Detecting high-risk scenarios before they are upgraded is one of the core motivations for developing artificial intelligence (AI) for secure applications. With AI, operators deploying monitoring solutions can go beyond simple monitoring scope, so as to use each video frame and available data to identify threats and notify emergency response. Artificial intelligence is still an emerging technology. However, the benefits of its functions are designed to minimize risk, prevent crime and save lives.

In the past, video recordings were saved for a short time before they were overwritten. Today, various parts of artificial intelligence (such as video analysis, machine learning and deep learning) use a large amount of data generated by the Internet of things ecosystem to distinguish meaningful patterns in the data set, and then turn them into insights, so as to strengthen the world of crime deterrence strategies everywhere. This technology looks at data from a holistic perspective, connecting various data points to describe what is happening, so as to quickly identify high-risk situations before problems escalate.

According to the data of London based brandessence market research, the overall global real-time video analysis market is estimated to be $3.2 billion in 2018, and is expected to grow to $9billion by 2023. AI is no longer just a buzzword or trend. It has become an integral part of our growing data field.

Contrary to popular belief, AI is not the exclusive property of development giants such as Google, Amazon or apple. They mainly use AI to optimize voice and image recognition and content management. Growing physical security issues have also been a catalyst for the steady growth of AI.

AI based video analytics can also improve efficiency and provide enterprises with non security related insights. For example, in the retail market, store owners who use surveillance cameras with analysis function can find shoplifters and remind security personnel to intervene in real time. In store analysis can also measure hot spots, visitor flow, stay time and product display activities. Smart cities also use intelligent sensor networks to capture data, organize system response to events when events occur, and improve traffic flow and other processes.

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