# EMF Assessment Utilizing Low-Cost Mobile Applications
## 4 Discussion
In another study [30], an app was developed to measure the received power of smartphones. Due to a lack of information regarding the smartphone's antenna gain, the authors normalized the received power from app measurements taken on a bicycle and used the kriging interpolation method to create an exposure heat map. A similar heat map was generated from measurements made with a broadband meter over a 6 min interval at several locations within the same area. The results showed a correlation between the heat maps produced by both methods, demonstrating that the smartphone-based approach can effectively generate exposure maps for electromagnetic field assessment. This method has the advantage of using interpolation to cover a wider area with heat maps. Moreover, because the received power is obtained by a custom app, the exact parameters can be customized. However, unlike our study, a conversion factor was not calculated, meaning that actual electric field strength values could not be estimated. This previous method has also been applied in other studies. For example, study [31] used a similar approach, utilizing RSRP combined with kriging interpolation to map exposure. The results were compared with actual electric field strength values obtained by a frequency-selective field strength meter. The advantage of this method over ours is that interpolation allows for estimating exposure in areas where no measurements were taken. However, as in other studies, the actual received power was not estimated, unlike in our research. Other studies have employed mobile apps to estimate exposure in a more indirect manner. For instance, in [32], RSRP was used to determine and validate the path loss distribution of electromagnetic field radiation emitted by small cell antennas by comparing measured RSRP values with theoretical calculations. This path loss distribution can then be used to estimate exposure at specific locations, given knowledge of the BS power emissions. Study [33] used RSRP to compare downlink exposure between small and macro cell antennas, with total exposure comparison (both uplink and downlink) made possible by incorporating the transmission (TX) power provided by the app and the throughput. Study [34] extrapolated electromagnetic field exposure levels from RSRP using a physics-informed machine learning model. In other studies, RSRP has been used to evaluate signal coverage [35], assess network performance [36; 37], and compare 4G and 5G network performance [38]. The advantage of the method introduced in this study is that it estimates actual electric field strength using only a linear conversion factor applied to low-cost app metrics. This approach requires one smartphone per mobile operator and an app capable of recording the RSRP values from the main and at least three neighbor cells, as well as the frequency of the received signal. Although not essential, knowledge of road traffic conditions and BS placement can help assess the accuracy of the results. Considering that the RSRP value ranged from \(-140\) to \(-44\) dBm [39], the estimated electric field using the 800 MHz and 2600 MHz frequency bands ranged from approximately 0.00008 to 31 V/m. This range covers extreme cases where the main cell and three neighbor cells have RSRP values of \(-44\) dBm at the upper limit in the 2600 MHz frequency band, while at the lower limit, only the main cell had an RSRP value of \(-140\) dBm in the 800 MHz frequency band. Future research could involve conducting confirmation measurements in both low- and high-variability areas with extended stationary data collection and instruments located closer together. Additionally, calculating the conversion factor in various environments could generalize this method. This study could also be expanded to other networks, including 2G, 5G, Wi-Fi, and Bluetooth, to provide a more comprehensive picture of actual exposure.