By akademiotoelektronik, 10/11/2022

Edge AI: booming technology that combines artificial intelligence and edge computing

According to Researchandmarkets forecasts, the commercial use of artificial intelligence could potentially generate up to $ 1,800 billion by 2027.If the global Edge AI software market should only reach $ 3.1 billion by 2027 according to the Research Dive report, it is also growing strong.

Cloud Computing and Edge Computing

Currently, companies, associations, organizations, experts and individuals are many to use data in large quantities.The majority of them are treated in datacenters: this is Cloud Computing.However, the increase in the number of data processed and exchanged generates risks of bandwidth saturation and therefore increases latency, while concentrating the consumption of resources.

Edge Computing makes it possible to respond to these constraints, by performing calculations on the outskirts of the network.This distributed computer division tries to bring data storage closer and the computing power to process as close as possible to the connected device.This approach makes it possible to increase performance tenfold while reducing operating costs.

Edge AI: The meeting of artificial intelligence and edge computing

The EDGE AI (or EDGE Intelligent) appeared in a desire to integrate artificial intelligence as close as possible to the sensors or connected objects (IoT).The advantages are multiple: lack of prerequisites for permanent internet connectivity, data confidentiality, latency reduction.

The EDGE AI makes it possible to move part of the computer processing flow directly in connected objects, and therefore to minimize the use of the cloud for the tasks linked to the treatment.

The advantages of Edge AI

The potential of Edge AI is very important.Here is a non -exhaustive list of advantages that can be drawn from this technology:

A technology whose market is growing

The EDGE AI can be used for several uses such as video surveillance where smart cameras that use this technology can locally treat videos to identify people or objects.Its exploitation in autonomous cars is eagerly awaited: the computing power required by these kinds of systems requires components like the EDGE AI to process locally and in real time all the data necessary for the operation of the vehicle: we could notImagine that a car is controlled by the cloud, for latency and connectivity issues.

EDGE servers and EDGE Intelligent technology are deployed in factories, stores, hospitals, financial institutions, etc..for many purposes.In video surveillance as mentioned before, but also in the management of inventories or administrative files, robotics, medical imaging or industrial maintenance.

The World EDGE AI software market is expected to reach $ 3.1 billion by 2027 according to the Research Dive report, an Indian institution specializing in market studies.The annual growth rate composed (CAGR) between 2020 and 2027 would be 28.8 %.Two figures that confirm that the EDGE Intelligent sector is booming.

So, cloud ai or edge ai?

These two solutions have advantages and disadvantages and are not intended for the same uses.To these two possibilities is added a third alternative, that of the Federated Learning, which tries to reconcile the advantages of the first two.