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A Survey of Machine Learning and Meta-heuristics Approaches for Sensor-based Human Activity Recognition Systems

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Abstract

Human Activity Recognition (HAR) is an important research area that has profound applications in healthcare, security and surveillance. Starting from traditional machine learning approaches to the recently evolving deep learning techniques, researchers have exhibited significant contributions in the HAR field in the last decade. Recently, meta-heuristic approaches have added a new dimension to this field by improving efficiency and effectiveness of activity recognition in terms of feature selection, feature extraction and parameter tuning of collected data from wearable as well as Smartphone sensors. Accordingly, this paper presents a comprehensive survey of the classic combination of machine learning and deep learning with meta-heuristic algorithms that has revolutionized HAR systems. The applications, and the underlying challenges associated with existing sensor based HAR systems are also discussed. Based on the recent state-of-the-art literature, the open issues on this topic are identified and presented in this paper for further research in this field.

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Notes

  1. https://archive.ics.uci.edu/ml/datasets/human+activity+recognition+using+smartphones

  2. https://archive.ics.uci.edu/ml/datasets/WISDM+Smartphone+and+Smartwatch+Activity+and+Biometrics+Dataset+

  3. https://archive.ics.uci.edu/ml/datasets/OPPORTUNITY+Activity+Recognition

  4. https://archive.ics.uci.edu/ml/datasets/PAMAP2+Physical+Activity+Monitoring

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Authors and Affiliations

  1. Information Technology, Techno Main Saltlake, Kolkata, West Bengal, 700091, India

    Anindita Saha

  2. Computer Science and Engineering, Jadavpur University, Kolkata, West Bengal, 700032, India

    Anindita Saha, Sajan Rajak & Chandreyee Chowdhury

  3. Computer Science and Engineering, Dayananda Sagar University, Bengaluru, Karnataka, 560068, India

    Jayita Saha

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  1. Anindita Saha
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Saha, A., Rajak, S., Saha, J. et al. A Survey of Machine Learning and Meta-heuristics Approaches for Sensor-based Human Activity Recognition Systems. J Ambient Intell Human Comput 15, 29–56 (2024). https://doi.org/10.1007/s12652-022-03870-5

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