1
|
Korkmaz E, Aerts S, Coesoij R, Bhatt CR, Velghe M, Colussi L, Land D, Petroulakis N, Spirito M, Bolte J. A comprehensive review of 5G NR RF-EMF exposure assessment technologies: fundamentals, advancements, challenges, niches, and implications. ENVIRONMENTAL RESEARCH 2024:119524. [PMID: 38972338 DOI: 10.1016/j.envres.2024.119524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 06/16/2024] [Accepted: 06/30/2024] [Indexed: 07/09/2024]
Abstract
This review offers a detailed examination of the current landscape of radio frequency (RF) electromagnetic field (EMF) assessment tools, ranging from spectrum analyzers and broadband field meters to area monitors and custom-built devices. The discussion encompasses both standardized and non-standardized measurement protocols, shedding light on the various methods employed in this domain. Furthermore, the review highlights the prevalent use of mobile apps for characterizing 5G-NR radio network data. A growing need for low-cost measurement devices is observed, commonly referred to as "sensors" or "sensor nodes," that are capable of enduring diverse environmental conditions. These sensors play a crucial role in both microenvironmental surveys and individual exposures, enabling stationary, mobile, and personal exposure assessments based on body-worn sensors, across wider geographical areas. This review revealed a notable need for cost-effective and long-lasting sensors, whether for individual exposure assessments, mobile (vehicle-integrated) measurements, or incorporation into distributed sensor networks. However, there is a lack of comprehensive information on existing custom-developed RF-EMF measurement tools, especially in terms of measuring uncertainty. Additionally, there is a need for real-time, fast-sampling solutions to understand the highly irregular temporal variations EMF distribution in next-generation networks. Given the diversity of tools and methods, a comprehensive comparison is crucial to determine the necessary statistical tools for aggregating the available measurement data.
Collapse
Affiliation(s)
- Erdal Korkmaz
- The Hague University of Applied Sciences, Research Group Smart Sensor Systems, 2627 AL, Delft, The Netherlands.
| | - Sam Aerts
- The Hague University of Applied Sciences, Research Group Smart Sensor Systems, 2627 AL, Delft, The Netherlands
| | - Richard Coesoij
- Delft University of Technology, Department of Microelectronics, 2628 CN, Delft, The Netherlands
| | - Chhavi Raj Bhatt
- Australian Radiation Protection and Nuclear Safety Agency, VIC 3085, Yallambie, Australia
| | - Maarten Velghe
- National Institute for Public Health and the Environment, Centre for Sustainability, Environment and Health, 3720 BA, Bilthoven, The Netherlands
| | - Loek Colussi
- Dutch Authority for Digital Infrastructure, 9700 AL, Groningen, The Netherlands
| | - Derek Land
- The Hague University of Applied Sciences, Research Group Smart Sensor Systems, 2627 AL, Delft, The Netherlands
| | - Nikolaos Petroulakis
- Institute of Computer Science, Foundation for Research and Technology-Hellas, 70013, Heraklion, Greece
| | - Marco Spirito
- Delft University of Technology, Department of Microelectronics, 2628 CN, Delft, The Netherlands
| | - John Bolte
- The Hague University of Applied Sciences, Research Group Smart Sensor Systems, 2627 AL, Delft, The Netherlands; National Institute for Public Health and the Environment, Centre for Sustainability, Environment and Health, 3720 BA, Bilthoven, The Netherlands
| |
Collapse
|