Artificial Intelligence for Edge Computing | KnowledgeNile

Edge computing has driven a lot of traction with the focus on the Industrial Internet of Things (IIoT) ever so increasing. This has raised many questions related to user privacy, data security, data efficiency, and the time required to fetch and transmit that data. But with the introduction of Artificial Intelligence (AI) for Edge Computing will clear most of these queries satisfactorily.

What is Edge Computing?

A Computing paradigm where most computing or in some cases total computing is performed on smart devices or edge devices instead of the centralized cloud is known as Edge Computing.

Edge Computing is considered as the first stage of Intent of Things; It handles the responsibility of collecting the data.
Since the data collection takes place on the end-to-end devices; unlike the existing centralized cloud computing in data centres; the data privacy and the data security aspects have come to the forefront.
But the introduction of Artificial Intelligence for Edge computing a.k.a. Edge AI has cleared these clouts with conviction.

What is Edge AI?

Edge AI is the process in which algorithms created for sensors or signals to fetch the data. The calculation takes place on the local hardware device. This device comprises of microprocessor and sensors.
Since the process requires local hardware device; there is no specific need of connecting the device to the internet and Artificial Intelligence can take the decisions without the internet connection quite easily and also with high accuracy.

Benefits of Artificial Intelligence for Edge Computing

Edge Computing allows real-time operations for critical processes such as data creation, analysis, decision making, and taking appropriate action for the same. There is a significant need for real-time action for the critical processes such as these as even the tiniest of milliseconds do matter.

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