Uploaded November 2025 | Updated September 2026, 2 weeks ago
The headache of wired IMU projects is over! In this video, we ditch the slow serial port and upgrade our setup to a fast wireless motion tracking system using an ESP32-S3, Python, and UDP streaming. See how we get immediate data processing and position results right after capture.
Hardware & Software Used:
Microcontroller: ESP32-S3
IMU Sensor: BNO-055 (We explain why we chose it over the built-in QMI8658!)
Programming: Python Script for Data Processing and Visualization
Protocol: UDP Streaming
[Waveshare ESP32-S3 2-inch Dev Board]
waveshare.com/product/esp32-s3-touch-lcd-2.htm?&aff_id=116255
[BNO055 Adafruit]
amzn.to/3XiHRRd
[BNO055 Clone Version]
amzn.to/3XZQD6J
[Project Github]
github.com/0015/Python-IMU-Data-Sampling-App
#IMU #MotionTracking #WirelessIMU #Python #ESP32 #UDP #ZUPT #DriftCorrection
The headache of wired IMU projects is over! In this video, we ditch the slow serial port and upgrade our setup to a fast wireless motion tracking system using an ESP32-S3, Python, and UDP streaming. See how we get immediate data processing and position results right after capture.
Hardware & Software Used:
Microcontroller: ESP32-S3
IMU Sensor: BNO-055 (We explain why we chose it over the built-in QMI8658!)
Programming: Python Script for Data Processing and Visualization
Protocol: UDP Streaming
[Waveshare ESP32-S3 2-inch Dev Board]
waveshare.com/product/esp32-s3-touch-lcd-2.htm?&aff_id=116255
[BNO055 Adafruit]
amzn.to/3XiHRRd
[BNO055 Clone Version]
amzn.to/3XZQD6J
[Project Github]
github.com/0015/Python-IMU-Data-Sampling-App
#IMU #MotionTracking #WirelessIMU #Python #ESP32 #UDP #ZUPT #DriftCorrection
![[AMB82-Mini IoT AI Camera] *On-Device* object detector powered by Tiny Yolo v7! #standalone](https://i.ytimg.com/vi/TGqOUVhQQY8/mqdefault.jpg "[AMB82-Mini IoT AI Camera] *On-Device* object detector powered by Tiny Yolo v7! #standalone
Tiny YOLO version 7 is a simplified version of YOLO version 7, which has a much smaller number of convolution layers than YOLO version 7, which means that Tiny YOLO version 7 does not need to have a large amount of memory and hardware performance but lose some of the detection accuracy.
Lets make one thing clear.
The object detector we are trying to build in a low-power MCU environment is a very simple one. For example, it triggers an action when it detects a person, or acts as a kind of switch to take a certain action. For better performance, it is recommended to run the latest full version of YOLO on a device such as Nano Jetson.
[AMB82-Mini Camera module]
https://amzn.to/4bYOuNk
[Project GitHub]
https://github.com/0015/AMB82-Mini-Board")
