The Internet of Things (IoT) is a growing field which is expected to generate and collect data everywhere at any time. Highly scalable cloud analytics systems are frequently being used to handle this data explosion. However, the ubiquitous nature of the IoT data imposes new technical and non-technical requirements which are difficult to address with a cloud deployment. To solve these problems, we need a new set of development technologies such as Distributed Data Mining and Ubiquitous Data Mining targeted and optimized towards IoT applications.

Much of the resilience and flexibility of production networks lies in the transparency of processes that allows timely perception of actual process states and adequate decisions or intervention at the proper point of the production system.

Business processes in production and logistics need to be monitored in order to comply with official regulations, to schedule and plan the production or transport route, to ensure quality and find errors, but also to optimize the process itself. Often this monitoring needs to be done in real-time, e.g.