This study presents an extensive analysis of electromagnetic field (EMF) exposure in Greek urban and suburban areas during the ongoing deployment of the 5G technology. A total of 400 in situ measurements of electric field strength were conducted at ground level across four distinct regions. The first part of the study provides a statistical analysis of the overall EMF exposure, highlighting the contributions of different cellular generations (2G–5G) to the total field. The results show that 4G networks are the dominant contributors, while the impact of 5G remains limited. The second part investigates the correlation between electric field levels in the 3.5 GHz band and the distance from 5G base stations (BS). Using geospatial analysis, we computed distances to the nearest BS and examined their relationship with measured EMF levels. The findings indicate a general inverse correlation between EMF levels and BS distance, although variations occur due to factors such as line-of-sight conditions and urban built environment characteristics. These results confirm that distance remains a key predictive feature for AI-based EMF exposure models, even in the case of 5G networks.

Radiofrequency (RF) exposure assessment in indoor environments has attracted considerable interest due to the widespread use of wireless communication technologies and the increasing amount of time people spend indoors. In the framework of the SEAWave project, extensive frequency-selective measurements were performed in Greece to characterize environmental RF exposure across diverse indoor environments. A harmonized dataset comprising more than 26,000 measurement samples collected at 40 indoor locations was statistically analyzed, covering residential, commercial, educational, office/workplace, public/cultural, event/market, and transport environments. Transport environments exhibited the highest exposure levels (RMS = 0.856 V/m), whereas residential (0.122 V/m) and office/workplace (0.136 V/m) environments showed the lowest values. Cellular networks accounted for more than 80% of the total RF exposure in all environments, reaching 94.4% in transport environments, while Wi-Fi contributed between approximately 5.6% and 17% depending on the environment. Repeated measurements revealed environment-dependent differences in RF exposure, with the largest variations between measurement campaigns observed in public transport, commercial, and public environments, whereas no statistically significant relationship between floor level and RF exposure was observed. RF exposure varied across indoor environment categories, while an exploratory geographical comparison within Commercial/Retail environments did not reveal statistically significant differences among urban, suburban, and rural groups.