1. Introduction to Edge Computing
2. The “platform concept” as a path for tech-transfer in solid-state physics
3. Skills available in the ECT
4. Conclusions and outlook
1. Introduction to Edge Computing Let’s assume that there is an interesting problem that requires: - thousands of measurement instruments - operating in real-time - with public demanding results in real-time - … before the ‘devices’ are ‘finished’ Examples : - Meteo (pre-smartphone era) - Covid19 epidemiology, research - Intensive agriculture, logistics, war...
1. We will attend a specific demand of society. We will actively scout for cases.
2. The platform
3. Technical skills
Machine learning “algorithms”
Internet of Things “secure data transport”
Edge Computing “hardware design”
Implementation and use of standard neural network packages to classify traffic and hand gestures. Cooperation with world-class institution : Cognigron Basic research to get familiar into the vast field
Upgrade of the ‘old’ cluster to optimize data in/out for IoT applications Mastering wireless comms and solar power: wireless boxes and wearables Continuous maintenance of the secure IT infrastructure
First PCB made-in-FZU coming up for testing lamp corrosion Setting up tools and equipment to manipulate electronic components, getting familiar with local suppliers. ~“build a lab”. We are able to quickly replicate ‘AFMEM 1.0’ and beyond (with light) internally
4. Conclusions and outlook
Machine learning “algorithms” Internet of Things “secure data transport” Edge Computing “hardware design” Theory and experimental fundamental research “The platform” Strategic decision of ECT: We choose not to specialize but to become advanced users across the entire supply-chain with the mission of spotting the locations were the “component-swap” can be attempted.
Machine learning, Internet of Things, Edge Computing, Keywords for fields that are expanding exponentially