Human Activity Recognition using Wearable Sensor Data and ML
Classifies walking, running, sitting and falling activities from accelerometer and gyroscope wearable data using a random-forest model, aimed at elderly fall-detection applications.
- Project code
- AUX-MLR-1907
- Domain
- Machine Learning
- Type
- Software project
- Level · Year
- Intermediate · 2025-26
Technologies and components
What is included
- Complete source code
- Database / dataset and setup guide
- Project report (college format)
- PPT for review and viva
- Installation and demo support
- Viva question guidance
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View project →Frequently asked questions
Can I get the Human Activity Recognition using Wearable Sensor Data and ML project for my final year?
Yes. This project (code AUX-MLR-1907) is available as a software project kit for the 2025-26 academic year. Contact us on WhatsApp to request it.
Can this project be customised?
Yes. Features, technology and documentation can be modified to suit your guide and college requirements.
Which departments is this project suitable for?
CSE, IT, AI & DS, BCA and MCA students, and ECE students interested in software.
Get this project with full support
Ask about customisation, delivery time and viva support.
