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Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), International Conference on

作者： Premalatha Gurumurthy R. Raffik P. Dinesh Kumar R. B. Saroo Raj Dharmalingam Murugesan Manjunathan Alagarsamy Department of Electronics and Communication Engineering Prathyusha Engineering College Chennai Tamil Nadu India Department of Mechatronics Engineering Kumaraguru College of Technology Coimbatore Tamil Nadu India Department of Computer Science and Engineering Vivekanandha College of Technology for Women Tiruchengode Tamil Nadu India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Electronics and Communication Engineering Kongunadu College of Engineering and Technology Trichy Tamil Nadu India Department of Electronics and Communication Engineering K. Ramakrishnan College of Technology Trichy Tamil Nadu India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

The Internet of Things (IoT) has disrupted home automation with device integration, real-time control, and better user comfort. Scalability, connection, and usability limitations plague traditional GSM-based home automation systems. IoT allows smartphones, tablets, and other smart devices to control electrical equipment remotely, ensuring energy efficiency, convenience, and security. IoT-based automation uses communication protocols, cloud computing, and sensors for intelligent functionality and real-time feedback. Modern smart home ecosystems are more flexible, scalable, and interoperable with IoT platforms like Zigbee, Wi-Fi, and MQTT than GSM-based systems. This study creates an IoT-based home automation system using microcontrollers, sensors, and IoT cloud platforms for smart homes that is cost-effective, user-friendly, and sustainable. This study shows how IoT is transforming home automation and can produce more sustainable, intelligent homes than conventional systems. As they evolve, IoT technologies could make home automation more efficient, safe, and user-friendly, enabling a more intelligent and connected future.

关键词： Home appliances Cloud computing Home automation Automation Virtual assistants Zigbee Real-time systems Internet of Things Artificial intelligence Wireless fidelity

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A Robust Prediction of Online Social Network Influencers by Using Elevated Deep Learning Strategy

A Robust Prediction of Online Social Network Influencers by ...

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Emerging Trends in engineering and Medical Sciences (ICETEMS), International Conference on

作者： S Agnes Shifani R Sathishkumar M Priscilla T Jayakumar Neeraj Sunheriya Maram Y Al Safarini Department of ECE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Saveetha University Chennai Tamil Nadu India Department of CSE St. Joseph College of Engineering Chennai Tamil Nadu India Department of ECE S.A Engineering College Chennai Tamil Nadu India Department of Mechatronics Engineering KCG College of Technology Chennai Tamil Nadu India Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Nagpur India Department of Computer Science Zarqa University Zarqa Jordan University of Business and Technology Jeddah Saudi Arabia

ISBN: (数字)9798331529352

ISBN: (纸本)9798331529390

Predicting influential users is crucial for targeted marketing, knowledge diffusion, and community participation on dynamic social networks. We offer a deep learning-based methodology to predict social network influencers in this research. Using a deep learning framework to integrate user behavior, interaction patterns, and network structure identifies influential users with top accuracy. In this paper, the Social Media Influence Principle (SMIP) is developed using state-of-the-art neural network architectures like Graph Neural Network (GNN) to capture relational dynamics and temporal aspects of user interaction. This method's cross-validation with Recurrent Neural Network (RNN), which considers multi-layer relations and temporal information inside a sequence of social media network snapshots, is better than any previous effort. NEMO can identify community battleground nodes using engagement analytics, sentiments analysis, and network centrality. The present research advances social network analysis by providing a reliable influencer prediction tool that informs data-driven digital marketing/environment management decisions.

关键词： Deep learning Knowledge engineering Sentiment analysis Recurrent neural networks Accuracy Social networking (online) Market research Graph neural networks Reliability

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Effects of Robotic Expertise and Task Knowledge on Physical Ergonomics and Joint Efficiency in a Human-Robot Collaboration Task

Effects of Robotic Expertise and Task Knowledge on Physical ...

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IEEE-RAS International Conference on Humanoid Robots

作者： Matteo Pantano Arianna Curioni Daniel Regulin Tobias Kamps Dongheui Lee Technology department Siemens Aktiengesellschaft Munich Germany Department of Electrical and Computer Engineering Human-Centered Assistive Robotics Technical University of Munich Munich Germany Autonomous Systems Institut für Computertechnik Technische Uni-versitat Wien Vienna Austria Institute of Robotics and Mechatronics German Aerospace Center Wessling Germany

With the trend of low batch manufacturing, more and more small and medium enterprises are leaning towards adopting collaborative robots to increase productivity and improve operator well-being. However, robots are often programmed by robot experts rather than the operators effectively working with the machine. Therefore, operators may perceive low levels of task autonomy due to the unpredictability of robot motions. Empowering operators to make their own choices regarding robot motions can improve such feelings. However, research in cognitive science shows that allowing operators to decide on robot motions in a collaborative task could be influenced by how people consider their travel path and their partner's action. To better understand these relations, considering preliminary results from a previous study, we designed a user study where we tested operators' decisions in a collaborative task where groups of robot experts and novices were asked to choose their preferred task configuration among four possible options that differed in terms of operators' physical ergonomics and robot travel path. Our results show that robotic experts prioritize joint team work rather than their ergonomics. Contrarily, novices prioritize individual efforts and tend to reduce the robot travel path while keeping their travel path constant, maintaining good physical ergonomics. In conclusion, providing operators with task decision autonomy can be advantageous, but operator background must be considered to ensure optimal physical ergonomics and travel paths.

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A Robust Design of Cooperative Model to Enhance Energy Efficiency over Heterogeneous 5G Wireless Sensor Network Paradigm

A Robust Design of Cooperative Model to Enhance Energy Effic...

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Innovation in Technology (APCIT), Asia Pacific Conference on

作者： C. Anitha G. M. Karthik M. Uma Maheswari L. Vinoth Kumar G. Sasikala Jayanthi S Department of CSE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Information Security School of Computer Science and Engineering (SCOPE) Vellore Institute of Technology Vellore Tamil Nadu India Department of Mechatronics Engineering Rajalakshmi Engineering College Chennai Tamil Nadu India Department of Information Technology RMK Engineering College Chennai Tamil Nadu India Department of ECE Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering R.M.D Engineering College Chennai Tamil Nadu India

ISBN: (数字)9798350361537

ISBN: (纸本)9798350361544

Multiple interconnecting Wireless Sensor Networks (WSN) built on the same region have grown increasingly prevalent in recent years due to the widespread diffusion of 5G Wireless Sensor Networks (WSNs). Cooperative packet forwarding is anticipated to prolong their lifespan in this scenario. While some studies have looked at 5G network models that work together, the majority of these studies ignore the fact that WSNs vary greatly in terms of factors like battery life, starting time of operation, number of nodes, locations of nodes, energy consumption, packet size and/or data transmission timing, and so on. Optimistic lifelong gains through teamwork could not hold water in a diverse setting. Improve Energy Efficient Communication Paradigm (EEECP) is a fair cooperative routing approach that we offer in this study for 5G wireless sensor networks that are diverse and overlapping. The efficiency of this suggested approach will be evaluated by cross-validating it with the usual Cooperative Data Communication (CDC) model of communication. In order to keep the overall energy usage down, it implements a cooperative forwarding system and an energy-pool. The energy pool mediates equitable collaboration. Last but not least, the suggested strategy performs exceptionally well according to the simulation findings.

关键词： Wireless sensor networks Energy consumption Technological innovation 5G mobile communication Array signal processing Data models Energy efficiency

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Research of Control Systems for Robotic Spatial Planning Platforms

Research of Control Systems for Robotic Spatial Planning Pla...

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International Conference on Modern Electrical and Energy Systems (MEES)

作者： Yurii Lebedenko Oksana Polyvoda Anatolii Derkachenko Yevhenii Modlo Svitlana Demishonkova Yurii Pylypenko Information and Computer Technologies Department Kyiv National University of Technologies and Design Kyiv Ukraine Automation Robotics and Mechatronics Department Kherson National Technical University Kherson Ukraine Technological Institute State University of Economics and Technology Kryvyi Rih Ukraine Department of Computer Engineering and Electromechanics Kyiv National University of Technologies and Design Kyiv Ukraine

ISBN: (纸本)9798350346848

The work is devoted to the study of the control system of the moving platform of the manipulative robot. The purpose of the work is the development and research of an instrumental complex of control, analysis and modeling of the operation of positioning platforms based on a spherical mechanism for use in automated industrial systems. The state of use of multi-link positioning platforms in various industries was analyzed and their classification was provided, the main areas of use were determined. A comparative analysis of mathematical methods for describing the kinematic properties of positioning platforms was performed, namely: the closed vector contour method, the coordinate transformation method. A model with an analytical apparatus for controlling the drive links of the spherical mechanism according to the given scenarios of the orientation of the positioning platform was developed, as well as a mathematical model of inverse kinematics was made, the working space was modeled, and the service angles were determined, and a calculation and real-life experiment was conducted. For the first time, the work uses the dependencies of analytical geometry to implement algorithms for controlling a spherical mechanism by inverse kinematics, and offers software and hardware that combines visual modeling tools with real-time data transmission to a controller that controls the drivers of a spherical mechanism by direct kinematics. The result of the field experiment is the testing of the proposed control algorithm on the manufactured manipulator mechanism on the most common movements of the platform of the spherical mechanism and its exit to the extreme positions in order to determine the working space and the values of the service angles. A system of remote control of the spherical mechanism at the hardware level with an interactive interface and tracking of the positioning target has been implemented.

关键词： Analytical models Target tracking Robot kinematics Software algorithms Kinematics Aerospace electronics Control systems

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AUTOMATED DRIVING ARCHITECTURE AND OPERATION OF A LIGHT COMMERCIAL VEHICLE

arXiv

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arXiv 2023年

作者： Gözü, Murat Emirler, Mümin Tolga Uygan, Ismail Meriç Can Böke, Tevfik Ali Güvenç, Levent Güvenç, Bilin Aksun Istanbul Okan University Institute of Sciences and Engineering Mechatronics Engineering Program Istanbul Turkey Yildiz Technical University Faculty of Applied Sciences Department of Aviation Electronics Istanbul Turkey Tübitak Bilgem Cyber Security Institute Kocaeli Gebze Turkey Tofaş Research and Development Center Bursa Turkey The Ohio State University Automated Driving Lab ColumbusOH United States The Ohio State University Department of Mechanical and Aerospace Engineering ColumbusOH United States The Ohio State University Department of Electrical and Computer Engineering ColumbusOH United States

This paper is on the automated driving architecture and operation of a light commercial vehicle. Simple longitudinal and lateral dynamic models of the vehicle and a more detailed CarSim model are developed and used in simulations and controller design and evaluation. Experimental validation is used to make sure that the models used represent the actual response of the vehicle as closely as possible. The vehicle is made drive-by-wire by interfacing with the existing throttle-by-wire, by adding an active vacuum booster for brake-by-wire and by adding a steering actuator for steer-by-wire operation. Vehicle localization is achieved by using a GPS sensor integrated with six axes IMU with a built-in INS algorithm and a digital compass for heading information. Front looking radar, lidar and camera are used for environmental sensing. Communication with the road infrastructure and other vehicles is made possible by a vehicle to vehicle communication modem. A dedicated computer under real time Linux is used to collect, process and distribute sensor information. A dSPACE MicroAutoBox is used for drive-by-wire controls. CACC based longitudinal control and path tracking of a map of GPS waypoints are used to present the operation of this automated driving vehicle. © 2023, CC BY-NC-ND.

关键词： Controllers

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A Smart Industrial Information System using a Business Process Model, Discrete Events Simulation, Optimization, and Machine Learning Algorithms

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Journal of Industrial Information Integration 2025年

作者： Seyed Alireza Mansoori Al-yasin Mohammad Gheibi Hassan Montazeri Reza Yeganeh Khaksar Mehran Akrami Amir M. Fathollahi-Fard Kuan Yew Wong Department of civil engineering Sadjad University of Technology Mashhad Iran Institute for Nanomaterials Advanced Technology and Innovation Technical University of Liberec 46001 Liberec Czech Republic Faculty of Mechatronics Informatics and Interdisciplinary Studies Technical University of Liberec Liberec Czech Republic Department of Logistics Kühne Logistics University 20457 Hamburg Germany Department of Civil and Environmental Engineering University of Virginia 151 Engineer's Way Charlottesville VA 22904 United States Department of Engineering Science Faculty of Innovation Engineering Macau University of Science and Technology Macau 999078 PR China Faculty of Mechanical Engineering Universiti Teknologi Malaysia 81310 Skudai Malaysia

In industrial systems, managers face the critical challenge of efficiently managing resources to reduce production costs and time while maximizing profits. To address these challenges, production managers require advanced industrial information systems that optimize production time, costs, and profits. This paper presents a smart industrial information system that integrates Business Process Model and Notation (BPMN), AnyLogic simulation software for Discrete Event (DE) modeling, Response Surface Methodology (RSM), and Machine Learning (ML) algorithms. The system’s effectiveness is demonstrated through its application in an industrial steel skeleton production facility in Iran. To enhance revenue, we optimize key factors of the production process through simulation. Various ML algorithms, including Random Forest (RF), Random Tree (RT), and Bagging, were employed to improve system performance, with the Bagging model yielding the best results. The findings indicate that small hardener chamfer and welder for spare parts, with P-values of 0.0002 and >0.0001 respectively, are the most significant parameters impacting total costs and profits. Ultimately, the proposed industrial information system provides a cost-effective simulation approach that improves process-driven business operations, aligning with BPMN standards and economic criteria.

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Autonomous Power Supply Development for Hydrometeorological Monitoring Station

Autonomous Power Supply Development for Hydrometeorological ...

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IEEE International Energy Conference and Exhibition (EnergyCon)

作者： Anatoliy Prystupa Volodymyr Kazymyr Anatolijs Zabaš ta Anatoliy Revko Serhii Stepenko Kateryna Novyk Electrical Engineering Information and Measurement Technologies Department Chernihiv Polytechnic National University Chernihiv Ukraine Information and Computer system Department Chernihiv Polytechnic National University Chernihiv Ukraine Institute of Industrial Electronics and Electrical Engineering Riga Technical University Riga Latvia Electronics Automation Robotics and Mechatronics Department Chernihiv Polytechnic National University Chernihiv Ukraine

This paper presents the results of the investigation of the power supply system of the autonomous monitoring system. In particular, calculations of the system’s daily balance of energy consumption were performed. Also, the question of the influence of the angle of inclination of solar converters on energy generation is considered and the necessity of collecting solar radiation during the whole daylight, not focusing on the maximum amount of energy, is substantiated. This research aimed to develop an algorithm for calculating the power supply system for autonomous monitoring systems. The proposed algorithm takes into account the coordination of diagrams of generation and consumption of energy within the autonomous monitoring station and statistical analysis of information from the NASA website. Experiments have shown the effectiveness of this method. It can be used in future design of power supply systems for autonomous monitoring stations.

关键词： Power measurement Power supplies Statistical analysis NASA Energy measurement Reliability theory Battery charge measurement

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Using of 3D printing technology in low cost prosthetics

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Materials Science Forum 2018年 919卷 199-206页

作者： Koprnicky, Jan Safka, Jiri Ackermann, Michal Institute of Mechatronics and Computer Engineering Faculty of Mechatronics Technical University of Liberec Czech Republic Department of industrial technology Institute for Nanomaterials Advanced Technology and Innovation Technical University of Liberec Czech Republic

The 3D printing technology used for final production of upper limb prostheses is the topic of this article. It focuses on different 3D printing technologies and testing of different thermoplastic materials. As the testing object an index finger of HACKberry open source myoelectric bionic hand was used. This part was 3D printed by using of different printing technologies (FFF/FDM, SLA, SLS, PolyJet), and different materials (PLA, ABS, PC-ABS, Though, etc.), and different strategies (height of layers). The fingers were mechanically tested to simulate flexion in a tip pinch grip. At the end of this paper results of this research and testing is summarized, and optimal material, technology and strategies of parts production is highlighted. © 2018 Trans Tech Publications, Switzerland.

关键词： Costs

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Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology 2022年第4期60卷 589-590页

作者： F van den Noort C Manzini C H van der Vaart M A J van Limbeek C H Slump A T M Grob Robotics and Mechatronics Faculty of Electrical Engineering Mathematics and Computer Science Technical Medical Centre University of Twente Enschede The Netherlands. Department of Obstetrics and Gynecology University Medical Centre Utrecht Utrecht The Netherlands. Dynamics of Complex Fluids Max Planck Institute for Dynamics and Self-Organization Göttingen Germany. Multi-Modality Medical Imaging Faculty of Science and Technology Technical Medical Centre University of Twente Enschede The Netherlands.

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