On Feasibility of Crowdsourced Mobile Sensing for Smarter City Life

This paper introduces the ongoing project that aims to develop a mobile sensing framework to collect sensor data reflecting personal-scale, or microscopic, roadside phenomena by crowdsourcing and also using social big data, such as traffic, climate, and contents of social network services like Twitter. To collect them, smartphone applications are provided. One of the typical applications is a driving recorder that collects not only sensor data but also recorded videos from the driver's view. To extract specific roadside phenomena, collected data are integrated and analyzed at the service platform. The proposed smartphone application can be replaced with appliances because of its advantages: (1) ordinary appliances work stand-alone, which means that local storage is limited; the application is connected to the cloud, (2) appliances are not cheep, at least users must pay for it; the application is free, (3) appliances only store driving records; the application can get feedback from the service. The authors expect that these advantages can be accepted by citizen as an incentive to use it. To reveal how effective such function is for users' motivation, an experiment and a survey are conducted with our prototyped service. As a result, most of the users accepted the function as attractive to use.