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A Detection and Information Processing Model Based on an Automatic Mechanism for Tax Payment control in Developing Countries 1

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3rd EAI international conference on Edge Computing and IoT, EAI ICECI 2022

作者： Havyarimana, Vincent Niyibikora, Patient Hanyurwimfura, Damien Semong, Thabo Department of Applied Sciences Burundi Higher Institute of Education Bujumbura6983 Burundi College of Science and Technology University of Rwanda Kigali3900 Rwanda Department of Computer Science and Information System Botswana International University of Science and Technology Palapye10071 Botswana

ISBN: (数字)9783031289903

ISBN: (纸本)9783031289897

The foundation of humanity is nowadays based on ways of living that can take many forms including controlling living conditions, reappraising work practices and developing new technologies. However, most of these activities are done to satisfy people’s needs, but they have a negative impact on their health and well-being. This is the reason why man seeks ways to develop and protect himself from fatigue and anything that can harm his health by using modern technology that reduces the consumption of resources. Recently, the most used modern technology is based on the "automatism" model which is very useful in multiple fields. The technology of automated systems is rapidly evolving in terms of components, structures, advanced control systems and application areas. The objective of this paper is to implement an automatic mechanism to ensure a better and wonderful control when collecting taxes especially in developing countries. The proposed mechanism is based on a case of paying parking tax. The mechanical part of our system is controlled by an ArdUINO micro controller under which works in parallel with a Windows application on a computer to control a servomotor that operates the barrier. The detection of the coordinates of the taxpayer is done using the radio frequency identification. This control model is composed of detection and information processing system and a mobile barrier whose structure is adapted to the opening or closing geometry of the taxpayer passage. © 2023, ICST Institute for Computer Sciences, Social informatics and Telecommunications Engineering.

关键词： Taxation

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Application of Realtime robotics platform to execute unstructured industrial tasks involving industrial robots, cobots, and human operators 3

Application of Realtime Robotics platform to execute unstruc...

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3rd international conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： Zaki, Ahmed Magdy Ahmed Fathy, Ahmed Mohsen Mohamed Carnevale, Marco Giberti, Hermes Univ Pavia Dipartimento Ingn Ind & Informaz Via Ferrata 5 I-27100 Pavia Italy

Small and medium-sized craft enterprises are still characterized by production process involving human labour to a large extent. The possibility of a safe interaction of the operator in the collaborative working area of the machine, and the development of an easy-to-program robotic cell, would pave the way to the introduction of automation in such an environment. This paper proposes an application of a commercial platform for collision avoidance, based on Dynamic Road-map algorithms, to execute unstructured industrial tasks involving industrial robots, cobots, and human operators at the same time. An example is presented in a pickand-place and assembling application, in which the components are feed by a conveyor belt with random order and random flow rate. The adopted platform enhances the possibility to exploit in the same robotic cell both industrial robots and human labour, thus allowing a reduction of costs and more precise applications. Moreover, the possibility to calculate at run-time alternative trajectories to avoid obstacles (both human being and other robot in the cell), avoiding to make the robot temporarily inactive, allows to improve the system productivity. (C) 2022 The Authors. Published by Elsevier B.V.

关键词： Industrial robots cobot collision avoidance collaborative industrial tasks human robot interaction

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Time-Scale Separation Analysis for Surgical Needle control in Electromagnetic Robotic Systems 3

Time-Scale Separation Analysis for Surgical Needle Control i...

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3rd Modeling, Estimation and control conference (MECC)

作者： Raval, Suraj Mair, Lamar Pryor, Will Erin, Onder Schwehr, Trevor Budaraju, Janya Krieger, Axel Diaz-Mercado, Yancy Univ Maryland Mech Engn Dept College Pk MD 20742 USA Johns Hopkins Univ Mech Engn Dept Baltimore MD 21218 USA Johns Hopkins Univ Dept Comp Sci Baltimore MD 21218 USA Weinberg Med Phys Inc Div Magnet Manipulat & Particle Res North Bethesda MD 20852 USA

ISBN: (纸本)9781713872344

In this work, we use the theory of time-scale separation to analyze motion of magnetic needles powered by electromagnetic coils for surgical tasks. In developing model-based controllers for such systems, it is often assumed that the magnetic needle orientation is aligned with the magnetic field direction. This assumption has enabled use of open-loop control techniques for orientation control of the magnetic agent. We provide a framework to show how this assumption might be highly inaccurate for certain system parameters. We show numerical simulations to depict this and validate results with experiments on a real magnetic control system. The results of this work can help ascertain whether the orientation alignment assumption is valid for a given set of parameters, paving the way to enable safe and accurate implementation of surgical tasks using magnetic needles in clinical settings. Copyright (c) 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Robotic System Modeling Surgical robotics Perturbation Methods Non-Linear System Analysis Magnetic Fields

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An Iterative Variable Step Error Compensation Approach for Enhancing Robot Trajectory Accuracy 3

An Iterative Variable Step Error Compensation Approach for E...

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3rd international conference on automation, robotics and Computer Engineering, ICARCE 2024

作者： Wang, Chengzhi Zhao, Sikai Zheng, Tianjiao Cai, Hegao Zhao, Jie Zhu, Yanhe Harbin Institute of Technology State Key Laboratory of Robotics and Systems Harbin China

ISBN: (纸本)9798331529505

In this paper, an iterative error compensation approach is analyzed and designed to improve trajectory accuracy of industrial robots. Advanced offline programming and robotic machining tasks require high trajectory accuracy of industrial robots, which is significantly affected by parameter inaccuracy, stiffness deformation, backlash, and so on. Such complicated coupling makes it impossible to model each factor separately, thus data-driven direct error compensation is the major solution to improve trajectory accuracy. Previous methods utilize external measurement equipment to obtain tracking error and rely on the error consistency assumption to compensate for the error by modifying the trajectory commands directly. However, such consistency assumption does not hold. Even a minor incremental modification of the initial commands can lead to unexpected influence on the robot's tracking performance, owning to unaccounted factors such as the robot's dynamic stiffness and natural frequency. This paper decomposes trajectory tracking errors based on servo encoder feedback and external laser tracker, and proposes a variable step error compensation scheme to improve tracking performance. Physical experiments are conducted on a standard 6 degree-of-freedom industrial robot to validate the effectiveness of the proposed method. The results of various error compensation approaches are analyzed to draw a possible error correlation model, in order to account for the error inconsistency in the compensation process. © 2024 IEEE.

关键词： Industrial robots

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3rd EAI international conference on Edge Computing and IoT, EAI ICECI 2022

3rd EAI International Conference on Edge Computing and IoT, ...

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3rd EAI international conference on Edge Computing and IoT, EAI ICECI 2022

ISBN: (纸本)9783031289897

The proceedings contain 21 papers. The special focus in this conference is on Edge Computing and IoT. The topics include: Evaluation of Higher Education System;defense Mechanisms Against Audio Adversarial Attacks: Recent Advances and Future Directions;an Empirical Study of Worldwide Plastic Waste Mitigation;prediction for Surface Subsidence of Shield Construction in Water-Rich Sand Egg Stratum Based on Edge Intelligence;highly Accurate Dynamic Gesture Recognition Method Based on Edge Intelligence;adversarial Example Attacks in Internet of Things (IoT);training Node Screening in Decentralized Trusted Federated Learning;exploration and Practice of Course Homework Metaverse Based on Extended Reality Under Edge Computing;federated Learning Based User Scheduling for Real-Time Multimedia Tasks in Edge Devices;the Data Exchange Protocol over Multi-chain Blockchain Using Zero-Knowledge Proof;a Co-caching Strategy for Edges Based on Federated Learning and Regional Prevalence;LSTM-DAM: Malicious Network Traffic Prediction for Cloud Manufacturing System;a Hybrid Task Offloading and Service Cache Scheme for Vehicular Edge Computing;on Enhancing Transmission Performance for IoV Based on Improved Greedy Algorithm;Precise Segmentation on Poly-Yolo, YoloV5 and FCN;Research on DAG Based Consensus Mechanism for Adjustable Load Metering Data;a Detection and Information Processing Model Based on an Automatic Mechanism for Tax Payment control in Developing Countries;IEC-FOF: An Industrial Electricity Consumption Forecasting and Optimization Framework;demons Hidden in the Light: Unrestricted Adversarial Illumination Attacks.

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Autonomous Water Quality Monitoring Surface Vehicle 3

Autonomous Water Quality Monitoring Surface Vehicle

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3rd IEEE international conference on Recent Advances in Systems Science and Engineering, RASSE 2023

作者： Nambiar, Manushri Saljith Ramakrishnan, Arjun Lakshman, Anirudh Abhiram, P.V. Girish, P. Toc H Institute of Science and Technology Dept. of Robotics and Automation India

ISBN: (纸本)9798350341676

Water pollution is the contamination of water sources by contaminants that render the water unfit for drinking, cooking, cleaning, swimming, and other uses. Pollutants include chemicals, waste, bacteria, and parasites. Traditional monitoring methods entail manually collecting water samples from vari-ous water resources, followed by testing and analysis in the laboratory. This procedure is frequently ineffective because itis time-consuming and does not produce results in real-Time. Water quality should be continuously monitored to ensure a safe supply of water to end users from any water resources or water bodies. Designing and creating a cost-effective system for real-Time monitoring of water quality utilising the Internet of Thingsis now required. A water vehicle is employed here to house the water quality monitoring system. The vehicle is self-contained, and set locations for measuring water quality can be provided. Using IoT devices and a Wi-Fi module, the proposed system aids in the continuous monitoring of water quality. The Wi-Fi moduleenables internet connectivity and sends sensor data to the Cloud. Various sensors are used to measure various factors in order to assess the water quality of water resources © 2023 IEEE.

关键词： Potable water

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Open-Source Digital Infrastructure Capacity Prediction System for Production Company 3

Open-Source Digital Infrastructure Capacity Prediction Syste...

引用

3rd international conference on control Systems, Mathematical Modeling, automation and Energy Efficiency, SUMMA 2021

作者： Panfilov, Peter Suleykin, Alexander Eldarawany, Ahmed Elpashev, Denis Hse University Department of Business Informatics Moscow Russia V.A. Trapeznikov Institute of Control Sciences Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9781665439817

We propose a system for prediction infrastructure capacity and metrics using Open-Source Big Data technologies. The proposed system is being built as a Digital Ecosystem comprised of various Services, which are needed for the prediction of Digital Infrastructure Capacity of a production company. Various techniques for the development of a digital ecosystem, such as integration, processing, prediction and visualization of server metrics are considered to provide prediction data from production companies. In our study, we review literature for Digital Infrastructure Capacity predictions, provide functional and component architecture of the proposed system, describe the methods and techniques for the development of prediction models, and finally implement the prototype system based on real server metrics data collected from a real-world production company. The forecasts visualizations for predicted server metrics are presented. © 2021 IEEE.

关键词： Data Analytics

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A Hybrid Nut Sorting System: Utilizing Machine Vision and Augmented Information for Efficient Human-Robot Collaboration 3

A Hybrid Nut Sorting System: Utilizing Machine Vision and Au...

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3rd international conference on Mechatronics, control and robotics, ICMCR 2025

作者： Sangchai, Kanisorn Adirekkittikun, Wongsakorn Vivatanaprasert, Kevin Boonpun, Methasit Chokthitirath, Wongpakorn Thipyophat, Nutdanai International School of Engineering Chulalongkorn University Robotics and Artificial Intelligence Faculty of Engineering Bangkok Thailand

ISBN: (纸本)9798331544546

Efficient sorting and classification of nuts is a critical task in various industries, yet current methods often rely on machine vision systems that inspect each nut individually, making the process time-consuming and inefficient. Additionally, most processes are fully automated, lacking the option for human monitoring or intervention. The novelty of this paper lies in the development of a hybrid nut sorting system that combines machine vision with augmented information to facilitate efficient human-robot collaboration. Unlike traditional fully automated systems that exclude human involvement, our approach integrates a projector-based visual aid to provide real-time, easily interpretable information for manual or semi-automated sorting. Additionally, the system incorporates a CoreXY robot path and mechanism, enabling collaboration between humans and robots. The detection system consistently identifies nuts of different sizes with reliable accuracy, particularly for simultaneous multi-object detection compared to singular detection methods. As a hybrid sorting system, our solution also allows humans to manually sort nuts at a faster rate than the machine while utilizing the system's assistance. © 2025 IEEE.

关键词： Collaborative robots

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A Critical Review on the Future of robotics in Manufacturing

A Critical Review on the Future of Robotics in Manufacturing

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international conference on Electrical Power and Energy Systems (ICEPES)

作者： Neeraj Agarwal U S Yadav Gurjeet Singh Rohit Kumar Singh Padmakar Pachorkar D K Gupta Department of Mechanical Engineering IES College of Technology Bhopal India Directorate General of Aeronautical Quality Assurance ORDAQA Kanpur India

ISBN: (数字)9798350390728

ISBN: (纸本)9798350390735

robotics has been an integral part of manufacturing for decades, revolutionizing industries with automation and efficiency. As technology advances, the future of robotics in manufacturing holds tremendous promise, with innovations such as collaborative robots (cobots), artificial intelligence (AI), and advanced sensor technologies reshaping the landscape. This review paper provides an in-depth analysis of current trends, challenges, and prospects of robotics in manufacturing, exploring how these technologies will continue to transform production processes and enhance competitiveness in the global market.

关键词： Technological innovation Service robots Reviews Collaborative robots Transforms Production Robot sensing systems

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A Research On The New Generation Artificial Intelligence Technology Generative Pretraining Transformer 3 3

A Research On The New Generation Artificial Intelligence Tec...

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3rd international informatics and Software Engineering conference, IISEC 2022

作者： Aydin, Nazif Ayhan Erdem, O. Gazi University Graduate School of Natural and Applied Sciences Department of Computer Engineering Ankara Turkey Gazi University Faculty of Technology Department of Computer Engineering Ankara Turkey

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

In the digitalizing world, Artificial Intelligence (AI) paves the way for the automation of routine work done by humans and makes life easier. Recently, there is no area where AI and its applications are not used in daily life, from health to education, from transportation to energy, and from agriculture to tourism. AI applications are making rapid progress in the direction of important and current developments, especially in Natural Language Processing (NLP) and Deep Learning (DL). A concrete example of progress in these areas is the GPT-3 (Generative Pre-trained Transformer 3) language model. AI-assisted GPT-3 technology is the DL model that is effectively used in many NLP fields, which can produce long and consistent content similar to the texts written by people using pre-trained algorithms. The GPT-3 architecture has reached a level that can compete with people in many areas by producing optimum solutions for all kinds of inputs by using the Transformer-based language model, which is an attention-based deep learning technique. This article aims to convey the efficiency, structure and potential of the Transformer-assisted GPT-3 model, which is one of the most up-to-date NLP technologies, to the reader. Since the number of Turkish studies in the field of GPT-3 AI is quite limited, it is considered that this study will contribute to the literature in terms of both quantity and quality. In addition, the performance parameters of the model were examined by making a customized fine-tuned sample application in the beta version of the GPT-3 model. © 2022 IEEE.

关键词： Deep learning

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