Integrating computer vision technique to support Tsunami Early Warning System

Abstract

Tsunami Early Warning System (TEWS) is built for minimizing impact of tsunami disaster. The generic system consists of two components: the first is sensor network for tsunami detection and the second is interconnected communication infrastructure for evacuation notification. In this paper, additional sensor based on computer vision technology is proposed for observing ocean and wave condition. This technology, combined with other sensors technology, will increase the effectiveness of the TEWS. In more detail, image frames captured from surveillance video camera are analyzed and interpreted semantically using imaging analysis techniques. If the system considered a tsunami-like situation based on image, it will transmit a warning signal to a centrally integrated system. The developed application adopted DeWa, a multiaspect framework for object detection that has been previously implemented. Although this camera-based TEWS has not been implemented in realistic situation, it has been successfully tested using extracted image from a tsunami-like wave video.