Optimal Localization of Internet of Things Nodes
Sheetal N Ghorpade, Marco Zennaro, Bharat S Chaudhari
Häftad, 2021
869 kr
2 199 kr
Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.
TinyML for Edge Intelligence in IoT and LPWAN Networks presents the evolution, developments, and advances in TinyML as applied to the Internet of Things (IoT) and low-power wide area networks (LPWANs). It starts by providing the foundations of IoT/LPWANs, low-power embedded systems and hardware, the role of AI and machine learning in communication networks in general, and cloud/edge intelligence. It then presents the concepts, methods, algorithms, and tools of TinyML. Practical applications of TinyML are given from the healthcare and industrial sectors, providing practical guidance on the design of applications and the selection of appropriate technologies.
2 199 kr
Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.
TinyML for Edge Intelligence in IoT and LPWAN Networks presents the evolution, developments, and advances in TinyML as applied to the Internet of Things (IoT) and low-power wide area networks (LPWANs). It starts by providing the foundations of IoT/LPWANs, low-power embedded systems and hardware, the role of AI and machine learning in communication networks in general, and cloud/edge intelligence. It then presents the concepts, methods, algorithms, and tools of TinyML. Practical applications of TinyML are given from the healthcare and industrial sectors, providing practical guidance on the design of applications and the selection of appropriate technologies.
2 199 kr
Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.
TinyML for Edge Intelligence in IoT and LPWAN Networks presents the evolution, developments, and advances in TinyML as applied to the Internet of Things (IoT) and low-power wide area networks (LPWANs). It starts by providing the foundations of IoT/LPWANs, low-power embedded systems and hardware, the role of AI and machine learning in communication networks in general, and cloud/edge intelligence. It then presents the concepts, methods, algorithms, and tools of TinyML. Practical applications of TinyML are given from the healthcare and industrial sectors, providing practical guidance on the design of applications and the selection of appropriate technologies.