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

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Mathematical Model for Determining the Geometric Location of the Environmental Pollutant Based on sensor Data

Mathematical Model for Determining the Geometric Location of...

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IEEE International Workshop on Intelligent Data Acquisition and advanced Computing systems: Technology and applications

作者： Vladyslav Khaidurov Bohdan Yailymov Andrii Shelestov National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Kyiv Ukraine Space Research Institute NASU-SSAU Kyiv Ukraine

The practical result of this work is the development of a generalized mathematical model for determining the position of an environmental pollutant. Computer simulation was carried out in order to verify the developed mathematical model. A number of computational experiments were conducted to verify the mathematical model. In the future, the developed algorithm is proposed to be used for real ground air quality measurement stations with additional use of air quality information from satellite data and specify the location of the pollution source using the Urban Atlas.

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Virtual sensor for Door Opening Detection and Anomaly Detection Using Machine Learning

Virtual Sensor for Door Opening Detection and Anomaly Detect...

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International conference on Intelligent systems applications to Power systems (ISAP)

作者： Almir Neto Luis Gomes Zita Vale Federal Institute of Education Science and Technology of Maranhão (IFMA) São Luís Brazil GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto (P.PORTO) Porto Portugal

ISBN: (数字)9798331531751

ISBN: (纸本)9798331531768

Currently, several studies are being developed using machine Learning with the aim of replacing real sensors with virtual sensors. One of the biggest challenges is obtaining quality data to enable the system modeling. This article proposes the replacement of a light dependent resistor sensor, applied to a refrigerator, which detects whether the door is open or closed and an anomaly test when the door is forgotten open for too long. The use of tiny machine learning is applied to ESP32 to enable the use of regression and classification models to detect the door opening and anomaly. The tested metrics for the regression were the root mean squared error. The comparative results between the virtual and real sensors are satisfactory with an accuracy of 99.59% for classification and a root mean squared error value of 0.01 for regression. Furthermore, a prototype was developed, and the model was embedded in the ESP32 microcontroller.

关键词： Temperature sensors Temperature measurement Microcontrollers Soft sensors Tiny machine learning Neural networks Prototypes Virtualization Intelligent sensors Anomaly detection

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UiAbot: A Versatile Autonomous Mobile Robot Platform for Research and Education

UiAbot: A Versatile Autonomous Mobile Robot Platform for Res...

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IEEE conference on Industrial Electronics and applications (ICIEA)

作者： Daniel Hagen Martin Mæland Tarjei Skotterud Martin Dahlseng Hermansen Husam Haij Martin Sauar Wad Dep. of Engineering Sciences University of Agder Grimstad Norway

ISBN: (数字)9798350360868

ISBN: (纸本)9798350360875

This paper presents UiAbot, an innovative autonomous mobile robot platform developed at the University of Agder to bridge the gap in hands-on robotics education. Using cost-effective sensors and the Robotic Operating System with the Navigation Stack, this internally developed platform facilitates advanced autonomous navigation, surpassing predecessors such as the TurtleBot3 in flexibility, functionality, and affordability. Integrated into master courses and research, the UiAbot demonstrates its effectiveness as an educational and research platform, showcasing the impact of open source technologies in democratizing robotics research and enhancing educational methodologies in autonomous systems.

关键词： Technological innovation Simultaneous localization and mapping Service robots Navigation Operating systems Education sensor systems

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Applied Machine Learning for Securing the Internet of Medical Things in Healthcare 37th

Applied Machine Learning for Securing the Internet of Medica...

引用

37th International conference on advanced Information Networking and applications, AINA 2023

作者： Lu, Wei Department of Computer Science Keene State College USNH KeeneNH United States

ISBN: (纸本)9783031284502

Integrating mobile computing technologies and human health activities using IoMT devices can accelerate biomedical discovery and improve the efficiency of healthcare research and delivery. However, the quality of the collected health data is critical for the success of these efforts. In this paper, a hybrid intrusion detection system is proposed to identify cyberattacks in real time on medical devices. The system combines a logistic regression-based detector using network traffic features with a gradient-boosted tree-based detector using medical sensor features. Evaluation of the system using a publicly available dataset shows an accuracy score of 95.4% using only 11 features, compared to the current best accuracy of 92.98% achieved by artificial neural networks using 40 features. Additionally, by combining the decisions of the two individual detection systems, the number of attacks detected is increased from 111 to 305 out of a total of 423 attack instances, improving the sensitivity score and addressing the challenge of effectively and efficiently integrating different detection technologies in a hybrid intrusion detection system. To the best of the authors’ knowledge, this is the first attempt to combine multiple misuse detection models in a hybrid system to secure both IoMT devices and their networking equipment across the entire healthcare spectrum of the IoMT. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Hybrid systems

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

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

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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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A TENG Finger sensor Enabled Human-Machine Interface for VR applications

A TENG Finger Sensor Enabled Human-Machine Interface for VR ...

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IEEE Region 10 International conference TENCON

作者： Chuyang Wu Zhongda Sun School of Electrical and Information Engineering Tianjin University Tianjin China the Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (数字)9798350350821

ISBN: (纸本)9798350350838

A wireless, triboelectric nanogenerator (TENG) sensor enabled handle-like human-machine interface (HMI) is proposed to capture finger motions and manipulate game objects in virtual reality. By utilizing advanced signal processing methods including logarithmic transform and integration, peak-like TENG signals are transformed into stage-like signals to achieve continuous control. Haptic feedback supported by vibrators can bring better game experiences to players. Finally, a gesture recognition system based on processed sensor signals is also developed to categorize 10 common gestures.

关键词： Wireless communication Wireless sensor networks Human-machine systems Games Transforms Gesture recognition Virtual reality Haptic interfaces Voltage control Wireless fidelity

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Classification of Coverage Algorithms in Multimedia Wireless sensor Networks 5

Classification of Coverage Algorithms in Multimedia Wireless...

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5th IEEE International conference on Networking and advanced systems, ICNAS 2021

作者： Bouhali, Manel Bendjeddou, Amira Ghoualmi-Zine, Nacira Badji Mokhtar-Annaba University Networks and System Laboratory Computer Science Department Annaba Algeria

ISBN: (纸本)9781665428217

In recent years, with the technological development that we are witnessing, the multimedia wireless sensor networks (WMSNs) are attracting more and more interest from researchers, these later are used in various applications for their advantages and reliability. However, the WMSNs have different problems that become the focus of attention of researchers who strived to make various proposals to address these problems. The best-known and popular problem for this type of network is improving and optimizing their coverage. In this paper, several approaches for the coverage optimization problem in the multimedia wireless sensor networks are presented and the advantages and limitations of each one of them are highlighted. Then, a classification of these approaches is made. © 2021 IEEE.

关键词： Heuristic algorithms

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advanced Color Sorting Conveyor System Using Arduino and TCS3200 Color sensor for Precise Color Classification

Advanced Color Sorting Conveyor System Using Arduino and TCS...

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International conference on Robotics,Electrical and Signal Processing Techniques (ICREST)

作者： Mushfiqur Rahman Habib A Hasan Yeasin Arafat Emon Arafat Hossain Abu Rubayat Rokon Muhibul Haque Bhuyan Department of Electrical and Electronic Engineering American International University-Bangladesh Dhaka Bangladesh

ISBN: (数字)9798331530952

ISBN: (纸本)9798331530969

This paper introduces an Arduino-based color-sorting conveyor belt system that automates object sorting by color. Employing a TCS3200 color sensor, an Arduino microcontroller detects red, green, and blue objects. Servo motors and IR sensors are utilized to sort objects accurately based on their color, while an LCD screen provides real-time feedback. The conveyor belt's motor controller regulates speed and direction, pausing during color detection for precise sorting. Experimental results demonstrate 100% efficiency in color detection and sorting, highlighting the system's potential for industrial automation applications.

关键词： Automation Microcontrollers Color Signal processing Robot sensing systems Belts Liquid crystal displays Real-time systems Servomotors Sorting

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The applications of Nano-Piezoelectric Composite in Flexible Wearable Self-Powered System 2

The Applications of Nano-Piezoelectric Composite in Flexible...

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2nd International conference on advanced Materials and Chemical Engineering, AMCE 2022

作者： Chen, Xinyu Materials Science and Engineering Hubei University Hubei Wuhan430062 China

Nanomaterials have permeated every sphere of life, industry, and research. Due to the unique piezoelectric properties of nanometer materials and piezoelectric types, it is possible to convert mechanical energy into electricity by certain mathematical relationships, equivalent to the energy supply for equipment. This capability allows for the creation of sensitive sensor elements that can perceive the external environment on various levels, including thermal, mechanical, electrical, and optical. The generation of piezoelectric nanogenerators indicates that nanomaterials devices can be expected to achieve a natural self-powered system without external power or only provide a small amount of energy, and play an irreplaceable role in the fields of microelectronics, artificial intelligence, and human-computer interaction. In this review, examples of nano-piezoelectric ceramic materials and nano-piezoelectric polymers that can be applied to flexible self-powered systems are listed, and the advantages and problems of these two kinds of materials in flexible self-powered systems are comprehensively analyzed. This paper focuses on the performance improvement of 0-3 nano-composites on the original piezoelectric ceramics and polymer materials and their application in the flexible wearable self-powered system. In addition, it summarizes the difficulties and challenges in their practical applications and provides future research directions for researchers. © Published under licence by IOP Publishing Ltd.

关键词： Piezoelectric ceramics

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Scalable Client-Server Home Automation over Wireless Networks

Scalable Client-Server Home Automation over Wireless Network...

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Intelligent systems for Cybersecurity (ISCS), International conference on

作者： Shashank Jagtap Shubham Shirke Rutika Shinde Reena Sonkusare Sneha A. Weakey Electronics and Telecommunication Department Sardar Patel Institute of Technology Mumbai India

ISBN: (数字)9798350375237

ISBN: (纸本)9798350375244

The paper 'Scalable Client-Server Lamp Automation & Monitoring Over Wireless Networks' introduces an advanced lamp control system. By combining modern wireless networks, smart presence sensors, and a strong client-server setup, this system not only controls lamps but also monitors data comprehensively. Going beyond basic on/off IOT functions, it allows detailed lamp control and insightful analysis of usage patterns. This project aims to redefine how lamps are automated, providing a flexible and connected setup. The paper explains the system's design, technical details, and practical applications, highlighting its adaptability in various settings. Its importance lies in making things easier, and more efficient, and embracing new technology. This effort aims to set higher standards in lamp automation, contributing to the development of smarter, more connected Iiving spaces.

关键词： Wireless sensor networks Automation Wireless networks Lighting Control systems sensor systems Energy efficiency

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