Heterogeneous data based danger detection for public safety
Hyunho Park, Eunjung Kwon, Eui‐Suk Jung, Hyunwoo Lee, Yong-Tae Lee · 2018
In recent days, public safety service attracts attentions because of increasing crime rates. In this paper, heterogeneous data based danger detection (HDDD) mechanism is proposed for reducing crime rates. The HDDD mechanism is a mechanism for detecting dangerous situations (e.g., homicide and violence) based on heterogeneous data that are data gathered from multiple devices such as closed circuit television (CCTV) cameras, smartphones, and wearable devices. The HDDD enables immediate detection of dangerous situations and then reduces crime rates by responding to the dangerous situations.