Abstract
The advent of new communication and information technologies offers great potential for capturing and transmitting information related to mobility. The use of these technologies makes it possible to collect information and transmit it in a participative production (crowdsourcing) perspective for organizational government services such as suspect investigation. The objective of this work is to improve the process of identifying suspects by combining collective intelligence with mobile devices. To do this, this article proposes an approach for the development of a framework based on the gathering of information by the crowd (crowd sensing), their filtering and their analysis. This framework increases the user participation by integrating the gamification technique as a motivation approach. The reliability of the crowd sensed information, in turn, is provided by an objectivity analysis algorithm. The experimental results of the case study, carried out through AnyLogic simulations, show that the methods and technologies incorporated in the suspect identification procedures accelerated the search and location process by ensuring high system performance as well as by improving the quality of the sensed data.
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El Alaoui El Abdallaoui, H., El Fazziki, A., Ennaji, F.Z., Sadgal, M. (2018). A Gamification and Objectivity Based Approach to Improve Users Motivation in Mobile Crowd Sensing. In: Abdelwahed, E., Bellatreche, L., Golfarelli, M., Méry, D., Ordonez, C. (eds) Model and Data Engineering. MEDI 2018. Lecture Notes in Computer Science(), vol 11163. Springer, Cham. https://doi.org/10.1007/978-3-030-00856-7_10
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