# Fuzzy Decision Algorithm for Health Impact Assessment in a 5G Environment
## 7 Conclusions and Future Work  
Currently, valid recommendations and guidelines for assessing RFs' impact on health do not fully cover all adverse health effects. In the ICNIRP 2020 guidelines, the analysis of thermal effects has been extended to the entire RF range, but it seems that this has not answered many open issues. Most doubts are related to various non-thermal effects that are a consequence of high-frequency RF radiation. A large number of scientific papers and expert opinions have appeared that indicate possible adverse health effects that are not only a consequence of tissue heating. This is especially emphasized for the frequency range above 30 GHz.  
The rapid scientific and technical development with the application of the Internet of Things (IoT) strategies requires fast data transfer with a low latency time. The 5G network  
Figure 12: Thermal effects are dominant in the sub-millimeter range (Mamdani FLS-T2).  
Figure 13: Non-thermal effects are dominant in the millimeter range (Mamdani FLS-T2).  
has emerged in response to these demands. This communication network involves a lot of transmitters with high operating frequencies, which has caused great concern for human health in urban areas. There is no reliable evidence that high-frequency RFs have adverse health effects, but it also cannot be said that such fears have no justification. The emergence of the 5G network has caused additional confusion.  
The paper describes in detail the methodology and fuzzy decision algorithm for estimating RFs' impact. The 3D graphs show the frequency bands in which some potentially adverse RF effects can occur. The paper represents a pioneering attempt to create a methodology for RF impact assessment with the aim of faster decision-making.  
In implementing a hands-on fuzzy decision-making algorithm, an important role is played by the process that involves the expert's role in analyzing knowledge bases and ICNIRP guidelines to define fuzzy numbers, choose inference methods, and create fuzzy rules. This is a three-step cyclical and iterative process affecting the final fuzzy model.  
The main contribution of this work is a practically applicable methodology for quickly determining the impact of electromagnetic radiation on human health. This methodology should provide a good foundation for developing software solutions for portable devices that would give a rapid assessment of the impact of measured radiation based on in situ measurements.  
The proposed algorithm should enable a straightforward assessment of the impact of electromagnetic radiation in field conditions where there is an unknown number of radiation sources.  
The authors will focus future research on improving the fuzzy decision-making algorithm by considering, in addition to the ICNIRP guidelines, the results of medical studies analyzing the effects of wireless IoT devices in the urban environment.  
For this research article with four authors, the following individual contributions must be emphasized: conceptualization, S.P., B.V., and S.M.; methodology, B.V. and S.M.; investigation, S.P. and B.V.; software, S.M.; validation, B.V. and S.M.; writing--original draft preparation, S.P., B.V. and S.M.; writing--review and editing, S.P., B.V. and S.M.; supervision, S.P. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.