SenseFleet: A smartphone-based driver profiling platform

Smartphones embed increasingly complex sensors that can be used for a wide range of connected applications. Their growing market penetration provides the opportunity to develop novel distributed sensing platforms that will constitute the foundation for emerging commercial applications. In this work we present SenseFleet, a smartphone-based driver profiling platform. The concept behind SenseFleet is to analyze the output of smartphone sensors while driving in order to identify risky maneuvers (e.g. acceleration, braking and cornering) and provide a score reflecting the overall performance of the driver. A Fuzzy Inference System (FIS) is used to detect events independently from the car and mobile phone used. A smartphone application has been developed to demonstrate the feasibility of our approach. In this demo we show interactive results of a test campaign performed in Luxembourg. The results show that the SenseFleet platform is able to identify risky driving maneuvers and provide representative scores. A second benefit of SenseFleet is that for a large number of participants, it will allow to monitor the road network and identify dangerous locations, i.e. locations that have a high event density.