTT broker and subscriber, with the UGV as publisher for sensor readings and subscriber for control commands. The web app acts as the publisher for control commands, generating signals based on user input. The Remote. it software plays a pivotal role in facilitating a cloud-based HTTP service for live video streaming, thereby significantly enhancing global accessibility. Moreover, diverse remote operation methods including keyboard, onscreen, and speech controls, provide flexible means for user interaction. The integration of YOLOv5, Tensorflow, and OpenCV yields a robust fire detection capability, effectively triggering SMTPbased email alerts. This system effectively showcases the seamless fusion of robotics, IoT, web technologies and machine learning, thereby contributing to safety enhancement and inspiring a wave of future advancements. © 2023 IEEE.

关键词： Web services

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A Gesture Recognition and Drone Control System based on Residual Neural Network 20

A Gesture Recognition and Drone Control System based on Resi...

引用

20th IEEE international conference on Mechatronics and automation, ICMA 2023

作者： Wang, Rui Sun, Chengjiao Hubei University of Arts and Science School of Computer Engineering 296 Longzhong Road Hubei Xiangyang China

ISBN: (纸本)9798350320831

To achieve visual communication between Drone and operator, a static gesture recognition and Drone control system based on residual neural network is designed. The system segments static gestures through YCrCb colour space and elliptical skin colour detection model, extracts gesture features using the residual neural network ResNet34 and uses deep learning techniques to realise the combination of gesture recognition and UAV control. The system uses the gesture images taken from the UAV viewpoint as the dataset and will send the corresponding control signals to the UAV side according to the calibrated control commands to achieve stable control of the UAV, and the classification accuracy is used as an evaluation index to assess the performance of the model of this system in gesture recognition. Finally, the control performance of the system was verified in a real flight in a Tello vehicle platform, and the experimental results showed that the average accuracy rate could reach 90.43%. © 2023 IEEE.

关键词： Deep learning

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Exploring ChatGPT in Network Management and Monitoring: Benefits and Challenges 2

Exploring ChatGPT in Network Management and Monitoring: Bene...

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2nd international conference on Information and Communication technology for Sustainable Development, ICICT4SD 2023

作者： Islam, Muhammad Nazrul Fahim, F.M. Shafiullah Akash, Pritidhrita Paul Arifeen, Kazi Afsana Nahian, Naila Baki, Ramisha Fariha Military Institute of Science and Technology Department of Computer Science and Engineering Dhaka1216 Bangladesh Bangladesh University of Professionals Department of Information Communication Technology Dhaka Bangladesh

ISBN: (纸本)9798350358667

ChatGPT is an AI-based natural language model that has made a significant impact across various technological domains, including software development, network management, and the like. Network monitoring is one of the critical tasks in network management to ensure the proper and safe functioning of the entire network. The primary objective of this research is to explore the potential benefits and challenges associated with using ChatGPT in network management and monitoring. As an outcome, this research has highlighted that ChatGPT offers diverse functionalities in networking, including automation of operations and easy code generation, enabling instant feedback to enhance the quality and accessibility of network management tasks. However, the study also acknowledges the challenges inherent in using ChatGPT. Biased output is identified as a concern that could potentially impact response accuracy and fairness. Additionally, the possibility of errors in the generated output can undermine system reliability and effectiveness. While ChatGPT demonstrates the ability to simulate human-like conversations, it is important to address these challenges promptly for responsible and effective utilization in the domain of computer network. © 2023 IEEE.

关键词： Network management

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Research on modular charging systems based on digital twins 3

Research on modular charging systems based on digital twins

引用

3rd IEEE international conference on Power, Electronics and computer Applications, ICPECA 2023

作者： Dong, Qicheng Xu, Zhigang Wang, Junyi Yang, Xiao Fan, Linlin Li, Wei Shenyang Aerospace University College of Mechanical and Electrical Engineering Shenyang China Chinese Academy of Sciences Institute of Robotics and Intelligent Manufacturing Innovation Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Northwestern Industries Group Co. Ltd Xi'an China

ISBN: (纸本)9781665472784

The development of ammunition loading technology plays a vital role in the improvement of my country's national defense construction level. Compared with the traditional charge, the modular charge has the advantages of high interchangeability and modularity, and can realize the rapid filling of the charge. However, for the application of modular charging technology, when building unit modules, it is still necessary to manually teach the charging target point, and the modular charging technology has the disadvantage of being difficult to adapt to flexibility. Therefore, in the face of the diversity of ammunition, modular charge is not conducive to the rapid and efficient production of ammunition. The current automation technology is difficult to improve the flexible adaptability of modular charge. Aiming at the disadvantages of modular charging technology, a modular flexible charging system based on digital twin is proposed, including the construction of virtual charging workstation, key point identification, automatic trajectory generation and automatic robot program generation. The system greatly improves the production efficiency of modular charge, provides a reference for the research of modular flexible charge, and improves the digital manufacturing level of ammunition production. © 2023 IEEE.

关键词： Industrial research

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Automated Evaluation System for Pull-Up Exercises in Physical Fitness Testing Scenarios 3

Automated Evaluation System for Pull-Up Exercises in Physica...

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3rd international conference on Information technology and Contemporary Sports, TCS 2023

作者： Liu, Ze Gao, Fei Song, Kangkang Xiao, Jiangjian Zhejiang University of Technology Mechanical Engineering College Hangzhou China The Institute of Advanced Manufacturing Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo China

ISBN: (纸本)9798350393934

With the cross-fusion development of artificial intelligence and computer vision in various fields, different industries are incorporating computer vision technology to achieve intelligence and automation. Especially in large-scale scenario tasks, unsupervised approaches can reduce labor and time costs. Physical fitness testing, as a necessary assessment subject for physical fitness, involves a large number of personnel and a relatively scarce number of professional instructors. This not only results in high manpower and time costs but also renders the assessment task meaningless without professional evaluation. In this context, this paper presents an intelligent analysis system based on computer vision that uses the pull-up exercise in physical fitness activities as an example. By utilizing the body pose coordinates feedback from pose estimation, combined with the proposed graph convolutional action evaluation network, the system can achieve segmentation of continuous actions and quality evaluation of segmented sub-actions. The test results demonstrate a high correlation between the proposed method's evaluation and the results given by professionals. This system can also be applied to intelligent analysis tasks in other physical fitness exercises. © 2023 IEEE.

关键词： computer vision

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Application of association rule algorithm in intelligent manufacturing of mechanical manufacturing and automation specialty

Application of association rule algorithm in intelligent man...

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2022 international conference on computer Application and Information Security, ICCAIS 2022

作者： Shi, Jia Zhao, Jia Liu, Fengbo Liaoning Agricultural Technical College Liaoning Yingkou115009 China Shenyang University of Technology Liaoning Shenyang110870 China

ISBN: (纸本)9781510663459

Due to the maturity of database technology and the increase of data applications, the total amount of data stored by people has increased exponentially. Due to the rapid increase of the total amount of information, once there is no reasonable way to obtain useful information and knowledge in computer and information technology, network information will become a mess. Faced with this challenge, data mining technology came into being. This paper studies the application of association rule algorithm in intelligent manufacturing of mechanical manufacturing and automation majors. The management system is designed, and the association rule algorithm applied in the design is tested. Through the test results, it is concluded that the running time of the improved algorithm is much shorter than that of the Aprior algorithm, and the difference of the total time will also vary with the newly added data. The number of episodes increases and becomes larger. Therefore, in some fields where the database needs to be updated frequently, the IUAC algorithm shows obvious advantages. © 2023 SPIE.

关键词： Data mining

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Collaborating the AI With IoT to Develop Cyber-Physical System to Estimate the Quality of Metal Casting by Using R Programming

Collaborating the AI With IoT to Develop Cyber-Physical Syst...

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2023 international conference on New Frontiers in Communication, automation, Management and Security, ICCAMS 2023

作者： Deepa, R. Kaur, Chamandeep Kapila, Dhiraj Singh, Pavitar Parkash Munagala, Madhu R.M.K. Engineering College Department of Computer Science and Engineering Taluk Gummidipoondi India Jazan University Department of Computer Science and Information Technology Jazan Saudi Arabia Lovely Professional University Department of Computer Science & Engineering Phagwara India Koneru Lakshmaiah Education Foundation Department of English Vaddeswaram India

ISBN: (纸本)9798350317060

Significant time and money savings may be realised if it were possible to foresee internal faults in metal casting immediately after the casting process. As was discussed before, the goal is achieved by the allocation of fewer resources to later phases like machining and the provision of adaptable scheduling. CPPS is accurate in meeting the standards above. This study explores CPPS (Cyber-Physical Production Systems) in a real-world manufacturing setting for quality prediction of metal castings and process control. The framework was first designed for use in the CPPS architecture of metal casting manufacturing, where it would aid in quality forecasting and operational *** framework explains how different types of technology, and simulations to improve teamwork. Then, a depiction of the concrete business's key process parameter system (or CPPS) was unveiled. The temperature has a significant impact on casting quality;hence casting machines are equipped with temperature sensors and internet connection devices. Typically, IoT data is stored in the NoSQL database HBase, while data preparation is handled using the lightning-fast processing and analysis tool Spark. Several machine learning methods were used to make accurate quality forecasting. R was used to analyse how well each method performed. A CPPS dashboard is used to showcase the overall system's effectiveness. Complex abstract models are used in most CPPS studies at present. This research provides an in-depth examination of existing architectural frameworks, practical examples of their use, and analytical approaches. © 2023 IEEE.

关键词： Forecasting

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