Hideyuki Tokuda

Evaluating the spatio-temporal coverage of automotive sensing for smart cities

Automotive sensing is a novel and appealing sensing technology in which sensors are installed into vehicles to utilize vehicles mobility to conduct urban sensing in smart cities. The coverage performance is a major metric to characterizing the quality-of-service of sensing systems. Despite of the coverage metrics studied in static sensor networks that consist of only spatial dimension, the lack of a proper metric to characterizing the spatio-temporal coverage of automotive sensing systems is stunting the research, development and commercialization of such mobile sensing systems. To address this issue, we propose, for the first time to the best of our knowledge, a spatio-temporal coverage metric for automotive sensing. The proposed metric characterizes the coverage in both spatial and temporal dimensions in order to provide a guideline for smart cities application developers to evaluate the quality-of-service that can be expected from an automotive sensing system. Evaluation based on an automotive sensing system implemented in Fujisawa City, Japan is conducted to demonstrate the usage of this metric in a realistic scenario.