Emerging data-based technologies such as IoT, Artificial Intelligence, Augmented Reality and Virtual Reality, Blockchain and edge computing dominate many conversations in the technology sector.

Organisations that map their digital transformation path must face the understanding of how these emerging technologies adapt to their strategies. An important consideration for these technologies is where they overlap or can be used together to achieve business results.

For example, where artificial intelligence meets the IoT, sometimes referred to as the Artificial Intelligence of Things (AIoT), it provides functions that go beyond the individual adoption of both technologies. AIOT offers networks of connected devices the possibility to collect large amounts of data from the physical world and, with programmable intelligence,

As Benita Mordi, Artificial Intelligence and IoT Strategy of Dell, points of intersection between the physical and digital worlds are what is called “Edge”. It is the point where data is generated, collected and processed to create new value, and it is as different as the sectors that define Edge’s use cases.

Lupidge presents new challenges to how IT processes data.Where we historically rely on traditional data centers and cloud computing to process data generated outside data centers, the need to get value in real time This led to the birth of the Edge Computing.

Edge Computing generates value for organizations by accelerating both the discovery of insights from data and the digitisation of key business processes. It also allows companies to redefine their end-customers’ experiences.

An interesting consequence of the Edge Computing regarding the Artificial Intelligence of Things, is that it becomes the vehicle that brings the Edge to the source of data generation (IoT).

In the new era of edge computing, Edge processing platforms will provide light projects that can be successfully implemented despite space, environmental, power and connectivity constraints. These projects can be protected and can support applications that require real-time insights.

According to Dell, the organisational strategy for the edge will be very different because there are no two equal projects.

Perhaps, Mordi comments, solutions that start with a basic level of implementations will be easier to be current at first stroke. A path, continues the manager, already followed in the first implementations of artificial intelligence.

Defining the use of the edge in terms of business results will be important for clarity.

For example, a farmer who has to check the proper functioning of windmills will use the edge computing in a very different way than the breeder who wants to monitor the health of his cows.

Although the case of use is similar, subtle differences around • what is monitored will affect the way technology implementations will take place; up to data architectures, the chosen platform, data processing and security all over the world. As with most adoptions of new technologies, the distribution of all the Edge should have measurable targets and allow a rapid return on investment to succeed.

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