Air Traffic Data Integration using the Semantic Web Approach

Air traffic management systems require constant development. Whenever regular radar devices are out of range, the wide network of the receivers may constitute global air traffic monitoring solutions. Surveillance methods of controlling aircrafts are being improved and the one which stands apart from the others is ADS-B (Automatic Dependent Surveillance Broadcast) introduced in most commercial and private aircrafts, and which was obligatory after the year 2020. Nowadays ADS-B receivers cover about 70% of European and 30% of U.S air traffic. The ADB-S system is based on GPS communication. Aircrafts estimate their position using satellite based navigation systems. Along with plane position, there is a vast number of additional data broadcasted by the ADS-B transponder, including speed, altitude, plane and flight identification data, also emergency codes. The large amount of professional and amateur ADS-B receivers located on most continents, covering significant amount of the airspace, has led to the conclusion that this kind of crowd-processing may establish valuable and reliable source of data using common interface. Currently there is no uniform layer of the ADS-B data presentation and interfaces over the Web. This paper regards standardisation of the data layer using WEB 3.0 - Semantic Web principals. It covers acquisition, processing and presentation of the data coming from the ADS-B receiver. A method of unifying data from distributed virtual radar stations has been proposed and is being presented in a way that allows this data to be combined across many sources with existing knowledge. Having ADS-B information integrated and expressed in RDF (Resources Description Format), it would be easy to perform such a query against these data sets, using Protocol and RDF Query Language (SPARQL). Now we stand at the verge of WEB 3.0, where applications vastly utilising Artificial Intelligence, semantic solutions and Natural Language Processing systems are going to become common.