A Framework for RF-EMF Time Series Analysis Through Multi-Scale Time Averaging

Five European systems for continuous monitoring of outside radio-frequency (RF) electromagnetic field (EMF) provide important insights into the long-term in situ variability of RF-EMF, as a valuable feature for accessing RF-EMF in areas with increased sensitivity to EMF exposure. Unfortunately, their current presentation of field variability through a simple timeline is not suitable for a comprehensive insight into RF-EMF behavior, especially not for applications where annual comparison of field levels over a certain period of time is required. Driven by the need to overview monitored data in some distinctive way and further examine hidden phenomena embedded in system’s EMF data series, this paper presents an additional method for analyzing RF-EMF time series through multi-scale time averaging. A case study was selected to demonstrate the time-averaging framework, using a five-year RF-EMF dataset obtained from a sensor, installed on the campus of the University of Novi Sad, as part of the Serbian EMF RATEL monitoring network. Although this case study reveals some site-specific details, such as a daily ratio between maximum and minimum field levels of 3.6 for weekdays and 2.1 for weekends, the time-averaging framework is applicable to any monitoring network. Furthermore, it is designed to present its findings in a simple manner and to be affirmative of the general population’s perception on unavoidable presence of RF-EMF in the environment, while ultimately contributing to a more rational understanding of the potential impact of everyday RF-EMF on their health.