Analysts explore technical and economic benefits of Edge Computing for IIoT
The industrial edge needs intelligence for many Industrial Internet of Things (IIoT) projects to produce successful results, both technically and financially. To make the edge “intelligent,” end users must understand what constitutes the real edge close to or even at the data sources, what both the edge and the cloud can and cannot accomplish, the key challenges in creating an intelligent industrial edge, and the significant technical and, most importantly, economic benefits this transformation will deliver.
ABI’s latest report, entitled “The Business Case for Industrial IoT Edge Intelligence” explores the technical and economic benefits of IIoT Edge intelligence.
Design considerations include:
Leveraging a hyper efficient complex event processor (CEP) for real time analytics on streaming industrial data.
Harnessing IIoT AI, including continuous, closed loop Edge to Cloud machine learning.
Lowering data persistence and transport requirements through edge intelligence.
Improving security posture by eliminating the need to transmit sensitive OT data across networks.
Deploying cloud agnostic edge intelligence to facilitate multi/hybrid cloud strategies.
Seamless bridging edge intelligence with OT tribal knowledge, transferring operator domain expertise into analytic expressions and ML models.
Leveraging small footprint edge computing and controller hardware to minimize new compute investments.
Benefiting from subscription, not consumption, based pricing for much more controllable / predictable operating costs and radically lower charges for data intensive applications.
Download the report and get expert analysis on the technical and economic benefits of adding edge intelligence into industrial operations, including several real-world use cases.