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Danger Detection based on Fusion Analysis of Multimodal Data from a Smartphone and Smartwatch

In recent days, technologies for detecting dangerous situations have been developed to support public safety. This paper proposes a danger detection technology based on fusion analysis of a smartphone's and smartwatch's multimodal data that include data from accelerometer and gyroscope sensors. The proposed danger detection technology enables fast and accurate danger detection by recognizing movements of an arm based on analysis of sensor data from a smartwatch and by recognizing movements of a leg based on analysis of sensor data from a smartphone. The fast and accurate danger detection of the proposed technology will help to enable fast and appropriate responses to dangers.