9 Chapter 9Figure 9.1 Impact of IT on top urban populace.Figure 9.2 Smart cities overview.Figure 9.3 Traffic management.Figure 9.4 Smart parking.Figure 9.5 Smart policing.Figure 9.6 Shrewd lighting.Figure 9.7 Smart power.Figure 9.8 Google maps.Figure 9.9 Innovation in urban communities.Figure 9.10 Smart cities for all.Figure 9.11 Smart cities to prevent road accidents.Figure 9.12 Applications of IoT.
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Scrivener Publishing100 Cummings Center, Suite 541J Beverly, MA 01915-6106
Publishers at Scrivener Martin Scrivener ( martin@scrivenerpublishing.com) Phillip Carmical ( pcarmical@scrivenerpublishing.com)
Machine Learning Approaches for Convergence of IoT and Blockchain
Edited by
Krishna Kant Singh
Faculty of Engineering & Technology, Jain (Deemed-to-be University), Bengaluru, India
Akansha Singh
Amity University Uttar Pradesh, Noida, India
and
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KIET Group of Institutions, Delhi-NCR, Ghaziabad, India
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Blockchain technology and the Internet of Things (IoT) are two of the most impactful trends to have emerged in the field of machine learning. And although there are a number of books available solely on the subjects of machine learning, IoT and blockchain technology, no such book has been available which focuses on machine learning techniques for IoT and blockchain convergence until now. Thus, this book is unique in terms of the topics it covers. Designed as an essential guide for all academicians, researchers and those in industry who are working in related fields, this book will provide insights into the convergence of blockchain technology and the IoT with machine learning.
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