This exposure-assessment study proposes a Voronoi-diagram approach to visualize RF-EMF exposure across a city using personal exposimeter measurements of RMS electric field at seed points. Most mapped areas corresponded to about 1.9 V/m, with a maximum reported value of 11.4 V/m, all below the cited ICNIRP guideline level. The authors conclude the method is useful for communicating spatial variability, while also noting broader literature discussing potential health risks from EMF exposure.

This exposure-assessment study compares RF-EMF exposure maps produced using a broadband meter versus a personal exposimeter and aims to correct personal exposimeter readings to match broadband-based maps. The authors report that LOS/NLOS-specific correction factors reduce discrepancies, particularly improving LOS measurements affected by body shielding. A genetic algorithm is used to optimize correction factors and support scalable urban exposure mapping, with the authors noting that additional validation in other environments is needed.

This protocol and pilot study evaluated whether smartphone signal strength indicators can be converted into RF-EMF exposure estimates using derived formulas and regression models. The study reports a positive log-linear association between LTE RSSI and far-field (base station) exposure aggregated by location, while handset-related exposure at the ear and chest during data transmission showed negative log-linear trends with improving signal quality. The authors conclude the ETAIN 5G-Scientist app may support large-scale RF-EMF exposure assessment, but emphasize the need for more data to improve accuracy and address uncertainties in individual measurements.