Parrot’s cloud enable users whom have chosen to share their data to manage their flight and fleet data, as well as the media taken by their drones.

 

Data collected

Our cloud collects 4 data types:

 

“Static” (product data):

• Drone serial number
• Batterie serial number
• Firmware version for drone and battery
• Hardware version for drone and battery
• Device model
• FreeFlight 7 release version

 

“Events”

• Alerts: battery, autopilot, sensors
• Connectivity: connection/disconnection, streaming start, interference alert, weak signal
• Camera: streaming statistics, settings changes
• Flight: status change (take-off, landing, hovering, etc.), flight mission activation (Flight Plan, Photogrammetry)

 

“Contextual images”

• Timelapse pictures (one every 2 minutes)
• Deep learning (matching more objects, landscapes for flight autonomy improvement, tracking, obstacle avoidance)
• Stereo vision (depth map)
• Images triggered by event
• Start and ending of precise hovering phrases, precise landing
• Drone crash
• Faces are automatically blurred when transferred

 

“Telemetry” (refer to the following table for details)

System	Description	Sampling
Flight control	GPS Position, speed, height, drone’s attitude (phi, theta, psi angles), wind strength estimate	5Hz
Connectivity	Wi-Fi Physical layer: RSSI, PER (packet error rate), throughput estimator, tx/rx bytes tx/rx packets, Wi-Fi and non Wi-Fi interference measurement Streaming RTP statistics piloting commands (jitter, lost count)	1Hz
Camera	Zoom factor, shutter speed, gain, NED reference	1Hz
GNSS	Number of satellites (in sight, in synch, precision) – GPS, Glonass, Galileo	1Hz
Gimbal	Camera tilt	5Hz
Battery	Temperature, tension, remaining capacity	1Hz
Autopilot	Position, speed, height, drone’s attitude	5Hz
Vertical camera	Exposure time, gain, brightness	1Hz
Controller	Roll, Pitch, Yaw and Speed commands Zoom command Gimbal command	1Hz

Final use of collected data

Parrot collects and exploits only data from customers who have accepted to share their data, and to improve the quality of its products.

 

Maintenance management

• Preventive maintenance: our tools collect all information relevant to missions (mission type, time of take-off and landing, missions count, drones’ locations, flight speed, Flight Plan and AirSDK settings). This offers us an accurate real time status of ANAFI Ai drones fleet (as well as their controllers and batteries).
• Corrective maintenance: collected information are useful to quickly pinpoint information pertaining the state of a particular drone or battery.

 

Artificial Intelligence (AI) improvement

AI elements carried by ANAFI Ai (PeleeNet, Convolutional Networks, etc.) offer users unequalled services and performances: obstacle avoidance, target following, several flight modes. The quality of IA relies on the quantity and quality of data (images and videos) collected: this data feeds the machine learning. In that respect, the quality of the data is not the only crucial element: the metadata associated to this data is fundamental too. For this reason, our tool collects images and metadata on a regular basis and depending on events, for a total of 30 to 50 Mb/minute flight.