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TinyML for Edge Intelligence in IoT and LPWAN Networks
Loot Price: R3,417
Discovery Miles 34 170
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TinyML for Edge Intelligence in IoT and LPWAN Networks
Expected to ship within 10 - 15 working days
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Recently, Tiny Machine Learning (TinyML) has gained incredible
importance due to its capabilities of creating lightweight machine
learning (ML) frameworks aiming at low latency, lower energy
consumption, lower bandwidth requirement, improved data security
and privacy, and other performance necessities. As billions of
battery-operated embedded IoT and low power wide area networks
(LPWAN) nodes with very low on-board memory and computational
capabilities are getting connected to the Internet each year, there
is a critical need to have a special computational framework like
TinyML. TinyML for Edge Intelligence in IoT and LPWAN Networks
presents the evolution, developments, and advances in TinyML as
applied to IoT and LPWANs. It starts by providing the foundations
of IoT/LPWANs, low power embedded systems and hardware, the role of
artificial intelligence 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 the use of TinyML are given from health and
industrial fields which provide practical guidance on the design of
applications and the selection of appropriate technologies. TinyML
for Edge Intelligence in IoT and LPWAN Networks is highly suitable
for academic researchers and professional system engineers,
architects, designers, testers, deployment engineers seeking to
design ultra-lower power and time-critical applications. It would
also help in designing the networks for emerging and future
applications for resource-constrained nodes.
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