Timo Hoyer

Proactive Resolution Support

Machine Learning for the IoT Ecosystem

Using algorithms that iteratively learn from data, machine learning allows Mission Control to find and present hidden insights without being explicitly programmed where to look. The machine learning backend needed for the control would come from the Development and Data Science team.

With Proactive Resolution Support [dubbed Mission Control;] we realized the idea to make contextual and intelligent live data readily available.

With the use of machine learning algorithms we are presenting discoveries of patterns, insights or solutions to the user by surfacing those observations as indicator cards.

This results in increasing operations efficiency — allowing users to get insights into otherwise hidden information.

︎ Atomic design elements of the different states.


Our design strategy focused primarily around a component system, constructing suggestions from a small number of atomic units.

Assistive AI embedded into the IoT suite will allow users to globally utilize the system’s intelligence and learning mechanisms to the Digital Supply Chain.

︎User Stories

  • As a Logistics Manager, I want to know which resolution options have which advantage to my supply chain, so that I can make meaningful decisions without much calculation and research.

  • As a Transportation Manager, I want to have a space to persist important data, so that I can keep everything in one place and don’t have to use third-party apps to keep track of everything related to my supply chain.

  • As a Transportation Manager, I want to know which notifications are recurring, so that I can create a rule that solves those issues automatically.