A Smart UAV-Femtocell Data Sensing System for Post-Earthquake Localization of People

Abstract

The paper proposes an intelligent data sensing and geo-localization algorithm, based on an innovative mobile computing system that measures the power level of RF sources through a 2G/5G femtocell-UAV system. In natural disasters (mainly earthquakes and floods) the system can identify any missing persons under the rubble within a range of precision between 1 to 2 meters. In this paper, more specifically, the algorithm allows classifying the terminal even in the presence of obstacles that cause anisotropic propagation of radio signals, through a series of power measurements based on the Reference Signal Received Power (RSRP). An attenuation model that takes into account the different types of materials is introduced, and a method for optimizing the drone's flight path and duration is proposed. The performances, expressed in terms of accuracy in identifying the mobile terminal and in terms of position estimation average error, are evaluated according to the material's density and its attenuation.