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Sensor-Based Benchmark Datasets: Comparison and Analysis

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IoT Sensor-Based Activity Recognition

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 173))

Abstract

Human Activity Recognition (HAR) using installed sensors has made renowned progress in the field of pattern recognition and human-computer interaction. To make efficient machine learning models, researchers need publicly available benchmark datasets. In this chapter, we have bestowed a comprehensive survey on sensor-based benchmark datasets. We have not considered RGB or RGB-Depth video-based action or activity-related datasets in this book. We have performed a complete analysis of benchmark datasets, that incorporates information about sensors, attributes, activity classes, etc. These datasets sum up a good number of sensor-based daily activities, medical activities, fitness activities, device usage, fall detection, transportation activity, and hand gesture data.

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Notes

  1. 1.

    http://ps.ewi.utwente.nl/Datasets.php.

  2. 2.

    http://hasc.jp/.

  3. 3.

    Cooking Activity Challenge with International Conference on Activity and Behavior Computing (ABC), 2020 https://abc-research.github.io/cook2020.

  4. 4.

    http://www.cs.ucr.edu/~eamonn/time_series_data/.

  5. 5.

    https://www.physionet.org/physiobank.

  6. 6.

    http://crawdad.org/.

  7. 7.

    Cooking Activity Challenge with International Conference on Activity and Behavior Computing (ABC), 2020 https://abc-research.github.io/cook2020.

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Authors and Affiliations

  1. Osaka University, Osaka, Japan

    Md Atiqur Rahman Ahad

  2. University of Dhaka, Dhaka, Bangladesh

    Md Atiqur Rahman Ahad

  3. University of Michigan, Ann Arbor, Michigan, USA

    Anindya Das Antar

  4. University of Maryland Baltimore County, Maryland, USA

    Masud Ahmed

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  1. Md Atiqur Rahman Ahad
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  2. Anindya Das Antar
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  3. Masud Ahmed
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Correspondence to Md Atiqur Rahman Ahad .

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Ahad, M.A.R., Antar, A.D., Ahmed, M. (2021). Sensor-Based Benchmark Datasets: Comparison and Analysis. In: IoT Sensor-Based Activity Recognition. Intelligent Systems Reference Library, vol 173. Springer, Cham. https://doi.org/10.1007/978-3-030-51379-5_6

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