Exposure to radio frequency electromagnetic fields from wireless computer networks: Duty factors of Wi-Fi devices operating in schools

Khalid, M.; Mee, Terry; Peyman, Azadeh; Addison, Darren; Calderón, Carolina; Maslanyj, Myron; Mann, Simon

doi:10.1016/j.pbiomolbio.2011.08.004

Cited by 51 publications

(45 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Therefore, also periods of less activity are included in our data resulting in lower duty cycles than in Khalid et al (2011). The standard deviation was 3.8% in Khalid et al (2011), which is within the range of our standard deviations (3.1-7.1%). We advise to always include the measurement of the duty cycle in exposure measurements using e.g., the method of Verloock et al (2010).…”

Section: General Results and Results Per Environmentsupporting

confidence: 70%

“…Standard deviations (SD) vary from 3.1 to 7.1%. These values correspond in order of magnitude with the duty cycles of the access points in Khalid et al (2011), which are measured in 7 networks in schools and ranged from 1.0% to 11.7% with a mean of 4.79%. The mean value of D in Khalid et al (2011) is higher because networks in schools are considered during lessons thus during activity (overall median of 1.4% versus 4.8% in Khalid et al (2011)).…”

Section: Procedures To Estimate Exposure Using Duty Cyclementioning

confidence: 53%

See 1 more Smart Citation

Determination of the duty cycle of WLAN for realistic radio frequency electromagnetic field exposure assessment

Joseph

Pareit

Vermeeren

et al. 2013

Progress in Biophysics and Molecular Biology

View full text Add to dashboard Cite

Wireless Local Area Networks (WLANs) are commonly deployed in various environments. The WLAN data packets are not transmitted continuously but often worst-case exposure of WLAN is assessed, assuming 100 % activity and leading to huge overestimations. Actual duty cycles of WLAN are thus of importance for time-averaging of exposure when checking compliance with international guidelines on limiting adverse health effects. In this paper, duty cycles of WLAN using Wi-Fi technology are determined for exposure assessment on large scale at 179 locations for different environments and activities (file transfer, video streaming, audio, surfing on the internet, etc.). The median duty cycle equals 1.4 % and the 95th percentile is 10.4 % (standard deviation SD = 6.4%). Largest duty cycles are observed in urban and industrial environments. For actual applications, the theoretical upper limit for the WLAN duty cycle is 69.8% and 94.7% for maximum and minimum physical data rate, respectively. For lower data rates, higher duty cycles will occur. Although counterintuitive at first sight, poor WLAN connections result in higher possible exposures. File transfer at maximum data rate results in median duty cycles of 47.6% (SD = 16%), while it results in median values of 91.5% (SD = 18%) at minimum data rate. Surfing and audio streaming are less intensively using the wireless medium and therefore have median duty cycles lower than 3.2% (SD = 0.5-7.5%). For a specific example, overestimations up to a factor 8 for electric fields occur, when considering 100 % activity compared to realistic duty cycles. We have included the document "Response to reviewers" at the end of the revised manuscript. This is a detailed summary of the changes made in preparing the revised manuscript. We have put an asterisk before our answers and changes. This document contains the detailed summary of the changes made in preparing the revised manuscript. We hope the changes we made according to your suggestions (explanation unit of time, multiple clients, far vs. near exposure vs. duty cycle, etc.) will satisfy you. We have put an asterisk before our answers and changes. We thank you for spending your time reviewing our paper. *We have put an asterisk (*) before every response. Reviewers' comments:Reviewer #1: This is a well written and interesting paper, reporting methods to calculate the duty cycle for WLAN transmitters under different real time scenarios. The data reported will be very useful in realistic assessment of the exposure of people to WLAN sources. *Thank you for appreciating our paper.Here are some comments:1-The main comment is related to the unit of time (relevant time frame) for duty cycle calculations. In Khalid et al 2011, the unit of time was considered as the duration of a typical lesson in a school ( about 30min). However the authors here considered the duration of a file transfer for example ( or any other activity), as the unit of time. This needs to be elaborated further as whether the time to transfer a file (which is very sma...

show abstract

Section: General Results and Results Per Environmentsupporting

confidence: 70%

Section: Procedures To Estimate Exposure Using Duty Cyclementioning

confidence: 53%

Determination of the duty cycle of WLAN for realistic radio frequency electromagnetic field exposure assessment

Joseph

Pareit

Vermeeren

et al. 2013

Progress in Biophysics and Molecular Biology

View full text Add to dashboard Cite

show abstract

“…On average, maximal variations of 11.9 dB (in some schools even up to 30 dB) were obtained here. This value is of course much higher than in [24] and [25] because we monitored the duty cycle over 24 hours and in [24] and [25] spatial measurements at different time instances were performed.…”

Section: Comparison Of Temporal Variations With Related Researchmentioning

confidence: 92%

“…The WiFi/WLAN duty cycle in schools has only been investigated in [25] and for various applications in [24]. No attempt to assess the 24 hour variation of the WiFi duty cycle was made.…”

Section: Comparison Of Temporal Variations With Related Researchmentioning

confidence: 99%

“…The duty-cycles in [24] and [25] are similar: median values varied from 1.2 to 1.9 % (standard deviations from 3.1 to 7.1% or 0.6 dB) in [24] and from 1.0% to 11.7% or 1.1 dB with a mean of 4.79% in [25]. Here, we obtained standard deviations of 1.5 dB, when considering all data (Table 3), which is similar.…”

Section: Comparison Of Temporal Variations With Related Researchmentioning

confidence: 99%

See 1 more Smart Citation

Temporal 24-hour assessment of radio frequency exposure in schools and homes

et al. 2014

View full text Add to dashboard Cite

show abstract

Assessment of human body influence on exposure measurements of electric field in indoor enclosures

Miguel-Bilbao

García²,

Ramos

et al. 2014

Bioelectromagnetics

View full text Add to dashboard Cite

Personal exposure meters (PEMs) used for measuring exposure to electromagnetic fields (EMF) are typically used in epidemiological studies. As is well known, these measurement devices cause a perturbation of real EMF exposure levels due to the presence of the human body in the immediate proximity. This paper aims to model the alteration caused by the body shadow effect (BSE) in motion conditions and in indoor enclosures at the Wi-Fi frequency of 2.4 GHz. For this purpose, simulation techniques based on ray-tracing have been carried out, and their results have been verified experimentally. A good agreement exists between simulation and experimental results in terms of electric field (E-field) levels, and taking into account the cumulative distribution function (CDF) of the spatial distribution of amplitude. The Kolmogorov-Smirnov (KS) test provides a P-value greater than 0.05, in fact close to 1. It has been found that the influence of the presence of the human body can be characterized as an angle of shadow that depends on the dimensions of the indoor enclosure. The CDFs show that the E-field levels in indoor conditions follow a lognormal distribution in the absence of the human body and under the influence of BSE. In conclusion, the perturbation caused by BSE in PEMs readings cannot be compensated for by correction factors. Although the mean value is well adjusted, BSE causes changes in CDF that would require improvements in measurement protocols and in the design of measuring devices to subsequently avoid systematic errors.

show abstract

Exposure to radio frequency electromagnetic fields from wireless computer networks: Duty factors of Wi-Fi devices operating in schools

Cited by 51 publications

References 2 publications

Determination of the duty cycle of WLAN for realistic radio frequency electromagnetic field exposure assessment

Determination of the duty cycle of WLAN for realistic radio frequency electromagnetic field exposure assessment

Temporal 24-hour assessment of radio frequency exposure in schools and homes

Assessment of human body influence on exposure measurements of electric field in indoor enclosures

Contact Info

Product

Resources

About