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Opportunities in Edge Intelligence
Opportunities in Edge Intelligence
Enabling the Interconnection of the Grid of Things
06-Jul-2015
North America
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
Popular Topics
| 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 |