Tria modules integrate edge AI processing with multi-core processors

Tria has introduced a family of embedded compute modules featuring Qualcomm Dragonwing processors with multi-operating system support. The modules support Android, Windows 11 IoT Enterprise, and Yocto Linux, enabling deployment across industrial, medical, agriculture, and construction sectors where edge computing, machine learning, and AI capabilities provide operational advantages.

The modules utilize Qualcomm Dragonwing processors designed for speed, scalability, and reliability in embedded systems applications. These processors deliver edge AI processing capabilities and networking functionality while maintaining low power consumption characteristics. The combination enables embedded designs to implement machine learning algorithms and AI processing locally, reducing latency and bandwidth requirements compared to cloud-based processing approaches.

A significant engineering development is Tria’s implementation of Microsoft Windows with ARM architecture, allowing engineers to transition from x86 architecture to ARM while maintaining the same operating system environment. This transition addresses previous limitations where Windows on ARM was not available for embedded applications, providing consistency in development tools and application compatibility.

The product lineup includes four module configurations built on SMARC standard modules and Open Standard Modules (OSM) formats. The Qualcomm Dragonwing IQ-615 processor modules support Linux operating systems. The QCS5430 and QCS6490 processor variants provide compatibility with Linux, Android, and Windows 11 IoT Enterprise operating systems. The IQ9 Series processors support Linux implementations, while the Snapdragon X Elite processor modules operate with Windows 11 IoT Enterprise.

The Qualcomm Dragonwing processors provide multi-core processing capabilities and GPU performance while maintaining power efficiency for mobile and portable system implementations. The processors integrate AI acceleration hardware that enables local inference processing, reducing the computational load on system CPUs and improving overall system response times.

These modules target industrial automation and robotic applications where multiple operating system compatibility provides flexibility in software development and system integration. Engineers can select the operating system that aligns with their existing development tools, legacy software requirements, or specific application needs without changing hardware platforms.