Opportunities in Edge Intelligence

Opportunities in Edge Intelligence

Enabling the Interconnection of the Grid of Things

RELEASE DATE
06-Jul-2015
REGION
North America
Research Code: 9AAE-00-24-00-00
SKU: EG00064-NA-MR_00559
$1,500.00
In stock
SKU
EG00064-NA-MR_00559
$1,500.00
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Description

Edge intelligence is the combination of business intelligence and automation that can sense and synthesize massive volumes of data and make decisions close to the data collection point. Applications include collecting, analyzing, and communicating data within the specified ecosystem and making real-time decisions to achieve unprecedented levels of reliability and efficiency. Earlier, monitoring systems used to gather data and communicate the same to the central control system to trigger alerts or generate standalone reports and displays for users. In today's edge intelligence architecture, the grid is designed to perform a host of functions, including decision making, close to the point of data collection, at speeds that centralized systems cannot match. This study includes a discussion of key drivers and challenges that influence the demand for edge intelligence.

Table of Contents

Future of Intelligence in the Utility Industry

Grid Edge Intelligence—Preparing for the Future

Executive Summary—Key Findings

Introduction to Edge Intelligence

Evolution of Grid Decision Making

Evolution of Grid Decision Making (continued)

How and why is Edge Intelligence So Important in a Smart Grid?

Challenge—Typical Edge Intelligence-related Concerns

Challenge—Typical Edge Intelligence-related Concerns (continued)

Driver—Siloed to De-siloed Business Structure

Driver—Rise of Operational Analytics

Driver—Focus on Maximizing Capabilities

The Era of Edge Intelligence (2015–2020)

Rise of Analytics—From Data to Intelligence

Edge Intelligence—Global Trends

Edge Intelligence—Global Trends (continued)

Edge Intelligence—Global Trends (continued)

Current and Future Outlook

Edge Intelligence—Stakeholders

Case Study 1—Grid Edge Implementation: Duke Energy

Case Study 1—Grid Edge Implementation: Duke Energy (continued)

Case Study 2—Achieving Distributed Intelligence by Converting Smart Meters into A Grid Edge Computing Platform

Case Study 3—Open Source Platforms And Software-defined Architecture Drive Distributed Grid Edge Intelligence

Conclusion

Legal Disclaimer

Additional Sources of Information on Smart Plants

Partial List of Companies Interviewed

The Frost & Sullivan Story

Value Proposition: Future of Your Company & Career

Global Perspective

Industry Convergence

360º Research Perspective

Implementation Excellence

Our Blue Ocean Strategy

Related Research
Edge intelligence is the combination of business intelligence and automation that can sense and synthesize massive volumes of data and make decisions close to the data collection point. Applications include collecting, analyzing, and communicating data within the specified ecosystem and making real-time decisions to achieve unprecedented levels of reliability and efficiency. Earlier, monitoring systems used to gather data and communicate the same to the central control system to trigger alerts or generate standalone reports and displays for users. In today's edge intelligence architecture, the grid is designed to perform a host of functions, including decision making, close to the point of data collection, at speeds that centralized systems cannot match. This study includes a discussion of key drivers and challenges that influence the demand for edge intelligence.
More Information
No Index No
Podcast No
Author Rajalingam Chinnasamy
Industries Energy
WIP Number 9AAE-00-24-00-00
Keyword 1 Opportunities in Edge Intelligence
Keyword 2 Edge Intelligence
Keyword 3 Edge Intelligence
Is Prebook No