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AI In Video Surveillance Market Size
- Report ID: GMI8110
- Published Date: Feb 2024
- Report Format: PDF
AI in Video Surveillance Market Size
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 |
|---|---|
| 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.
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AI In Video Surveillance Market Scope
