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检索条件"任意字段=Conference on Advanced Sensor Systems and Applications"

共 4752 条记录，以下是61-70 订阅

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Quantitative Analysis and Optimization of sensor Deployment for Enhanced Activity Recognition in Smart Home Environments: A Multidimensional Approach to Data-Driven Intelligence and Efficiency in Universal Computing Spaces

Quantitative Analysis and Optimization of Sensor Deployment ...

引用

2024 International conference on Advancements in Power, Communication and Intelligent systems, APCI 2024

作者： Aziz, Khalid Dua, Sakshi Gupta, Prabal Lovely Professional University Punjab Phagwara India

ISBN: (纸本)9798350363289

This paper presents a comprehensive study on the enhancement of smart home automation and monitoring systems through the application of advanced activity recognition algorithms and sensor deployment optimization. We start by taking a CASAS dataset capturing a wide range of daily living activities, detected through an array of environmental sensors. This study conducts an in-depth analysis of activity recognition performance, leveraging precision, recall, and f1score metrics to identify areas for improvement in existing machine learning models. Further, we investigate sensor activation data to propose optimizations in sensor deployment, aimed at increasing the accuracy of activity recognition while reducing unnecessary sensor data processing. Through temporal analysis of activity patterns, we develop predictive models that forecast future activities with significant accuracy, facilitating smarter resource management and personalized automation strategies. This paper also explores the implications of our findings on user experience enhancement. Our methodology showcases the integration of machine learning techniques, statistical analysis, and practical considerations for deploying smart home technologies. The results indicate a promising avenue for future research and development in smart environments, with potential applications extending beyond residential settings to include healthcare facilities and office spaces. The findings underscore the importance of adaptive and intelligent systems in enhancing the quality of life through technology. © 2024 IEEE.

关键词： Smart homes

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The Optimal Design of a Rotor System with Elastic Ring 10

The Optimal Design of a Rotor System with Elastic Ring

引用

10th IEEE International conference on Dependability in sensor, Cloud and Big Data systems and applications, DependSys 2024

作者： Shi, Yihang Yang, Zhongyu Feng, Yinli Liu, Di University of Chinese Academy of Sciences Chinese Academy of Sciences School of Aeronautics and Astronautics Natl. Key Lab. of Sci. and Technol. on Adv. Light-duty Gasturbine Inst. of Engineering Thermophysics Beijing China University of Chinese Academy of Sciences Chinese Academy of Sciences School of Engineering Sciences Natl. Key Lab. of Sci. and Technol. on Adv. Light-duty Gasturbine Inst. of Engineering Thermophysics Beijing China Chinese Academy of Sciences Institute of Engineering Thermophysics National Key Laboratory of Science and Technology on Advanced Light-duty Gasturbine Beijing China

ISBN: (纸本)9798331540500

Elastic ring (ER) is widely adopted for its compact size and ease of assembly and have become a prevalent type of elastic support within rotor-support systems. However, it may exhibit stiffness nonlinearity under specific operating conditions, potentially compromising the safety of the rotor system. This paper examines the influence of elastic ring stiffness on the critical speed of a specific aero-engine rotor support structure, focusing on related nonlinear phenomena. The Levenberg-Marquardt method was employed to optimize key parameters, including the stiffness and clearance of the elastic ring, with the second-order critical speed as the optimization goal. Finite element analysis was performed to validate the optimization results, which were found to be both effective and practically applicable. The finding provides a significant reference for the design and analysis of aero-engine rotor systems and similar applications. © 2024 IEEE.

关键词： Optimal systems

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Investigation of Hardware-Software Solutions for an Energy-Efficient Wireless sensor Network 12

Investigation of Hardware-Software Solutions for an Energy-E...

引用

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

作者： Yatsenko, Anastasiia Parkhomenko, Anzhelika Wolff, Carsten Tulenkov, Artem Parkhomenko, Andriy National University Zaporizhzhia Polytechnic Zaporizhzhia Ukraine Institute for the Digital Transformation of Application and Living Domains University of Applied Sciences and Arts Dortmund Germany

ISBN: (纸本)9798350358056

This work is devoted to the study of methods and tools for minimizing power consumption of wireless sensor networks. The results of processing experimental data for various operating modes of network nodes, as well as options for organizing their power supply and software settings are given. Practical recommendations have been developed to improve the energy efficiency of wireless sensors networks for the Smart Home systems. © 2023 IEEE.

关键词： communication module energy efficiency Smart Home system solar panel wireless sensors network

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A Predictive Maintenance Platform for a Conveyor Motor sensor System Using Recurrent Neural Networks 5th

A Predictive Maintenance Platform for a Conveyor Motor Senso...

引用

5th International conference on Neural Computing for advanced applications (NCAA)

作者： Kiangala, Kahiomba Sonia Wang, Zenghui Univ South Africa UNISA Dept Elect & Smart Syst Engn ZA-1709 Johannesburg Gauteng South Africa

ISBN: (纸本)9789819770007;9789819770014

Since the effusion of Industry 4.0 (I40) and smart manufacturing, predictive maintenance (PdM) has become critical to prevent severe system breakdowns and costly production downtime in various industries. Several state-of-the-art Artificial Intelligence (AI) approaches, such as machine learning models (ML), empower the PdM design concept to produce more accurate outcomes. In this study, we propose the development of a PdM platform that effectively detects future possible warnings and failures in the vibration speed sensor of a conveyor motor. We build the platform backend using recurrent neural networks (RNN) regression ML models to predict vibration speed values and their trends. We train our RNN models using univariate time-series historical vibration sensor data recorded over the years. The experimental results demonstrate the robustness of our platform built on RNN models compared to other traditional regression machine learning models such as Extreme Gradient Boosting (XGboost). We compare the effectiveness of the PdM platform with two RNN models: a basic RNN model and a long short-term memory (LSTM) model. Unlike other regression PdM systems focusing on predicting devices Remaining Useful Life (RUL), our PdM platform forecasts and generates new vibration sensor data based on the desired future time range. It also pinpoints set warning and failure values and indicates when these faults are more likely to occur. Factories can utilize this feature for analytics purposes.

关键词： Conveyor Motor sensor Predictive Maintenance (PdM) Recurrent Neural Networks (RNN) Regression Models time-series data

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Smart systems for Precision Agriculture, Environmental Protection and Healthcare 12

Smart Systems for Precision Agriculture, Environmental Prote...

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

作者： Romanov, Volodymyr Galelyuka, Igor Hrusha, Volodymyr Voronenko, Oleksandr Kovyrova, Oleksandra Antonova, Hanna Kedych, Anna V.M. Glushkov Institute of Cybernetics National Academy of Sciences of Ukraine Kyiv03187 Ukraine

The paper represents the result of developments of the Institute of Cybernetics of NAS of Ukraine in the field of smart systems for precision agriculture, environmental protection and healthcare. Main conceptions, str... 详细信息

ISBN: (纸本)9798350358056

关键词： digital agriculture environmental protection healthcare wireless sensor network

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Wearable Electronic Textiles for Healthcare, Wellbeing, and Protective applications

Wearable Electronic Textiles for Healthcare, Wellbeing, and ...

引用

CHI conference on Human Factors in Computing Sytems (CHI)

作者： Hughes-Riley, Theo Shahidi, Arash M. Marasinghe, Kalana Rahemtulla, Zahra Ehelagasthenna, Malindu Ebrahimi, Parvin Arm, Richard Oliveira, Carlos Holmquist, Lars Erik Dias, Tilak Nottingham Trent Univ Nottingham Sch Art & Design Nottingham England

ISBN: (纸本)9798400703317

Electronic textiles (E-textiles) can act as an exceptional substrate for incorporating sensing devices for monitoring physiological parameters, as they are comfortable to wear close to the skin. This makes them excellent for a variety of applications in the healthcare, wellbeing, and personal protection sectors. One method of creating E-textiles with good textile properties is to integrate an electronic component into a yarn to create an electronic yarn (or E-yarn), which can then be used to construct a textile. This Interactivity Lab Demonstration will present electronic textiles developed by the advanced Textiles Research Group (ATRG) from Nottingham Trent University (UK). The group has conducted a wealth of research into the development of E-yarns and the incorporation of these into textiles and garment. At CHI, users will be able to interact with textiles capable of fall and near-fall detection, temperature sensing, acoustic sensing, giving haptic feedback, and harvesting solar energy.

关键词： Electronic textiles E-textiles wearables sensor systems health wellbeing

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Designing A Fall Detection System for Elderly People in Smart Healthcare IoT Using Multi sensor Data Fusion

Designing A Fall Detection System for Elderly People in Smar...

引用

2024 International conference on Artificial Intelligence and Quantum Computation-Based sensor applications, ICAIQSA 2024

作者： Krishna, Awantika Yadav, Brijkant Prakash, Devansh Dwivedi, Rajendra Kumar University of Technology Madan Mohan Malaviya Department of ITCA Gorakhpur India

ISBN: (纸本)9798331517953

This study presents a novel approach to deal with prototyping a smart healthcare IoT framework for precise fall detection in older adults using multi-sensor data fusion. The proposed framework utilizes advanced filtering and context-aware analysis to enhance the accuracy of fall detection, addressing key challenges in current systems such as high false positives and slow reaction times. A MPU6050 accelerometer and gyrator, incorporated with an ESP32 microcontroller, is used to distinguish falls while limiting false-alarms precisely. The framework utilizes Blynk, an IoT platform, to work with continuous observing and warnings. The methodology includes gathering information from the MPU6050 sensor, handling it with the ESP32, and utilizing AI calculations to separate falls from different exercises of everyday living. The system includes coordinating wearable sensors with lightweight AI calculations to guarantee continuous location and similarity with low-power gadgets. The discoveries exhibit improved reliability, sensibility, and real-world applicability of the system in elderly care settings. This research has critical ramifications for improving the wellbeing and freedom of older adults by giving convenient mediation in case of a fall. © 2024 IEEE.

关键词： Wearable sensors

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Power-of-Two Quantized YOLO Network for Pedestrian Detection with Dynamic Vision sensor 26

Power-of-Two Quantized YOLO Network for Pedestrian Detection...

引用

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

作者： Przewlocka-Rus, Dominika Kryjak, Tomasz AGH Univ Krakow Dept Automat Control & Robot Krakow Poland

ISBN: (纸本)9798350344196

Pedestrian detection algorithms have a wide range of applications: from video surveillance, to driver assistance systems and autonomous vehicles. The performance of these systems must be as high as possible, with minimal response time and, due to the often battery-powered operation (like in electric vehicles), low energy consumption. When designing such solutions, we therefore face challenges typical for embedded vision systems: the problem of fitting algorithms of high memory and computational complexity into small low-power devices. In this paper, we propose a system based on a Dynamic Vision sensor (DVS), which has low power requirements and operates well in conditions with variable illumination. It is these features that may make event cameras a preferential choice over frame cameras in some applications. To ensure high accuracy, for pedestrian detection we use the YOLO (You Only Look Once) deep network on event data representation. Due to the high complexity of the applied algorithm, we propose a low precision architecture: the weights of the convolution layers are quantized logarithmically to 4 bits powers-of-two values (PoT quantization). Such compression reduces not only the memory complexity by almost 8x, but also the computational complexity by replacing most multiplication operations with bit-shifting, due to use of powers-of-two weights. At the same time, the proposed system achieves the accuracy on par with the floating point baseline, of mAP0.5 0.708.

关键词： pedestrian detection logarithmic quantization power-of-two quantization energy efficiency embedded vision systems dynamic vision sensor

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Mm-wave wireless sensor networks with zero energy consumption thUough backscattering metasurfaces 25

Mm-wave wireless sensor networks with zero energy consumptio...

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25th International conference on Electromagnetics in advanced applications, ICEAA 2024

作者： Costa, F. Genovesi, S. Rodini, S. Manara, G. Dipartimento di Ingegneria dell’Informazione Università di Pisa Pisa56122 Italy

ISBN: (纸本)9798350360974

The future of 6G communications emphasizes a deep understanding of human environments for improved quality of life and work efficiency. IoT sensors will play a crucial role, gathering extensive data about living environments for tasks like environmental monitoring and structural oversight [1]. The success of these systems hinges on cost-effectiveness, energy efficiency, and minimal maintenance requirements. Traditional IoT sensors, despite advancements, still face challenges such as power consumption and limited lifespans, particularly in indoor settings where energy harvesting is difficult. RFID sensors offer potential with their ability to transmit data without additional power, but their cost and reliability in harsh environments pose barriers to widespread adoption [2]. © 2024 IEEE.

关键词： Environmental monitoring

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The Data Communication Transmitter and Receiver for a 5.8 GHz AIPAA MPT-sensor System by ICEt Technology 31

The Data Communication Transmitter and Receiver for a 5.8 GH...

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31st Asia-Pacific Microwave conference (APMC) - Microwave Linking the World

作者： Lin, Zhengdong Kobuchi, Daisuke Narusue, Yoshiaki Suda, Tamotsu Kawasaki, Shigeo Univ Tokyo Grad Sch Engn Tokyo Japan Space&Mobile Wireless Technol Inc Tokyo Japan

ISBN: (纸本)9781665494182

This paper presents the fabrication of an Active Integrated Phased Array Antennas (AIPAA) sensor system prototype utilizing Information, Communication & Energy transfer (ICEt) technology. Through the high-density integration of hardware components and software algorithms, this system enables adaptive adjustments in diverse scenarios, leading to optimal system performance. The proposed prototype demonstrates the capability to fulfill sensing, communication, and energy transfer tasks in various environments, including spacecraft exploration and river disaster warning systems. This research represents a significant step towards the development of advanced wireless sensor networks with ICEt technology for multifunctional applications.

关键词： Active integrated phased array antenna microwave power transmission wireless sensor networks

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