Obemannade luftfartygssystem och artificiell intelligens. Inverkan på svensk operativ förmåga i räddningstjänst

The rescue service can benefit from the latest technology for unmanned aircraft systems (UAS) to, for example, improve its situation awareness during operations and thereby reduce risks for its staff while strengthening the ability to solve the mission. Through a number of interviews with staff in the municipal rescue service who work with UAS, certain capability gaps are identified. These needs are compared to the AI methods identified in a previous study and the methods are evaluated based on their relevance to the capability gaps and some additional evaluation factors (contribution to the work environment and technical maturity, specifically) that are presented. Nine capability gaps are identified, including image processing, airspace coordination, autonomous control, IT security and payload. Of these, it is mainly image processing that is supported by the AI methods. Through improved image processing, the operational picture can be enriched and better decision support obtained. The AI methods, grouped into eight different application areas, are studied and compared with the capability needs. Combined with estimates of their usefulness for other valuation factors, the assessment is made that some methods are more relevant than others. The methods that in the near future seem to be most useful for UAS usage in the rescue service concern detection of people, life signs, objects, damage (to infrastructure), and fire.