GEOVISUALIZATION FOR SMART VIDEO SURVEILLANCE

Nowadays with the emergence of smart cities and the creation of new sensors capable to connect to the network, it is not only possible to monitor the entire infrastructure of a city, including roads, bridges, rail/subways, airports, communications, water, power, but also to optimize its resources, plan its preventive maintenance and monitor security aspects while maximizing services for its citizens. In particular, the security aspect is one of the most important issues due to the need to ensure the safety of people. However, if we want to have a good security system, it is necessary to take into account the way that we are going to present the information. In order to show the amount of information generated by sensing devices in real time in an understandable way, several visualization techniques are proposed for both local (involves sensing devices in a separated way) and global visualization (involves sensing devices as a whole). Taking into consideration that the information is produced and transmitted from a geographic location, the integration of a Geographic Information System to manage and visualize the behavior of data becomes very relevant. With the purpose of facilitating the decision-making process in a security system, we have integrated the visualization techniques and the Geographic Information System to produce a smart security system, based on a cloud computing architecture, to show relevant information about a set of monitored areas with video cameras

A CLOUD-BASED ARCHITECTURE FOR SMART VIDEO SURVEILLANCE

Turning a city into a smart city has attracted considerable attention. A smart city can be seen as a city that uses digital technology not only to improve the quality of people’s life, but also, to have a positive impact in the environment and, at the same time, offer efficient and easy-to-use services. A fundamental aspect to be considered in a smart city is people’s safety and welfare, therefore, having a good security system becomes a necessity, because it allows us to detect and identify potential risk situations, and then take appropriate decisions to help people or even prevent criminal acts. In this paper we present an architecture for automated video surveillance based on the cloud computing schema capable of acquiring a video stream from a set of cameras connected to the network, process that information, detect, label and highlight security-relevant events automatically, store the information and provide situational awareness in order to minimize response time to take the appropriate action