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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 36766 条记录，以下是51-60 订阅

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Waste Sorting System Using AI: Development of An embedded Solution for Efficient Waste Management 6

Waste Sorting System Using AI: Development of An Embedded So...

引用

6th ieee international conference on Image Processing, applications and systems, IPAS 2025

作者： Remili, Amal Mahdi, Mouna Zouari Elleuch, Jihen Frikha Fakhfakh, Ahmed Sellami, Dorra National Engineering School of Sfax Electrical Engineering Department Sfax Tunisia Sfax Digital Research Center Sfax Tunisia

ISBN: (纸本)9798331506520

Waste is causing a serious environmental problem. Waste management and circular economy offers a best alternative for preserving the environment and protecting nature resources. This paper presents an AI-based system for waste identification and sorting, particularly focusing on plastic, which is the less decomposed waste, using computer vision techniques. The data, used for system validation, comprises publicly available datasets and a locally collected dataset, devoted to plastic classification and detection. Performance metrics demonstrate that YOLOv8 outperforms other deep learning solutions, in real-time waste detection and is well suited for implementation on a Raspberry Pi 4 Model B. The system outperforms also existing methods in terms of efficiency, accuracy, and speed, and is a promising solution for addressing the global waste management challenge. © 2025 ieee.

关键词： AI models Computer vision Waste detection Waste management Waste sorting

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Hybrid AI-Electronic systems for real-time Edge Processing in IoT Networks 3

Hybrid AI-Electronic Systems for Real-Time Edge Processing i...

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3rd international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Sweety Prasanna Kiruba, G. Esakki Madura, E. Kumar, Bura Vijay Kavitha, M. Reddy, T. Srinivas Athiraja, A. Bannari Amman Institute of Technology Department of Computer Technology Tamil Nadu Sathyamangalam India Bannari Amman Institute of Technology Department of Artificial Intelligence and Data Science Tamil Nadu Sathyamangalam India School of Computer Science and Artificial Intelligence Sr University Warangal India Kathir College of Engineering Department of Artificial Intelligence and Data Science Neelambur Coimbatore India Malla Reddy Engineering College Department of Ece Main Campus Maisammaguda Telangana Medchal India Hyderabad India

ISBN: (纸本)9798331515911

real-time data processing is facing many issues as a result of the Internet of Things' rapid expansion, especially at the network's edge where latency, bandwidth, and compute resources are limited. The creation of hybrid AI-electronic systems for real-time edge processing is investigated as a solution to these problems. To improve the effectiveness and precision of data processing in Internet of Things contexts, the research combines machine learning algorithms with sophisticated electronic circuits. The techniques include creating a brand-new hybrid framework that blends edge computing and AI models and focuses for low latency and low power consumption. When compared to conventional edge processing systems, extensive simulations and real-world research show a 25% reduction in processing latency and a 15% gain in data categorization accuracy. According to the findings, the suggested hybrid AI-electronic system can successfully handle the requirements of contemporary IoT networks and offer a scalable real-time edge processing solution. This strategy has potential for use in smart city applications, industrial automation, and other fields in the future. © 2025 ieee.

关键词： Adversarial machine learning

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real-time Sign Language Detection Using Deep Learning

Real-Time Sign Language Detection Using Deep Learning

引用

2025 ieee international conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Selvi, A. Senthil Ratiraju, Gautham Jeevan, Akhil Reddy, Jinnam Sai Kiran Krishna, Molakalapalli Vamsi Senthil Pandi, S. SRM IST Dept of CSE Ramapuram Chennai India Rajalakshmi Engineering College Department of CSE Chennai India

ISBN: (纸本)9798331512965

Sign language is the primary mode of communication for deaf and hard of hearing community. This paper discusses the development of a real time sign language recognition system by deploying deep learning techniques. For instance, the aim is to establish a good model which could be used to identify different hand gestures as used in sign languages. Once trained on a data set of 10 different hand gestures, the system is able to recognize and predict gestures in other images. The use of TensorFlow and Keras in the implementation ensures scalability of the system for real-time application. This method aims at assisting the deaf and mute people by developing an application that will improve their social life. Furthermore, TensorFlow and Python facilitate the porting of the system to mobile and embedded systems, which enhance its reach among different gadgets. This system is intended to help avoid one of the main concerns of sign language users in which they have limited ability to interact with others and thus limited engagement with basic services. The objective of the researcher is to make the quality of life of sign language users better by translating their gestures into a format that is easier to understand. © 2025 ieee.

关键词： embedded systems

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PyBlkSim: An Open-Source Block-Based Discrete-time Simulator 17

PyBlkSim: An Open-Source Block-Based Discrete-Time Simulator

引用

17th international conference on COMmunication systems and NETworkS, COMSNETS 2025

作者： Polachan, Kurian Basak, Bijeet International Institute of Information Technology Bangalore India

ISBN: (纸本)9798331531195

PyBlkSim is a block-based simulator developed for discrete-time simulations. PyBlkSim is useful for simulating a wide range of real-world discrete-time systems including systems belonging to signal processing and communications domains. PyBlkSim is written in Python and built using Python's discreteevent simulation library, SimPy. PyBlkSim blocks use popular Python libraries such as NumPy and SciPy, which have been tried and tested extensively for various scientific computing applications. In its current form, PyBlkSim supports several blocks, ranging from different signal sources and sinks to filters, math, and signal operations. The simulator and its accompanying blocks are open-sourced, allowing developers to edit and extend the code to suit their needs. PyBlkSim differs from its counterparts, such as GNU Radio and Simulink, in that it is open-source, supports multiple operating systems, and can natively incorporate Python scientific libraries in its blocks. In this paper, we discuss the need for PyBlkSim, its design framework, the structure of its blocks and the characterization of its performance. As an example, we also demonstrate the use of PyBlkSim to simulate an On-Off Keying (OOK) modulation and demodulation scheme. © 2025 ieee.

关键词： Python

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"Cropmaster" - real-time Coordination of Multirobot systems for Autonomous Crop Harvesting: Design and Implementation 5

"Cropmaster" - Real-Time Coordination of Multirobot Systems ...

引用

5th ieee international conference on Power, Electronics and Computer applications, ICPECA 2025

作者： Pramod, Isuranga Arachchi, Avishka Mallawa Rashen, Chemuthu Chinthaka, Gayan Pandithage, Dinithi Gamage, Narmada Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798331533694

The CropMaster is an autonomous rover system designed to enhance Scotch Bonnet production by improving disease management, crop sorting, autonomous navigation, and real-time environmental monitoring. Equipped with sensors to measure sunlight, humidity, pH, NPK content, and soil moisture, the rover securely transmits analyzed data to a web-based dashboard. LIDAR technology enables efficient autonomous navigation, allowing the rover to move around fields and avoid obstacles. The MQTT protocol facilitates communication between multiple rovers, preventing duplicate measurements and ensuring data is sent to the dashboard for comprehensive data collection across large areas. TensorFlow's machine learning models allow the rover to accurately assess crop health and detect early-stage diseases, followed by automated pesticide and fertilizer application through a spraying system. To maintain reliability, the rover's operations, including data transfer and task execution, are continuously monitored for Quality of Service (QoS). All collected data is stored in the cloud for long-term access. Built with a lightweight aluminum and plastic chassis and robotic arms, the rover is designed for adaptability and operational efficiency, aiming to improve crop management and increase yields across extensive agricultural fields. © 2025 ieee.

关键词： Robotic arms

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SafeFloatZone: Identify Safe Domains for Elementary Functions 24th

SafeFloatZone: Identify Safe Domains for Elementary Function...

引用

24th international conference on embedded Computer systems: Architectures, Modeling, and Simulation

作者： Krahl, Markus Guedemann, Matthias Wallentowitz, Stefan Hsch Munchen Univ Appl Sci Munich Germany TASKING Germany GmbH Munich Germany

ISBN: (纸本)9783031783760;9783031783777

Formal verification of embedded system software can profoundly influence both safety and security, and has the potential to alter the development process substantially. However, the complexity of formal verification, along with stringent time-to-market and resource constraints of embedded systems, has posed significant barriers to its adoption. Moreover, ensuring the accessibility of formal methods in the design and implementation of embedded systems remains a major challenge. In our paper, we evaluate formal methods and demonstrate the accessibility and benefits within a critical area of many industries: ieee754 floating-point values are widely used and due to their fixed size, they can only approximate real numbers. For the most part, their behavior aligns with programmer expectations;however, certain corner cases exist in which they are susceptible to value cancellation, rounding errors, and deviations from standard mathematical rules. Such discrepancies can be problematic when calculated results diverge from software developer expectations, potentially leading to fatal errors. We propose SafeFloatZone which allows for the identification of safe domains for algorithms utilizing ieee754 floating-point numbers. The approach is rooted in formal verification, leveraging modern, efficient Satisfiability Modulo Theories (SMT) solvers to deduce preconditions for functions, thereby providing stronger guarantees of correctness. In this work we demonstrate how SafeFloatZone can readily benefit embedded system developers and show that it is transferable to a variety of algorithms based on ieee754 floating-point numbers.

关键词： embedded systems ieee754 Floating-Point Formal Verification

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Nonplanar Wireless Differential Microsensor for Integration on Intravenous Catheters for Therapeutic Drug Monitoring and Other applications 38

Nonplanar Wireless Differential Microsensor for Integration ...

引用

38th ieee international conference on Micro Electro Mechanical systems, MEMS 2025

作者： Jiang, Jiaxin Chidambaran, Vidya Li, Tao University of Cincinnati Department of Electrical and Computer Engineering United States Cincinnati Children's Hospital Medical Center Department of Anesthesia United States

ISBN: (纸本)9798331508890

This paper reports a nonplanar passive wireless differential microsensor integrated with intravenous (IV) catheters of small diameters to facilitate in situ real-time monitoring of concentrations of drugs or other target molecules/biomarkers in the bloodstream. The sensor is based on magnetoelastic (ME) transduction with passive wireless interrogation to detect target molecules as mass loading using a functionalized coating. It uses a differential configuration to distinguish the mass loading effect from variations caused by changes in surrounding fluid medium. The sensor was curved to match the catheter form factor with maximized active sensor surface area, packaged in housing with embedded microfluidic features for sample filtration/pretreatment, and integrated on an 18-gauge catheter with 1.3 mm outer diameter for demonstration. Preliminary experimental results validated functions of curved ME sensors with degraded performance due to curving fully restored by an optimized annealing process, demonstrating 5.3 Hz/ng mass sensitivity and proper differential operation with the medium effect eliminated. © 2025 ieee.

关键词： Catheters

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A Comprehensive Survey on Unmanned Aerial Vehicles (UAVs): Types, Structural Components, Communication systems, and Operating Platforms 3

A Comprehensive Survey on Unmanned Aerial Vehicles (UAVs): T...

引用

3rd international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Tauseef, Md. Reddy, T. Sai Sankalp Lohith, R. Thanushree, M.P. Sravani, K. Reva University School of Ece Bengaluru India

ISBN: (纸本)9798331515911

Unmanned Aerial Vehicles (UAVs), commonly known as drones, have experienced rapid growth and widespread adoption across military and civilian applications in recent years. This paper offers a comprehensive survey of UAV technologies, focusing on their classifications, structural components, communication systems, and operating platforms. UAVs are categorized based on size, range, and altitude capabilities. Key structural elements such as frames, propulsion systems, sensors, and control mechanisms are examined. The paper also addresses communication requirements, architectures, protocols, and associated challenges. Furthermore, it reviews real time operating systems utilized in UAVs, high-lighting their design considerations. The survey concludes by identifying emerging trends and future research directions in UAV development, providing valuable insights for both newcomers and seasoned researchers in the field. © 2025 ieee.

关键词： Drones

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A Robust Framework for Online Fault Detection in Environmental Monitoring Using Pretrained Probabilistic Models 17

A Robust Framework for Online Fault Detection in Environment...

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17th international conference on COMmunication systems and NETworkS, COMSNETS 2025

作者： Dash, Ritwik Sagar, Kasturi Gyanaguna Jenamani, Mamata Indian Institute of Technology Industrial & Systems Engineering Kharagpur India

ISBN: (纸本)9798331531195

Accurate detection and classification of sensor faults are vital for maintaining the integrity and reliability of air quality monitoring systems, where faulty data can degrade decision-making and hinder timely environmental interventions. Thus, early identification of such anomalies is critical for the deployment of fault-tolerant systems, specifically in environmental monitoring. The concept of pretrained probabilistic time series models is utilized to design a framework for online fault detection in the AQI(Air Quality Index) Monitoring applications. The framework tokenizes the multivariate sensor data through scaling and quantization into a fixed vocabulary and leverages transformer-based language model architectures trained via cross-entropy loss on these tokenized values. The performance of the proposed framework is also evaluated across a range of fault injection scenarios, testing its robustness and efficiency. The model consistently demonstrates strong fault detection capabilities, maintaining high accuracy and reliability even under varying levels of artificially induced sensor faults, further outperforming classical methods and specialized models for air quality monitoring. The evaluation results of the proposed method demonstrate a fault detection rate that exceeds 95% in all scenarios while effectively categorizing faults in data quality monitoring systems at the sensor node level. © 2025 ieee.

关键词： Environmental monitoring

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Low-Power Feature Extraction for BCI applications using Approximate Continuous Wavelet Transform 13

Low-Power Feature Extraction for BCI Applications using Appr...

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13th international Winter conference on Brain-Computer Interface, BCI 2025

作者： Saad, Joe Evans, Adrian Miro-Panades, Ivan Aksenova, Tetiana Anghel, Lorena Univ. Grenoble Alpes CEA LIST Grenoble France Univ. Grenoble Alpes CNRS Grenoble INP Grenoble France

ISBN: (纸本)9798331521929

The wavelet transform is commonly used as a feature extraction method for brain signal decoding, but extracting this type of feature has a high energy cost as the wavelet transform relies on computing a convolution operation. Certain portable or implantable medical applications for Brain-Computer Interfaces (BCIs) require low-power signal decoding approaches. We investigate two methods to compute approximate wavelet transforms using fewer operations than existing techniques, which is attractive for embedded implementations. Both methods are validated on Electrocorticography (ECoG) signal decoding, reducing the energy consumption of feature extraction by up to 4×, with a negligible loss in decoding accuracy. © 2025 ieee.

关键词： Medical computing

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