How AI is Applied in Embedded Computing Systems Designs Aligned to SOSA

Publish Date:
July 15, 2021

“AI technologies are the most powerful tools in generations for expanding knowledge, increasing prosperity, and enriching the human experience.”  — National Security Commission on Artificial Intelligence; 2021 Final Report

AI benefits the warfighter in the field with improved tools

In a world where the amount of data inputs and video feeds continue to increase, embedded system designers need the tools and means to properly manage these inputs and make this data actionable.  For mission-critical and safety-related military and defense operations, this task becomes even more important.

Implementing AI-based solutions in rugged embedded computing isn’t the only trend affecting system development. The mandate across the US DoD (Department of Defense) for systems and electronics to be interoperable across all platforms and manufacturers is driving change within the industry as well.  

Fortunately, the SOSA™ Technical Standard, one of the open standards initiatives supported by the DoD’s Modular Open System Approach (MOSA), is enabling the needed level of data computation and processing that AI requirements mandate. The ability for systems to utilize a common architecture provides the means for quick development of advanced processing capabilities that enables AI-based computation.

Supporting AI Infrastructure Through SOSA

AI applications make use of SBCs, and GPGPUs and FPGA accelerators with an embedded system.  In SOSA, the boards that implement them are called PICs or Plug-In Cards.
It’s the actual application — ISR, EW, etc. — that drives the algorithms and data sets specific to the use case, which in turn drives the system topology.
Some system implementations may require more than one accelerator, or GPGPU.  Because GPGPUs or accelerators require use of the Expansion Plane, a system designed to align with SOSA must consider the connections needed to facilitate data transfers.

Effective System Development

When building an embedded system that will require AI level data processing, as well as adherence to the SOSA Technical Standard, taking into account certain design principles will enable you to meet all of your system requirements.

Simplicity of SOSA Proves Performance

As part of ensuring interoperability across different systems and platforms, SOSA restricts the number of acceptable profiles that can be applied in system development. This limited number of design options benefits compute-intensive systems, since profiles get re-used, reducing the need for complex integration efforts.

The goal of the standard is to design a non-proprietary open systems architecture to lower system development costs as well as make system reconfigurability and future system upgrades easier and faster. A key part is ensuring conformance for sensor components and SOSA modules in alignment with the Technical Standard.


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