Artificial Intelligence Tools And Applications In Embedded And Mobile Systems
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Artificial Intelligence Tools And Applications In Embedded And Mobile Systems
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Author : Jorge Marx Gómez
language : en
Publisher: Springer Nature
Release Date :
Artificial Intelligence Tools And Applications In Embedded And Mobile Systems written by Jorge Marx Gómez and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Artificial Intelligence Tools And Applications In Embedded And Mobile Systems
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Author : Jorge Marx Gómez
language : en
Publisher: Springer
Release Date : 2024-06-08
Artificial Intelligence Tools And Applications In Embedded And Mobile Systems written by Jorge Marx Gómez and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-08 with Computers categories.
The emergence of Artificial Intelligence (AI) has had a tremendous impact on embedded and mobile systems. This book presents a diverse collection of papers that showcase cutting-edge research and practical applications of AI in this field. The peer-reviewed research articles stem from the First International Conference on Embedded and Mobile Systems (ICTA-EMOS), which was held on November 24th – 25th, 2022, in Arusha, Tanzania, East Africa. They demonstrate the breadth and depth of AI’s impact across various domains, exploring topics such as healthcare advances, transportation optimization, sustainable solutions, and business and process optimization.
Embedded Artificial Intelligence
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Author : Ovidiu Vermesan
language : en
Publisher: CRC Press
Release Date : 2023-05-05
Embedded Artificial Intelligence written by Ovidiu Vermesan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-05 with Computers categories.
Recent technological developments in sensors, edge computing, connectivity, and artificial intelligence (AI) technologies have accelerated the integration of data analysis based on embedded AI capabilities into resource-constrained, energy-efficient hardware devices for processing information at the network edge. Embedded AI combines embedded machine learning (ML) and deep learning (DL) based on neural networks (NN) architectures such as convolutional NN (CNN), or spiking neural network (SNN) and algorithms on edge devices and implements edge computing capabilities that enable data processing and analysis without optimised connectivity and integration, allowing users to access data from various sources. Embedded AI efficiently implements edge computing and AI processes on resource-constrained devices to mitigate downtime and service latency, and it successfully merges AI processes as a pivotal component in edge computing and embedded system devices. Embedded AI also enables users to reduce costs, communication, and processing time by assembling data and by supporting user requirements without the need for continuous interaction with physical locations. This book provides an overview of the latest research results and activities in industrial embedded AI technologies and applications, based on close cooperation between three large-scale ECSEL JU projects, AI4DI, ANDANTE, and TEMPO. The book’s content targets researchers, designers, developers, academics, post-graduate students and practitioners seeking recent research on embedded AI. It combines the latest developments in embedded AI, addressing methodologies, tools, and techniques to offer insight into technological trends and their use across different industries.
Artificial Intelligence Applications And Reconfigurable Architectures
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Author : Anuradha D. Thakare
language : en
Publisher: John Wiley & Sons
Release Date : 2023-03-21
Artificial Intelligence Applications And Reconfigurable Architectures written by Anuradha D. Thakare and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-21 with Computers categories.
ARTIFICIAL INTELLIGENCE APPLICATIONS and RECONFIGURABLE ARCHITECTURES The primary goal of this book is to present the design, implementation, and performance issues of AI applications and the suitability of the FPGA platform. This book covers the features of modern Field Programmable Gate Arrays (FPGA) devices, design techniques, and successful implementations pertaining to AI applications. It describes various hardware options available for AI applications, key advantages of FPGAs, and contemporary FPGA ICs with software support. The focus is on exploiting parallelism offered by FPGA to meet heavy computation requirements of AI as complete hardware implementation or customized hardware accelerators. This is a comprehensive textbook on the subject covering a broad array of topics like technological platforms for the implementation of AI, capabilities of FPGA, suppliers’ software tools and hardware boards, and discussion of implementations done by researchers to encourage the AI community to use and experiment with FPGA. Readers will benefit from reading this book because It serves all levels of students and researcher’s as it deals with the basics and minute details of Ecosystem Development Requirements for Intelligent applications with reconfigurable architectures whereas current competitors’ books are more suitable for understanding only reconfigurable architectures. It focuses on all aspects of machine learning accelerators for the design and development of intelligent applications and not on a single perspective such as only on reconfigurable architectures for IoT applications. It is the best solution for researchers to understand how to design and develop various AI, deep learning, and machine learning applications on the FPGA platform. It is the best solution for all types of learners to get complete knowledge of why reconfigurable architectures are important for implementing AI-ML applications with heavy computations. Audience Researchers, industrial experts, scientists, and postgraduate students who are working in the fields of computer engineering, electronics, and electrical engineering, especially those specializing in VLSI and embedded systems, FPGA, artificial intelligence, Internet of Things, and related multidisciplinary projects.
Artificial Intelligence And Hardware Accelerators
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Author : Ashutosh Mishra
language : en
Publisher: Springer Nature
Release Date : 2023-03-15
Artificial Intelligence And Hardware Accelerators written by Ashutosh Mishra and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-15 with Technology & Engineering categories.
This book explores new methods, architectures, tools, and algorithms for Artificial Intelligence Hardware Accelerators. The authors have structured the material to simplify readers’ journey toward understanding the aspects of designing hardware accelerators, complex AI algorithms, and their computational requirements, along with the multifaceted applications. Coverage focuses broadly on the hardware aspects of training, inference, mobile devices, and autonomous vehicles (AVs) based AI accelerators
Smart Embedded Systems
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Author : Arun Sinha
language : en
Publisher: CRC Press
Release Date : 2023-12-01
Smart Embedded Systems written by Arun Sinha and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-01 with Technology & Engineering categories.
"Smart Embedded Systems: Advances and Applications" is a comprehensive guide that demystifies the complex world of embedded technology. The book journeys through a wide range of topics from healthcare to energy management, autonomous robotics, and wireless communication, showcasing the transformative potential of intelligent embedded systems in these fields. This concise volume introduces readers to innovative techniques and their practical applications, offers a comparative analysis of wireless protocols, and provides efficient resource allocation strategies in IoT-based ecosystems. With real-world examples and in-depth case studies, it serves as an invaluable resource for students and professionals seeking to harness the power of embedded technology to shape our digital future. Salient Features: 1. The book provides a comprehensive coverage of various aspects of smart embedded systems, exploring their design, implementation, optimization, and a range of applications. This is further enhanced by in-depth discussions on hardware and software optimizations aimed at improving overall system performance. 2. A detailed examination of machine learning techniques specifically tailored for data analysis and prediction within embedded systems. This complements the exploration of cutting-edge research on the use of AI to enhance wireless communications. 3. Real-world applications of these technologies are extensively discussed, with a focus on areas such as seizure detection, noise reduction, health monitoring, diabetic care, autonomous vehicles, and communication systems. This includes a deep-dive into different wireless protocols utilized for data transfer in IoT systems. 4. This book highlights key IoT technologies and their myriad applications, extending from environmental data collection to health monitoring. This is underscored by case studies on the integration of AI and IoT in healthcare, spanning topics from anomaly detection to informed clinical decision-making. Also featured is a detailed evaluation and comparison of different system implementations and methodologies. This book is an essential read for anyone interested in the field of embedded systems. Whether you're a student looking to broaden your knowledge base, researchers looking in-depth insights, or professionals planning to use this cutting-edge technology in real-world applications, this book offers a thorough grounding in the subject.
Cognitive Computing For Big Data Systems Over Iot
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Author : Arun Kumar Sangaiah
language : en
Publisher: Springer
Release Date : 2017-12-30
Cognitive Computing For Big Data Systems Over Iot written by Arun Kumar Sangaiah and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-30 with Technology & Engineering categories.
This book brings a high level of fluidity to analytics and addresses recent trends, innovative ideas, challenges and cognitive computing solutions in big data and the Internet of Things (IoT). It explores domain knowledge, data science reasoning and cognitive methods in the context of the IoT, extending current data science approaches by incorporating insights from experts as well as a notion of artificial intelligence, and performing inferences on the knowledge The book provides a comprehensive overview of the constituent paradigms underlying cognitive computing methods, which illustrate the increased focus on big data in IoT problems as they evolve. It includes novel, in-depth fundamental research contributions from a methodological/application in data science accomplishing sustainable solution for the future perspective. Mainly focusing on the design of the best cognitive embedded data science technologies to process and analyze the large amount of data collected through the IoT, and aid better decision making, the book discusses adapting decision-making approaches under cognitive computing paradigms to demonstrate how the proposed procedures as well as big data and IoT problems can be handled in practice. This book is a valuable resource for scientists, professionals, researchers, and academicians dealing with the new challenges and advances in the specific areas of cognitive computing and data science approaches.
Ambient Intelligence Software And Applications
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Author : Carlos Ramos
language : en
Publisher: Springer
Release Date : 2014-05-16
Ambient Intelligence Software And Applications written by Carlos Ramos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-16 with Technology & Engineering categories.
Ambient Intelligence (AmI) is a recent paradigm emerging from Artificial Intelligence (AI), where computers are used as proactive tools assisting people with their day-to-day activities, making everyone’s life more comfortable. Another main concern of AmI originates from the human computer interaction domain and focuses on offering ways to interact with systems in a more natural way by means user friendly interfaces. This field is evolving quickly as can be witnessed by the emerging natural language and gesture based types of interaction. The inclusion of computational power and communication technologies in everyday objects is growing and their embedding into our environments should be as invisible as possible. In order for AmI to be successful, human interaction with computing power and embedded systems in the surroundings should be smooth and happen without people actually noticing it. The only awareness people should have arises from AmI: more safety, comfort and wellbeing, emerging in a natural and inherent way. ISAmI is the International Symposium on Ambient Intelligence and aiming to bring together researchers from various disciplines that constitute the scientific field of Ambient Intelligence to present and discuss the latest results, new ideas, projects and lessons learned, namely in terms of software and applications, and aims to bring together researchers from various disciplines that are interested in all aspects of this area.
Intelligent Software Methodologies Tools And Techniques
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Author : Hamido Fujita
language : en
Publisher:
Release Date : 2015
Intelligent Software Methodologies Tools And Techniques written by Hamido Fujita and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
This book constitutes the best papers selection from the proceedings of the 14th International Conference on Intelligent Software Methodologies, Tools and Techniques, SoMeT 2015, held in Naples, Italy, in September 2015. The 47 full papers presented together with one short paper were carefully reviewed and selected from 118 submissions. The papers are organized in topical sections on embedded and mobile software systems, theory and application; real-time systems; requirement engineering, high-assurance and testing system; social networks and big data; cloud computing and semantic web; artificial intelligence techniques and intelligent system design; software development and integration; security and software methodologies for reliable software design; new software techniques in image processing and computer graphics; software applications systems for medical health care.
Embedded Machine Learning For Cyber Physical Iot And Edge Computing
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Author : Sudeep Pasricha
language : en
Publisher: Springer Nature
Release Date : 2023-10-09
Embedded Machine Learning For Cyber Physical Iot And Edge Computing written by Sudeep Pasricha and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-09 with Technology & Engineering categories.
This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.