Opportunities in Edge Intelligence

Enabling the Interconnection of the Grid of Things

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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

Opportunities in Edge IntelligenceExecutive SummaryFuture of Intelligence in the Utility IndustryGrid Edge Intelligence—Preparing for the FutureExecutive Summary—Key FindingsDefinition of Edge IntelligenceIntroduction to Edge IntelligenceEvolution of Grid Decision MakingEvolution of Grid Decision Making (continued)How and why is Edge Intelligence So Important in a Smart Grid?Challenges and DriversChallenge—Typical Edge Intelligence-related ConcernsChallenge—Typical Edge Intelligence-related Concerns (continued)Driver—Siloed to De-siloed Business StructureDriver—Rise of Operational AnalyticsDriver—Focus on Maximizing CapabilitiesGlobal Market OutlookThe Era of Edge Intelligence (2015–2020)Rise of Analytics—From Data to IntelligenceEdge Intelligence—Global TrendsEdge Intelligence—Global Trends (continued)Edge Intelligence—Global Trends (continued)Current and Future OutlookEdge Intelligence—StakeholdersCase StudyCase Study 1—Grid Edge Implementation: Duke EnergyCase Study 1—Grid Edge Implementation: Duke Energy (continued)Case Study 2—Achieving Distributed Intelligence by Converting Smart Meters into A Grid Edge Computing PlatformCase Study 3—Open Source Platforms And Software-defined Architecture Drive Distributed Grid Edge IntelligenceConclusionConclusionLegal DisclaimerAppendixAdditional Sources of Information on Smart PlantsPartial List of Companies InterviewedThe Frost & Sullivan StoryThe Frost & Sullivan StoryValue Proposition: Future of Your Company & CareerGlobal PerspectiveIndustry Convergence360º Research PerspectiveImplementation ExcellenceOur Blue Ocean Strategy




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