IoT Machine Learning Applications in Telecom, Energy, and Agriculture
Apress (Verlag)
978-1-4842-5548-3 (ISBN)
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
Implement machine learning with IoT and solve problems in the telecom, agriculture, and energy sectors with Python
Set up and use industrial-grade IoT products, such as Modbus RS485 protocol devices, in practical scenarios
Develop solutions for commercial-grade IoT or IIoT projects
Implement case studies in machine learning with IoT from scratch
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.
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.
| Erscheinungsdatum | 21.05.2020 |
|---|---|
| Zusatzinfo | 105 Illustrations, black and white; XV, 278 p. 105 illus. |
| Verlagsort | Berkley |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Informatik ► Weitere Themen ► Hardware | |
| Schlagworte | Arduino Mega • Cloud Computing • IOT • machine learning • Python • Raspberry Pi • Telecom |
| ISBN-10 | 1-4842-5548-8 / 1484255488 |
| ISBN-13 | 978-1-4842-5548-3 / 9781484255483 |
| Zustand | Neuware |
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