Structure of context recognition in computer-based systems for transportation management

Abstract

The process of context recognition in dynamically changing transportation processes is quite complex. The complexity arises from many aspects of understanding the concept of “context”. When developing computer-based systems, it is important to define what is included and how the concept of context is understood. Of course, a fairly wide range of ICT infrastructure components can be integrated into the digitization of contextual data. Quite a variety of devices and software can be included to help capture environmental data: different wireless channels, heterogeneous wireless sensor networks (WNSs), different flow management and e-document management systems, and various monitoring systems. Heterogeneity arises when we want to include different sensors and different means of communication. Vehicles can also be equipped with a wide variety of specialized apparatus and systems. Roads are equipped with special tools and road infrastructure software components. One of the goals of this part of the study is the desire to convey a wide range of context recognition processes. Artificial intelligence (AI) methods can be used for context recognition and such components form the basis of intelligent service systems. The provision of smart services should be based on a wide range of management needs in freight transport processes. How primary data sources are incorporated into all possible interconnected infrastructures is analysed in this section.