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Enhancing Industrial Production Efficiency: A Comprehensive IoT-Based Supervision and Control System

Enhancing Industrial Production Efficiency: A Comprehensive ...

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International conference on advanced systems and Electric Technologies (IC_ASET)

作者： Skander HADJ ABDALLAH Rahma BOUCETTA Walid LAABIDI Mohamed Ali ZDIRI National School of Electronics and Telecommunications of Sfax (ENET'Com) University of Sfax Sfax Tunisia Faculty of Sciences of Sfax (FSS) University of Sfax Sfax Tunisia Smart Ways Innovation Society Sfax Tunisia Control and Energy Management Laboratory University of Sfax Sfax Tunisia

ISBN: (数字)9798350384895

ISBN: (纸本)9798350384901

The Fourth Industrial Revolution, also known as Industry 4.0, represents the culmination of all the transformations experienced by the industrial world. Consumer demand continues to rise, coupled with the expectation of higher quality at lower costs. The concept of Industry 4.0 emerged from a contemplation initiated by the German government in 2011, which became the subject of extensive research in academic and industrial circles within the country. Industry 4.0 follows in the footsteps of three previous industrial revolutions (1.0, 2.0, and 3.0). It is considered disruptive as it aims to imbue the manufacturing system with intelligence, through interconnected and intelligent factories, products, and services. The work presented in this paper revolves around applying the principles of Industry 4.0 to a prototype of an industrial production line. The endeavor comprises two essential components. One is dedicated to the practical realization of the prototype, utilizing electronic components capable of connecting to Wifi. The second is reserved to the development of a mobile application that enables the control of the process and real-time remote supervision of its status.

关键词： Protocols Operating systems Prototypes sensor systems Fourth Industrial Revolution Mobile applications sensors

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Unveiling Synergies: Integrating IEEE 1451 and ISO 15926 for advanced Interoperability in Smart Manufacturing and Transportation

Unveiling Synergies: Integrating IEEE 1451 and ISO 15926 for...

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IEEE International conference on Electronics, Circuits and systems (ICECS)

作者： Vahid Tavakkoli Kabeh Mohsenzadegan Witesyavwirwa Vianney Kambale Kyandoghere Kyamakya Institute for Smart System Technologies Universitaet Klagenfurt Klagenfurt Austria Universitaet Klagenfurt/Inst. f. Smart Systems Technologies Austria Faculté Polytechnique Université de Kinshasa DR-Congo

ISBN: (数字)9798350377200

ISBN: (纸本)9798350377217

In smart manufacturing and transportation systems, seamless interoperability is crucial for efficient data exchange and informed decision-making. This paper explores integrating IEEE 1451 and ISO 15926 data models to enhance interoperability in these sectors. We align sensor and actuator models to bolster interoperability and assess leveraging these standards within the Arrowhead flexible Production Value Network (fPVN). We propose innovative solutions, including an ontology mapping tool for seamless data integration, a wrapper service for real-time data translation, and a lightweight semantic reasoner at the fog computing layer. These solutions bridge the gap between theoretical constructs and practical applications, overcoming interoperability barriers, enhancing decision-making, and refining operational effectiveness. Our study shows significant potential for improving system cohesiveness, efficiency, and robustness tailored to Industry 5.0. This research provides a foundation for future implementations in smart manufacturing and transportation, paving the way for advanced, responsive, and sustainable industrial ecosystems.

关键词： ISO Standards Decision making Semantics Ecosystems Transportation Ontologies Data models Fifth Industrial Revolution Interoperability Smart manufacturing

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State-of-the-Art Technologies in Plantar Pressure Assessment: A Comprehensive Review

State-of-the-Art Technologies in Plantar Pressure Assessment...

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Sustainable Communication Networks and Application (ICSCNA), International conference on

作者： Nisanth Krishnan Balamurugan V Department of ECE Sathyabama Institute of science and technology Chennai

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530020

Plantar pressure, the force exerted by the foot on the ground during standing, walking, and running, provides crucial insights into foot health and functionality. Foot plantar pressure is a crucial biomechanical parameter that influences various aspects of human locomotion and foot health. Understanding and accurately measuring plantar pressure distribution can provide insights into gait abnormalities, foot deformities, and the effectiveness of orthotic interventions. This research synthesizes recent advancements in plantar pressure measurement technologies and methodologies across diverse research studies. It explores the significance of plantar pressure in clinical diagnostics, rehabilitation strategies, and sports biomechanics. Despite its importance, existing methods such as platform systems and in-shoe sensors have limitations. Platform systems offer precise spatial resolution but are restricted to laboratory settings and may alter natural gait patterns. In-shoe sensors provide mobility and reflect real-world conditions but are prone to sensor displacement and may not capture pressure changes during dynamic activities effectively. Moreover, both types of systems often simplify foot biomechanics and soft tissue properties, potentially limiting their applicability in complex clinical scenarios. This study identifies these limitations and discusses recent innovations aimed at overcoming them, including deep learning algorithms for real-time pressure mapping and advanced sensor technologies for enhanced accuracy and reliability. By analyzing these advancements and their implications, this study aims to provide a comprehensive understanding of current trends and future directions in plantar pressure research, facilitating improved clinical outcomes and innovative applications in foot health management.

关键词： Biomechanics Deep learning Technological innovation Accuracy sensor systems sensors Pressure measurement Reliability Foot Sports

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Multi-sensor Satellite Image Cloud Classification with Deep Learning

Multi-Sensor Satellite Image Cloud Classification with Deep ...

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Data Science, Agents & Artificial Intelligence (ICDSAAI), International conference on

作者： Rakesh Asery Burungale Swapnil Birudev Pankaj Saini Bigdata Research & Supercomputing CSIR-Fourth Paradigm Institute Bangalore India

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

Advancements in remote sensing (RS) have greatly increased the availability of satellite imagery, enabling diverse applications. However, cloud-cover remains a significant challenge, obstructing the acquisition and analysis of optical satellite images. This necessitates advanced cloud classification techniques as a crucial preprocessing step. The proposed MobileNetV2-based convolutional neural network architecture demonstrates unprecedented cloud classification capabilities, effectively processing imagery across diverse spatial resolutions ranging from 10 to 56 meters. By leveraging sophisticated machine learning algorithms, the model transcends traditional pixel-based thresholding techniques, capturing complex inter-pixel spatial correlations with remarkable precision. Experimental validation across heterogeneous datasets including IRS (AWiFS, LISS-iii), Landsat, and Sentinel platforms reveals exceptional performance metrics, consistently achieving classification accuracies exceeding 99.94%.

关键词： Accuracy Satellites Clouds Scalability Landsat Robustness Satellite images Convolutional neural networks Spatial resolution Remote sensing

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Multi-Target Tracking with GPU-Accelerated Data Association Engine 26

Multi-Target Tracking with GPU-Accelerated Data Association ...

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26th International conference on Information Fusion, FUSION 2023

作者： Kawtikwar, Samiran Nagi, Rakesh University of Illinois at Urbana-Champaign Department of Industrial and Enterprise Systems Engineering UrbanaIL United States

ISBN: (纸本)9798890344854

Multi-Target Tracking (MTT) is a challenging problem in the field of data association and sensor data fusion. Many solutions to MTT assume a Markovian nature to the motion of the target to solve the problem and avoid the potential computational complexity. Recently, we have shown that considering a sequence of three time steps and their resulting triplet costs in data association provides a superior solution that better incorporates the kinematic behavior of maneuvering targets. Nevertheless, the triplet costs pose significant computational overhead and scaling challenges. In this paper, we present significant computational advances in a triplet cost-based data association engine for MTT using Graphics Processing Units (GPUs). We achieve this by improving the computational performance of the dual ascent algorithm for dense Multi-Dimensional Assignment Problem (MAP), presented in Vadrevu and Nagi, 2022. Our contributions include: (1) A very fast GPU-accelerated Linear Assignment Problem (LAP) solver that solves an array of tiled LAPs without synchronizing with the CPU, (2) Reduction in computational overheads of triplet costs by using gating and compressed matrix representations, and (3) Computational performance studies that demonstrate the effectiveness of our computational enhancements. Our resulting solution is 5.8 times faster than the current solution without compromising the accuracy. © 2023 International Society of Information Fusion.

关键词： Graphics processing unit

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Gesture Controlled Bot with Temperature & Humidity (TH) Sensing Features

Gesture Controlled Bot with Temperature & Humidity (TH) Sens...

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Information and Communication Technology (ICICT), International conference on

作者： Mohammad Tahsin Alam Yasir Mahmud Zafrin Jahan Nikita Sajid Muhaimin Choudhury Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh

ISBN: (数字)9798331508227

ISBN: (纸本)9798331508234

The paper presents a design and implementation for a gesture-controlled robotic system that can operate in remote regions. This system can send environmental data through wireless data interchange, which a user can then remotely access to operate an application. The robot, being equipped with advanced sensors and communication modules, can capture data about the environment in real-time and perform monitoring and interaction with the environment. What distinguishes it is an intuitive gesture control mechanism that allows a user to interact with and give commands to a robot using natural hand movements, making it easy to use with increased accuracy. This innovative approach allows users to control and navigate the robot using simple palm gestures, fostering an intuitive interaction with the robotic system. The gestures are interpreted by a gyroscope sensor, which directs the robot's movements accordingly. Data collected by this robot is transmitted through a sturdy wireless network to the mobile application, where users can receive, analyze, and respond promptly to this information. It offers a potentially significant benefit for practical applications in harmful working environments, disaster management, or remote exploration where direct human intervention is impossible or hazardous. The paper presents technical specifications, design challenges, and a performance evaluation of the system developed, indicating its usability and robustness in real practical applications.

关键词： Temperature sensors Hands Temperature distribution Wireless sensor networks Wireless networks Humidity Robot sensing systems Real-time systems sensors Temperature control

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Transforming Energy Efficiency in IoMT: advanced Modulation Strategies for Sustainable Wireless Medical sensor Networks

Transforming Energy Efficiency in IoMT: Advanced Modulation ...

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Data Intelligence and Cognitive Informatics (ICDICI), International conference on

作者： Ayoub Hadj Sadek Salma Rattal Gunjan Varshney El Miloud Ar-Reyouchi Kamal Ghoumid Dept. of Electronics Informatics and Telecommunications Mohammed I University ENSAO Oujda Morocco Ecole Marocaine des Sciences de l’Ingénieur (EMSI) Casablanca Morocco Dept. of Robotics and Artificial Intelligence JSS University Noida Noida India Dept. of Telecommunication and Computer Science Abdelmalek Essaâdi University Tetouan Morocco

ISBN: (数字)9798350389609

ISBN: (纸本)9798350389616

The investigation focuses on advanced modulation strategies to optimize energy efficiency in Wireless Medical sensor Networks (WMSNs) within the Internet of Medical Things (IoMT). The study addresses the balance between energy consumption and spectral efficiency, specifically targeting challenges associated with WMSN deployment in critical healthcare applications. The analysis rigorously evaluates energy consumption across various distances and modulation schemes, particularly in the presence of Additive White Gaussian Noise (AWGN) channels. Modulation techniques are categorized into linear and nonlinear types, allowing for a comprehensive examination of each class’s energy efficiency. The objective is to minimize energy usage while ensuring reliable and secure communication in remote healthcare systems through the optimal selection of modulation schemes and transmission parameters. The results offer significant contributions to sustainable healthcare technology, enhancing the operational lifespan of medical sensors without compromising data transmission quality.

关键词： Wireless communication Energy consumption Wireless sensor networks Power demand Spectral efficiency Machine learning Energy efficiency Reliability Communication system security Security

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CORP CONNECT- A Comprehensive System for Efficient Municipal Services, Manhole Lid Management, and Toxic Gas Monitoring

CORP CONNECT- A Comprehensive System for Efficient Municipal...

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International conference on Communication, Computing and Internet of Things (IC3IoT)

作者： T Sheela P K Prithvi B Advaith Krishna R Abishek Department Of Information Technology Chennai India

ISBN: (数字)9798350352689

ISBN: (纸本)9798350352696

In urban environments, the safety and wellbeing of citizens depend significantly on the efficient functioning of municipal services, particularly in the management of drainage systems and manhole lids. This paper introduces Corp Connect a ground-breaking mobile application designed exclusively for Municipal Corporation workers. Corp Connect aims to enhance coordination among team members, addressing and resolving issues in their respective areas, with a primary focus on ensuring the proper closure of manhole lids and monitoring toxic gases within drainage systems. The mobile application facilitates real-time communication, enabling municipal workers to coordinate effectively. IoT-based hardware module plays a pivotal role in enhancing safety measures. This module is adept at monitoring the status of manhole lids, ensuring they are securely closed to prevent accidents. Furthermore, it employs advanced sensors to detect and monitor toxic gases within drainage systems, providing early warnings to mitigate health hazards.

关键词： Gases Urban areas Real-time systems sensor systems sensors Mobile applications Telecommunication computing

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Cutting-Edge Innovations in Biomedical Sensing Technologies for Enhanced Remote Healthcare Monitoring

Cutting-Edge Innovations in Biomedical Sensing Technologies ...

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Cybernation and Computation (CYBERCOM), International conference on

作者： Anusharani V M Mudhu Krishnan T. Muthamizhan Mohammad Aijaz Guna. G Department of Electronics and Instrumentation Engineering Saveetha Engineering College (Autonomous) Chennai India Department of Mechanical Engineering R.M.K. Engineering College Chennai India Department of Electrical And Electronics Engineering Sri Sai Ram Institute of Technology Chennai Tamil Nadu India Department Of EEE Kodada Institute Of Technology And Science For Women Kodad Telangana India Department of Electrical and Electronics Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India

ISBN: (数字)9798331542344

ISBN: (纸本)9798331542351

This study discusses the state-of-the-art advancements in approaches and systems of biomedical sensing used to implement distant healthcare monitoring. The performance and accuracy of wearable and implantable sensors as well as their compatibility with mHealth Apps is assessed in the study. The study includes the processing of data collected through wearable devices, implantable sensors, and health applications to evaluate sensor reliability, data aggregation, and system efficiency. As the study has demonstrated, wearable sensors such as heart rate sensors and activity sensors, both have close to perfect accuracy of 95% and, 92% respectively. Other implantable sensors, namely the glucose and pressure sensors, exhibit high accuracy levels of 97% and 96%, respectively, and a minimal latency level. The use of mobile health applications captures the data from the sensors in a very integrated manner with accuracy levels of 92-94%. These interactive conclusions stress the opportunity bestowed by biomedical sensing technologies in advanced chronic disease, eldercare, and other healthcare system arrangements. These and other innovations in the sectors of sensors, data merging, and artificial intelligence will furthermore improve the potential of remote monitoring systems. This paper establishes a foundation for the continuous development of biomedical sensing technologies, as a key constituent of remote health monitoring systems.

关键词： Temperature sensors Technological innovation Accuracy Medical services sensor systems sensors Biomedical monitoring Wearable sensors Remote monitoring Diseases

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Real-Time Medical IoT for Continuous Glucose Monitoring

Real-Time Medical IoT for Continuous Glucose Monitoring

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Intelligent systems and advanced applications (ICISAA), International conference on

作者： Akanksha Goel Poi Tamrakar Mily Lal Manisha Bhende Minal Wani Saurabh Saoji Dr.D.Y. Patil School of Science & Technology Dr.D.Y. Patil Vidyapeeth Pimpri Pune India Dr.D.Y. Patil Vidyapeeth Pimpri Dr.D.Y. Patil Biotechnology and bioinformatics Institute Pune India Dept.of Computer Engineering Nutan Maharashtra Institute of Engineering and Technology Pune

ISBN: (数字)9798331539948

ISBN: (纸本)9798331539955

This research is about Continuous Glucose Monitoring (CGM) technology and its pivotal role in revolutionizing diabetes care. Leveraging data obtained from a comprehensive study focused on evaluating CGM’s efficacy in diabetes management, this study investigates the impact and potential benefits of CGM usage on patients’ health after collecting the real secondary data through online forms. It encompasses a diverse array of patient-centric variables, including medical history, medication intake, physiological parameters, and CGM-derived glucose *** integrating machine learning techniques and statistical analysis, this study aims to derive valuable insights into the interplay between CGM data patterns and real-time activities, patients’ physiological profiles, and diabetes management outcomes. The extracted features and processed data serve as a foundation for subsequent predictive modeling, classification, and regression analysis. This research aims to contribute to the expansion of knowledge regarding the effectiveness of CGM technology in diabetes treatment. By exploring correlations between CGM data, patient attributes, and clinical outcomes, this study endeavors to pave the way for personalized and optimized diabetes management strategies.

关键词： Continuous glucose monitoring Wireless sensor networks Reviews Medical services Machine learning Quality of service Feature extraction Real-time systems Diabetes Internet of Things

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