Crowdsourcing through cognitive opportunistic networks

Mordacchini, Matteo, Passarella, Andrea, Conti, Marco, Allen, Stuart M. ORCID: https://orcid.org/0000-0003-1776-7489, Chorley, Martin J. ORCID: https://orcid.org/0000-0001-8744-260X, Colombo, Gualtiero, Tanasescu, Vlad and Whitaker, Roger M. ORCID: https://orcid.org/0000-0002-8473-1913 2015. Crowdsourcing through cognitive opportunistic networks. ACM Transactions on Autonomous and Adaptive Systems 10 (2) , 13. 10.1145/2733379

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Abstract

Until recently crowdsourcing has been primarily conceived as an online activity to harness resources for problem solving. However the emergence of opportunistic networking (ON) has opened up crowdsourcing to the spatial domain. In this paper we bring the ON model for potential crowdsourcing in the smart city envi- ronment. We introduce cognitive features to the ON that allow users’ mobile devices to become aware of the surrounding physical environment. Specifically, we exploit cognitive psychology studies on dynamic memory structures and cognitive heuristics, i.e. mental models that describe how the human brain handles decision- making amongst complex and real-time stimuli. Combined with ON, these cognitive features allow devices to act as proxies in the cyber-world of their users and exchange knowledge to deliver awareness of places in an urban environment. This is done through tags associated with locations. They represent features that are perceived by humans about a place. We consider the extent to which this knowledge becomes available to participants, using interactions with locations and other nodes. This is assessed taking into account a wide range of cognitive parameters. Outcomes are important because this functionality could support a new type of recommendation system that is independent of the traditional forms of networking.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics Systems Immunity Research Institute (SIURI)
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Additional Information:	© ACM, 2015. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Autonomous and Adaptive Systems, {10, 2, June 1015} http://doi.acm.org/10.1145/2733379
Publisher:	Association for Computing Machinery (ACM)
ISSN:	1556-4665
Date of First Compliant Deposit:	30 March 2016
Last Modified:	09 Nov 2024 17:45
URI:	https://orca.cardiff.ac.uk/id/eprint/74108

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