Workflow for Defence Embedded Systems using AI

Unveiling the Future of Defence and Aerospace Technology

Welcome to an exciting exploration into the future of Defence and Aerospace technologies. Firstly, this white paper is written by Dowson Robotics and WOLF Advanced Technology. This document provides an in-depth analysis and guidance on the workflow for Defence and Aerospace embedded systems using Artificial Intelligence (AI).

The Collaboration of Dowson Robotics and WOLF Advanced Technology

In this venture, Dowson Robotics and WOLF Advanced Technology, two pioneers in the field, combine their expertise. Dowson Robotics provides technical consulting and management services in AI and computer vision applications. Meanwhile, WOLF Advanced Technology has been making strides with its GPU and FPGA-based modules used in numerous AI and computer vision programs, particularly in the Defence and Aerospace sectors.

AI: The Game-Changer in Embedded Systems

The white paper delves into how AI and machine vision projects differ from traditional embedded processor projects. While typical systems may require occasional updates, AI-driven systems need regularly scheduled updates to incorporate the latest deep learning results. This process is crucial to stay abreast of new or changing data sets.

Data: The Cornerstone of AI in Defence and Aerospace

One of the key insights is the amount of data required for successful AI training. In high-stakes fields like Defence and Aerospace, the quantity and quality of training data can make a significant difference in the performance and reliability of AI applications.

The Multifaceted World of AI

The paper highlights various capabilities of AI, including computer vision, natural language processing, knowledge representation, automated reasoning, machine learning, and robotics. These aspects are crucial in developing advanced systems for this industry.

Investing in the Future

The focus of this paper is the investment required in AI projects.  Such as in resources for training, testing, and validation. It underscores the importance of quality data.  For example, citing the ImageNet Large Scale Visual Recognition Challenge as an example of a comprehensive data set used for AI training.


This white paper serves as an essential guide for professionals and enthusiasts in the defence and aerospace sectors. It offers a comprehensive understanding of the challenges and solutions in implementing AI in embedded systems. By highlighting the unique aspects of AI development workflows, Dowson Robotics and WOLF Advanced Technology pave the way for innovative, efficient, and effective solutions in these critical fields.

The white paper is a must-read.  Especially for those looking to grasp the complexities and potentials of AI in defence and aerospace. It stands as a testament to the collaborative efforts of Dowson Robotics and WOLF Advanced Technology. Shaping the future of technology in these vital industries.

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