There’s often a disparity between AI dreams and the reality of existing hardware/digital infrastructure. A "crawl, walk, run" approach is vital, focusing on user experience and the four stages of IoT analytics. Learn how an IoT system topology supports the IoT AI journey and provides a solid starting point to demonstrate key challenges and opportunities in deploying an IoT AI Platform. Takeaways: Bridging the gap between AI aspirations and existing digital infrastructure realities. Learn the "crawl, walk, run" approach for systematic IoT ecosystem development. – Insight into sensing, analyzing, summarizing, and directing actions. Learn how IoT system topology is a starting point for deploying IoT AI platforms. Deploying intelligence cloud, edge, or both—within IoT AI platforms.
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With a Master’s of Aerospace Engineering and a Master of Business Administration, Daniel Fudge has over 20 years of experience bringing advanced analytics to reality in a wide array of applications, including space robotics, military flight simulators, and business jet engines. This synthesis of hardware, cloud computing, and Machine Learning (ML) is now focused on deploying intelligence to IoT systems.
Tracks: 3D/Additive, Automation, Cutting, Laser, Forming & Fabricating, Job Shop, Lean, Management, Marketing & Sales, Robotics, Smart Manufacturing, Stamping, Workforce Development
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