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Research on disaster information dissemination based on social sensor networks.

Authors :
Wan, Shanshan
Chen, Zhuo
Lyu, Cheng
Li, Ruofan
Yue, Yuntao
Liu, Ying
Source :
International Journal of Distributed Sensor Networks. Mar2022, Vol. 18 Issue 3, p1-15. 15p.
Publication Year :
2022

Abstract

Sudden disaster events are usually unpredictable and uncontrollable, and how to achieve efficient and accurate disaster information dissemination is an important topic for society security. At present, social sensor networks which integrate human mobile sensors and traditional physical sensors are widely used in dealing with emergencies. Previous studies mainly focused on the impact of human mobility patterns on social sensor networks. In this article, based on the inherent autonomy property of human individuals, we propose a social sensor information dissemination model, which mainly focuses on the impact of the individual characteristics, social characteristics, and group information dissemination mode on social sensor networks. Specifically, the human sensor model is first constructed based on the inherent social and psychological attributes of human autonomy. Then, various information dissemination models such as one-to-one, one-to-many, and peer-to-peer are proposed by considering different transmission media and human interaction preferences. We simulate the environment of information dissemination in disaster events based on the NetLogo platform. Evaluation matrix is applied to test the performance of social sensor information dissemination model, such as event dissemination coverage, event delivery time, and event delivery rate. With the comparisons to epidemic model, social sensor information dissemination model shows excellent performance in improving the efficiency and accuracy of information transmission in disaster events. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15501329
Volume :
18
Issue :
3
Database :
Academic Search Index
Journal :
International Journal of Distributed Sensor Networks
Publication Type :
Academic Journal
Accession number :
156076354
Full Text :
https://doi.org/10.1177/15501329221080666