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Data Science and Internet of Things [electronic resource] : Research and Applications at the Intersection of DS and IoT / edited by Giancarlo Fortino, Antonio Liotta, Raffaele Gravina, Alessandro Longheu

Published:
Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition:
1st ed. 2021.
Physical Description:
XII, 182 pages 87 illustrations, 77 illustrations in color : online resource
Additional Creators:
Fortino, Giancarlo, Liotta, Antonio, Gravina, Raffaele, Longheu, Alessandro, and SpringerLink (Online service)
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Series:
Contents:
Introduction -- Machine learning algorithms, techniques & applications in IoT domains -- Network science and IoT -- Social media analysis in scale -- UAV solutions in IoT -- IoT aided Smart Home Architecture for Anomaly Detection -- A modeling approach based on Multiplexity and EGT for resource sharing in Fog/Cloud Computing -- Correlations among Game of Thieves and other centrality measures in large networks -- Optimization strategy in data transmission on Narrowband IoT with LWM2M -- Improving Hydroponic Agriculture through IoT-enabled Collaborative Machine Learning -- An Energy-efficient Techniques for Constrained Application Protocol (CoAP) -- Analysis of GPS power consumption in constrained-resources devices -- A Collaborative BSN-enabled Architecture for Multi-user Activity Recognition -- Conclusion.
Summary:
This book focuses on the combination of IoT and data science, in particular how methods, algorithms, and tools from data science can effectively support IoT. The authors show how data science methodologies, techniques and tools, can translate data into information, enabling the effectiveness and usefulness of new services offered by IoT stakeholders. The authors posit that if IoT is indeed the infrastructure of the future, data structure is the key that can lead to a significant improvement of human life. The book aims to present innovative IoT applications as well as ongoing research that exploit modern data science approaches. Readers are offered issues and challenges in a cross-disciplinary scenario that involves both IoT and data science fields. The book features contributions from academics, researchers, and professionals from both fields. .
Subject(s):
ISBN:
9783030671976
Digital File Characteristics:
PDF
text file
Part Of:
Springer Nature eBook
View MARC record | catkey: 33184156