How Advantech Empowers AI at the Edge

Your Data is at the Edge

Industrial applications in the 21^st century require vast amounts of data to be generated on-site. This is the case whether working with smart sensor networks, image and video processing (such as pattern or object recognition), machines and systems (for optimisation and predictive maintenance), or ‘intelligent’ robots that feature path and runtime optimisation.

Driven by cost and performance benefits, over the years there has been a steady shift of increasing amounts of AI applications away from the cloud and towards the Edge, enabling local data processing to be carried out where it’s generated.

Why Edge AI matters for Industry

In the past, AI’s high-performance computer demands meant that it was only possible to run AI applications in the cloud. However, thanks to advances in technology, more powerful processors make it possible for AI applications to be run directly at the Edge.

This transition from cloud to the Edge offers several major advantages over a purely cloud-based solution for industrial applications, especially those where real-time responsiveness is vital.

Key benefits of this approach include:

• ultra-low latency for real-time execution of programs
• increased reliability through secure off-line operation
• significantly lower power consumption
• higher data and operational security due to sensitive data being processed on-site
• major cost savings due to lower bandwidth requirements

Evaluating AI Performance for Your Application

The first step when deploying Edge AI is to identify the specific AI performance requirements of your application. This is achieved by carrying out tests using real-world data and models – or at least the closest possible approximations to your own use case.

Advantech’s EdgeAI SDK offers an inference benchmarking tool that is unparallelled in its power. Allowing you to run identical models across various hardware platforms, the EdgeAI SDK compares such performance metrics as maximum frame rate (FPS), latency and power consumption. What’s more, it achieves this within just a few minutes.

Sample applications currently available include object detection, facial recognition, person tracking and pose estimation. In this way, Advantech provides a quick and easy solution for selecting the most suitable silicon for implementing your own AI projects. However, choosing the right hardware is only one piece in the larger puzzle. When it comes to Edge AI, software compatibility and ecosystem integration are equally vital.
 

Scalable AI Solutions for Customer Satisfaction 

In order to deploy Edge AI effectively, it is essential to achieve a harmonious blend of the most suitable hardware, optimised models and a robust software infrastructure. To deliver optimal integration of these elements there has to be the correct balance of computing platforms, toolchains, operating systems and AI frameworks – all tailored to the specific application.

To address these challenges, Advantech, backed by strong partnerships with leading silicon vendors, is able to support customers to achieve their goals with a comprehensive suite of hardware and software tools. We have extensive experience in adapting diverse AI model formats to specific platforms – ensuring your solution is not only ideally suited to your specific requirements but is easily scalable too.

For more information, visit www.advantech.com/en-eu.