In this paper, we proposed an autonomous place naming system for providing place names according to three types. Our system leverages the place characteristics mined from opportunistically crowdsensed data using smartphones and crowdsourced information in social networks. By integrating sensing system and exploiting crowdsourcing to gather large volumes of data, our system is able to provide place name from a person’s perspective, beyond raw location coordinates.
Our study presents the possibility of linking sensing systems to social networks, toward the advanced understanding of human life. The proposed system provides rich awareness of the places that have been annotated manually by users in previous works. Such advanced information is a building block for many context-aware applications, such as cityscale activity recognition, mobile advertising, or enhanced place recommendations. Our future work includes study on a crowdsensing framework that will explore effective incentives to encourage active participation of end users.