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Related Experiment Video

Updated: Jan 20, 2026

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
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AI-Based Early Change Detection in Smart Living Environments.

Giovanni Diraco1, Alessandro Leone2, Pietro Siciliano2

  • 1CNR-National Research Council of Italy, IMM-Institute for Microelectronics and Microsystems, 73100 Lecce, Italy. giovanni.diraco@cnr.it.

Sensors (Basel, Switzerland)
|August 17, 2019
PubMed
Summary

Unsupervised deep learning excels at detecting early changes in older adults' behavior using sensor data. This AI approach offers superior accuracy and prediction lead-time compared to traditional methods, supporting independent living.

Failed At:

2026-06-19T13:38:19.780285+00:00

Keywords:
activity of daily livingambient assisted livingartificial intelligencebig data analyticschange detectiondeep learninghuman behaviormachine learningmulti-sensor systemsmart living

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