1615053680 sardo is a smartphone sniffing search and rescue drone

SARDO Is a Smartphone-Sniffing Search and Rescue Drone

For anyone who misuses their iPhone, Apple’s “Find My” app is a game-changer that borders on pure magic. Sign in to the app, tap a button to sound the alarm on your MIA device, and within seconds, it will emit a loud noise – even if your phone is set to silent mode – allowing you to find the missing handset gives. Yes, it usually gets stuck on the back of your couch cushion or faced somewhere on a shelf.

You can think of SArdo, a new drone project created by researchers at Germany’s NEC Laboratories Europe GmbH, such as Apple’s “Find My” app on steroids. The difference is that, while finding your iPhone is usually a matter of convenience, the technology developed by NEC investigators can be a literal lifeboat.

Sardo is a smartphone sniffing search and rescue drone
Antonio Albany

“SARDO is a single-UAV [unmanned aerial vehicle] Antonio Albinius, a research associate at NEC Laboratories Europe, told , “Cellular connectivity is designed to address victims only in disaster situations.” “The intuition behind this is to adapt the classical cellular multilayer technique, which is based on estimation of simultaneous target distances from multiple anchors, for example, the base station, in the case when only a single moving anchor is available.”

Let’s take off a little bit. For starters, SARDO stands ostensibly, often doing such projects for “search-and-rescue DrOne-based solutions” in a strange backronym manner. However, there is no dearth of projects that have investigated the use of drones for search-and-rescue missions in settings such as disaster areas, which makes SARDO stand out (or at least, hover) in addition to how it is missing. Tracks People: Their Phone Signals.

SARDO to the rescue

To begin with, SARDO periodically performs flight measurements using information extracted from the user’s smartphone signals to estimate its distance. Machine learning tools are then applied to work at the exact location of the individual, even compensating for scenarios in which cellular signals are adversely affected by debris. If the person being searched is moving, another machine learning algorithm leaps into action to assess its trajectory based on the current move. After performing a scan of a field, the SARDO drone system will automatically change its position to be closer to the victim and to obtain more accurate distance measurements.

Sardo is a smartphone sniffing search and rescue drone

“To the best of our knowledge, this is the first single-drone search-and-rescue solution capable of accurately localizing only missing people via mobile phones,” Albnis said. “There are competing solutions, but they either rely on other sensors – [such as] IR or thermal cameras – or ad hoc ultraviolet bandwidth signals – are not employed by … common cellular networks. SARDO makes the most of the high and high penetration rates of mobile phones in our society to provide a ubiquitous plug-and-play emergency localization system. “

The idea of ​​tracking people through their phone signals is smart, not least because it makes it possible to see both for specific people (something that other drone search-and-rescue approaches cannot easily do ) And required when retrieving the identity of individuals. But there is also a very clever bit of technique in play.

Field trials in progress

The major potential problem with such technology is that, in a natural disaster scenario, there is no guarantee that cellphones will be working. For example, when Hurricane Harvey struck the coast of Texas in 2017, it dropped more than 70% of the cell towers in the affected areas overall. Meanwhile, Hurricane Katrina knocked in 2005 with a total of 1,000 cell towers.

Then, do you make sure that a drone that is trying to track people by its phone signal is capable of doing so? Simple: You build the drone into a flying, lightweight cellular base station.

“We [have so far] Tested the prototype in several field trials, ”said Albany. “First, we validated our error model, and empirically proved the dependence of the error variance on the actual distance between UAV and.” [user equipment]. Then, we tested the localization [convolutional neural network] For different UAV heights and user speeds. Finally, we assessed closed loop SARDO performances, showing that some complete revolutions are required to achieve low localization error for different user speeds. “

Right now, technology can only work in outdoor environments. However, Albnis said that the team expects this to change with indoor localization in the future.

“As we developed our prototype through off-the-shelf hardware, we offered SARDO as a software module product to execute on available hardware solutions or as a complete solution including UAVs and base stations Can, ”noted.

He said that there has been interest from the departments of public safety, although no final decision has been made about its adoption.

A paper describing the work was recently published in the Journal on Mobile Computing in IEEE Transactions.

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