Arshad, Muhammad and Jaskani, Fawwad and Sabri, Muhammad and Ashraf, Fatima and Farhan, Muhammad and Sadiq, Maria and Raza, Hammad (2021) Hybrid Machine Learning Techniques to detect Real Time Human Activity using UCI Dataset. EAI Endorsed Transactions on Internet of Things.
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Abstract
The cell phone is assuming a crucial job in present day life. It offers types of assistance and applications, for example, location tracking, medical applications, and human activity examination. All android smartphones have motion sensors i.e. Accelerometer, gyroscope, in order to detect motion of
| Item Type: | Article |
|---|---|
| Date Deposited: | 04 Mar 2026 15:09 |
| Last Modified: | 17 Apr 2026 08:31 |
| URI: | http://eprints.eai.eu/id/eprint/38035 |
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