Cloud computing (CC) is generating new compute and business models thanks to its service-based nature, which enables collaboration and data exchange at higher level, more flexibility with better efficiency and parallel decreasing costs. Manufacturing environments can also benefit from cloud technology and follow fast changes in market demands. In these new scenarios interoperability has vital importance in the operation and interaction among industrial realizations of the Cyber-physical Systems.

Industry 4.0 is an emerging business paradigm that is reaping the benefits of enabling technologies driving intelligent systems and environments. By acquiring, processing and acting upon various kinds of relevant context information, smart automated manufacturing systems can make well-informed decisions to adapt and optimize their production processes at runtime.

With the advent of Industry 4.0, production processes have been endowed with intelligent cyber-physical systems generating massive amounts of streaming sensor data. Internet of Things technologies have enabled capturing, managing, and processing production data at a large scale in order to utilize this data as an asset for the optimization of production processes. In this work, we focus on the automatic detection of physical defects in the production of surfacemount devices.

We argue that Genetic Improvement can be successfully used for enhancing road trac data mining. Œis would support the relevant decision makers with extending the existing network of devices that sense and control city trac, with the end goal of improving vehicle ƒow and reducing the frequency of road accidents. Our position results from a set of preliminary observations emerging from the analysis of open access road trac data collected in real time by the Birmingham City Council.