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检索条件"任意字段=IEEE International Conference on Embedded and Real-Time Computing Systems and Applications"

共 36882 条记录，以下是421-430 订阅

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Internet of Things in Robotic systems: Development Trends and Challenges

Internet of Things in Robotic Systems: Development Trends an...

引用

Robotics and Technologies for Industrial Automation (ROBOTHIA), ieee international conference on

作者： Jingheng Shan School of Electrical Engineering and Artificial Intelligence Xiamen University Malaysia Sepang Selangor Malaysia

ISBN: (数字)9798350356755

ISBN: (纸本)9798350356762

The integration of the Internet of Things (IoT) with robotic systems is revolutionizing various industries. This topic is crucial today as it enhances efficiency, reduces human error, and boosts automation in sectors like healthcare, manufacturing, and military. This paper surveys current advancements in IoT-aided robotic systems and highlights challenges and future research opportunities. Key advances include improved healthcare through contactless technologies, enhanced industrial safety via real-time monitoring, military applications reducing casualties, and IoT-enabled airport management. Future research will address privacy, standardization, and integration complexity, focusing on multi-robot collaboration and autonomy. The IoT-robotics convergence offers significant benefits but also presents new challenges for optimization.

关键词： Surveys Automation Service robots Medical services Standardization Robot sensing systems Airports User experience Sensors Internet of Things

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Data Fusion Algorithm in Agricultural Internet of Things System

Data Fusion Algorithm in Agricultural Internet of Things Sys...

引用

Integrated Circuits and Communication systems (ICICACS), ieee international conference on

作者： Fang Wang School of Business Changchun College of Electronic Technology Changchun China

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Agricultural production relies on a large number of sensors to obtain environmental data, and how to effectively integrate this data has become a major challenge in current agricultural IoT applications. Therefore, this article proposes a novel data fusion algorithm. Firstly, the weighted average method is used to preliminarily fuse data from different types of sensors; Then, deep neural networks (DNNs) are used to further extract potential features from the fused data. Finally, the weighting strategy and network model were optimized through experiments. The experimental results indicate that the research method performs well in terms of accuracy, spatiotemporal consistency, and real-time performance. Compared with the weighted average method, this research method reduced the mean square error (MSE) by about 29% and increased the dynamic time warping (DTW) score by about 40.7%. The results verified that the method is practical in improving data quality and suitable for large-scale data processing in agricultural IoT.

关键词： Accuracy Data integrity Data integration Artificial neural networks Production Feature extraction real-time systems Spatiotemporal phenomena Internet of Things Optimization

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Method of Tracking Inclined Geosynchronous Orbit Satellite for Satcom on-the-Move Antenna

Method of Tracking Inclined Geosynchronous Orbit Satellite f...

引用

Power Electronics, Computer applications (ICPECA), ieee international conference on

作者： Chao Qin Lianwu Guan Yanbin Gao Shuo Zhang Yuanqing Huang Yihuan Wang College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin China The 54th Research Institute of China Electronics Technology Group Corporation Shijiazhuang China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

The Inclined Geosynchronous Orbit (IGSO) satellite has garnered significant attention for its extensive coverage and high-latitude capabilities. Traditionally, tracking methods rely on Two Line Element (TLE) data for satellite position prediction. To decrease reliance on external TLE data and avoid the complex orbit prediction algorithms, this paper conducts an in-depth analysis of the orbital characteristics of IGSO satellites and the accuracy of TLE-based predictions. A tracking method that employs curve fitting is proposed. Experiment results indicate that the tracking accuracy of this method surpasses 0.1°.

关键词： Satellite antennas Satellites Accuracy Tracking Simulation Prediction algorithms Orbits real-time systems Reliability Curve fitting

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A Pathway to Efficiency and Transparency of Indian Taxation System Through AI Technologies: NLP and Big Data Analytics

A Pathway to Efficiency and Transparency of Indian Taxation ...

引用

Cognitive computing in Engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), international conference on

作者： Pooja Devi Gaurav Bagra Renu Pandey Gurleen Kaur Anand Ankita Chaturvedi Uttaranchal institute of management Uttaranchal University Dehradun India School of Management Avantika University MIT Dolphin (PG) Institute of Biomedical & Natural Sciences Dehradun India IIS (deemed to be University) Rajasthan India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

There are few Challenges in the Indian taxation system such as complexity, lack of efficiency & transparency, long procedure and compliances which makes it cumbersome. In this paper we will go through how these Challenges are faced out and overcome from it with the help of AI technologies such as natural language processing (NLP) and big data analytics. These technologies can play a transformative role in streamlining in the process of taxation. By implementing NLP, unstructured data like legal statutes, tax documents can be automatically processed, classified and interpreted. It contributes in improving the transparency, efficiency and user-friendly tax system. In parallel, big data analytics helps in detecting anomalies, reducing tax evasion and forecasting revenue collection by real time processing, advance pattern Recognition and predictive analysis. In this paper we include the various platforms for implementing these AI technologies in taxation system. We also discussed about process and applications of applying NLP & data analytics in Indian taxation system and how these technologies resolve the tax disputes of India. In this paper research methodologies involve secondary data of various good qualitative journal such as Scopus indexed and data from ieee explore and real-world practical approaches for applying NLP and big data analytics in taxation system of India.

关键词： Finance Big Data Reliability engineering Natural language processing real-time systems Filling Fraud Artificial intelligence Predictive analytics Forecasting

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Data-Driven Decision Making in Smart Health and Emergency Management

Data-Driven Decision Making in Smart Health and Emergency Ma...

引用

ieee Students' conference on Electrical, Electronics and Computer Science (SCEECS)

作者： K. Sudharson K. Selvi V. Ramu V. Monika A. SureshKumar S. Nagarajan Department of AIML R.M.D. Engineering College Chennai India Department of MBA S.A. Engineering College Chennai India Department of MBA Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering College Chennai India Department of MBA Vel Tech Ranga Sanku Arts College Chennai India Department of MBA Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering College

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

Phenomena such as smart health and emergency management systems when embedded with data-driven decision-making have become a game-changer in the field of healthcare and an emergency response. In this paper, we investigate the use of advanced data analytics, machine learning algorithms and real-time data processing in improving decision-making activities in these domains. Using data from a diverse set of large datasets such as EHRs, wearables, emergency response systems etc., we hope to build predictive models and decision support systems which can help save lives by predicting the epidemic before it peaks saving valuable time when every minute counts. The research also deals with issues such as data privacy, interoperability and real-time data integration. Early findings suggest large efficiencies and effectiveness gains in health and emergency management, showing the game-changing potential of datadriven solutions in their domains.

关键词： Epidemics Machine learning algorithms Smart healthcare Machine learning Predictive models Emergency services real-time systems Wearable devices Sustainable development Interoperability

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ASIC Design For High Speed Flash Analog To Digital Converter

ASIC Design For High Speed Flash Analog To Digital Converter

引用

Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), ieee conference on

作者： Brijesh Patel Rutu Parekh DA-IICT Gandhinagar India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

This paper presents the design and implementation of an Application Specific Integrated Circuit ( ASIC) of a high-performance 4-bit Flash Analog-to-Digital Converter (ADC) using 180nm digital CMOS technology. Designed to meet the stringent demands of high speed and low power consumption, this ADC is tailored for modern signal processing applications requiring rapid and energy-efficient data conversion. The Flash ADC leverages a fully parallel architecture, utilizing an array of precision comparators and a resistor ladder network to achieve ultra-fast conversion of analog signals into digital format. Operating at a clock frequency of 100 MHz, the proposed design delivers exceptional performance while consuming only 59.71 μW from a 1.8V supply, making it ideal for power-sensitive applications. This compact and efficient A DC underscores the critical role of Flash ADCs in enabling real-time digital signal processing across diverse domains, including communication systems, medical imaging, and high-speed instrumentation.

关键词： Application specific integrated circuits Resistors Performance evaluation Technological innovation Power demand CMOS technology real-time systems CMOS integrated circuits Transistors Analog-digital conversion

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Conformal Ultrasound Patch for real-time Blood Flow Monitoring

Conformal Ultrasound Patch for Real-Time Blood Flow Monitori...

引用

ieee international conference on Micro Electro Mechanical systems

作者： Taemin Lee Jongcheol Park Il-Seop Kim Sangho Bang Joontaek Jung Hyunjoo J. Lee School of Electrical Engineering Korea Advanced Institute of Science and Technology Korea Office of Nano Convergence Technology National NanoFab Center Korea Healcerion Co. Ltd. Korea

ISBN: (数字)9798331508890

ISBN: (纸本)9798331508906

Wearable ultrasound systems are opening up new ultrasound applications that were previously not possible with conventional handheld probes, such as continuous blood flow monitoring, which address unmet clinical needs. The wearable ultrasound systems are rapidly advancing in terms of array order, array size, conformality with human skin, and form factors. Despite these advancements, current fabrication and packaging methods remain time-intensive and lack scalability, while the acoustic interface is inefficient for prolonged monitoring sessions. To address these issues, we present a two-dimensional (2D) conformal ultrasound patch developed for real-time continuous blood flow monitoring. A 2D conformal ultrasound patch is fabricated through a stable and efficient anisotropic conductive film (ACF) bonding and packaged with a silk layer which serves both as an adhesive and as an effective acoustic interface, enhancing long-term usability. A single element of the 2D array exhibits a transmit sensitivity of 5.7 kPa/V pp and a receive sensitivity of 2.4 mV pp /kPa, which is 8.7 times higher than that of a commercial hydrophone. These acoustic properties are sufficient to monitor blood flow at 2 cm depth of the skin.

关键词： Fabrication Ultrasonic imaging Sensitivity Acoustics real-time systems Skin Biomedical monitoring Probes Monitoring Blood flow

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An image processing-based method for determining the geometry transmission ratio of a continuously variable transmission gearbox

An image processing-based method for determining the geometr...

引用

international Symposium on Applied Science 2024, ISAS 2024

作者： Tran, Dang Long Do, Tri Nhut 268 Ly Thuong Kiet Street District 10 Ho Chi Minh City Viet Nam Department of Embedded Systems and Robotics Faculty of Computer Engineering University of Information Technology Thu Duc City Ho Chi Minh City71308 Viet Nam Vietnam National University in Ho Chi Minh City Linh Trung Ward Thu Duc City Ho Chi Minh City71308 Viet Nam

Nowadays, many applications based on image processing methods are deployed to bring convenience to use due to its outstanding superior features. This paper proposes an image processing-based method for determining the geometry transmission ratio of a continuously variable transmission (CVT) gearbox made up of a push-belt and two pulleys with synchronized width adjustments. The proposed method is demonstrated by many experiments on a real system consisting of 1 Logitech C992 Pro Webcam camera and 1 CVT gearbox. The experiments were conducted on more than 100 images. The experimental results show that the method's error is between 6% and 8%, and the average processing time of 1 image is 0.07 seconds. This error depends on whether the camera position is parallel to the CVT gearbox's cross-sectional plane or not. Furthermore, the reliability of the method is evaluated by the RMSE method up to 99%. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Gears

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MULiving: Towards real-time Multi-User Survival State Monitoring Using Wearable RFID Tags

MULiving: Towards Real-time Multi-User Survival State Monito...

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international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Shang Gao Dawei Yan Yubo Yan University of Science and Technology of China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Human presence detection is crucial in various scenarios, from law enforcement surveillance to smart health-care systems. Traditional methods like cameras and acoustic signals face challenges such as privacy concerns, the need for line of sight (LoS), and susceptibility to environmental noise. This paper proposes MULiving, a real-time RFID-based system designed to monitor the survival status of multiple users simultaneously. Unlike previous RFID-based solutions, MULiving addresses two key challenges: achieving real-time detection and accurately identifying stationary users. By leveraging a signal threshold-based approach that adapts automatically to non-living states, MULiving can distinguish between living and non-living users, even during periods of minimal movement(e.g., sleep). Extensive experiments using Commercial off-the-shelf (COTS) RFID devices demonstrate that MULiving is not only highly accurate but also robust across different users, RFID tags, and behaviors. The results confirm MULiving as a promising solution for real-time multi-user survival monitoring, with significant potential for practical deployment in real-world applications.

关键词： Radio frequency Privacy Working environment noise Surveillance Signal processing real-time systems Acoustics Sensors RFID tags Speech processing

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Overview of Accent Conversion Techniques Based on Deep Learning

Overview of Accent Conversion Techniques Based on Deep Learn...

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international Image Processing, applications and systems conference (IPAS)

作者： Aayam Shrestha Seyed Ghorshi Issa Panahi Department of Electrical and Computer Engineering The University of Texas at Tyler Tyler Texas USA Department of Electrical and Computer Engineering The University of Texas at Dallas Richardson Texas USA

ISBN: (数字)9798331506520

ISBN: (纸本)9798331506537

In modern communication, speech technology plays a vital role, with accent being one of the key features that reflects the nuances of spoken technology. However, differences in accent can make communication difficult, especially in global contexts like language learning and human computer interaction. Accent conversion approaches often solve these issues by transforming the accent of speaker to that of the other speakers, while maintaining linguistic information and speaker identity. This technology holds great applications to speech recognition, language learning, and cross-lingual communication. This paper explores the use of advanced deep learning techniques in accent conversion systems which have improved both the naturalness and intelligibility of converted speech. Additionally, we discuss the methods generally used for performance evaluation of these systems.

关键词： Deep learning Adaptation models Accuracy Reviews Vocoders Speech recognition Phonetics Speech enhancement Semisupervised learning real-time systems

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