Mobile crowd sensing (MCS) is a new paradigm enabled by Internet of Things (IoT) in which sensor-rich ubiquitous devices collect and share the data over a large geography. Human behaviour attributes (perception, comprehension and projection) play a key role in the decision-making process for sharing and processing the data. This study aims to understand how situation awareness plays an important role in MCS in an IoT ecosystem.
A systematic literature review was conducted by following a rigorous search protocol that identified a total of 470 peer-reviewed research papers. These papers were further filtered and finally 31 relevant papers were selected.
The major issues and concerns arising due to human participation in the MCS system were identified. Further, probable strategies were explored to deal with the challenges resulting due to certain human behaviour attributes.
This study provides the recommendations to address the major challenges related to the MCS system, which in turn may enhance the adoption of emerging smart technology-driven services.
The study is original and is based on the existing literature and its interpretation.
Agarwal, N., Chauhan, S., Kar, A. and Goyal, S. (2017), "Role of human behaviour attributes in mobile crowd sensing: a systematic literature review", Digital Policy, Regulation and Governance, Vol. 19 No. 2, pp. 168-185. https://doi.org/10.1108/DPRG-05-2016-0023Download as .RIS
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