Emara, Karim and El-Kady, Aya and shaaban, Eman and ElEliemy, Mohamed (2021) MOBILE CROWDSENSING FRAMEWORK FOR ROAD SURFACE QUALITY DETECTION. International Journal of Intelligent Computing and Information Sciences, 21 (3). pp. 95-106. ISSN 2535-1710
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Abstract
Smartphones became ubiquitous and are used by so many people, at least to know the driving directions to their destination. Smartphones come with rich embedded sensors (e.g., GPS, accelerometer, and camera) as well as built-in radios (e.g., Bluetooth, Wi-Fi, and Cellular), which both enable users to gather data and distribute it among people at any time or location. These features have come up with the mobile crowdsensing (MCS) development which can be used in a wide range of applications. In this paper, we introduce a complete mobile crowdsensing framework for road surface condition detection. Various modules have been addressed such as task management, data fusion, reputation scoring, incentive awarding, security and privacy, as well as discussing popular techniques and algorithms utilized in the proposed MCS framework modules. A prototype of the crowd sensing application is designed which is related to our framework. The proposed framework considers the data quality and trustiness between the users and the server as well.
Item Type: | Article |
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Subjects: | STM Repository > Computer Science |
Depositing User: | Managing Editor |
Date Deposited: | 13 Jul 2023 04:01 |
Last Modified: | 02 Nov 2023 06:09 |
URI: | http://classical.goforpromo.com/id/eprint/3617 |