As global populations continue to migrate from rural areas into urban centers, cities need to deploy technology that can understand and optimize infrastructure to serve citizens in efficient and meaningful ways. Ensuring water, electricity, gas for heating, and other services are delivered uninterrupted is critical for the welfare of citizens. Unexpected outages with industrial pumping equipment, compressors, and similar machinery can be costly and disruptive. Predictive maintenance solutions can be deployed that monitor and measure machinery, and provide workers with information about the health of a machine, before a failure occurs. In this talk, we'll examine the Nordic Thingy:53 as a solution for understanding a machine's movement, and building a predictive maintenance machine learning model. We'll discuss the hardware, explain the workflow, and talk about the path from prototype to production in smart city infrastructure.

Speaker: David Tischler - Developer Program Manager, Edge Impulse
Nordic Thingy:53 https://www.hackster.io/nordic-semico...