IoT Machine Learning Applications in Telecom, Energy, and Agriculture
- Paperback: 293 pages
- Publisher: WOW! eBook; 1st edition (May 10, 2020)
- Language: English
- ISBN-10: 1484255488
- ISBN-13: 978-1484255483
IoT Machine Learning Applications in Telecom, Energy, and Agriculture: With Raspberry Pi and Arduino Using Python
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.
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
After reading this IoT Machine Learning Applications in Telecom, Energy, and Agriculture 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.