Skip to content
This repository was archived by the owner on Jul 23, 2026. It is now read-only.
BranchesTags

Latest commit

 

History

5 Commits

Folders and files

NameName
Last commit message
Last commit date
main
main
 
 
.gitignore
.gitignore
 
 
CMakeLists.txt
CMakeLists.txt
 
 
LICENSE
LICENSE
 
 
README.md
README.md
 
 

Repository files navigation

Grove Vision AI V2 on LilyGO T-SIM7080G-S3

Note: Active development has relocated to aggerritsen/VespaSmartTrap-BASE. This repository is kept in archive status to maintain Git submodule updates from external providers if needed.

ESP-IDF firmware for processing Grove Vision AI V2 detection results on the LilyGO T-SIM7080G-S3. Visual feedback via LEDs indicates detected species.

Prerequisites

  1. ESP-IDF v5.x installed and configured
  2. Grove Vision AI V2 flashed with YOLO11n model and UART1 firmware
    See gv2-esp32 for flashing instructions

Hardware Connections

UART (GV2 to LilyGO)

GV2 Socket LilyGO T-SIM7080G-S3
RXD GPIO43 (TXD)
TXD GPIO44 (RXD)
5V 5V
GND GND

LED Indicators

LED Color GPIO Detection Class
Green GPIO9 Class 0: Apis mellifera
Yellow GPIO10 Class 1/2: Vespa crabro, Vespula sp.
Red GPIO11 Class 3: Vespa velutina

Build and Flash

# Set up ESP-IDF environment
source ~/esp/esp-idf/export.sh

# Build the project
idf.py build

# Flash to device (replace PORT with your USB port)
idf.py -p /dev/cu.usbmodem* flash

# Monitor serial output
idf.py -p /dev/cu.usbmodem* monitor

Detection Classes

Class Species LED
0 Apis mellifera Green
1 Vespa crabro Yellow
2 Vespula sp. Yellow
3 Vespa velutina Red

References

About

ESP-IDF firmware for processing YOLO11n Grove Vision AI V2 detection results on the LilyGO T-SIM7080G-S3. Visual feedback via LEDs indicates detected species.

Resources

Readme
AGPL-3.0 license
Activity
Custom properties

Stars

0 stars

Watchers

0 watching

Forks

0 forks
Report repository

Releases

Packages

Contributors

Languages