More and more products, services, processes, and things are being digitized, virtualized and connected. As a result, the number of connected things, the availability of cloud services and the volume of data is exponentially increasing and thus offers unprecedented opportunities for new kinds of innovative applications. This digitization facilitates a new generation of software systems, which combine things, services, and data into value-added applications delivered over future networks. Increasingly, future software systems are driven by the unprecedented amount and speed of data, which allows novel ways of decision making and innovation (“Big Data”).
An example for a promising sector for digitization and Big Data applications is transport and logistics. Big Data applications enable the end-to-end visibility along the entire supply chain and thus foster significant opportunities for efficiency and performance improvements along the transport and logistics processes. Information derived from the real world (e.g., data retrieved from sensors attached to a transport container) can be ubiquitously accessed by all the partners of the supply chain and mutually shared and integrated among them through the negotiation and collaboration among software services. The data stemming from such interaction and supply chain visibility, in turn, enables novel opportunities, such as predictive monitoring of transport processes and proactive decision making and process adaptation.
- Machine-learning for predictive business process monitoring
- Proactive decision making and process adaptation
- Software engineering with and for Big Data
- Domain-specific platforms for Big Data applications, in particular for smart transport and logistics