EBookClubs

Read Books & Download eBooks Full Online

EBookClubs

Read Books & Download eBooks Full Online

Book 2019 International Conference on Indoor Positioning and Indoor Navigation

Download or read book 2019 International Conference on Indoor Positioning and Indoor Navigation written by and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book IPIN 2018

Download or read book IPIN 2018 written by and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book 2021 International Conference on Indoor Positioning and Indoor Navigation IPIN

Download or read book 2021 International Conference on Indoor Positioning and Indoor Navigation IPIN written by and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Machine Learning for Indoor Localization and Navigation

Download or read book Machine Learning for Indoor Localization and Navigation written by Saideep Tiku and published by Springer Nature. This book was released on 2023-06-29 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: While GPS is the de-facto solution for outdoor positioning with a clear sky view, there is no prevailing technology for GPS-deprived areas, including dense city centers, urban canyons, buildings and other covered structures, and subterranean facilities such as underground mines, where GPS signals are severely attenuated or totally blocked. As an alternative to GPS for the outdoors, indoor localization using machine learning is an emerging embedded and Internet of Things (IoT) application domain that is poised to reinvent the way we navigate in various indoor environments. This book discusses advances in the applications of machine learning that enable the localization and navigation of humans, robots, and vehicles in GPS-deficient environments. The book explores key challenges in the domain, such as mobile device resource limitations, device heterogeneity, environmental uncertainties, wireless signal variations, and security vulnerabilities. Countering these challenges can improve the accuracy, reliability, predictability, and energy-efficiency of indoor localization and navigation. The book identifies severalnovel energy-efficient, real-time, and robust indoor localization techniques that utilize emerging deep machine learning and statistical techniques to address the challenges for indoor localization and navigation. In particular, the book: Provides comprehensive coverage of the application of machine learning to the domain of indoor localization; Presents techniques to adapt and optimize machine learning models for fast, energy-efficient indoor localization; Covers design and deployment of indoor localization frameworks on mobile, IoT, and embedded devices in real conditions.

Book 2015 International Conference on Indoor Positioning and Indoor Navigation IPIN

Download or read book 2015 International Conference on Indoor Positioning and Indoor Navigation IPIN written by IEEE Staff and published by . This book was released on 2015-10-13 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The IPIN series of meetings is a forum of excellence to join researchers, system developers, and service providers in the area of indoor positioning and navigation

Book 2014 International Conference on Indoor Positioning and Indoor Navigation IPIN

Download or read book 2014 International Conference on Indoor Positioning and Indoor Navigation IPIN written by IEEE Staff and published by . This book was released on 2014-10-27 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Location Information of Devices in indoor environments has become a key issue for many emerging applications However, there is no ubiquitous and straightforward solution IPIN brings together experts in electronics, surveying and computer science Researchers, system providers and users are invited to contribute with papers, presentations, posters, demonstrations, exhibitions, competition and discussions to create synergies between different indoor positioning techniques

Book 2010 International Conference on Indoor Positioning and Indoor Navigation

Download or read book 2010 International Conference on Indoor Positioning and Indoor Navigation written by IEEE Staff and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Advances in AI for Biomedical Instrumentation Electronics and Computing

Download or read book Advances in AI for Biomedical Instrumentation Electronics and Computing written by Vibhav Sachan and published by CRC Press. This book was released on 2024-06-13 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the proceedings of 5th International Conference on Advances in AI for Biomedical Instrumentation, Electronics and Computing (ICABEC - 2023), which provided an international forum for the exchange of ideas among researchers, students, academicians, and practitioners. It presents original research papers on subjects of AI, Biomedical, Communications & Computing Systems. Some interesting topics it covers are enhancing air quality prediction using machine learning, optimization of leakage power consumption using hybrid techniques, multi-robot path planning in complex industrial dynamic environment, enhancing prediction accuracy of earthquake using machine learning algorithms and advanced machine learning models for accurate cancer diagnostics. Containing work presented by a diverse range of researchers, this book will be of interest to students and researchers in the fields of Electronics and Communication Engineering, Computer Science Engineering, Information Technology, Electrical Engineering, Electronics and Instrumentation Engineering, Computer applications and all interdisciplinary streams of Engineering Sciences.

Book Artificial Intelligence for Edge Computing

Download or read book Artificial Intelligence for Edge Computing written by Mudhakar Srivatsa and published by Springer Nature. This book was released on 2024-01-10 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is undeniable that the recent revival of artificial intelligence (AI) has significantly changed the landscape of science in many application domains, ranging from health to defense and from conversational interfaces to autonomous cars. With terms such as “Google Home”, “Alexa”, and “ChatGPT” becoming household names, the pervasive societal impact of AI is clear. Advances in AI promise a revolution in our interaction with the physical world, a domain where computational intelligence has always been envisioned as a transformative force toward a better tomorrow. Depending on the application family, this domain is often referred to as Ubiquitous Computing, Cyber-Physical Computing, or the Internet of Things. The underlying vision is driven by the proliferation of cheap embedded computing hardware that can be integrated easily into myriads of everyday devices from consumer electronics, such as personal wearables and smart household appliances, to city infrastructure and industrial process control systems. One common trait across these applications is that the data that the application operates on come directly (typically via sensors) from the physical world. Thus, from the perspective of communication network infrastructure, the data originate at the network edge. From a performance standpoint, there is an argument to be made that such data should be processed at the point of collection. Hence, a need arises for Edge AI -- a genre of AI where the inference, and sometimes even the training, are performed at the point of need, meaning at the edge where the data originate. The book is broken down into three parts: core problems, distributed problems, and other cross-cutting issues. It explores the challenges arising in Edge AI contexts. Some of these challenges (such as neural network model reduction to fit resource-constrained hardware) are unique to the edge environment. They need a novel category of solutions that do not parallel more typical concerns in mainstream AI. Others are adaptations of mainstream AI challenges to the edge space. An example is overcoming the cost of data labeling. The labeling problem is pervasive, but its solution in the IoT application context is different from other contexts. This book is not a survey of the state of the art. With thousands of publications appearing in AI every year, such a survey is doomed to be incomplete on arrival. It is also not a comprehensive coverage of all the problems in the space of Edge AI. Different applications pose different challenges, and a more comprehensive coverage should be more application specific. Instead, this book covers some of the more endemic challenges across the range of IoT/CPS applications. To offer coverage in some depth, we opt to cover mainly one or a few representative solutions for each of these endemic challenges in sufficient detail, rather that broadly touching on all relevant prior work. The underlying philosophy is one of illustrating by example. The solutions are curated to offer insight into a way of thinking that characterizes Edge AI research and distinguishes its solutions from their more mainstream counterparts.