Intelligence at the Edge

Using SAS with the Internet of Things (Hardcover edition)

Michael Harvey

• Publisher: SAS Institute
• Year: 2020
• ISBN:
  9781642957785
• Topic: Computer Science
• Subtopic: Computer Science General
• Index: Computer Science

Explore powerful SAS analytics and the Internet of Things!

The world that we live in is more connected than ever before. The Internet of Things (IoT) consists of mechanical and electronic devices connected to one another and to software through the internet. Businesses can use the IoT to quickly make intelligent decisions based on massive amounts of data gathered in real time from these connected devices. IoT increases productivity, lowers operating costs, and provides insights into how businesses can serve existing markets and expand into new ones.

Intelligence at the Edge: Using SAS with the Internet of Things is for anyone who wants to learn more about the rapidly changing field of IoT. Current practitioners explain how to apply SAS software and analytics to derive business value from the Internet of Things. The cornerstone of this endeavor is SAS Event Stream Processing, which enables you to process and analyze continuously flowing events in real time. With step-by-step guidance and real-world scenarios, you will learn how to apply analytics to streaming data. Each chapter explores a different aspect of IoT, including the analytics life cycle, monitoring, deployment, geofencing, machine learning, artificial intelligence, condition-based maintenance, computer vision, and edge devices.

Chapter 1: Using SAS Event Stream Processing to Process Real World Events

By Michael Harvey, Robert Ligtenberg, and Jerry Baulier

Introduction

How Does SAS Event Stream Processing Work?

What is a SAS Event Stream Processing Model?

Processing Events in Derived Windows

Examples of Event Transformations

Example: Using a Join Window

Example: Using a Pattern Window and a Notification Window

Streaming Analytics

Using SAS Micro Analytic Service Modules with Streaming Analytics

Addressing Big Data and the Internet of Things

Edge Model to Process Measurements from a Power Substation

On-Premises Model for Further Processing

Conclusion

About the Contributors

Introduction

As Andrew G. Psaltis, the regional CTO for Cloudera, observes, “Data is flowing everywhere around us, through phones, credit cards, sensor-equipped buildings, vending machines, thermostats, trains, buses, planes, posts to social media, digital pictures and video – and the list goes on.” Being able to harness that data presents abundant business opportunities. How can a business best capitalize on those opportunities?

The answer: SAS Event Stream Processing. It enables you to process and analyze continuously flowing real-world events in real time. Events arrive through high-throughput, low-latency data flows called event streams. These data flows are generated by occurrences such as sensor readings or market data. Each event within an event stream can be represented as a data record that consists of any number of fields. For example, an event generated by a pressure sensor could include two fields: a pressure reading and a timestamp. A more complex financial trade event could include multiple fields for transaction type, shares traded, price, broker, seller, stock symbol, timestamp, and so on. SAS Event Stream Processing can process the pressure data or the trades at any given moment. It can alert you to events of interest the instant that they occur.

Innovations in technology have enabled the reduction of the cost and size of sensors. Now sensors can be readily deployed within industrial equipment and consumer products. The number of sensors available has exploded, and a large portion of these sensors are now connected through the internet. The deluge of resulting data streams is often called Big Data. The Internet of Things (IoT) attaches a plethora of devices, sensors, and objects in our world to the internet. Big Data is collected and processed in real time from these “things.”

SAS Event Stream Processing processes real-world data as it is generated. This instantly processed data is called streaming data. Processing streaming data introduces a paradigm shift from the traditional approach, where data is captured and stored in a database. After an event from an event stream is processed, it can be stored or discard...

Table of contents

• Contents
• Preface
• About the Author
• Chapter 1: Using SAS Event Stream Processing to Process Real World Events
• Chapter 2: Linking Real-World Data to SAS Event Stream Processing Through Connectors and Adapters
• Chapter 3: Applying Analytics to Streaming Data
• Chapter 4: Administering SAS Event Stream Processing Environments with SAS Event Stream Manager
• Chapter 5: SAS Event Stream Processing in an IoT Reference Architecture
• Chapter 6: Artificial Intelligence and the Internet of Things
• Chapter 7: Using Geofences with SAS Event Stream Processing
• Chapter 8: Using Deep Learning with Your IoT Digital Twin
• Chapter 9: Leveraging ESP to Adapt to Variable Data Quality for Location-Based Use Cases
• Chapter 10: Condition Monitoring Using SAS Event Stream Processing
• Chapter 11: Analytics with Computer Vision on the Edge
• Summary