Speaker
Description
The number of scientific publications on artificial intelligence (AI) based outdoor radio frequency exposure (RF-EMF) calculations has increased significantly in recent years. AI RF-EMF applications can be used for regulatory and public information activities, in addition to general exposure level assessment.
Two application domains appear to be especially promising for this purpose, in addition to the general assessment of exposure levels. On the one hand, the prediction of the locations with the highest exposure levels is of paramount importance for health protection. Furthermore, the utilisation of visual representations, such as heat maps, to illustrate the electric field strength / power density as a percentage of the health limit, as determined by artificial intelligence calculations, has the ability to serve as a public information tool.
However, their widespread and continuous use over time requires system integration of individual applications. The elements of an integrated system and the associated research topics can be outlined based on the development experience of previous systems using wave propagation calculations and by comparing the specifications of individual AI RF-EMF applications.
It is reasonable to assume that the integrated system utilises a combination of AI-based calculations to determine the exposure level. The employment of different types of computation facilitates the investigation of various sources, including broadcast transmitters with significant transmission power, as well as 5G mobile base stations.
Furthermore, having reviewed the teaching databases of the scientific publications examined, three recommendations can be made.
