Machine learning, IoT and Erlang: is this the right mix for reliable federated learning?

Edge computing and has ground-breaking potential to impact in IoT. Porting Machine Learning capabilities to the IoT device is highly desirable to reduce cloud dependency. Attempts to standardise IoT stacks have not yet gained significant acceptance due to introducing the issues of large incoming data flows, trust, privacy and security, and these are prohibitive for many scenarios. New resilient IoT stacks are necessary to address the problems at the source. That is to enable federated de-centralised solutions, and to maintain accuracy, low computational and power consumption.

OBJECTIVE

Bounce the idea of the wall and get feedback from the community. Identify other projects working in this domain and explore collaborations.

AUDIENCE

Anyone working on Embedded systems using Erlang with a keen interest on supporting data driven decision support.