Algorithm of wind-related hazards prediction for UAS flight and urban operations based on meteorological data fusion

Nowadays unmanned aircraft systems (UASs) are planned to be used in many branches of people's activity and fulfill different tasks. It is also considered one of the prospective technologies for realization of the concepts of Industry 4.0. and Society 5.0. Many of the tasks in the frame of prospective concepts including cargo delivery, photo and filmmaking, future transportation, monitoring, different security applications, and others are, obviously the subject of urban flying. It is obvious that to provide safe, secure, efficient UAS operations the operators and corresponding services should be aware of possible hazards during the flight and mission realization. The paper considers the possibilities of modern and prospective technologies to collect, fuse, and process diverse weather data including real-time data focusing on meteorological information. An algorithm that is based on statistical meteorological data analysis for machine learning to indicate and forecast potentially hazardous areas for unmanned aircraft flight was proposed. The concept of common information space for the exchange of operative information and study components of the common information space for advanced weather service of aviation was presented and discussed. The data exchange pattern in the advanced system for weather service of aviation was also considered and characteristics that should be taken into account were discussed. The simulation was done to demonstrate the benefits of the proposed approach.