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AI in Video Surveillance Market size was valued at USD 5.5 billion in 2023 and is estimated to register a CAGR of over 15.5% between 2024 and 2032. With increasing security threats globally, there is a growing demand for advanced surveillance systems that can effectively monitor and protect public and private spaces. AI-powered video surveillance offers enhanced capabilities such as real-time threat detection, facial recognition, and behavior analysis, making it a preferred choice for security applications.
The rapid advancements in artificial intelligence and deep learning technologies have enabled the development of sophisticated video analytics algorithms. These algorithms can automatically detect and classify objects, people, and activities in video feeds with high accuracy, improving the overall effectiveness of surveillance systems. AI-driven video surveillance systems can automate many tasks that would otherwise require human intervention, leading to cost savings for organizations.
Report Attribute | Details |
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Base Year: | 2023 |
AI In Video Surveillance Market Size in 2023: | USD 5.5 Billion |
Forecast Period: | 2024 - 2032 |
Forecast Period 2024 - 2032 CAGR: | 15.5% |
2032 Value Projection: | USD 19.5 Billion |
Historical Data for: | 2018 - 2023 |
No. of Pages: | 250 |
Tables, Charts & Figures: | 296 |
Segments covered: | Component, deployment, use cases, end user, and region |
Growth Drivers: |
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Pitfalls & Challenges: |
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Additionally, these systems can analyze vast amounts of video data in real-time, enabling proactive responses to security threats and reducing the need for manual monitoring. Additionally, In May 2023, Motorola Solutions, the parent company of Avigilion, released the V700 body camera a mobile broadband-enabled camera, to ensure a clear, accurate account of events, the V700's precision high-definition sensor adjusts to low lighting like a human eye.
AI algorithms used in video surveillance systems are susceptible to biases, both in their development and deployment. Biases can result from various factors, including biased training data, flawed algorithms, or improper calibration. These biases can lead to inaccurate or discriminatory outcomes, such as misidentifying individuals or misclassifying activities. Addressing algorithmic bias and ensuring the accuracy and fairness of AI-powered video surveillance systems is crucial to maintain trust, credibility, and effectiveness in security applications.
A notable trend in the AI in video surveillance industry is the increasing integration of edge computing capabilities. Edge computing involves processing data closer to its source rather than relying on centralized servers. In the context of video surveillance, this means deploying AI algorithms directly on cameras or edge devices, enabling real-time analysis of video feeds. This trend is driven by the need for faster response times, reduced bandwidth usage, and improved privacy by processing sensitive data locally.
Additionally, edge computing facilitates distributed intelligence, allowing surveillance systems to operate effectively even in environments with limited connectivity or latency constraints. As edge computing technologies continue to mature, we can expect further advancements in AI-powered video surveillance solutions, enhancing their scalability, efficiency, and effectiveness.
Another significant trend is the adoption of hybrid cloud architectures in AI in video surveillance market. Hybrid cloud solutions combine on-premises infrastructure with cloud-based services, offering a balance between data locality, scalability, and cost-effectiveness. In the context of video surveillance, hybrid cloud architectures allow organizations to store and analyze video data both locally and, in the cloud, depending on factors such as storage requirements, processing capabilities, and regulatory compliance. This trend enables seamless integration with existing surveillance infrastructure while leveraging the scalability and computational power of the cloud for tasks such as long-term storage, analytics, and machine learning.
By embracing hybrid cloud solutions, organizations can optimize their video surveillance operations, enhance situational awareness, and adapt to evolving security needs effectively. For Insttance, In Sep-2022: Hikvision made enhancements to its Pro series PTZ cameras with the addition of ColorVu technology. The integration of ColorVu in Hikvision's new Pro series cameras would deliver consistent image brightness and complete color imaging as the camera zooms in and out. Furthermore, the enhancement makes sure crystal-clear details and vivid color for distant objects at all times and in all situations.
Based on the use cases, the gun detection segment is poised to witness over 15% CAGR from 2024 to 2032. Gun detection technology has emerged as a critical component in the market, leveraging semantic networks to enhance its capabilities. Semantic networks, a form of artificial intelligence, enable systems to understand the relationships between different entities within a given context, facilitating more accurate and contextualized analysis of video data.
Furthermore, semantic networks enable interoperability and integration with other AI-based modules within the surveillance ecosystem. For example, gun detection algorithms can communicate with facial recognition systems to identify individuals carrying firearms or with object tracking modules to monitor the movement of weapons within a monitored area. This holistic approach enhances the overall effectiveness of video surveillance systems in detecting and responding to potential security threats, making semantic networks a valuable tool in the evolving landscape of AI-powered video surveillance.
Based on the end user, the commercial segment held over 30% of the AI in video surveillance market share in 2023. In the commercial segment, AI-powered video surveillance systems offer various benefits tailored to the specific needs of businesses. These systems can detect and deter theft, vandalism, and unauthorized access in retail environments, thereby reducing losses and enhancing safety for employees and customers.
Additionally, AI algorithms can analyze customer behavior and preferences, providing valuable insights for marketing, merchandising, and operational decision-making. Furthermore, commercial establishments leverage AI-driven video analytics to improve operational efficiency and customer service. For instance, real-time monitoring of foot traffic can help optimize staffing levels and queue management, while video analytics can identify maintenance issues or safety hazards before they escalate.
North America AI in video surveillance market accounted for 25% of the revenue share in 2023. With rising security threats and incidents, there is a growing demand for advanced surveillance solutions in North America. AI-powered video surveillance offers enhanced capabilities such as real-time threat detection, facial recognition, and behavior analysis, making it a preferred choice for security applications in the region.
North America is home to many leading technology companies and research institutions driving innovations in artificial intelligence and video analytics. These advancements enable the development of sophisticated AI algorithms that can automatically detect and classify objects, people, and activities in video feeds with high accuracy, further fueling the adoption of AI in video surveillance.
Honeywell International holds a significant market share in the AI in video surveillance industry. Offering a range of innovative solutions tailored to meet the security needs of diverse industries. Honeywell's video surveillance offerings combine advanced AI technologies with robust hardware and software solutions to provide comprehensive security and surveillance.
Major players, such as Avigilon Hikvision Dahua Technology Axis Communications Hanwha Techwin Bosch Security Systems Honeywell., are constantly implementing strategic measures including geographical expansion, acquisitions, mergers, collaborations, partnerships, and product or service launches.
Major companies operating in the AI in video surveillance industry are:
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Market, By Deployment
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The above information has been provided for the following regions and countries: