AI In Video Surveillance Market Analysis
Segmentation Analysis:
In terms of segmentation, the global ai in video surveillance market is analyzed on the basis of Component, Deployment, Use Cases, End User
The AI in video surveillance market is segmented based on components, which include hardware, software, and services. The hardware segment includes cameras, sensors, and network equipment, while the software segment consists of video analytics and deep learning algorithms. The services segment comprises installation, maintenance, and consulting services. In 2020, the hardware segment held the largest market share due to the increasing adoption of advanced video surveillance systems.
Deployment:
The deployment segment of the AI in video surveillance market is divided into cloud-based and on-premise solutions. Cloud-based deployment offers scalability, flexibility, and cost-effectiveness, making it a popular choice among businesses. On the other hand, on-premise deployment provides better control, security, and data privacy. In 2020, the cloud-based deployment segment witnessed significant growth due to the rising trend of remote monitoring and management.
End Users:
The AI in video surveillance market is categorized based on end users, including commercial, residential, infrastructure, defense and military, public facilities, and industrial sectors. The commercial sector, encompassing retail, healthcare, and banking, is the largest end-user segment due to the need for security and surveillance solutions. The defense and military segment is expected to witness substantial growth due to the increasing adoption of AI-powered video surveillance systems for national security.
Use Cases:
The AI in video surveillance market is further segmented based on use cases, such as facial recognition, vehicle tracking, intrusion detection, and crowd management. Facial recognition technology is gaining traction in various industries, including retail and law enforcement, due to its advanced capabilities in identifying individuals. Vehicle tracking use case is popular in smart city projects and transportation management, enabling real-time monitoring and tracking of vehicles. Intrusion detection and crowd management are essential applications in security and public safety sectors, driving the demand for AI-powered video surveillance systems.
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