Fogsy: Towards holistic industrial AI management in fog and edge environments
Patrick Wiener, Philipp Zehnder, Marco Heyden, Patrick Philipp, Dominik Riemer
Published in KuVS-Fachgespräch Fog Computing, 2020
The proliferation of industrial IoT is one of the driving forces that lead to a deluge of generated data bridging the physical and virtual worlds. Consequently, harvesting such data bears a vast potential for companies to realize intelligent, datadriven decisions. In recent years, the decreasing costs for compute resources as well as new decentralized computing paradigms such as fog computing enable companies to invest in artificial intelligence (AI) use cases. However, realizing industrial AI applications is still a major challenge due lack of know-how in AI as well as a complex surrounding infrastructure. In this paper, we present the vision of Fogsy, a holistic industrial AI management system aiding to support domain experts to manage analytical AI pipelines from data access, modeling, and training to deployment, monitoring and adaptation in fog and edge environments.