Predictive exponential modeling of the RF electromagnetic field generated by cellular base stations in a university environment
DOI:
https://doi.org/10.37135/ns.01.18.09Keywords:
Cellular antennas, Electric field, Mathematical modeling, Predictive model, Electromagnetic radiationAbstract
The rapid growth of mobile telecommunications has increased the density of base stations in urban and educational environments, raising concerns about the possible effects of prolonged exposure to electromagnetic fields. This situation highlights the need to develop local studies that quantify and predict radiation levels in specific contexts. Therefore, a quantitative quasi-experimental methodology was employed, comprising five phases: planning, empirical data collection, data processing, mathematical modeling, and statistical validation. Measurements were conducted over 34 days using Narda SRM-3006 and EME Spy-200 equipment at different time slots and distances from the antennas. The data were processed using R software, employing statistical tests and linear, logarithmic, and exponential regression models. The results showed that the electric field intensity decreases exponentially as distance increases, with a determination coefficient (R² = 0.8844), validating the exponential model as the best fit. Furthermore, the measured values were well below the limits established by the International Commission on Non-Ionizing Radiation Protection (ICNIRP), confirming safe exposure conditions. It is concluded that the developed model constitutes a reliable scientific tool for assessing and predicting electromagnetic radiation levels in educational and urban environments. Its application enables optimization of antenna placement, improvement of radio spectrum management, and reinforcement of sustainable technological planning. This work provides relevant empirical evidence and a replicable methodological framework for future research on non-ionizing radiation and environmental safety.
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