The rapid deployment of 5G spectrum by the telecommunication industry is intended to promote better connectivity and data integration among various industries. However, since exposures to radio frequency radiations (RFR) >2.4 GHz are still uncommon, concerns about their potential health impacts are ongoing. In this study, we used the embryonic zebrafish model to assess the impacts of a 3.5 GHz RFR on biology-a frequency typically used by 5G-enabled cell phones and lies within the 4G and 5G bandwidth. We established a plate-based exposure setup for RFRs, exposed developing zebrafish to 3.5 GHz RFR, specific absorption rate (SAR) � 8.27 W/Kg from 6 h post fertilization (hpf) to 48 hpf, and measured a battery of morphological and behavioral endpoints at 120 hpf. Our results revealed no significant impacts on mortality, morphology or photomotor response and a modest inhibition of startle response suggesting some levels of sensorimotor disruptions. This suggests that the cell phone radiations at low GHz-level frequencies are likely benign, with subtle sensorimotor effects. Through this assessment, we have established a robust setup for zebrafish RFR exposures readily amenable to testing various powers and frequencies. Future developmental exposure studies in zebrafish will evaluate a wider portion of the radio frequency spectrum to discover the bioactive regions, the potential molecular targets of RFR and the potential long-term effects on adult behavior.

Ranging accuracy is a critical parameter in time-based indoor positioning systems. Indoor environments often have complex structures, which make centimeter-level-accurate ranging a challenging task. This study proposes a new distance measurement method to decrease the ranging error in multipath environment. Our method uses an artificial neural network that utilizes the received signal strength indicator along with a signal’s angle of arrival to calculate the line-of-sight distance. This combination results in a significant reduction of the error caused by multipath effects that common RSSI-based methods suffer from. It outperforms traditional ranging methods while the implementation complexity is kept low.