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Review
. 2022 Aug 27;22(17):6463.
doi: 10.3390/s22176463.

Human Activity Recognition: Review, Taxonomy and Open Challenges

Muhammad Haseeb Arshad  1 , Muhammad Bilal  2 , Abdullah Gani  3
Affiliations
Review

Human Activity Recognition: Review, Taxonomy and Open Challenges

Muhammad Haseeb Arshad et al. Sensors (Basel). .

Abstract

Nowadays, Human Activity Recognition (HAR) is being widely used in a variety of domains, and vision and sensor-based data enable cutting-edge technologies to detect, recognize, and monitor human activities. Several reviews and surveys on HAR have already been published, but due to the constantly growing literature, the status of HAR literature needed to be updated. Hence, this review aims to provide insights on the current state of the literature on HAR published since 2018. The ninety-five articles reviewed in this study are classified to highlight application areas, data sources, techniques, and open research challenges in HAR. The majority of existing research appears to have concentrated on daily living activities, followed by user activities based on individual and group-based activities. However, there is little literature on detecting real-time activities such as suspicious activity, surveillance, and healthcare. A major portion of existing studies has used Closed-Circuit Television (CCTV) videos and Mobile Sensors data. Convolutional Neural Network (CNN), Long short-term memory (LSTM), and Support Vector Machine (SVM) are the most prominent techniques in the literature reviewed that are being utilized for the task of HAR. Lastly, the limitations and open challenges that needed to be addressed are discussed.

Keywords: CCTV; computer vision; human activity recognition; machine learning; sensors.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Steps performed for selection of articles.
Figure 2
Figure 2
Taxonomy of HAR.
Figure 3
Figure 3
Frequency of application areas targeted by existing literature on HAR.
Figure 4
Figure 4
Frequency of data sources used by existing literature on HAR.
Figure 5
Figure 5
Frequency of techniques/algorithms used in the existing literature on HAR.
See this image and copyright information in PMC

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