Nowadays, security agencies are focusing on investing in better surveillance products and are deploying more and more surveillance cameras for round-the-clock monitoring of large areas.. This has led to a rise in the amount of video data generated. This data is difficult for security professionals to monitor as they can watch only a limited amount of data. Also, they tend to lose their concentration in a short span of time, and suspicious movements on screen are frequently overlooked. AI in video analytics solutions play an important role in monitoring video data as they can analyze large amounts of video data quickly, thus improving the effectiveness and accuracy of surveillance.
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Also, the application of AI in video analytics solutions is not only limited to surveillance as it also helps in improving marketing effectiveness, store operation, building layout design, traffic patterns, and other activities. AI in video analytics involves three type of configurations: edge-based, server-based, and hybrid systems. In the edge-based configuration, cameras are provided with inbuilt analytics solutions for auto tracking and face detection. In the server-based configuration, the solution is deployed on the central server, thereby helping in complex processing. The hybrid system involves both the edge-based system and the server based-system, thereby substantially reducing the overload of network and servers.
The global AI in video analytics market is driven by a rise in demand among enterprises for actionable insights from video data and increase in investments by governments in emerging technologies and public infrastructure to enhance public safety. Some of the major restraints hampering the market include high amount of investments involved during the installation of legacy products and privacy issues associated with the solutions. Also growing deployments, investments and shift towards the IP based cameras is playing an important role in the AI in video analytics market.
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The global AI in video analytics market can be segmented based on component, integration, end-use industry, application, enterprise size, and region. In terms of component, the market can be categorized into software and services. The services segment can further be bifurcated into professional and managed services. Professional services include integration & implementation services, consulting, and training & support services. Based on integration, the global AI in video analytics market can be classified into edge-based solutions, server-based solutions, and hybrid solutions.
In terms of software, the global AI in video analytics market can be classified into on premise and cloud-based. Based on enterprise size, the market can be categorized into large enterprises and small and medium enterprises. In terms of application, the global AI in video analytics market can be categorized into home security, enterprise and commercial security, urban and public monitoring, transportation, airports and ports, maritime, and government institutions. Based on end-use industry, the global AI in video analytics market can be segmented into BFSI, media and entertainment, hospitality, military and defense, retail, transportation, government, and many more.