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Updated: Jan 17, 2026
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Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
Published on: December 11, 2015
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Enhancing human activity recognition with machine learning: insights from smartphone accelerometer and magnetometer
Luis Augusto Silva Zendron1, Paulo Jorge Coelho2,3, Christophe Soares4,5
1Department of Computer Science and Automation, Universidad de Salamanca, Salamanca, Spain.
Peerj. Computer Science
|September 24, 2025
Summary
This study enhances human activity recognition (HAR) using smartphone sensors and machine learning. Novel methods achieved high accuracy, making HAR efficient and deployable on mobile devices.
Area of Science:
- Computer Science
- Artificial Intelligence
- Machine Learning
Background:
- Human Activity Recognition (HAR) has advanced significantly due to sensor and AI progress.
- Previous studies established baseline results for HAR using smartphone sensor data.
Purpose of the Study:
- To implement and evaluate various machine learning techniques for improved HAR.
- To analyze the effectiveness of neural networks, random forest, and other models on existing HAR datasets.
Main Methods:
- Data collection from smartphone sensors, followed by cleaning and normalization.
- Feature extraction and implementation of diverse machine learning models including neural networks and random forest.
- Utilized non-normalized data and integrated magnetometer signals for enhanced performance.
Main Results:
- Neural network and random forest models demonstrated high effectiveness.
- Achieved an Area Under the Curve (AUC) of 98.42%, classification accuracy of 90.14%, F1-score of 90.13%, precision of 90.18%, and recall of 90.14%.
- Outperformed earlier models with reduced computational cost, comparable to deep learning approaches.
Conclusions:
- The developed approach is novel, efficient, and suitable for real-time mobile applications.
- Lightweight models and a reproducible visual workflow enhance deployability.
- The integration of non-normalized data and magnetometer signals improved HAR performance.
