Engineering Edge AI Hardware for Aerospace & Defense

Overview

This document features an insightful discussion with Jeff Baldwin, Director of Engineering at Sealevel Systems, addressing the evolving role of AI-ready embedded computing at the edge in aerospace and defense systems. As AI increasingly moves processing closer to sensors and operators, the demands on edge computing grow, necessitating solutions that balance data throughput and performance with power, thermal, and lifecycle constraints in harsh, mission-critical environments.

A key trend shaping today’s edge system designs is the adoption of modular computing architectures. Modular designs start with a stable computing core, commonly a computer-on-module, around which specialty I/O and system components are built. This approach provides significant advantages for aerospace and defense applications, where systems require ruggedness, reliability, and long-term evolvability without full redesigns. Modularity accelerates development, enhances flexibility, and helps engineers manage the complex trade-offs between cost, functionality, delivery schedules, and strict size, weight, and power (SWaP) requirements.

“AI-ready” hardware today signifies a close collaboration between hardware capabilities and the customer’s AI software and models. Sealevel Systems focuses on providing application-specific hardware optimized to ingest sensor data from cameras or other inputs. AI acceleration can be supplied via various forms such as new CPU instruction sets, GPUs, NPUs, or TPUs. A tightly controlled core processor and RAM configuration with a stable board support package (BSP) underpins the system, ensuring operating system and driver reusability. Availability and supportability are critical considerations—particularly given rapid advances such as the shift from DDR4 to DDR5 memory—and systems must balance cutting-edge performance with long-term sustainment.

AI integration at the edge has significantly increased power and thermal management challenges. High-performance AI functionality demands substantially more power, and given the high current draw in short bursts, systems generate intense heat concentrated in small silicon areas. Sealevel addresses these challenges by eliminating moving parts, which are typical failure points, and designing for peak thermal conditions using dynamic, rugged thermal solutions.

To combat obsolescence in the fast-evolving AI hardware landscape, modular architectures provide adaptability, enabling system upgrades without full redesign. This design philosophy supports long program lifecycles characteristic of aerospace and defense projects, providing flexibility, reducing revalidation risks, and maintaining reliability in demanding environments.

In sum, Sealevel’s approach to edge AI computation tightly integrates modular, rugged, and supportable hardware platforms tailored to evolving aerospace and defense use cases, enabling sustained performance and agility over extended lifecycles.

For more information, visit www.sealevel.com.