https://github.com/gusdulwacikul/fall-detection

Fall detection using MPU6050 with CNN method, here is all the code related to my project from get raw accelerometer data( X,Y, Z ) axis. Accelerometer data then uploaded to computer or raspi using UDP method and automatically create a CSV files with 500 data row per 5 secs. CSV files exported to spectrogram for training dataset
https://github.com/gusdulwacikul/fall-detection

arduino cnn detection esp8266 fall mpu6050 python udp

Last synced: about 2 months ago
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Fall detection using MPU6050 with CNN method, here is all the code related to my project from get raw accelerometer data( X,Y, Z ) axis. Accelerometer data then uploaded to computer or raspi using UDP method and automatically create a CSV files with 500 data row per 5 secs. CSV files exported to spectrogram for training dataset

• Host: GitHub
• URL: https://github.com/gusdulwacikul/fall-detection
• Owner: Gusdulwacikul
• Created: 2025-05-27T03:44:01.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-05-27T04:12:09.000Z (about 1 year ago)
• Last Synced: 2025-06-04T08:59:40.752Z (about 1 year ago)
• Topics: arduino, cnn, detection, esp8266, fall, mpu6050, python, udp
• Language: Python
• Homepage:
• Size: 13.7 KB
• Stars: 1
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# Fall-detection

Fall detection using MPU6050 with CNN method. Below is all the code related to my project, starting from acquiring raw accelerometer data (X, Y, Z axes). The accelerometer data is then uploaded to a computer or Raspberry Pi using UDP. The system automatically creates CSV files with 500 rows of data every 5 seconds. These CSV files are then converted to spectrograms for the training dataset.

If you want, I can help improve your whole project description or comments in your code as well!