Participatory Sensing Systems Research Articles

A privacy-aware framework for participatory sensing

With the abundance and ubiquity of mobile devices, a new class of applications is emerging, called participatory sensing (PS), where people can contribute data (e.g., images, video) collected by their mobile devices to central data servers. However, privacy concerns are becoming a major impediment in the success of many participatory sensing systems. While several privacy preserving techniques exist in the context of conventional location-based services, they are not directly applicable to the PS systems because of the extra information that the PS systems can collect from their participants. In this paper, we formally define the problem of privacy in PS systems and identify its unique challenges assuming an un-trusted central data server model. We propose PiRi, a privacy-aware framework for PS systems, which enables participation of the users without compromising their privacy. Our extensive experiments verify the efficiency of our approach.

A General Framework for Participatory Sensing Systems

Participatory Sensing (PS) systems consist of many mobile users collecting data in a cooperative way. Due to the spatial resolution that a PS system can provide, we are now capable of detecting and analysing events that occur at different spatial scales. Nevertheless, since the measuring devices are cheaper and they are in the hands of the users, PS systems face several design challenges related to the sensor’s accuracy and failures, tampered data, user’s privacy, participation, and visualization. However, the previous work in the area of participatory sensing has focused on particular problems or just a subset of these challenges. Taking this into account, this paper proposes a general framework to guide the design and implementation of PS systems that considers all these challenges, splitting the design into 5 modules: sample size determination, data collection, data verification, data visualization, and density maps generation modules. P-Sense, a PS system to monitor pollution levels, is used as a validation example and to describe some of the solutions available thus far