Participact for smart and connected communities: exploiting social networks with profile extension in crowdsensing systems

Crowdsensing systems are demonstrating to be effective in increasing the interest of citizens in actively participating to create a better environment around them. Getting information about users to create a representation of their interests and relationships allows creating richer profiles, of high relevance for crowdsensing systems. The increasing knowledge about users could provide administrators with all the information about who is the right person, e.g., to complete environmental monitoring tasks and, thus, help them in assigning tasks to the most suitable subset of users. In this way, it is possible to complete crowdsensing tasks more efficiently, with increased successful rate and minimized latency. Here, we propose to extend the ParticipAct platform by exploiting data obtained from the Facebook social network to extend users' profile for a better understanding of which tasks people feel more comfortable to execute. In particular, we propose a theoretical analysis, as well as a system implementation, of how to manage and benefit from users' relationships and interests to increase users' involvement in collaborative tasks over ParticipAct.