ak
Published © GPL3+

Flying Fellows in Distress Seeker

Machine learning at the edge for distress calls surveys using drones.

IntermediateFull instructions providedOver 1 day633

Things used in this project

Hardware components

KIT-HGDRONEK66
NXP KIT-HGDRONEK66
×1
RDDRONE-FMUK66
NXP RDDRONE-FMUK66
×1
Coral USB Accelerator
Google Coral USB Accelerator
https://coral.ai/products/pcie-accelerator or alike would speed it up, as the USB3 port is not really available as USB3 port.
×1
NXP 8MMNavQ (imx8mmnavq)
×1
Google Coral MIPI-CSI interface Camera
×1
Bench Power Supply, USB Programmable DC
Bench Power Supply, USB Programmable DC
acting as battery and multimeter for development
×1
Android device
Android device
for development - playing videos in loop for testing end-to-end
×1
7'' HDMI Display with Capacitive Touchscreen
DFRobot 7'' HDMI Display with Capacitive Touchscreen
an HDMI screen for starting with device
×1
SIM7600X-H
SIMCom Wireless Solutions SIM7600X-H
SIM7000E or equivalent
×1

Software apps and online services

MAVLink
PX4 MAVLink
gstreamer
TensorFlow
TensorFlow
tensorflow lite for machine learning inferencing on the drone itself
Google Posenet
pre-trained model
graphviz
pipeline visualisation

Hand tools and fabrication machines

Multitool, Screwdriver
Multitool, Screwdriver

Story

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Schematics

high level architecture

Code

posenet_waving

Credits

ak

ak

2 projects • 2 followers

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