Measurement and Prediction of Electromagnetic Radiation Exposure Level in a University

Karpat E., Bakcan M. R.

TEHNICKI VJESNIK-TECHNICAL GAZETTE, cilt.29, sa.2, ss.449-455, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 29 Sayı: 2
  • Basım Tarihi: 2022
  • Doi Numarası: 10.17559/tv-20200418183308
  • Dergi Adı: TEHNICKI VJESNIK-TECHNICAL GAZETTE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Directory of Open Access Journals, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.449-455
  • Anahtar Kelimeler: artificial neural network, electrical field, electromagnetic radiation, electromagnetic field measurement, prediction method, MOBILE PHONE, POLLUTION, FIELDS
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

The importance of electromagnetic (EM) sources in human life has been increasing with the development of technology. EM radiation triggers some problems in our life such as EM interference and human health problems. EM radiation level which is emitted by the base station increases in proportion to the density of population in a region. EM exposure is higher in areas where people are highly concentrated such as hospitals, military barracks, schools, shopping malls, than in any other region. It is important to show sustained concern about the EM radiation intensity in these areas to keep the levels under the permissible limits. In this study, electric field values are measured statically at locations where the population density is too high, to examine the electric field intensity levels throughout the campus. Besides, two different artificial neural models (ANN) are developed to estimate the electric field values of random locations which are specific regions for electromagnetic exposure. Moreover, measurement results and estimated results are evaluated within the limits defined by national (ICTA) and international (ICNIRP) standards. Finally, the EM exposure map is constructed with data that is average electric field intensity versus measurement locations.