Data analytics in the era of the industrial internet of things / Aldo Dagnino.
2021
QA76.9.Q36 D34 2021
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Title
Data analytics in the era of the industrial internet of things / Aldo Dagnino.
Author
ISBN
9783030631390 (electronic bk.)
3030631397 (electronic bk.)
3030631389
9783030631383
3030631397 (electronic bk.)
3030631389
9783030631383
Publication Details
Cham : Springer, 2021.
Language
English
Description
1 online resource
Item Number
10.1007/978-3-030-63139-0 doi
Call Number
QA76.9.Q36 D34 2021
Dewey Decimal Classification
001.4/2
Summary
This book presents the characteristics and benefits industrial organizations can reap from the Industrial Internet of Things (IIoT). These characteristics and benefits include enhanced competitiveness, increased proactive decision-making, improved creativity and innovation, augmented job creation, heightened agility to respond to continuously changing challenges, and intensified data-driven decision making. In a straightforward fashion, the book also helps readers understand complex concepts that are core to IIoT enterprises, such as Big Data, analytic architecture platforms, machine learning (ML) and data science algorithms, and the power of visualization to enrich the domains experts' decision making. The book also guides the reader on how to think about ways to define new business paradigms that the IIoT facilitates, as well how to increase the probability of success in managing analytic projects that are the core engine of decision making in the IIoT enterprise. Useful for any industry professional interested in advanced industrial software applications, including business managers and professionals interested in how data analytics can help industries and to develop innovative business solutions, as well as data and computer scientists who wish to bridge the analytics and computer science fields with the industrial world, and project managers interested in managing advanced analytic projects.
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Print version: 9783030631383
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Table of Contents
Chapter 1: Industrial Internet of Things Framework
Chapter 2: Industrial Analytics
Chapter 3: Machine Learning to Predict Fault Events in Power Distribution Systems
Chapter 4: Analyzing Events and Alarms in Control Systems
Chapter 5: Condition Monitoring of Rotating Machines in Power Generation Plants
Chapter 6: Machine Learning Recommender for New Products and Services
Chapter 7: Managing Analytic Projects in the IIoT Enterprise.
Chapter 2: Industrial Analytics
Chapter 3: Machine Learning to Predict Fault Events in Power Distribution Systems
Chapter 4: Analyzing Events and Alarms in Control Systems
Chapter 5: Condition Monitoring of Rotating Machines in Power Generation Plants
Chapter 6: Machine Learning Recommender for New Products and Services
Chapter 7: Managing Analytic Projects in the IIoT Enterprise.