Toradex leverages Amazon® Web Services (AWS) and NXP® to demonstrate how to simplify the creation of Industry 4.0-ready industrial automation solutions. A live demonstration that leverages expertise and technology across all three companies will be on display at the Industry of Things World in Berlin from September 16 through September 17.
The demo includes:
- NXP’s high performance MX 8QuadMax application processor, optimized for safety and reliability
- AWS IoT Greengrass and Amazon SageMaker Neo, which provide optimized machine learning at the device edge, plus seamless online and offline capabilities
- Toradex’s easy-to-use Computer on Modules/System on Modules and software, which simplify development and maintenance while lowering time to market
The demo is built around a conveyor belt simulating a factory automation line. A MIPI CSI Camera is used to detect and classify objects. Different types of pasta are used as an example for this showcase. The demo shows how to solve many challenges faced in today’s smart factories, some of which include:
- Secure connectivity for integrations with business tools, remote monitoring, updates, etc.
- Maximum uptime and reliability even with intermittent connectivity
- Small rugged and cost-optimized computing hardware
- Use of the latest technologies in computer vision and machine learning
- Short time to market and limited development resources
It highlights how the collaboration between these companies simplifies many of the steps required to build advanced industrial automation equipment for Industry 4.0.
In the future, this demo will be made available as a starting point to reduce the risk and time to market.
More Information On The Hardware:
Toradex’s Apalis iMX8QM System on Module features NXP’s i.MX 8 QuadMax SoCs. The i.MX 8 applications processor family is built with a high-level integration to support graphics, video, image processing, audio, and voice functions, and is ideal for safety-certifiable and efficient performance requirements.
The demo has a local graphical user interface, as well as a cloud-based control dashboard hosted on AWS.
With Amazon SageMaker a neural network was trained to detect and classify different types of pasta. The trained network was optimized with Amazon SageMaker Neo for the Apalis iMX8QM, resulting in increased performance and efficiency.