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The exponential growth of advanced video surveillance technology, as well as the immeasurable amount of information that the field produces, poses a challenge: how can we keep up without getting overwhelmed? Systems developers, researchers, and researchers all ask themselves this question. Security technology is today being aided by another technology that has boomed in recent years – artificial intelligence.
We are witnessing the increasing integration of cloud-based data analysis in video surveillance technologies. With artificial intelligence, these technologies can communicate among different repositories of variable data, and they can analyze and plan real-time response strategies.
We can use artificial intelligence to provide the “brains” to our advanced technological systems, which can comprehend and analyze data from a wide range of sensors in great quantities with more accuracy than humans. The use of artificial intelligence in video analysis can help count, identify, and locate anomalous activities in the video to motivate various security applications, and even help fight crime.
Can all this data be turned into knowledge quickly, and how can it be done? The new Airship AI product seeks to answer this question. After examining various security challenges among data analysts, the use of artificial intelligence software has proven to be successful at processing and analyzing video data.
An artificial intelligence analysis is provided by the video processing module, according to securityinfowatch.com. As innovative technology expands and IoT devices are connected to the Internet, this trend is likely to continue. Following the collection of data, the next step is to analyze it. This is necessary since almost all organizations hold a large volume of dark data (about 80% of all data) that is stored remotely, which presents significant challenges when it comes to organization and placement, and is a challenge in itself prior to evaluation. This type of tool enables the analysis of the same dark data and their integration in real time within the data analysis system – so that information from many different sources and on a very large scale can be analyzed with the help of an artificial intelligence engine, which can identify patterns and extract intelligence from them.