Khalifa sara (5 Ergebnisse)
- Softcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
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EUR 55,21
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Zustand: New. In.
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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EUR 164,49
EUR 62,44 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers cutting edge advancements on self-powered Internet of Things, where sensing devices can be energy-positive while capturing context from the physical world. It provides new mechanisms for activity recognition without the need of conventional… inertial sensors, which demand significant energy during their operation and thus quickly deplete the batteries of internet-of-things (IoT) devices. The book offers new solutions by employing energy harvesters as activity sensors as well as power sources to enable the autonomous and self-powered operation of IoT devices without the need of human intervention. It provides useful content for graduate students as well as researchers to understand the nascent technologies of human activity, fitness and health monitoring using autonomous sensors. In particular, this book is very useful for people working on pervasive computing, activity recognition, wearable IoT, fitness/healthcare and autonomous systems.This book covers a broad range of topics related to self-powered activity recognition. The main topics of this book include wearables, IoT, energy harvesting, energy harvesters as sensors, activity recognition and self-powered operation of IoT devices. This book starts with the introduction of wearable IoT devices and activity recognition and then highlights the conventional activity recognition mechanisms. After that, it describes the use of energy harvesters to power the IoT devices. Later, it explores the use of various energy harvesters as activity sensors. It also proposes the use of energy harvesters as simultaneous source of energy and context information and defines the emerging concept of energy-positive sensing compared to conventional energy-negative sensing. Finally, it explores sensor/signal fusion to enhance the performance using multiple energy harvesters and charts a way forward for future research in this area.This book covers all important and emerging topics that have significance in the design and implementation of autonomous wearable IoT devices. We believe that this book will lay the foundation for designing self-powered IoT devices which can ultimately replace the conventional wearable IoT devices which need regular recharging and replacement.
- Softcover
Anbieter: preigu, Osnabrück, Deutschlandpreigu
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EUR 167,00
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Taschenbuch. Zustand: Neu. Machine Learning for Drone-Enabled IoT Networks | Opportunities, Developments, and Trends | Jahan Hassan (u. a.) | Taschenbuch | Advances in Science, Technology & Innovation | ix | Englisch | 2026 | Springer | EAN 9783031809637 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 1…7, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Self-powered Internet of Things: How Energy Harvesters Can Enable Energy-positive Sensing, Processing, and Communication
Sandhu, Muhammad Moid/ Khalifa, Sara/ Portmann, Marius/ Jurdak, Raja
- Hardcover
Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books
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EUR 237,71
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Hardcover. Zustand: Brand New. 185 pages. 9.25x6.10x0.63 inches. In Stock.
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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EUR 192,59
EUR 64,00 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book aims to explore the latest developments, challenges, and opportunities in the application of machine learning techniques to enhance the performance and efficiency of IoT networks assisted by aerial unmanned vehicles (UAVs), commonly known as drone…s. The book aims to include cutting edge research and development on a number of areas within the topic including but not limited to: -Machine learning algorithms for drone-enabled IoT networks -Sensing and data collection with drones for IoT applications -Data analysis and processing for IoT networks assisted by drones -Energy-efficient and scalable solutions for drone-assisted IoT networks -Security and privacy issuesin drone-enabled IoT networks -Emerging trends and future directions in ML for drone-assisted IoT networks.
