Juneeee98/Realtime-Fall-Dectection-and-Human-Activity-Recognition-Using-MLP
Realtime Fall Detection and Human Activity Recognition using Multilayer Perceptron Neural Network from gyroscope and accelerometer sensor sent from a ESP-32 Microcontroller
This project helps caregivers, safety managers, or system integrators monitor individuals for falls and specific activities in real-time. It takes data from gyroscope and accelerometer sensors (like those found in wearables) and outputs immediate predictions about whether a person has fallen or is performing a recognized activity. This is for professionals managing safety for elderly individuals, workers in hazardous environments, or anyone needing automated activity monitoring.
No commits in the last 6 months.
Use this if you need a quick, reliable way to detect falls and identify common human activities using wearable sensor data.
Not ideal if you require highly nuanced activity recognition (e.g., distinguishing between very similar complex actions) or need to process data from non-IMU sensor types.
Stars
13
Forks
6
Language
Python
License
MIT
Category
Last pushed
Jul 11, 2021
Commits (30d)
0
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