Estimation of Electromagnetic Dosimetric Values from Non-Ionizing Radiofrequency Fields in an Indoor Commercial Airplane Environment

Aguirre, Erik; Arpon, Javier; Azpilicueta, Leyre; Lopez, Pilar; Miguel, Silvia de; Ramos, Victoria; Falcone, Francisco

doi:10.3109/15368378.2013.810155

Cited by 26 publications

(14 citation statements)

References 46 publications

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“…The rays on the impact surface will contribute to the total received field at that point, depending on the electromagnetic parameters of the materials interacting with the propagating waves. Implementation based on a combination of geometric optics and physical optic allowed using ray tracing in order to characterize wireless propagation and consequently RF-EMF exposure in very complex indoor scenarios [38,39].…”

Section: Resultsmentioning

confidence: 99%

Radio Frequency Electromagnetic Fields Exposure Assessment in Indoor Environments: A Review

Chiaramello

Bonato

Fiocchi

et al. 2019

IJERPH

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Exposure to radiofrequency (RF) electromagnetic fields (EMFs) in indoor environments depends on both outdoor sources such as radio, television and mobile phone antennas and indoor sources, such as mobile phones and wireless communications applications. Establishing the levels of exposure could be challenging due to differences in the approaches used in different studies. The goal of this study is to present an overview of the last ten years research efforts about RF EMF exposure in indoor environments, considering different RF-EMF sources found to cause exposure in indoor environments, different indoor environments and different approaches used to assess the exposure. The highest maximum mean levels of the exposure considering the whole RF-EMF frequency band was found in offices (1.14 V/m) and in public transports (0.97 V/m), while the lowest levels of exposure were observed in homes and apartments, with mean values in the range 0.13–0.43 V/m. The contribution of different RF-EMF sources to the total level of exposure was found to show slightly different patterns among the indoor environments, but this finding has to be considered as a time-dependent picture of the continuous evolving exposure to RF-EMF.

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Section: Resultsmentioning

confidence: 99%

Radio Frequency Electromagnetic Fields Exposure Assessment in Indoor Environments: A Review

Chiaramello

Bonato

Fiocchi

et al. 2019

IJERPH

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“…Res. Public Health 2020, 17, x; doi: FOR PEER REVIEW www.mdpi.com/journal/ijerph microenvironments [15,16,20,24,[43][44][45][46], and third, to make sporadic and point measurements, and to design models to estimate exposure levels [12,[47][48][49][50][51][52]. Despite the results obtained in these studies, a large part of the population remains concerned as diseases of unknown etiology appear [53][54][55][56], which is why it is necessary to continue researching to try to respond to these concerns.…”

Section: Introductionmentioning

confidence: 99%

Georeferencing of Personal Exposure to Radiofrequency Electromagnetic Fields from Wi-Fi in a University Area

Ramirez-Vazquez

Arabasi

Al-Ta’ani

et al. 2020

IJERPH

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In the last two decades, due to the development of the information society, the massive increase in the use of information technologies, including the connection and communication of multiple electronic devices, highlighting Wi-Fi networks, as well as the emerging technological advances of 4G and 5G (new-generation mobile phones that will use 5G), have caused a significant increase in the personal exposure to Radiofrequency Electromagnetic Fields (RF-EMF), and as a consequence, increasing discussions about the possible adverse health effects. The main objective of this study was to measure the personal exposure to radiofrequency electromagnetic fields from the Wi-Fi in the university area of German Jordanian University (GJU) and prepare georeferenced maps of the registered intensity levels and to compare them with the basic international restrictions. Spot measurements were made outside the university area at German Jordanian University. Measurements were made in the whole university area and around two buildings. Two Satimo EME SPY 140 (Brest, France) personal exposimeters were used, and the measurements were performed in the morning and afternoon, and on weekends and weekdays. The total average personal exposure to RF-EMF from the Wi-Fi band registered in the three study areas and in the four days measured was 28.82 μW/m2. The average total exposure from the Wi-Fi band registered in the ten measured points of the university area of GJU was 22.97 μW/m2, the one registered in the eight measured points of building H was 34.48 μW/m2, and the one registered in the eight points of building C was 29.00 μW/m2. The maximum average values registered in the campus of GJU are below the guidelines allowed by International Commission on Non-ionizing Radiation Protection (ICNIRP). The measurement protocol used in this work has been applied in measurements already carried out in Spain and Mexico, and it is applicable in university areas of other countries.

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“…As previously stated, in order to analyze wireless channel behaviour, a deterministic approach based on an in-house 3D ray launching code is employed. This simulation code, which considers electromagnetic interaction with the material elements of the scenario, as well as reflection, refraction and diffraction, has been tested in a wide range of complex environments [3][4][5][6][7][8]. The main simulation parameters that have been used for the scenario are shown in Table I.…”

Section: Scenario Description and Simulation Parametersmentioning

confidence: 99%

Analysis of efficient dense wireless sensor network deployment in Smart City environments

López-Iturri

Aguirre

Azpilicueta

et al. 2014

IEEE SENSORS 2014 Proceedings

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In this work, the massive deployment of wireless sensor networks inherent in the implementation of context aware Smart City environments is presented. A precise estimation considering the topology and the morphology of wide service areas, with a potential large density of transceivers is performed with the aid of in-house deterministic 3D ray launching algorithm, which is specifically adapted to the conditions of large volume and large traffic density. Due to the co-existence of multiple wireless systems (such as wireless local area networks, mobile networks, body area networks or RF proprietary systems), a heterogeneous scenario, in terms of traffic distribution and hence overall interference is present. The precise characterization of coverage areas of all wireless transceivers, as information sources or undesired interference sources, leads to optimal deployment configurations, in which interference levels are minimized, quality of service is enhanced and overall energetic consumption can be optimized.

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Estimation of Electromagnetic Dosimetric Values from Non-Ionizing Radiofrequency Fields in an Indoor Commercial Airplane Environment

Cited by 26 publications

References 46 publications

Radio Frequency Electromagnetic Fields Exposure Assessment in Indoor Environments: A Review

Radio Frequency Electromagnetic Fields Exposure Assessment in Indoor Environments: A Review

Georeferencing of Personal Exposure to Radiofrequency Electromagnetic Fields from Wi-Fi in a University Area

Analysis of efficient dense wireless sensor network deployment in Smart City environments

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