Smarter Decisions – The Intersection of Internet of Things and Decision Science

Enter the world of Internet of Things with the power of data science with this highly practical, engaging book

Smarter Decisions – The Intersection of Internet of Things and Decision Science

Jojo Moolayil

1 customer reviews
Enter the world of Internet of Things with the power of data science with this highly practical, engaging book
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Book Details

ISBN 139781785884191
Paperback392 pages

Book Description

With an increasing number of devices getting connected to the Internet, massive amounts of data are being generated that can be used for analysis. This book helps you to understand Internet of Things in depth and decision science, and solve business use cases. With IoT, the frequency and impact of the problem is huge. Addressing a problem with such a huge impact requires a very structured approach.

The entire journey of addressing the problem by defining it, designing the solution, and executing it using decision science is articulated in this book through engaging and easy-to-understand business use cases. You will get a detailed understanding of IoT, decision science, and the art of solving a business problem in IoT through decision science.

By the end of this book, you’ll have an understanding of the complex aspects of decision making in IoT and will be able to take that knowledge with you onto whatever project calls for it

Table of Contents

Chapter 1: IoT and Decision Science
Understanding the IoT
Demystifying M2M, IoT, IIoT, and IoE
Digging deeper into the logical stack of IoT
The problem life cycle
The problem landscape
The art of problem solving
The problem solving framework
Summary
Chapter 2: Studying the IoT Problem Universe and Designing a Use Case
Connected assets & connected operations
Defining the business use case
Sensing the associated latent problems
Designing the heuristic driven hypotheses matrix (HDH)
Summary
Chapter 3: The What and Why - Using Exploratory Decision Science for IoT
Identifying gold mines in data for decision making
Exploring each dimension of the IoT Ecosystem through data (Univariates)
Studying relationships
Exploratory data analysis
Root Cause Analysis
Summary
Chapter 4: Experimenting Predictive Analytics for IoT
Resurfacing the problem - What's next?
Linear regression - predicting a continuous outcome
Decision trees
Logistic Regression - Predicting a categorical outcome
Summary
Chapter 5: Enhancing Predictive Analytics with Machine Learning for IoT
A Brief Introduction to Machine Learning
Ensemble modeling - random forest
Ensemble modeling - XGBoost
Neural Networks and Deep Learning
Packaging our results
Summary
Chapter 6: Fast track Decision Science with IoT
Setting context for the problem
Defining the problem and designing the approach
Exploratory Data Analysis and Feature Engineering
Building predictive model for the use case
Packaging the solution
Summary
Chapter 7: Prescriptive Science and Decision Making
Using a layered approach and test control methods to outlive business disasters
Connecting the dots in the problem universe
Story boarding - Making sense of the interconnected problems in the problem universe
Implementing the solution
Summary
Chapter 8: Disruptions in IoT
Edge/fog computing
Cognitive Computing - Disrupting intelligence from unstructured data
Next generation robotics and genomics
Autonomous cars
Privacy and security in IoT
Summary
Chapter 9: A Promising Future with IoT
The IoT Business model - Asset or Device as a Service
Smartwatch – A booster to Healthcare IoT
Smart healthcare - Connected Humans to Smart Humans
Evolving from connected cars to smart cars
Summary

What You Will Learn

  • Explore decision science with respect to IoT
  • Get to know the end to end analytics stack – Descriptive + Inquisitive + Predictive + Prescriptive
  • Solve problems in IoT connected assets and connected operations
  • Design and solve real-life IoT business use cases using cutting edge machine learning techniques
  • Synthesize and assimilate results to form the perfect story for a business
  • Master the art of problem solving when IoT meets decision science using a variety of statistical and machine learning techniques along with hands on tasks in R

Authors

Table of Contents

Chapter 1: IoT and Decision Science
Understanding the IoT
Demystifying M2M, IoT, IIoT, and IoE
Digging deeper into the logical stack of IoT
The problem life cycle
The problem landscape
The art of problem solving
The problem solving framework
Summary
Chapter 2: Studying the IoT Problem Universe and Designing a Use Case
Connected assets & connected operations
Defining the business use case
Sensing the associated latent problems
Designing the heuristic driven hypotheses matrix (HDH)
Summary
Chapter 3: The What and Why - Using Exploratory Decision Science for IoT
Identifying gold mines in data for decision making
Exploring each dimension of the IoT Ecosystem through data (Univariates)
Studying relationships
Exploratory data analysis
Root Cause Analysis
Summary
Chapter 4: Experimenting Predictive Analytics for IoT
Resurfacing the problem - What's next?
Linear regression - predicting a continuous outcome
Decision trees
Logistic Regression - Predicting a categorical outcome
Summary
Chapter 5: Enhancing Predictive Analytics with Machine Learning for IoT
A Brief Introduction to Machine Learning
Ensemble modeling - random forest
Ensemble modeling - XGBoost
Neural Networks and Deep Learning
Packaging our results
Summary
Chapter 6: Fast track Decision Science with IoT
Setting context for the problem
Defining the problem and designing the approach
Exploratory Data Analysis and Feature Engineering
Building predictive model for the use case
Packaging the solution
Summary
Chapter 7: Prescriptive Science and Decision Making
Using a layered approach and test control methods to outlive business disasters
Connecting the dots in the problem universe
Story boarding - Making sense of the interconnected problems in the problem universe
Implementing the solution
Summary
Chapter 8: Disruptions in IoT
Edge/fog computing
Cognitive Computing - Disrupting intelligence from unstructured data
Next generation robotics and genomics
Autonomous cars
Privacy and security in IoT
Summary
Chapter 9: A Promising Future with IoT
The IoT Business model - Asset or Device as a Service
Smartwatch – A booster to Healthcare IoT
Smart healthcare - Connected Humans to Smart Humans
Evolving from connected cars to smart cars
Summary

Book Details

ISBN 139781785884191
Paperback392 pages
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