Continuous EMF Monitoring as an Emergency and Disaster Detection Tool

A number of applications founded on electromagnetic field (EMF) has increased, since wireless personal communication devices are used by a large number of people. Simultaneously, the controversy about adverse health effects of EMF exposure is in a focus of the public debate. Thus, there are constant demands for comprehensive investigation and monitoring of existing exposure to EMF. In last decade, the wireless sensors networks emerged as an innovative solution for EMF monitoring in the environment. The newest established is Serbian EMF RATEL network that performs continuous wideband monitoring, counting contribution of all active EMF sources, in particular frequency range and in the vicinity of observed location. Besides the monitoring for the health protection purposes, this network can be used as an emergency and disaster detection tool, as demonstrated in a case study of COVID-19 presence in campus of the University of Novi Sad. In this paper, technical details of the Serbian EMF RATEL monitoring network are presented, along with monitoring results from two campus locations, which clearly indicate some significant changes in the EMF level. © 2022 IEEE.

Causality of COVID-19 on EMF Radiation in Campus Area of University of Novi Sad

The mobile telephony became one of the worldwide most important technology, allowing wireless communication at any moment and virtually at any place. It is based on electromagnetic field (EMF) radiation from its network base stations, which inevitable cause EMF expansion in surrounding. However, the new base stations are followed by strong controversy, increasing concerns of the public, regarding potentially dangerous health effects of the EMFs. Thus, there is a constant demand for overall investigation and supervision of existing EMF exposure. In last decade, the wireless sensors networks emerged as an innovative solution for effective monitoring of EMFs in the environment. The latest established is the Serbian EMF RATEL network, which offers a sophisticated approach of telecommunication service-based EMF monitoring. This network performs wideband monitoring, taking into account the contribution of all active EMF sources in the vicinity of specific location. In this paper, the new role of the EMF RATEL system is considered, analyzing it as a smart solution for an emergency management. The perceptible causality of the COVID-19 on EMF radiation in campus area of University of Novi Sad is investigated, regarding the extensive activities of students in this part of the city of Novi Sad. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Complexity and Nonlinearity Analysis of the Time Series of Electric Field Intensity

In this work, the conditional entropy (CE) and the method of surrogate data are applied on time series of electric field (EF) intensity to explore their degree of complexity and the possible presence of nonlinear dynamics. The time series were obtained during the wide-band cumulative EF intensity monitoring, performed by one sensor of the Serbian EMF RATEL monitoring system installed in the campus area of the University of Novi Sad, and are re-sampled at one sample per two hours over consecutive time epochs of one month duration. The field intensity measurements during the years 2019 and 2020 allowed us to explore the effects of mobility restrictions related to the COVID-19 pandemic on the patterns of complexity and nonlinearity underlying the EF dynamics. Using the kernel-based estimator of CE, which realizes the well-known Sample Entropy measure, and generating phase-randomized Fourier transform surrogate series, we highlight the presence of predictable but nonlinear EF dynamics associated to months of regular population mobility, while months with reduced human mobility result in more complex but linear EF patterns. In perspective, this analysis may serve to complement standard evaluation of EF intensity and variability, with implications ranging from safety assessment to optimization of sensor placement and social mobility analysis. © 2021 IEEE.