Crowdsourcing through Cognitive Opportunistic Networks

TL;DR

This paper explores integrating cognitive features into opportunistic networks to enable location-aware crowdsourcing in smart cities, facilitating context-aware knowledge exchange and novel recommendation systems.

Contribution

It introduces cognitive features into opportunistic networks, allowing mobile devices to act as proxies for urban environment awareness based on human cognitive models.

Findings

Cognitive features enable devices to exchange location-based knowledge.

The approach supports context-aware recommendations independent of traditional networks.

Potential to enhance smart city applications with cognitive-aware crowdsourcing.

Abstract

Untile 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 environment. 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 handle 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.