查看文章

Since the popularity of city monitoring systems has increased, surveillance videos have become more common. However, due to the massive increment of social event needs after lifting the coronavirus pandemic lockdown, the pressure of handling anomalies on government departments is growing with each passing day. In addition, surveillance cameras cannot record every corner of our city. There are still blind areas such as indoor environments and remote regions. Therefore, this paper introduces and develops an comprehensive system for video anomaly detection in smart city management, which is based on mobile phones, to enlarge the coverage of the current surveillance system. This system can capture and transmit abnormal videos. In addition, a deep learning method (VGG16) is implemented in the system to do video anomaly detection.