Uploaded October 2025 | Updated September 2026, 2 weeks ago
This system features an OV5647 camera for live video display on a 7-inch screen, and we control its movement (pan/tilt) using two servo motors driven by the PCA9685 I2C servo driver. The user interface is built with LVGL, featuring simple sliders for smooth control.
Components Used:
- ESP32-P4 Development Board w/ 7-inch Display Screen (Waveshare)
waveshare.com/esp32-p4-wifi6-touch-lcd-7b.htm?&aff_id=116255
- OV5647 CSI Camera Module
amzn.to/477KBGM
- PCA9685 Servo Driver
amzn.to/47pkSbP
- Servo Motor
amzn.to/43BlGsM
- 18650 Battery Holder
amzn.to/49kEoIP
This system features an OV5647 camera for live video display on a 7-inch screen, and we control its movement (pan/tilt) using two servo motors driven by the PCA9685 I2C servo driver. The user interface is built with LVGL, featuring simple sliders for smooth control.
Components Used:
- ESP32-P4 Development Board w/ 7-inch Display Screen (Waveshare)
waveshare.com/esp32-p4-wifi6-touch-lcd-7b.htm?&aff_id=116255
- OV5647 CSI Camera Module
amzn.to/477KBGM
- PCA9685 Servo Driver
amzn.to/47pkSbP
- Servo Motor
amzn.to/43BlGsM
- 18650 Battery Holder
amzn.to/49kEoIP
![IMU Motion Tracking UPGRADE: Python Processing with Wireless UDP Stream!
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]
https://www.waveshare.com/product/esp32-s3-touch-lcd-2.htm?&aff_id=116255
[BNO055 Adafruit]
https://amzn.to/3XiHRRd
[BNO055 Clone Version]
https://amzn.to/3XZQD6J
[Project Github]
https://github.com/0015/Python-IMU-Data-Sampling-App
#IMU #MotionTracking #WirelessIMU #Python #ESP32 #UDP #ZUPT #DriftCorrection IMU Motion Tracking UPGRADE: Python Processing with Wireless UDP Stream!](https://i.ytimg.com/vi/RUpNuuojN5Q/mqdefault.jpg)


![2025, My first ESP32 device is T5 E-Paper S3 Pro! #ESP32 #LoRa #E-Paper
Product: T5 E-Paper S3 Pro
MCU: ESP32-S3-WROOM-1
Flash / PSRAM: 16M / 8M
Lora: SX1262
Touch: GT911
Driver IC: ED047TC1 (4.7 inches, 960x540 , 16 gray)
Battery Capacity: 1500mAh
Battery Chip: BQ25896, BQ27220
RTC: PCF85063
[T5 E-Paper S3 Pro]
https://lilygo.cc/products/t5-e-paper-s3-pro 2025, My first ESP32 device is T5 E-Paper S3 Pro! #ESP32 #LoRa #E-Paper](https://i.ytimg.com/vi/SFUErz3VVJY/mqdefault.jpg)

![I failed it. I dont recommend the basic model of ESP-Drone. #ESP32
I started this project with high expectations but I failed. Please use this as a reference and I hope your project will be successful.
*When connecting the drone via WiFi from the mobile, the password is 12345678
[ESP-Drone]
https://docs.espressif.com/projects/espressif-esp-drone/en/latest/index.html
[ESP-Drone Sensor Calibration]
https://docs.espressif.com/projects/espressif-esp-drone/en/latest/system.html#sensor-calibration
#ESP32 #Drone #Crazyflie I failed it. I dont recommend the basic model of ESP-Drone. #ESP32](https://i.ytimg.com/vi/SXpK2IH-JWE/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 [AMB82-Mini IoT AI Camera] *On-Device* object detector powered by Tiny Yolo v7! #standalone](https://i.ytimg.com/vi/TGqOUVhQQY8/mqdefault.jpg)
![2024 E-Paper Displays! 5.65 7-Color eInk / ePaper Display with 600x448 Pixels
As E-Ink/E-Paper Display market grows, various products are being released. So what is the quality of the 5.65-inch, 7-color product?
[5.65 Seven-Color eInk (GDEP0565D90)]
https://www.seeedstudio.com/5-65-Seven-Color-ePaper-Display-with-600x480-Pixels-p-5786.html
#EDisplay #EINK #ESP32 #ThatProject 2024 E-Paper Displays! 5.65 7-Color eInk / ePaper Display with 600x448 Pixels](https://i.ytimg.com/vi/TgspnasSGL4/mqdefault.jpg)
![Interactive Vision Questioning with GPT-4o: MCU Integration Demo #ESP32CAM #CHATGPT #GPT4o
Discover the latest advancements in AI integration with MCU environments in our demonstration featuring GPT-4o! In this video, I showcase how GPT-4os capabilities now extend to image-based questions, offering a glimpse into the future of interactive AI applications. Follow along as I capture images using an MCU device, pose questions about them, and receive insightful responses from OpenAI Server.
[ChatGPT Library]
https://github.com/0015/ChatGPT_Client_For_Arduino Interactive Vision Questioning with GPT-4o: MCU Integration Demo #ESP32CAM #CHATGPT #GPT4o](https://i.ytimg.com/vi/TovfijE0pBg/mqdefault.jpg)