Innovative Stochastic Modeling of Residential Exposure to Radio Frequency Electromagnetic Field Sources
Abstract
This study focused on the assessment of radio-frequency electromagnetic fields (RF-EMF) exposure in a realistic apartment due to the presence of a WiFi source deployed in uncertain position. In order to describe the 2D spatial distribution of electric field induced in the whole apartment for whatever position of the WiFi source, an innovative approach that combines Principal Component Analysis (PCA) and Gaussian process regression (Kriging method) was applied. The 2D surrogate model was used to investigate the exposure in three different usage scenarios of the WiFi sources, i.e. surfing to a new web site, using a Skype video call and watching a You Tube video at 1080p, evaluating the electric field E induced at each location of the apartment for 10,000 different positions of the source. Across all the examined conditions, we found E values distributions with median values in the range 2.2-96.1 mV/m and 90 th percentiles in the range 4.9-209.3 mV/m. The 2D surrogate model allowed obtaining a complete statistical description of the exposure for any positions of the WiFi source in the apartment, with a computational effort equal to about 10% of the one needed by using only the WiCa Heuristic Indoor Propagation Prediction (WHIPP) network planner.