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Pothole Detection Using Jetson Nano embedded System - An Evaluation of Training Models 11th

Pothole Detection Using Jetson Nano Embedded System - An Eva...

引用

11th international conference on E-Health and Bioengineering (EHB)

作者： Obreja, Marius-Emanuel Dobrea, Dan-Marius Gheorghe Asachi Tech Univ Iasi Elect Telecommun & Informat Technol Iasi Romania

ISBN: (纸本)9783031625015;9783031625022

the field of "smart city" has recently seen an increasing demand on the technology consumer market, this leads to the need to develop new solutions to meet the demands of users. A smart city is defined as an urban area that uses various types of electronic methods and sensors to collect data. Statistics obtained from this data are used to manage assets, resources, and services effectively;moreover, this data is used to improve or optimize the various activities within the city. the present research consisted of studying and implementing different neural network training models using the NVIDIA Jetson Nano development kit. this is a small embedded system capable of running Artificial Intelligence applications supported by the parallel processing capabilities of the embedded GPU. Using this built-in system, certain real-time applications can be developed for image classification or object detection, in our case asphalt pits.

关键词： Pothole Detection embedded systems Deep Learning Artificial Intelligence Smart City

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An Amalgamation of Machine Learning and embedded systems for Smart Street Lightning systems 18

An Amalgamation of Machine Learning and Embedded Systems for...

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18th INDIAcom;11th international conference on computing for Sustainable Global Development, INDIACom 2024

作者： Gupta, Sakshi Singh, Rishit Parikh, Jolly Puri, Yugnanda Vashisht, Ridham Bharati Vidyapeeth's College of Engineering Department of Electronics and Communication Engineering New Delhi110063 India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering New Delhi110063 India

ISBN: (纸本)9789380544519

this research paper introduces an innovative Smart Street Light System that optimizes street lighting operations by harnessing ambient light levels to govern the activation and deactivation of streetlights. Lux value thresholds are employed to distinguish between various lighting scenarios, ranging from bright sunlight to subdued sunlight and complete darkness. Moreover, the paper explores the potential integration of an ultrasonic sensor (US 100) for detecting approaching vehicles and pedestrians, by using advanced machine learning algorithms, thereby enhancing system capabilities. the novel use of Machine Learning algorithms, extensive training of the model, on dataset built using real world conditions, enhances the output accuracy of the model, which gives the model the capabilities to take decisions on its own and thus create a self-sustainable ecosystem, harnessing advanced technologies, without any human involvement. the model was created and implemented with an accuracy of 97.35 percent. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Ambient Light Sensing BH1750 Energy Efficiency Lux Machine Learning Nucleo-F401 RE Smart Street Light System Ultrasonic Sensor Urban Sustainability US -100

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Agnostic Hardware-Accelerated Operating System for Low-End IoT 28

Agnostic Hardware-Accelerated Operating System for Low-End I...

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28th IEEE international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Silva, Miguel Gomes, Tiago Pinto, Sandro Univ Minho Ctr ALGORITMI Braga Portugal

ISBN: (数字)9781665453448

ISBN: (纸本)9781665453448

there is increasing pressure to optimize Internet of things (IoT) low-end devices. the ever-growing number of requirements and constraints is pushing towards maximizing performance and real-time, but simultaneously minimizing power consumption, form factor, and memory footprint. this has motivated the adoption of Field-Programmable Gate Array (FPGA) technology to accelerate computing-intensive workloads in hardware. However, and despite the ongoing trend of migrating application-level tasks to hardware, recently, the offload of system software such as operating system (OS) services has received little attention. this paper presents CHAMELIoT, a framework for FPGA-based IoT platforms that provides agnostic hardware acceleration to OS services by leveraging RISC-V technology. CHAMELIoT allows for developers to run unmodified applications in a set of well-established IoT OSes. Currently, the framework has support for RIOT, Zephyr, and FreeRTOS. the evaluation showed that latency and determinism can be enhanced up to 10x while the system's performance can be increased to nearly 200%. CHAMELIoT will be open-sourced.

关键词： Performance evaluation Power demand Operating systems Memory management Jitter Market research real-time systems

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On the Trade-offs between Generalization and Specialization in real-time systems 28

On the Trade-offs between Generalization and Specialization ...

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28th IEEE international conference on embedded and real-time computing systems and applications (RTCSA)

作者： von der Brueggen, Georg Burns, Alan Chen, Jian-Jia Davis, Robert, I Reineke, Jan TU Dortmund Univ Dept Comp Sci Dortmund Germany Univ York Dept Comp Sci York N Yorkshire England Saarland Univ Saarland Informat Campus Homburg Germany

ISBN: (数字)9781665453448

ISBN: (纸本)9781665453448

While academia favours general research that is applicable to a large class of systems, this paper highlights the necessity of research into specific scenarios and aims to increase its acceptance in the real-time systems community. We argue that such research is not only motivated by greater applicability to industry, but that specialization can also provide valuable information from a purely academic perspective. In addition, the trade-offs between generalization and specialization are examined, considering not only theoretical performance, but also the impact on essential non-functional properties that are important for industry, namely composability, robustness, extensibility, and parametric simplicity.

关键词： Industries Analytical models Philosophical considerations Terminology Focusing real-time systems Robustness

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Automatic Question Generation: A Comparative Analysis of Rule-Based and Neural Network-Based Models 11th

Automatic Question Generation: A Comparative Analysis of R...

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11th international conference on Intelligent computing and applications, ICRTC 2023

作者： Velmurugan, Haemanth Pandiarajan, Naveena Ravi, Lisa Voleti, Sravani Sheik, Reshma Nirmala, S. Jaya National Institute of Technology Tamil Nadu Tiruchirappalli India

ISBN: (纸本)9789819717231

Questioning is essential for learning and higher-level cognitive abilities. Manual question construction is time-consuming and requires experts. To streamline the process, researchers have proposed various automatic question generation (AQG) approaches for real-time applications in natural language processing (NLP). this paper provides an overview of the latest developments in AQG and discusses the state-of-the-art rule-based and neural network-based models employed in these systems. In addition, this paper incorporates an empirical assessment of the effectiveness of two prominent models, namely the Heilman and Smith (H &S) model and the transformer-based T5 model, using educational resources’ book chapters as the basis for performance evaluation. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Natural language processing systems

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Edge computing and Distributed Ledger Technology for the Industrial IoT 11

Edge Computing and Distributed Ledger Technology for the Ind...

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11th IEEE international conference on Intelligent computing and Information systems, ICICIS 2023

作者： Abo-Soliman, Mohamed Ahmed Shabaan, Eman Al-Qutt, Mirvat Emara, Kareem Ain Shams University Computer Systems Department Cairo Egypt

ISBN: (纸本)9798350322101

the tremendous increase in implementing IoT devices for critical infrastructures yells for higher performance and robust protection. Traditional cloud based IoT architecture is unsuitable for delay-sensitive or real-time applications and lacks the robust security needed by industrial systems. thus, new technologies are introduced to endorse the industry's digital transformation. Edge computing greatly satisfies required performance while Distributed Ledger Technology (DLT) mitigates potential data compromises. this work proposes an integrated four layers architecture based on Edge computing and DLT that provides efficient computing, security, and scalability. Edge computing handles transmission delay and scalability issues, while DLT handles data validation and trust. A lightweight DLT model is introduced to enable faster data commitment and better networking. the model incorporates two main features: a new grouping technique that enables network segmentation reducing network complexity. the second technique dynamically optimizes resource-utilization by adjusting DLT requirements according to the hardware capabilities of each participating node. © 2023 IEEE.

关键词： Internet of things

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Investigating Requirements and Expectations of Wearable Telexistence Robotic systems 29

Investigating Requirements and Expectations of Wearable Tele...

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29th IEEE international conference on embedded and real-time computing systems and applications, RTCSA 2023

作者： Iskandar, Abdullah Al-Sada, Mohammed Halabi, Osama Nakajima, Tatsuo Waseda University Dept. of Computer Science and Engineering Tokyo Japan Qatar University Dept. of Computer Science and Engineering Doha Qatar

ISBN: (纸本)9798350337860

Telexistence refers to various technologies that enable a high sense of embodiment and interaction capabilities with remote environments. Although numerous telexistence systems have been explored in previous works of literature, no prior studies have investigated the usability of telexistence systems for daily use. therefore, this study focuses on Piton, which is a novel wearable telexistence robot which has a high degree of freedom in a snake-shaped design. Piton offers a unique opportunity for remote interaction and manipulation in diverse environments, owing to its flexible movement, which enables users to adapt to various scenarios with ease. the robot's wearability is also an essential feature that allows the user to wear it as a backpack. However, despite its promising features, deeper investigation is necessary to explore potential use cases for Piton in users' daily lives and the challenge of Piton. © 2023 IEEE.

关键词： Robots

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real-time and approximate iterative optical flow implementation on low-power embedded CPUs 34

Real-time and approximate iterative optical flow implementat...

引用

34th IEEE international conference on Application-Specific systems, Architectures and Processors (ASAP)

作者： Millet, Maxime Cassagne, Adrien Rambaux, Nicolas Lacassagne, Lionel Sorbonne Univ CNRS LIP6 Paris France ALCEN Lerity Cergy France Sorbonne Univ Observ Paris PSL CNRS IMCCE Paris France

ISBN: (纸本)9798350346855

Optical flow estimation is used in many embedded computer vision applications, and it is known to be computationally intensive. In the literature, many methods exist to estimate optical flow. thus, the challenge is to find a method that matches the applicative constraints. In an embedded system, a trade-off between power consumption and execution time has to be made to meet both energy and framerate constraints. this work proposes methods to implement an approximate HORN & SCHUNCK optical flow estimation that meets embedded CPUs constraints. this is achieved thanks to architectural optimizations, software optimizations and algorithm tuning. For instance, on the NVIDIA Jetson Nano, and for HD video sequences, the achieved frame latency is 12 ms for 5 Watts. To the best of our knowledge, this is the fastest optical flow implementation on embedded CPUs.

关键词： computer vision optical flow SIMD approximate computing low power tradeofs embedded systems

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Machine Learning in embedded systems: Limitations, Solutions and Future Challenges 13

Machine Learning in Embedded Systems: Limitations, Solutions...

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IEEE 13th Annual computing and Communication Workshop and conference (CCWC)

作者： Batzolis, Eleftherios Vrochidou, Eleni Papakostas, George A. Int Hellen Univ MLV Res Grp Dept Comp Sci Kavala 65404 Greece

ISBN: (纸本)9798350332865

Machine learning has attracted a lot of interest in the last few years as a solution to a variety of difficult challenges in many disciplines. An emerging area is that of embedded devices, where machine learning is deployed to efficiently carry out tasks like data analysis, prediction, and decision-making in real-time applications. Challenges such as the necessity for fast and effective algorithms and the restricted resources available in embedded systems to cover the computational and storage demands need to be confronted to successfully integrate machine learning models into embedded systems. this work aims to provide an overview of the use of machine learning in embedded systems, including past and current solutions, and to present the challenges that need to be addressed. Future directions for the use of machine learning in embedded systems are also discussed.

关键词： machine learning deep learning artificial intelligence embedded systems Internet of things (IoT)

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Containerized Computer Vision applications on Edge Devices 7

Containerized Computer Vision Applications on Edge Devices

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7th IEEE international conference on Edge computing and Communications (IEEE EDGE) / IEEE World Congress on Services (SERVICES)

作者： Alqaisi, Osamah I. Tosun, Ali Saman Korkmaz, Turgay Univ Texas San Antonio Dept Comp Sci San Antonio TX 78249 USA Univ North Carolina Pembroke Dept Math & Comp Sci Pembroke NC 28372 USA

ISBN: (纸本)9798350304831

the proliferation of IoT devices has led to various computer vision applications, where addressing bandwidth and latency challenges through edge nodes presents significant benefits. However, there are still existing gaps and a need for improvements to optimize IoT applications, especially in the field of computer vision, by overcoming limited resources and enhancing device performance. Addressing these challenges is essential to unlock the full potential of IoT applications in real-world scenarios. this paper evaluates the use of lightweight container technology for computer vision applications which using different algorithms, such as Haar Cascades, HOG and CNN with YOLO algorithm, on edge devices and provides a comprehensive comparison and analysis of different versions of computer vision applications in containers in terms of processing ability, and performance. It focuses on containerizing computer vision applications using Docker to achieve safe execution of multiple applications on these devices without interference and to enable flexibility, efficiency, portability, scalability, and isolation. the study also examines the resource usage, execution time, and receiving time of containerized computer vision applications. the research findings significantly advance our understanding of computer vision processing in IoT and edge computing, thereby opening up new avenues for real-time computing scenarios. these insights have the potential to drive transformative advancements in the field, enabling more efficient and accurate computer vision applications in IoT and paving the way for enhanced real-time decision-making, automation, and intelligent systems.

关键词： Edge computing embedded Vision Container Technology OpenCV Container Docker IoT

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