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Methods for Assessment of Gait Asymmetry Based on Data from Depth sensors 12

Methods for Assessment of Gait Asymmetry Based on Data from ...

12th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems: Technology and applications, IDAACS 2023

作者： Wagner, Jakub Warsaw University of Technology Institute of Radioelectronics and Multimedia Technology Faculty of Electronics and Information Technology Warsaw00-665 Poland

ISBN: (纸本)9798350358056

Six quantitative indicators of asymmetry of human gait, whose values can be estimated by processing data acquired using depth sensors, are considered. Procedures for the estimation of these indicators have been developed and tested using measurement data representative of typical gait and two types of asymmetric pathological gait. The results of the completed experiments indicate that among the considered indicators, the one based on the quasi-correlation between the speed of the feet allows for best differentiating among the three considered types of gait. © 2023 IEEE.

关键词： data processing depth sensor gait analysis gait asymmetry healthcare Kinect

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Computational Analysis of No-Core Fiber sensor for Detecting Aging Traces in Transformer Oil

Computational Analysis of No-Core Fiber Sensor for Detecting...

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2024 IEEE International conference on advanced Telecommunication and Networking Technologies, ATNT 2024

作者： Zaidi, Nurul Farah Adilla Saris, Nur Najahatul Huda Noor, Muhammad Yusof Mohd Salim, Mohd Rashidi Ambran, Sumiaty Othman, Marinah Universiti Teknologi Malaysia Faculty of Electrical Engineering Johor81310 Malaysia Malaysia Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur54100 Malaysia Universiti Sains Islam Malaysia Faculty of Engineering and Built Environment Negeri Sembilan71800 Malaysia

ISBN: (纸本)9798350353501

The presence of aging traces in transformer oil poses a significant concern for industries heavily dependent on power transformers, as it can potentially lead to breakdowns that disrupt critical business processes. This paper introduces a computational analysis study of a no-core fiber (NCF) sensor for detecting aging traces in transformer oil. Employing the Wave Optics Module in COMSOL Multiphysics 5.5®, the computational analysis study delves into the efficacy of the no-core fiber (NCF) sensor in detecting transformer oil with refractive indices spanning from 1.46 RIU to 1.55 RIU, encompassing the typical aging range of transformer oil. The study explores various parameters, including electric field distribution, mode field diameter, and effective mode index, across a spectrum of refractive index (RI) values. The findings highlight the potential of the sensor for effectively evaluating and analyzing aging traces in transformer oil by observing the RI and electric field intensity changes. This research lays the groundwork for future applications of the sensor in real-time scenarios especially for high-RI implementation conditions, offering a promising avenue for enhancing the reliability and longevity of power transformer systems. © 2024 IEEE.

关键词： Distribution transformers

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An Automatic Navigation System for New Technical advanced Drones for Different Alpplications 5

An Automatic Navigation System for New Technical Advanced Dr...

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5th IEEE International conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Talwandi, Navjot Singh Thakur, Payal Khare, Shanu Chandigarh University Dept of Computer Science Engineering Punjab India

ISBN: (纸本)9798350383522

Autonomous pilot technology integrated into drones has ushered in a new era of unmanned aircraft systems, creating a multitude of applications This abstract examines the importance of the importance and potential of autonomous pilot aircraft, underscoring its transformative impact on industries ranging from agriculture to surveillance and beyond Navigation requires intelligent a unmanned aerial vehicles (UAVs) will be equipped with sophisticated artificial and sensor systems, enabling them to operate autonomously without constant human intervention A rapidly growing field in robotics and aerospace technology Tires It is showing to do so, the paper provides a comprehensive overview, including key concepts, challenges, and recent developments in autonomous automation enter the box. It also discusses, and educates, the critical importance of real-time operations, the critical role of obstacle detection and avoidance systems, and the use of GPS and optical-based navigation delves into how machine learning and artificial intelligence enhance the autonomy of drones. In addition, the paper explores the many potential applications and benefits of autonomous drone communications, from search and rescue missions to precision agricultural delivery Growing interest and investment in this technology in 2013 highlights its potential to transform industries, promising a future marked by improved safety and performance. © 2024 IEEE.

关键词： and applications artificial intelligence Autonomous drones GPS machine learning navigation obstacle avoidance real-time data processing vision-based navigation

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Real Time Fire Detection with Simple Thermal Imaging: A Novel Integration of Threshold and Change Detection Techniques

Real Time Fire Detection with Simple Thermal Imaging: A Nove...

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2024 IEEE International Students' conference on Electrical, Electronics and Computer Science, SCEECS 2024

作者： Hotkar, Vinayak Prakash Meena, Om Jaiman, Tanmay Maulana Azad National Institute of Technology Department of Electronics and Communication Engineering Bhopal India

ISBN: (纸本)9798350348460

This research study aims to develop a system, for imaging and fire detection by exploring the integration of the ESP32 microcontroller and AMG8833 thermal sensor for image processing. The ESP32 microcontroller is chosen for its power consumption, wireless connectivity and adaptability which simplifies the integration of sensors. The AMG8833 thermal sensor with its 8x8 array of sensors makes thermal imaging more accessible. Our proposed solution leverages the capabilities of the ESP32 to collect and transmit data from the AMG8833 sensor in time for monitoring and analysis purposes. Python is utilized as a programming language to facilitate image processing and implement fire detection systems. By combining these technologies we can create a rather cost effective solution for imaging and fire detection applications. The outcomes of this study lay a foundation for developing reliable systems that advance imaging and fire detection technology. Moreover this combination of ESP32, AMG8833 and Python opens up prospects for research and development in areas such as IoT (Internet of Things) and smart sensing applications. © 2024 IEEE.

关键词： AMG8833 ESP32 Fire Detection Image processing Python Thermal Imaging thermal sensor

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RF Energy Harvesting Techniques for Battery-Less Wireless Sensing, Industry 4.0, and Internet of Things: A Review

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IEEE sensorS JOURNAL 2024年第5期24卷 5732-5745页

作者： Moloudian, Gholamhosein Hosseinifard, Mohammadamin Kumar, Sanjeev Simorangkir, Roy B. V. B. Buckley, John L. Song, Chaoyun Fantoni, Gualtiero O'Flynn, Brendan Univ Coll Cork Tyndall Natl Inst Wireless Sensor Network Grp Cork T12R5CP Ireland Univ Pisa Dept Civil & Ind Engn I-56122 Pisa Italy Kings Coll London Dept Engn London WC2R 2LS England

As the Internet of Things (IoT) continues to expand, the demand for the use of energy-efficient circuits and battery-less devices has grown rapidly. Battery-less operation, zero maintenance, and sustainability are the desired features of IoT devices in fifth-generation (5G) networks and green Industry 4.0 wireless systems. The integration of energy harvesting systems, IoT devices, and 5G networks has the potential impact to digitalize and revolutionize various industries such as Industry 4.0, agriculture, food, and healthcare, by enabling real-time data collection and analysis, mitigating maintenance costs, and improving efficiency. Energy harvesting plays a crucial role in envisioning a low-carbon net zero future and holds significant political importance. This survey aims at providing a comprehensive review on various energy harvesting techniques including radio frequency (RF), multisource hybrid, and energy harvesting using additive manufacturing technologies. However, special emphasis is given to RF-based energy harvesting methodologies tailored for battery-free wireless sensing, and powering autonomous low-power electronic circuits and IoT devices. The key design challenges and applications of energy harvesting techniques, as well as the future perspective of system on chip (SoC) implementation, data digitization in Industry 4.0, next-generation IoT devices, and 5G communications are discussed.

关键词： Battery-less wireless sensing energy harvesting Internet of Things (IoT) low-power electronic circuits next-generation communications wireless sensor networks

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An Antifreeze Gel as Strain sensors and Machine Learning Assisted Intelligent Motion Monitoring of Triboelectric Nanogenerators in Extreme Environments

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advanced FUNCTIONAL MATERIALS 2025年

作者： Han, Delong Cai, Yuting Wang, xinze Zhang, Weining Li, xusheng Hou, Zhaoru Liu, Jiahui Song, Dengke xu, Wenlong Ludong Univ Sch Chem & Mat Sci Yantai 264025 Peoples R China

Traditional hydrogels tend to freeze and lose performance at low temperatures, limiting their applications. Additionally, hydrogels need to exhibit low hysteresis, excellent cycling stability, and self-adhesion to ensure high-quality signal acquisition in complex environments. To address this challenge, this study designed a dual-network gel in a glycerol (Gly)/H2O solvent system. Due to the combination of chemical and physical crosslinking (hydrogen bonding and electrostatic interactions), the resulting gel exhibits skin-adaptive modulus, high cycling stability, anti-freezing ability, body temperature-induced adhesion, and excellent electrical performance, making it suitable for wearable sensors at low temperatures. Based on this gel, a single-electrode triboelectric nanogenerator (gel-TENG) is developed, achieving efficient conversion of mechanical energy into electrical energy. Further applied to a smart insole, it successfully enabled real-time visualization of plantar pressure distribution and skiing motion recognition. Using a random forest machine learning algorithm, the system accurately classified 11 basic skiing motions, achieving a classification accuracy of 97.1%. This study advances flexible sensors and self-powered systems, supporting intelligent materials research in extreme environments.

关键词： antifreeze gel machine learning self-power sensor

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Transforming Energy Efficiency in IoMT: advanced Modulation Strategies for Sustainable Wireless Medical sensor Networks 5

Transforming Energy Efficiency in IoMT: Advanced Modulation ...

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5th International conference on Data Intelligence and Cognitive Informatics, ICDICI 2024

作者： Sadek, Ayoub Hadj Rattal, Salma Varshney, Gunjan Ar-Reyouchi, El Miloud Ghoumid, Kamal Mohammed I University Ensao Dept. of Electronics Informatics and Telecommunications Oujda Morocco Casablanca Morocco Jss University Noida Dept. of Robotics and Artificial Intelligence Noida India Abdelmalek Essaâdi University Dept. of Telecommunication and Computer Science Tetouan Morocco

ISBN: (纸本)9798350389609

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. © 2024 IEEE.

关键词： Gaussian noise (electronic)

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Intelligent Mixed-Signal Embedded systems for Electromagnetic Tracking applications

Intelligent Mixed-Signal Embedded Systems for Electromagneti...

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IEEE lnternational conference on advanced Trends in Radioelectronics, Telecommunications and Computer Engineering, TCSET 2024

作者： Holyaka, Roman Marusenkova, Tetyana Shpur, Olha Lviv Polytechnic National University S. Bandery Str. 12 Lviv79013 Ukraine

ISBN: (纸本)9783031612206

Real-time analytics is the main advantage of Edge Computing (EC) in the concept of Artificial Intelligence (AI). AI EC brings high-performance computing capabilities to the edge, where sensors of Internet of Things (IoT) devices are located and data is processed locally, which significantly improves processing speed as compared to cloud computing. The core of AI EC is based on real-time embedded systems. This work presents intelligent embedded systems for electromagnetic tracking (EMT) applications. EMT is a novel development trend in sensor electronics and object navigation for IoT, Virtual, and Augmented Reality. The EMT technology relies on calculating the position of an object being tracked based on dynamic measurement of reference electromagnetic field vectors. In contrast to optical tracking systems, EMT does not require any clear line of sight (LOS) and therefore is not susceptible to occlusions. Inertial sensor tracking (IST) systems, which are based on inertial measurement units (IMUs), suffer from measurement errors intrinsic for accelerometers and gyroscopes, primarily from bias drift and random walk. EMT systems are free of these errors and overcome inertial tracking systems in their accuracy. The former provides the opportunity to obtain high-precision measurements of the sensor coordinates in 3D EM field space formed by the actuator array. Nevertheless, EMT systems have a limited application area. Such limitations are caused by significant signal changes and strict requirements set to the environment where reference EM fields are supposed to be formed. We have shown that one faces two main issues when designing an EMT system. Firstly, one should ensure a wide measurement range (up to 120 dB). Secondly, highly noise-immune measurements are required under specific operating conditions. The novelty of the presented solution is the intelligent algorithm of noise-immune conversion in conditions when the signal chain parameters are switched dynamically. This

关键词： Signal detection

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Compact Multichannel Imaging System with Wide FOV and 4x Optical Magnification 8

Compact Multichannel Imaging System with Wide FOV and 4x Opt...

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conference on Optics, Photonics, and Digital Technologies for Imaging applications VIII

作者： Katopodis, Christos Zergioti, Ioanna Papazoglou, Dimitris G. Natl Tech Univ Athens Dept Phys Iroon Polytehneiou 9 Athens 15780 Greece Fdn Res & Technol Hellas FORTH Inst Elect Struct & Laser Iraklion 71110 Greece Univ Crete Dept Mat Sci & Technol Iraklion 70013 Greece

ISBN: (纸本)9781510673151;9781510673144

A novel multichannel optical imaging system capable of high-resolution imaging across a wide field of view (FOV) of 7x7 mm(2) with a 4x magnification. Comprised by microlens arrays (MLAs) and micro-aperture arrays, our design circumvents the traditional trade-off between resolution and field size. Each channel of the system is optically isolated by micro-aperture arrays acting as field stops, ensuring high-quality imaging without crosstalk. A 5x5 step micro-scanning technique extends the imaging capability to the entire FOV. Experimental validation of the prototype, which employs commercially available MLAs and fabricated micro-aperture arrays, demonstrates agreement with theoretical predictions, achieving clear imaging without the need for a large sensor. This approach promises significant advancements in applications requiring detailed imaging over large areas.

关键词： Multichannel imaging systems Imaging systems Design Microlens array Channel projecting optics Imaging arrays Image resolution Image segmentation Image visualization Zemax

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Towards a Smart Multi-sensor Ionizing Radiation Monitoring System 26

Towards a Smart Multi-Sensor Ionizing Radiation Monitoring S...

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26th Euromicro conference on Digital System Design (DSD) / 49th Euromicro conference on Software Engineering and advanced applications (SEAA)

作者： Andjelkovic, Marko Chen, Junchao Syed, Rizwan Tariq Vargas, Fabian Ulbricht, Markus Krstic, Milos Ilic, Stefan Marjanovic, Milos Veljkovic, Sandra Mitrovic, Nikola Dankovic, Danijel Ristic, Goran Duane, Russell Vasovic, Nikola Jaksic, Aleksandar Palma, Alberto J. Lallena, Antonio M. Carvajal, Miguel A. IHP Leibniz lnst Innovat Mikroelekt Franfurt Germany Univ Potsdam Potsdam Germany Univ Nis Fac Elect Engn Nish Serbia Tyndall Cork Ireland Varadis Cork Ireland Sievert Consultancy Cork Ireland Univ Granada Granada Spain

ISBN: (纸本)9798350344196

Detection and measurement of ionizing radiation is required in a wide range of terrestrial applications, as well as in space missions. For this purpose, special instruments composed of radiation sensors and readout electronics are utilized. As ionizing radiation may affect the operation of electronic systems, radiation hardness is one of the main design requirements for radiation monitoring systems. In this work, we present a concept of a smart multi-sensor radiation monitoring system. The proposed design is based on the results achieved within the framework of EU-funded ELICSIR project. Our solution provides a new perspective on smart radiation monitoring by combining the concepts of self-awareness, self-adaptivity and artificial intelligence. This solution is suitable for applications where long-term autonomous radiation monitoring is required, such as environmental monitoring at terrestrial level or radiation monitoring in space missions.

关键词： smart radiation monitoring artificial intelligence self-awareness self-adaptivity reliability monitors

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