Identifying trends in artificial intelligence and edge-computing security

Identifying trends in artificial intelligence and edge-computing security

About the Client:

The Client was a leading producer of programmable logic devices that wanted to learn about emerging techs and trends regarding hardware-rooted security standards and artificial intelligence & machine learning (AI/ML) technologies in order to expand their product application into low-power edge computing for mobile devices and IoT sensors. 

Challenge:

The goals of this engagement were to:

  1. Focus on state-of-the-art hardware-rooted security technologies 
  2. Present differentiators among emerging technologies
  3. Cover strategic information (technology trends) and operational information (acquisition targets)

Approach:

PreScouter put together a team of Advanced Degree Researchers (ADRs) and recruited an IoT Subject Matter Expert (SME) who was a professor at Tampere University as the team leader. During the project, sequential research was performed that studied the hardware-rooted security standards and AI/ML technologies.

First, PreScouter landscaped AI/ML technology advances by looking at companies providing relevant products or services, startups, and research labs studying low-power edge applications as well as other potential applications. With information collected from publicly available resources, PreScouter and the Client culled the list for a deep-dive study.

PreScouter then switched gears toward studying sensor fusions applied in the IoT space for AI/ML. By identifying potential applications and landscaping the major players and possible competitors, PreScouter and the Client identified the most promising application and conducted an in-depth study of it.

Outcome:

PreScouter presented a total of 6 deliverables to the Client, including 4 that focused on AI/ML technology advances and 2 that focused on IoT hardware standards. For AI/ML technology advances, a total of 14 research groups, 19 companies, and 7 applications were identified and analyzed. For IoT hardware standards, 7 standards and 15 potential competitors were identified and analyzed. These results are summarized in the following diagram.

Impact of PreScouter’s work: 

PreScouter recommended to the Client a strategy for future application focuses, a potential acquisition target in the AI/ML market, and a strategy to comply with multiple standards in order to expand their product application.

A downloadable version of this case study is available here.

If you have any questions or would like to know if we can help your business with its innovation challenges, please contact us here or email us at solutions@prescouter.com.

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