  Natural disasters affect millions of people every year. Finding missing
persons in the shortest possible time is of crucial importance to reduce the
death toll. This task is especially challenging when victims are sparsely
distributed in large and/or difficult-to-reach areas and cellular networks are
down. In this paper we present SARDO, a drone-based search and rescue solution
that exploits the high penetration rate of mobile phones in the society to
localize missing people. SARDO is an autonomous, all-in-one drone-based mobile
network solution that does not require infrastructure support or mobile phones
modifications. It builds on novel concepts such as pseudo-trilateration
combined with machine-learning techniques to efficiently locate mobile phones
in a given area. Our results, with a prototype implementation in a field-trial,
show that SARDO rapidly determines the location of mobile phones (~3 min/UE) in
a given area with an accuracy of few tens of meters and at a low battery
consumption cost (~5%). State-of-the-art localization solutions for disaster
scenarios rely either on mobile infrastructure support or exploit onboard
cameras for human/computer vision, IR, thermal-based localization. To the best
of our knowledge, SARDO is the first drone-based cellular search-and-rescue
solution able to accurately localize missing victims through mobile phones.
