Ensuring energy efficient coverage for participatory sensing in urban streets

Participatory sensing is an approach to data collection for monitoring different scenarios with the help of smartphone sensors. As more and more sensors are being added to smartphones, monitoring a wide range of scenarios has become possible with participatory sensing. An important issue in such participatory sensing application is the coverage of the collected data that reflects how well the data samples represent the monitored area. In the traditional approach, the data collection process is assisted by a server that knows the location of the participating devices and selects the necessary ones to cover the monitored area efficiently. However, for battery powered devices like smartphones, sending frequent location updates to the server is quite energy expensive. In this paper, we propose a framework, called STREET, for data collection from urban streets that can address the coverage problem where a participating mobile device is not required to send location updates to the server. In particular, our framework can collect data samples to ensure the requirements of a specified partial coverage, full coverage and k-coverage. STREET is assisted by a simple localization scheme for mobile devices that minimizes the usage of location sensor (e.g., GPS) while participating in the data collection process. Experiments from simulation studies show that our approach can significantly reduce energy consumption of the participating mobile devices.