Drone-Mounted BLE Scanners for Search and Rescue: Commercial Options and DIY Builds
Yes, it works — and there’s already a commercial product
Mounting a Bluetooth Low Energy scanner on a drone to locate missing persons is not just theoretically feasible — it’s been validated in academic research and there is at least one commercially available product built specifically for this mission. Parsons Corporation, through their QRC subsidiary, launched BlueFly™ in July 2025. It’s a drone-agnostic payload weighing under a pound that detects classic Bluetooth, BLE, and Wi-Fi signals from wearable electronics — smartwatches, fitness trackers, wireless earbuds, glucose monitors — at up to 200 meters line of sight, and plots relative signal strength on a TAK (Team Awareness Kit) heat map in real time.
That said, the DIY path on a Raspberry Pi is worth understanding. Budget, procurement timelines, integration flexibility, and the need to customize scanning for specific device types all push some agencies toward building their own.
How BLE detection from a drone actually works
BLE devices advertise their presence by broadcasting packets at regular intervals — typically every 100–1000 milliseconds. A scanner picks up these advertisements without needing to pair with the source. Every packet includes the device’s MAC address and a Received Signal Strength Indicator (RSSI) value. RSSI is what lets you estimate proximity: stronger signal, closer device.
From a drone, the workflow is straightforward in concept. Fly a grid pattern over the search area, record every BLE advertisement packet along with GPS coordinates and timestamp, then plot RSSI values on a map. Clusters of strong readings point to where a device was when the drone passed overhead. A second pass can narrow the zone.
The practical challenge is that RSSI over open terrain is noisy. Obstacles, body shielding (a phone in a jacket pocket), antenna orientation, and atmospheric conditions all introduce variance. Don’t expect meter-level accuracy from RSSI alone — expect a zone, maybe 10–30 meters wide, that tells you where to concentrate a ground search.
The Raspberry Pi DIY approach
A Raspberry Pi 4 or Pi Zero 2 W with built-in Bluetooth works as a BLE scanner out of the box. For software, the Bleak library (available on PyPI) is the current recommended choice for BLE scanning in Python. It’s cross-platform, async-friendly, and better maintained than the older bluepy library most tutorials still reference.
A minimal scanning script:
import asyncio
from bleak import BleakScanner
async def scan():
devices = await BleakScanner.discover(timeout=5.0)
for d in devices:
print(d.address, d.name, d.rssi)
asyncio.run(scan())That gives you MAC addresses, device names (when advertised), and RSSI. Wrap it in a loop that also reads a GPS module — a cheap UART GPS works fine with gpsd or the gps Python library — and logs everything to a CSV or SQLite file keyed by timestamp and coordinates.
Antenna choices
The stock chip antenna on a Pi or a cheap USB dongle reaches maybe 10–30 meters under ideal conditions. For drone use, a USB Bluetooth adapter with an RP-SMA connector lets you attach a standard 2.4 GHz antenna. Patch antennas — flat, directional, higher gain — mounted facing downward can extend effective detection range. The tradeoff is a narrower beam, which means slower flight or more passes to cover the same area. A short-range omnidirectional antenna at higher altitude often serves better for initial area searches than a directional antenna at lower altitude.
BlueFly’s claimed 200-meter range reflects purpose-built RF hardware well beyond what a stock Pi delivers. DIY builders should realistically expect 40–80 meters with good external antennas, depending on which devices they’re targeting and how those devices are being carried.
Which devices will you actually detect?
Almost any modern smartphone, smartwatch, or fitness tracker broadcasts BLE. Apple AirTags, Tile trackers, and similar item-finders are designed to broadcast continuously — they’re easy to detect. Phones are trickier: iOS and Android both use MAC address randomization for privacy, so you can’t reliably identify a specific phone by its MAC address. You can still detect that a phone is in the area, which is useful in SAR even without confirming whose it is.
AirPods, Galaxy Buds, and similar earbuds advertise when near their case. Glucose monitors and certain medical wearables also broadcast. The target list is wide — in a remote area with no reason for human presence, almost any BLE signal is meaningful.
Drone integration and flight planning
Most mapping autopilot software — Mission Planner for ArduPilot, QGroundControl, DJI Pilot 2 with waypoint missions — can fly a boustrophedon (lawnmower) grid over a defined polygon. Key parameters are altitude and flight speed. For open terrain, 20–30 meters AGL at 5–8 m/s is a reasonable starting point. Fast enough to cover ground; slow enough that a 1-second BLE scan interval captures several packets per pass.
Connect the Pi to your ground station via USB serial or local Wi-Fi for live data. If that adds too much RF complexity to an already busy environment, post-processing the log file after landing is simpler and works just as well for most SAR applications.
Visualizing results
QGIS is free, handles GPS-tagged data well, and can render RSSI values as a heat map from a point layer with graduated symbology. For TAK integration — BlueFly’s native output format — the open-source Python library takproto lets you push Cursor on Target (CoT) messages to a TAK server. That adds complexity but puts scanner data directly into the common operating picture your other responders are already using.
Legal and operational considerations
For US law enforcement agencies, the FAA’s Public Safety Toolkit covers operating UAS under governmental COAs (Certificates of Authorization) and Part 107 waivers. SAR operations generally have a more accessible path to BVLOS waivers than commercial operators. A separate, non-FAA question is whether passively collecting MAC addresses and device identifiers triggers state-level drone surveillance statutes or requires a warrant. Some states — Illinois is the most cited example — have explicit carve-outs for SAR; others don’t. Run this past your department’s legal counsel before operational deployment.
Getting the legal framework sorted first makes the technical work easier, not the other way around.
Where to start
If procurement isn’t an obstacle, contact Parsons/QRC about BlueFly directly — it’s purpose-built for this niche and drone-agnostic. For agencies that need to experiment first or can’t wait on procurement cycles, a Raspberry Pi 4 with a USB Bluetooth adapter, a GPS hat, and a Bleak-based Python script is achievable in a weekend. Test it on foot first: walk a grid, log what you see, and get a feel for what RSSI values look like at different distances from your target devices before the first flight. That step alone will save a lot of debugging time in the field.