eDashA: Edge-based Dash Cam Video Analytics

While the real-time analysis of dash cam video is of great practical importance for improving road safety, commercial dash cams lack the resources necessary to perform such video analytics. It is impractical to use clouds for this due to high latency and high bandwidth consumption. In this paper, we present eDashA, the first edge-based system that demonstrates the potential of near real-time video analytics using a network of mobile devices, on the move. In particular, it simultaneously processes videos produced by two dash cams of different angles (outward facing and inward facing dash cams) with one or more mobile devices on the move. Further, we devise several optimization techniques and incorporated them into eDashA. These techniques are simultaneous download and analysis, scheduling, segmentation and early stopping. We have implemented eDashA as an Android app and evaluated it using two dash cams and several heterogeneous smartphones. Experiment results show the feasibility of real-time video analytics on the move.