Apply machine learning using the Internet of Things (IoT) in the agriculture, telecom, and energy domains with case studies. This book begins by covering how to set up the software and hardware components including the various sensors to implement the case studies in Python.
The case study section starts with an examination of call drop with IoT in the telecoms industry, followed by a case study on energy audit and predictive maintenance for an industrial machine, and finally covers techniques to predict cash crop failure in agribusiness. The last section covers pitfalls to avoid while implementing machine learning and IoT in these domains.
After reading this book, you will know how IoT and machine learning are used in the example domains and have practical case studies to use and extend. You will be able to create enterprise-scale applications using Raspberry Pi 3 B+ and Arduino Mega 2560 with Python.
What You Will Learn
Who This Book Is For
Raspberry Pi and Arduino enthusiasts and data science and machine learning professionals.
Puneet Mathur is an author, AI consultant, and speaker who has over 20 years of corporate IT industry experience. He has risen from being a programmer to a third line manager working with multinationals such as HP, IBM, and Dell at various levels. For several years he has been working as an AI consultant through his company Boolbrite International for clients around the globe, by guiding and mentoring client teams stuck with AI and machine learning problems. He also conducts leadership and motivational workshops, and AI-based hands-on corporate workshops. His latest bestselling book, Machine Learning Applications using Python (Apress, 2018), is for machine learning professionals who want to advance their career by gaining experiential knowledge from an AI expert. His other books include The Predictive Program Manager, Prediction Secrets, and Good Money Bad Money.
IoT Machine Learning Applications in Telecom, Energy, and Agriculture
CHAPTER 1: Getting Started: Software and Hardware Needed
CHAPTER 2: Overview of IoT and IIoT
CHAPTER 3: Using Machine Learning with IoT and IIoT in Python
CHAPTER 4: Using Machine Learning and IoT in Telecom, Energy, and Agriculture
CHAPTER 5: Preparing for the Case Studies
CHAPTER 6: Configuring IIoT Energy Meter
CHAPTER 7: Telecom Industry Case Study: Solving the Problem of Call Drops with IoT
CHAPTER 8: Energy Industry Case Study: Predictive Maintenance for an Industrial Machine
CHAPTER 9: Agriculture Industry Case Study: Predicting a Cash Crop Yield
Apply machine learning using the Internet of Things (IoT) in the agriculture, telecom, and energy domains with case studies. This book begins by covering how to set up the software and hardware components including the various sensors to implement the case studies in Python.
The case study section starts with an examination of call drop with IoT in the telecoms industry, followed by a case study on energy audit and predictive maintenance for an industrial machine, and finally covers techniques to predict cash crop failure in agribusiness. The last section covers pitfalls to avoid while implementing machine learning and IoT in these domains.
After reading this book, you will know how IoT and machine learning are used in the example domains and have practical case studies to use and extend. You will be able to create enterprise-scale applications using Raspberry Pi 3 B+ and Arduino Mega 2560 with Python.
What You Will Learn
Who This Book Is For
Raspberry Pi and Arduino enthusiasts and data science and machine learning professionals.
Puneet Mathur is an author, AI consultant, and speaker who has over 20 years of corporate IT industry experience. He has risen from being a programmer to a third line manager working with multinationals such as HP, IBM, and Dell at various levels. For several years he has been working as an AI consultant through his company Boolbrite International for clients around the globe, by guiding and mentoring client teams stuck with AI and machine learning problems. He also conducts leadership and motivational workshops, and AI-based hands-on corporate workshops. His latest bestselling book, Machine Learning Applications using Python (Apress, 2018), is for machine learning professionals who want to advance their career by gaining experiential knowledge from an AI expert. His other books include The Predictive Program Manager, Prediction Secrets, and Good Money Bad Money.
IoT Machine Learning Applications in Telecom, Energy, and Agriculture
CHAPTER 1: Getting Started: Software and Hardware Needed
CHAPTER 2: Overview of IoT and IIoT
CHAPTER 3: Using Machine Learning with IoT and IIoT in Python
CHAPTER 4: Using Machine Learning and IoT in Telecom, Energy, and Agriculture
CHAPTER 5: Preparing for the Case Studies
CHAPTER 6: Configuring IIoT Energy Meter
CHAPTER 7: Telecom Industry Case Study: Solving the Problem of Call Drops with IoT
CHAPTER 8: Energy Industry Case Study: Predictive Maintenance for an Industrial Machine
CHAPTER 9: Agriculture Industry Case Study: Predicting a Cash Crop Yield
CHAPTER 1: Getting Started: Software and Hardware Needed.- CHAPTER 2: Overview of IoT and IIoT.- CHAPTER 3: Using Machine Learning with IoT and IIoT in Python.- CHAPTER 4: Using Machine Learning and IoT in Telecom, Energy, and Agriculture.- CHAPTER 5: Preparing for the Case Studies.- CHAPTER 6: Configuring IIoT Energy Meter.- CHAPTER 7: Telecom Industry Case Study: Solving the Problem of Call Drops with IoT.- CHAPTER 8: Energy Industry Case Study: Predictive Maintenance for an Industrial Machine.- CHAPTER 9: Agriculture Industry Case Study: Predicting a Cash Crop Yield.
Puneet Mathur is an author, AI consultant, and speaker who has over 20 years of corporate IT industry experience. He has risen from being a programmer to a third line manager working with multinationals such as HP, IBM, and Dell at various levels. For several years he has been working as an AI consultant through his company Boolbrite International for clients around the globe, by guiding and mentoring client teams stuck with AI and machine learning problems. He also conducts leadership and motivational workshops, and AI-based hands-on corporate workshops. His latest bestselling book, Machine Learning Applications using Python (Apress, 2018), is for machine learning professionals who want to advance their career by gaining experiential knowledge from an AI expert. His other books include The Predictive Program Manager, Prediction Secrets, and Good Money Bad Money.
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