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检索条件"任意字段=International Conference on Sensor Technologies and Applications, SensorComm"

共 9453 条记录，以下是1131-1140 订阅

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Efficient Human Activity Recognition through Multi-sensor Data and Deep Learning Techniques

Efficient Human Activity Recognition through Multi-Sensor Da...

引用

Advanced Computing technologies (ICoACT), international conference on

作者： Rhenius A Anitha J Immanuel Alex Pandian S CSE KITS Coimbatore India

ISBN: (数字)9798331509859

ISBN: (纸本)9798331509866

Extensive research takes place in the field of Human Activity Recognition (HAR) systems with wearable computing that helps in healthcare applications, fitness tracking and smart environments. sensor technology advances have propelled Human Activity Recognition systems to utilize innovative machine learning methods for accurate and robust activity classification. This work evaluates the effectiveness of four cutting-edge deep learning models-Temporal Convolutional Networks (TCN), Long Short-Term Memory (LSTM), Recurrent Neural Networks (RNN) and Gated Recurrent Units (GRU)-through their implementation on publicly accessible accelerometer and gyroscope HAR datasets. These classification models underwent testing through different activation functions namely ReLU, Leaky ReLU, and Swish to assess their practicality for classification operations. Standard evaluation metrics including accuracy, precision, recall, ROC-AUC and F1-score demonstrate the best features of each implemented model while providing descriptive visual representations. TCN delivered 98.59% accuracy and exhibited superior training speed efficiency thus establishing itself as the suitable AI algorithm for real-time implementation. This research offers an extensive breakdown for choosing optimal models in real-time HAR systems which supports advances in wearable computing and activity recognition technologies.

关键词： Deep learning Training Visualization Accuracy Computational modeling Real-time systems Human activity recognition Convolutional neural networks Wearable devices Long short term memory

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Deep Learning-based Out-of-Distribution Detection and Recognition of Human Activities with IMU sensors 1

引用

14th international conference on Sensing Technology, ICST 2022

作者： Lyons, Niall Santra, Avik Pandey, Ashutosh Infineon Technologies Dublin Ireland Infineon Technologies Neubiberg85579 Germany Infineon Technologies IrvineCA United States

ISBN: (数字)9783030988869

ISBN: (纸本)9783030988852

Human activity classification has several applications in smart homes, healthcare and human-machine interaction systems. Several human activity recognition systems using IMU sensors, namely accelerometer and gyroscope, have been proposed in literature. In this paper, we propose an improved integrated solution involving two stages with detection network followed by recognition network for classification of human activities. In a practical deployed environment, the IMU sensor is expected to encounter out-of-distribution (OoD) samples due to sensor degradation, alien operating environment or unknown activities. To handle such adverse examples we propose to use generalized out-of-distribution detector for Neural Networks (ODIN), which also acts to engage the following recognition network only when a valid activity example is encountered leading to power saving. Furthermore, compared to conventional cross-entropy based loss function, we propose quadruplet-loss to train our activity recognition network leading to improved classification and clustering scores. We demonstrate the performance of our proposed solution using commercial off-the-shelf IMU sensors. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Accelerometers

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Mesh Network Application 8

Mesh Network Application

引用

8th international conference on Military technologies, ICMT 2021

作者： Hopjan, Miroslav University of Defence Department of Communiation Technology Electronic Warfare and Radiolocation Brno Czech Republic

The paper brings a survey of ad hoc networks, their basic classification and characteristic features. Overview of routing concepts explains differences between infrastructure and mesh networks. More detailed insight i... 详细信息

ISBN: (纸本)9781665437240

关键词： Wireless sensor networks

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Square Shaped MEMS Capacitive Pressure sensors for Biological applications 1

Square Shaped MEMS Capacitive Pressure Sensors for Biologica...

引用

1st international conference on technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Suman Bhatia, Deepak Department of Electronics Engineering Rajasthan Technical University Rajasthan Kota324010 India

ISBN: (纸本)9781607685395

The focus of this study is on mathematical modelling analysis and simulation of a micromechanical system based on a capacitive pressure sensor with a square diaphragm of 500 μm × 500 μm. The mechanical operation of the suggested device under the impact of a uniform pressure range employing different materials on the same arrangement is the subject of this research. The principle, design and comparative analysis of several MEMS materials are covered in this work. The deflection of the capacitive pressure sensor of roughly 0.285 μm and 30.36 pF, as well as the change in the capacitance value, are used to evaluate the device's performance. At a maximum pressure of 20 kPa at room temperature, the sensor's sensitivity is 56.24× 10-6 pF/pa, and the sensor's response time is also reduced under static and dynamic loading circumstances. It can be seen that graphene materials have linear, stable, and repeatable properties when subjected to a uniform pressure range. © The Electrochemical Society

关键词： Capacitance Capacitive Pressure sensor Deflection Graphene Sensitivity

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IoT Based Temperature Control System of Home by using an Android Device 1

IoT Based Temperature Control System of Home by using an And...

引用

1st international conference on Emerging Smart technologies and applications (eSmarTA)

作者： Foysal, Musfiqur Rahman Hossain, Refath Ara Islam, Mohammad Monirul Sharmin, Shayla Moon, Nazmun Nessa Daffodil Int Univ Dept Comp Sci & Engn Dhaka Bangladesh

ISBN: (纸本)9781665411530;9781665440783

This IoT-based architecture research project is created for people who are familiar with emerging smart technologies. This project is primarily based on controlling the voltage of AC-supported equipment and developing an automatic temperature ventilation system that can make a space fully temperate. Additionally, this will protect our appliances from overheating. Using the widely used Node MCU microcontroller and IP networking for remote access and control, this project aims to automate machines and appliances. You can also use an Android-based smartphone app to access these computers while you are not at work. Many electrical and appliances, such as lamps, fans, and refrigerators, can be controlled by an Android smartphone, which can also help against overheating. This technology is more valuable in today's world in business environments where temperature control is a big concern. The proposed voltage control scheme has been combined with products such as an AC lamp, an AC fan, and a DC cooling fan to demonstrate its feasibility and effectiveness.

关键词： IoT Node MCU Microcontroller Blynk App Voltage Control Temperature sensor LDR

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Attack Detection in IoT using RF and ANN

Attack Detection in IoT using RF and ANN

引用

Smart Information Systems and technologies (SIST), IEEE international conference on

作者： Aigul Adamova Tamara Zhukabayeva Nurgalym Adamov Department of Computer Engineering Astana IT University Astana Kazakhstan Faculty of Information Technology L.N. Gumilyov Eurasian National University Astana Kazakhstan Astana International University Astana Kazakhstan

ISBN: (数字)9798350374865

ISBN: (纸本)9798350374872

Internet of Things (IoT) devices are the weak link in organizing a Wireless sensor Network. Various Attacks on IoT devices can lead to different complex consequences. Real applications of the IoT generate a large amount of data every second, the confidentiality of which is of very high value. Therefore, detecting attacks in IoT interactions is of paramount interest from both science and industry. Among various attack detection approaches, machine learning methods show great potential due to their early detection ability. The paper presents a methodology for detecting attacks based on two machine learning methods: Random Forest (RF) and Artificial Neural Network (ANN). To conduct the experiment, various data sets were considered, the descriptions of which are given in the work. The experiment was carried out using open data sets obtained from real IoT devices. As a result, RF demonstrated a high accuracy of 98.6%.

关键词： Training Performance evaluation Wireless sensor networks Accuracy Training data Artificial neural networks Internet of Things

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Recent Advances in the Synthesis, Characterization of Pure and Doped NiO Nanostructures for Gas sensor applications 1

Recent Advances in the Synthesis, Characterization of Pure a...

引用

1st international conference on technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Manjunatha, C. Khosla, Ajit Hari Krishna, R. Vijay Kumar, P. Chakraborty, Sujan Krishna, M. Department of Chemistry RV College of Engineering Bengaluru560059 India RV College of Engineering Bengaluru560059 India Department of Mechanical System Engineering Graduate School of Science and Engineering Yamagata University Yamagata Yonezawa992-8510 Japan Department of Chemistry Ramaiah Institute of Technology Bengaluru560054 India Department of Mechanical Engineering RV College of Engineering Bengaluru560059 India

ISBN: (纸本)9781607685395

Nowadays, developing the nanomaterials for the sensors capable of sensing at low temperature is given prime importance. In line with this review describes the latest investigations on the effect of metal ion doping on nickel oxide (NiO) sensor capabilities towards various gases. NiO is used as base material of the sensor because of its p-type semiconducting behaviours and its long term stability, transition metals like Fe, W, Cu, Sn, Nb, In, Ti and Zn are used as dopants because of their good thermal and electrical conductivity. In this short review article, various synthesis approaches to prepare doped NiO nanostructures and their structural feature are discussed. The development of sensor device using doped NiO nanostructures and investigation of its sensing property for various gasses such as xylene, methane, ethanol, butanol, NO2, etc are discussed in detail. At the end all the sensing results were correlated and proposed the suitable conditions, to develop the potential doped nanoscaled NiO for better sensor applications. © The Electrochemical Society

关键词： Doped NiO Gas sensor H2 sensor Methane sensor Nanomaterials Nickel Oxide

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Flexible Pressure sensors and Their applications in Wearable Electronics 4

Flexible Pressure Sensors and Their Applications in Wearable...

引用

4th international Academic Exchange conference on Science and Technology Innovation, IAECST 2022

作者： Yu, Mujun Zhang, Yang Han, Yuchen Zhang, Yuzhen Nanjing University of Posts and Telecommunications School of Communications and Information Engineering Nanjing China Suzhou Foreign Language School Suzhou China University of Sheffield Electronic and Electrical Engineering Sheffield United Kingdom Fuzhou University Maynooth International Engineering College Fujian China

ISBN: (纸本)9798350320008

With the development of modern technology, flexible human-machine interaction, artificial intelligence, portable detection, and other emerging fields have been built up. The demand for high flexibility in these fields leads to flexible pressure sensors getting more and more attention. Using flexible materials can enable them to realize the pressure sensing function while giving them lighter weight, smaller size, and better deformation ability. These characteristics make flexible pressure sensors can be widely used in emerging fields and have more longterm development potential. In recent years, many technologies have been devoted to improving the performance of flexible pressure sensors. Among them, microstructure engineering is the most significant for high-performance flexible sensors. This review focuses on the rapid development of flexible pressure sensors and the microstructure of high-performance flexible sensors. This article describes four sensing mechanisms: capacitive, resistive, piezoelectric, and triboelectric. Besides, the microstructure system, which can improve the sensitivity of capacitive flexible pressure sensors, is discussed comprehensively. In addition, the current applications of the capacitive flexible pressure sensor are introduced. Furthermore, this article discusses prospects for developing direction and application fields of high-performance flexible pressure sensors according to some currently developed microstructure technologies. The research in this review has essential foreshadowing significance and reference value for developing flexible pressure sensors in various intelligent fields in the future. © 2022 IEEE.

关键词： Pressure sensors

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Unsupervised Learning of Wearable sensor Data for Assessing Upper Limb Function

Unsupervised Learning of Wearable Sensor Data for Assessing ...

引用

Communication, Computing and Energy Efficient technologies (I3CEET), international conference on

作者： Samweslin S Janani S S. G. Hymlin Rose Department of ECE PeriyarManiammai Institute of Science and Technology Vallam Thanjavur India Department of ECE Periyar Maniammai Institute of Science and Technology Vallam Thanjavur India Department of ECE RMD Engineering College Kavarapettai India

ISBN: (数字)9798331541583

ISBN: (纸本)9798331541590

Assessment of upper limb function is integral to both rehabilitation and clinical care, guiding tailored treatment plans and monitoring patient progress. Recent advances in wearable sensor technology and unsupervised learning offer promising avenues for objective and continuous evaluation of upper limb function. This review paper offers an in-depth exploration of the application of unsupervised learning techniques to wearable sensor data for this *** with an examination of the limitations inherent in traditional assessment methods, the review highlights the growing demand for more sophisticated approaches capable of capturing the nuanced movements of the upper limb. Wearable sensor technologies, including inertial measurement units (IMUs), electromyography (EMG), and force sensors, are introduced for their potential to provide real-world movement data. Furthermore, the review elucidates the principles of unsupervised learning, focusing on clustering algorithms and dimensionality reduction techniques as key tools for analysing sensor data without the need for labelled training samples.A thorough review of existing literature showcases the diverse applications of unsupervised learning approaches in upper limb function assessment, ranging from motion pattern recognition to gesture classification and motor performance evaluation. Case studies and research findings demonstrate the effectiveness of these methods in identifying abnormal movement patterns, monitoring rehabilitation progress, and offering objective feedback to patients and *** challenges such as data variability, model interpretability, and integration into clinical practice, the review underscores the need for further research and development in this field. It concludes by emphasizing the transformative potential of unsupervised learning and wearable sensor technology in advancing upper limb rehabilitation and clinical *** summary, this review paper serves as a comp

关键词： Limbs Measurement units Reviews Inertial navigation Motors Electromyography Wrapping Unsupervised learning Wearable sensors Monitoring

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SoK on DLT Solutions for Agri-food Traceability

SoK on DLT Solutions for Agri-food Traceability

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Blockchain Computing and applications (BCCA), international conference on

作者： Fabio Scanu Giovanni Farina Silvia Bonomi Sapienza University of Rome Rome Italy

ISBN: (数字)9798350351538

ISBN: (纸本)9798350351545

This paper reviews the application of distributed ledger technologies (DLT) in food traceability systems, noting the benefits and growing adoption of DLT despite limited details on implementation and architecture. The study addresses this gap by analyzing the hardware, software, and DLT platforms discussed in the scientific literature. Most projects are in early development, focusing on proof-of-concept stages, with Ethereum and Hyperledger as the dominant platforms. However, the rationale for these choices is often unclear. The findings suggest significant potential for DLT in food traceability, although the sector is still nascent and requires more rigorous methodological approaches to improve effectiveness and scalability.

关键词： Distributed ledger Scalability Supply chains Smart contracts Prototypes Software Hardware sensor systems Blockchains Systematic literature review

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