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Scalable Data Streaming with Amazon Kinesis

You're reading from   Scalable Data Streaming with Amazon Kinesis Design and secure highly available, cost-effective data streaming applications with Amazon Kinesis

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781800565401
Length 314 pages
Edition 1st Edition
Languages
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Authors (4):
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Rajeev Chakrabarti Rajeev Chakrabarti
Author Profile Icon Rajeev Chakrabarti
Rajeev Chakrabarti
Tarik Makota Tarik Makota
Author Profile Icon Tarik Makota
Tarik Makota
Brian Maguire Brian Maguire
Author Profile Icon Brian Maguire
Brian Maguire
Danny Gagne Danny Gagne
Author Profile Icon Danny Gagne
Danny Gagne
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Table of Contents (13) Chapters Close

Preface 1. Section 1: Introduction to Data Streaming and Amazon Kinesis
2. Chapter 1: What Are Data Streams? FREE CHAPTER 3. Chapter 2: Messaging and Data Streaming in AWS 4. Chapter 3: The SmartCity Bike-Sharing Service 5. Section 2: Deep Dive into Kinesis
6. Chapter 4: Kinesis Data Streams 7. Chapter 5: Kinesis Firehose 8. Chapter 6: Kinesis Data Analytics 9. Chapter 7: Amazon Kinesis Video Streams 10. Section 3: Integrations
11. Chapter 8: Kinesis Integrations 12. Other Books You May Enjoy

Building video-enabled applications with KVS

Now that we have learned the fundamentals of KVS and KVS-WebRTC, they can be combined to enable video functionality in the SmartCity use case. The architecture shown in the following diagram fully exercises the video capabilities of KVS:

Figure 7.9 – SmartCity monitoring architecture

Throughout this chapter, we have built the component pieces of this architecture. The full solution is available in this book's GitHub repository. The application provides security and situational awareness for the users of the SmartCity bike system. It all starts with a camera pointed at the bike stands and supports the following three capabilities:

  • Real-time access to the camera via a browser using WebRTC
  • The ability to pull archival clips based on a timeframe using the AWS CLI to get a media file and using the CLI and VLC to view a stream
  • Automatic detection of known vandals via facial recognition using...
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