IoT, AI, and Blockchain for .NET
Create applications using Industry 4.0. Discover how artificial intelligence (AI) and machine learning (ML) capabilities can be enhanced using the Internet of things (IoT) and secured using Blockchain, so your latest app can be not just smarter but also more connected and more secure than ever before. This book covers the latest easy-to-use APIs and services from Microsoft, including Azure IoT, Cognitive Services APIs, Blockchain as a Service (BaaS), and Machine Learning Studio.
Author: Nishith Pathak & Anurag Bhandari
Printing Type: High Quality, Colored
Number of Pages: 321 pages
Number of Chapters: 10 chapters
As you work through the book, you’ll get hands-on experience building an example solution that uses all of these technologies―an IoT suite for a smart healthcare facility. Hosted on Azure and networked using Azure IoT, the solution includes centralized patient monitoring, using Cognitive Services APIs for face detection, recognition, and tracking. Blockchain is used to create trust-based security and inventory management. Machine learning is used to create predictive solutions to proactively improve quality of life. By the end of the book, you’ll be confident creating richer and smarter applications using these technologies.
What you’ll learn?
Know the technologies underpinning Industry 4.0 and AI 2.0
Develop real-time solutions using IoT in Azure
Bring the smart capabilities of AI 2.0 into your application using a simple API call
Host and manage your solution on Azure
Understand Blockchain as a Service
Capture and analyze data on the fly
Make predictions using existing data
Book Chapters
Chapter 1: The Artificial Intelligence 2.0 Revolution
Chapter 2: Understanding the Internet of Things and Azure IoT Suite
Chapter 3: Creating Smart IoT Applications
Chapter 4: Understanding Cognitive APIs
Chapter 5: Consuming Microsoft Cognitive APIs
Chapter 6: Building Smarter Applications Using Cognitive APIs
Chapter 7: Understanding Blockchain
Chapter 8: Implementing Blockchain as a Service
Chapter 9: Capturing, Analyzing, and Visualizing Real-Time Data
Chapter 10: Making Predictions with Machine Learning
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