The video shows a sample of the output of the KPI query executed on the dataset specified in the table below.
With the proliferation of Closed-circuit Television (CCTV) systems for public safety and their decreasing cost, real-time monitoring of the video feeds, has become impossible to manually control all this data on the fly. In the Dublin city alone, there are approximately 200 CCTV cameras for public safety, and there is no possibility to manually monitor all these videos simultaneously. Therefore, our goal is to provide a method to select the best cameras to monitor in real-time the city “behaviour”. In order to do that, we need to query real-time stream information from the city and perform this selection of cameras placed into the most interesting areas of the city. We identify the most interesting areas by considering the biggest changes that are happening into the city, starting from a regular situation.
In this scenario, we need to consider both data stream and static information, to have a complete description of the studied real-time environment, and also to give the correct attention to every single event that could happen into the city. In order to achieve this goal, we can specify a continuous query in DubExtensions and its relative translation into a complex SPL streaming application, executable on InfoSphere Streams.
In the table below one can see and example of the dataset that have been used in the simulation.
