Main Article Content

Ana OLIVEIRA Alves
Centre of Informatics and Systems, University of Coimbra, Portugal & Polytechnic Institute of Coimbra, Portugal
Portugal
Biography
Tiago Dias
Polytechnic Institute of Coimbra, Portugal
Portugal
Biography
David Silva
Polytechnic Institute of Coimbra, Portugal
Portugal
Biography
Vol. 4 No. 2 (2015), Articles, pages 25-40
DOI: https://doi.org/10.14201/ADCAIJ2015422540
Accepted: Feb 27, 2016
Copyright

Abstract

We present a project implemented on the field which has two separate strands, one refers on collecting crowd sensing data through mobile apps where context is (near) automatically induced, another is related to a practical application of this method in a real time system to manage solidarity campaigns in collecting goods. Here, we cover both parts, we applied an experimental setup and obtained results and insights in a third sector institution, Caritas Diocesana of Coimbra[1], a non-profit organization part of Caritas[2]. As main contribution, we propose a distributed architecture for Mobile Crowd Sensing able not only to allow real time inventory through simultaneous campaigns but also it gives feedback to volunteers in order to instantly acquire information about which categories of goods are more needed[1] http://www.caritas.pt/site/nacional/ Portuguese Website (last visited in October 2015)[2] http://www.caritas.eu/ (last visited in October 2015)

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References

Alves, A., and Silva, D., 2015. Mobile CrowdSensing for Solidarity Campaings, in 6th International Symposium on Ambient Intelligence (ISAmI 2015), 125-133. doi: 10.1007/978-3-319-19695-4_13.

Chen, W., and Givens, T., 2013. Mobile donation in America. Mobile Media & Communication, 1(2), 196-212. doi: 10.1177/2050157913476028.

CITEK, 2014. Lyon, France. [Online]. http://www.yourinnovationday.eu/wp-content/uploads/2014/10/Pr%C3%A9sentation-CARITAS.pdf (last visited in March 2016)

Estrin, D., Hansen, M., Parker, A., Ramanathan, N., Reddy, S., and Burke, M., 2006. Participatory sensing, in Workshop on World- Sensor-Web, ACM SenSys.

Liang, A., Biderman, A., Ratti, C., Pereira, F., Oliveirinha, J., Gerber, A., and Vaccari, A., 2009. A holistic framework for the study of urban traces and the profiling of urban processes and dynamics, in 12th Intl. IEEE Conference on Intelligent Transportation Systems, 2009

Rheingold, H., 2002. Smart Mobs: The Next Social Revolution. New York: Basic Books.

Riches, T., and Graham, T., 2014. First World Hunger Revisited: Food Charity or the Right to Food? 2nd Edition: Palgrave Macmillan. http://dx.doi.org/10.1057/9781137298737

Rodrigues, F., Alves, A., Polisciuc, A., Jiang, S., Ferreira, J., and Pereira, F., 2013. Estimating disaggregated employment size from Points-of-Interest and census data: From mining the web to model implementation and visualization," International Journal on Advanced Intelligent Systems, p. Vol. 7.

Ryan, N., Pascoe, J., Morse, D., 1999. Enhanced Reality Fieldwork: the Context Aware Archaeological Assistant, in: Dingwall, L., S. Exon, V.

Gaffney, S. Laflin and M. van Leusen (eds.), Archaeology in the Age of the Internet. CAA97. Computer Applications and Quantitative Methods in Archaeology. Proceedings of the 25th Anniversary Conference, University of Birmingham, April (BAR International Series 750). Archaeopress, Oxford, pp. 269-274

Ye, F., and Ganti, H., 2011. Mobile crowdsensing: current state and future challenge, IEEE Communications Ma.