PublicSense: A Crowd Sensing Platform for Public Facility Management in Smart Cities

The prevalence of mobile crowd sensing (MCS) facilitates the collection of large-scale sensing data. There are many MCS platforms developed in various aspects. But there are few existing MCS platforms used for public facility. In this paper, we propose a crowd sensing platform for public facility management. Participants use their smart phones to collect the information of public facility by the smart phone's current time, camera, and GPS sensors data. All information will be transmitted to the backend server. An image classification method based on Fourier descriptor algorithm is presented to classify the uploaded data. The experimental results show this system can detect the problem type according the uploading data.