  The expansion of network infrastructure in Greece has raised concerns about
the possible negative health effects on sensitive groups, such as children,
from exposure to long-term radiofrequency electromagnetic fields (RF-EMFs). The
objective of this study is to apply Unsupervised Machine Learning methods such
as hierarchical clustering, in order to establish patterns of EMF radiation in
schools. To this end we performed measurements in the majority schools units in
the region of Thessaly in order to calculate the mean value for RF - EMF
exposure in the 27 MHz - 3 GHz range, which covers the whole spectrum of RF -
EMF sources. Hierarchical clustering dendrogram analysis shows that population
density in urban areas of Thessaly bears no relation to the level of EMF
exposure in schools. Furthermore, in $97.5\%$ of schools found in the Thessaly
region, the exposure level is at least 3500 times below the Greek exposure
limits while in $2.5\%$ it is a little less than 500 times below the limit.
