![]() |
市場調查報告書
商品編碼
1677376
視訊監控市場中的人工智慧按組件、技術、功能模組、應用、最終用戶和部署模式分類 - 2025 年至 2030 年的全球預測AI in Video Surveillance Market by Component, Technology, Functionality Module, Application, End-User, Deployment Mode - Global Forecast 2025-2030 |
※ 本網頁內容可能與最新版本有所差異。詳細情況請與我們聯繫。
視訊監控市場中的人工智慧預計到 2024 年將達到 41.7 億美元,到 2025 年將達到 48.2 億美元,到 2030 年將達到 101 億美元,複合年成長率為 15.86%。
主要市場統計數據 | |
---|---|
基準年 2024 年 | 41.7億美元 |
預計 2025 年 | 48.2億美元 |
預測年份 2030 | 101億美元 |
複合年成長率(%) | 15.86% |
視訊監控中人工智慧的出現重新定義了安全解決方案的設計和部署方式。人工智慧演算法和電腦視覺的快速進步正在將傳統視訊監控轉變為智慧、預測和自適應的系統。這些技術進步不僅簡化了當前的安全業務,而且還實現了主動威脅偵測、高效的事件回應和更強的情境察覺。
本報告檢驗了人工智慧監控的發展,並描述了這些技術如何實現前所未有的精確度和效率。系統的穩健性、擴充性、自動化檢測和分析能力領先產業,為全面的風險管理策略奠定了基礎。隨著組織面臨日益複雜的安全形勢,了解這些趨勢對於做出明智的投資和策略決策至關重要。
在當今快速發展的環境中,人工智慧不斷為效能和可靠性設定新的基準。敦促相關人員(從技術開發人員到最終用戶)認知到創新在透過可擴展、變革性解決方案克服傳統監控挑戰方面所發揮的作用。透過增強的自動化和整合分析,視訊監控領域的人工智慧革命將確保公共和私營部門在定義安全社區方面保持領先一步。
重新定義視訊監控創新的轉型
近年來,在技術的快速進步和不斷變化的安全需求的推動下,視訊監控領域經歷了一段轉型期。人工智慧的融合重新定義了傳統實踐,成為大幅提高系統準確性和即時回應能力的關鍵。這種轉變的核心不僅是技術,更是監控如何預防和降低風險的策略性重新思考。
一個顯著的變化是資料分析和即時影像處理的融合。這種整合使系統能夠同時分析多個資料流,識別異常行為模式並及時發出警報。主要依賴手動監控的傳統視訊系統正在讓位給可以隨著時間的推移而學習並透過回饋迴路進行改進的自動化平台。因此,系統不斷發展,越來越擅長偵測未授權存取、可疑行為或環境中的細微變化等異常情況。
此外,邊緣運算的採用最大限度地減少了延遲並確保資料處理負載更靠近來源。這不僅提高了速度,而且透過減少對集中式資料中心的依賴也增強了隱私和安全性。向分散處理的轉變表明了該行業致力於平衡營運效率和增強的通訊協定。
這項改變得益於硬體製造商、軟體開發商和網路安全專家之間的密切合作。我們的整體方法培育了一個生態系統,其中技術突破可以迅速傳播並推動設定新行業標準的全球趨勢。透過調整策略以專注於敏捷性和彈性,視訊監控產業能夠更好地應對當前和新出現的威脅。
透過市場區隔的關鍵見解,制定更清晰的市場方法
深入了解市場後發現,細分對於了解視訊監控中人工智慧各個方面的細微需求和成長潛力至關重要。市場已按多個維度進行細分,以了解可用機會的廣度。一個關鍵的細分是基於明確分離的組件:硬體,服務和軟體。在硬體部分,進一步分析了門禁系統、攝影機、監視器和儲存設備,而服務方面則包括諮詢服務、安裝和維護。
另一個重要方面是基於技術的細分。這將包括深入探索一系列先進技術,包括電腦視覺、深度學習、邊緣運算、機器學習和自然語言處理。這些技術是提供智慧監控解決方案的支柱,對於提高系統效能和決策準確性至關重要。
功能性進一步細分了市場領域。我們已經對行為分析、運動偵測和物體偵測等功能模組進行了仔細的研究。這些特定的功能使系統能夠根據不同的操作場景自訂其方法,確保每個應用程式都發揮最佳效能。這種對功能的關注使得監控系統能夠適應各種環境,包括交通繁忙的都市區和安靜的工業環境。
基於應用程式的細分透過考慮行為分析、人群控制、工業監控和交通監控中的部署提供了進一步的見解。這種程度的細分對於理解不同環境下的營運效率至關重要。最終用戶細分顯示市場滿足了廣泛的領域,包括商業設施、政府機構、國防安全保障機構、工業設施和住宅環境。在每種情況下,我們都提供客製化的監控解決方案來應對與該行業相關的獨特挑戰和監管要求。
此外,我們研究部署類型以深入了解雲端、混合和內部部署配置。這種細分反映了對可擴展、經濟高效的部署的偏好,這對於組織適應不斷變化的安全需求至關重要。綜合起來,這些細分層面呈現出一個複雜但高度組織化的市場格局,每個維度都為人工智慧主導的視訊監控的開發、商業化和營運成功提供了關鍵見解。
The AI in Video Surveillance Market was valued at USD 4.17 billion in 2024 and is projected to grow to USD 4.82 billion in 2025, with a CAGR of 15.86%, reaching USD 10.10 billion by 2030.
KEY MARKET STATISTICS | |
---|---|
Base Year [2024] | USD 4.17 billion |
Estimated Year [2025] | USD 4.82 billion |
Forecast Year [2030] | USD 10.10 billion |
CAGR (%) | 15.86% |
The emergence of artificial intelligence in video surveillance has redefined the way security solutions are designed and deployed. Rapid advancements in AI algorithms and computer vision have transformed conventional video monitoring into smart, predictive, and highly adaptive systems. These innovations are not only streamlining current security operations but are also enabling proactive threat detection, efficient incident response, and a higher level of situational awareness.
This report examines the evolution of AI-powered surveillance and captures how these technologies have introduced unprecedented levels of accuracy and efficiency. System robustness, scalability, and automation in detection and analysis have collectively driven the industry forward, laying the foundation for comprehensive risk management strategies. As organizations navigate an increasingly complex security landscape, understanding these trends is critical for making informed investment and strategic decisions.
In today's rapidly evolving environment, AI continues to set new benchmarks for performance and reliability. Stakeholders-from technology developers to end-users-are encouraged to recognize the role of innovation in overcoming traditional surveillance challenges with scalable and transformative solutions. Through enhanced automation and integrated analytics, the AI revolution in video surveillance ensures that both public and private sectors can maintain a step ahead in defining secure communities.
Transformative Shifts Redefining Video Surveillance Innovation
In recent years, the landscape of video surveillance has experienced transformative shifts driven by rapid technological advancements and evolving security needs. AI integration has become a linchpin that is redefining traditional practices, providing a quantum leap in system accuracy and real-time responsiveness. The core of these transformative shifts is not only technological but also a strategic rethinking of how surveillance can preempt and mitigate risks.
One of the prominent shifts in the landscape is the convergence of data analytics with real-time video processing. This integration enables systems to analyze multiple data streams simultaneously, recognize unusual behavioral patterns, and issue timely alerts. Traditional video systems, which relied primarily on manual monitoring, have given way to automated platforms that learn over time and improve through feedback loops. The result is a system that continuously evolves, becoming more adept at detecting anomalies such as unauthorized access, suspicious behaviors, or even subtle environmental changes.
Moreover, the adoption of edge computing has minimized latency, ensuring that the heavy lifting of data processing happens near the source. This not only enhances speed but also augments privacy and security by reducing the reliance on centralized data hubs. The shift towards decentralized processing showcases the industry's commitment to balancing operational efficiency with enhanced security protocols.
Enabling these changes are robust collaborations between hardware manufacturers, software developers, and cybersecurity experts. The holistic approach fosters an ecosystem where technological breakthroughs are rapidly disseminated, driving global trends that set new industry standards. By reorienting strategies around agility and resilience, the video surveillance industry has become better equipped to handle both current and emerging threats.
Key Segmentation Insights for a Nuanced Market Approach
A deep dive into the market reveals that segmentation is pivotal for understanding the nuanced demands and growth potential across various facets of AI in video surveillance. The market has been segmented on multiple dimensions to capture the breadth of opportunities available. One vital segmentation is based on the component with a clear division into hardware, service, and software. Within the hardware segment, there is further analysis across access control systems, cameras, monitors, and storage devices; meanwhile, the service component encompasses consulting services, installation, and maintenance; the software side is analyzed via three key aspects: AI in edge computing, video analytics, and video management software solutions.
Another important aspect is the segmentation based on technology. Here, a detailed examination is undertaken across various advanced methodologies including computer vision, deep learning, edge computing, machine learning, and natural language processing. These technologies serve as the backbone for delivering smart surveillance solutions and have been pivotal in elevating system performance and decision accuracy.
Functionality further refines the market segmentation. The functionality module is carefully studied across behavioral analysis, motion detection, and object detection. These specific capabilities allow systems to tailor their approach to different operational scenarios, ensuring that each application delivers optimal performance. The focus on functionality ensures that surveillance systems can adapt to varying environments, whether high-traffic urban areas or quiet industrial settings.
Application-based segmentation offers additional insights by examining the deployment in behavioral analysis, crowd management, industrial monitoring, and traffic monitoring. This level of segmentation is crucial to understanding operational effectiveness in diverse contexts. End-user segmentation indicates that the market caters to a broad range of sectors, including commercial establishments, government and homeland security agencies, industrial setups, and residential environments. In each case, customized surveillance solutions are offered to address the unique challenges and regulatory requirements relevant to the sector.
Moreover, the deployment mode is studied to extract insights across cloud, hybrid, and on-premise configurations. This segmentation reflects the preference for scalable and cost-effective deployments, which are essential for organizations's adapting to evolving security needs. Collectively, these layers of segmentation illustrate a complex yet highly organized market landscape, where each dimension brings critical insights into the development, commercialization, and operational success of AI-driven video surveillance.
Based on Component, market is studied across Hardware, Service, and Software. The Hardware is further studied across Access Control Systems, Cameras, Monitors, and Storage Devices. The Service is further studied across Consulting Services, Installation, and Maintenance. The Software is further studied across AI in Edge Computing, Video Analytics, and Video Management Software (VMS).
Based on Technology, market is studied across Computer Vision, Deep Learning, Edge Computing, Machine Learning, and Natural Language Processing.
Based on Functionality Module, market is studied across Behavioral Analysis, Motion Detection, and Object Detection.
Based on Application, market is studied across Behavioral Analysis, Crowd Management, Industrial Monitoring, and Traffic Monitoring.
Based on End-User, market is studied across Commercial, Government & Homeland Security, Industrial, and Residential.
Based on Deployment Mode, market is studied across Cloud, Hybrid, and On-Premise.
Key Regional Insights Underscoring Global Market Dynamics
The market for AI-powered video surveillance exhibits notable regional diversity, which is crucial to understanding its global dynamics. In the Americas, technological advancements are being rapidly adopted to enhance public and private security infrastructures, driven by a focus on safety and regulatory compliance. The region is characterized by strong investments in technology innovation and partnerships that drive both the emergence and maturation of AI in the security domain.
Across Europe, the Middle East, and Africa, the markets have experienced accelerated growth facilitated by progressive regulatory frameworks and heightened security concerns. These regions are witnessing a dynamic shift as governments and corporations strive for an advanced surveillance setup that integrates real-time analytics and autonomous operation in high-risk environments such as urban centers and critical infrastructure networks.
In Asia-Pacific, the growth trajectory has been particularly impressive, fueled by an already robust technology manufacturing base and a growing appetite for smart city initiatives. Increasing urbanization and heightened awareness of security have led to significant investments in modern surveillance systems. This region continues to evolve, with innovations increasingly aimed at harnessing the full potential of artificial intelligence to deliver context-aware, adaptive security solutions.
Each of these regions contributes uniquely to the overall market, with distinct regulatory requirements, economic dynamics, and cultural influences shaping the adoption and innovation of AI in video surveillance. The interplay between regional trends establishes a global marketplace where localized challenges meet universal technological breakthroughs.
Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.
Key Company Insights Highlighting Industry Leaders and Innovators
Significant players in the AI-powered video surveillance market are driving the transformation with innovative products and strategic collaborations. Notable companies include Agent Video Intelligence Ltd. and AllGoVision Technologies Pvt Ltd, which are making considerable strides in enhancing video analytics through AI-based solutions. Companies such as Avigilon Corporation by Motorola Solutions, Inc. and Axis Communications AB are recognized for their robust hardware innovations and comprehensive surveillance systems that consistently set industry benchmarks.
Other industry leaders-like Calipsa Ltd., Canon Inc., and Cognitec Systems GmbH-are deeply engaged in refining image processing and facial recognition technologies. Dahua Technology Co., Ltd. and Digital Barriers plc are known for their cutting-edge video processing equipment, while FLIR Systems, Inc. and Genetec Inc. continue to influence the market with state-of-the-art thermal imaging and integrated security platforms. Meanwhile, Gorilla Technology Group Inc. and Hangzhou Hikvision Digital Technology Co., Ltd. have made substantial investments into developing scalable and reliable systems that combine traditional surveillance with modern analytics capabilities.
Established names including Hanwha Group, Honeywell International Inc., Huawei Technologies Co., Ltd., and IC Realtime LLC have bolstered their market presence through strategic innovations and tailored solutions to emerging security challenges. Companies like Infinova Corporation and Intellivision Technologies Corp. have risen as notable competitors in segments like cloud integration and smart deployment. MOBOTIX AG and NEC Corporation have delivered high-performance surveillance solutions that focus on both ease of implementation and long-term reliability.
In addition, Panasonic Corporation and Robert Bosch GmbH continue to be at the forefront of integrating advanced AI functionalities within their products. SenseTime Group Limited, Sony Corporation, Turing AI, Verint Systems Inc., Vivint, Inc., and VIVOTEK Inc. further diversify the landscape with their varied specialties and comprehensive portfolio of products. These companies collectively drive the market by blending innovative research with practical implementations, ensuring that the industry remains adaptive, forward-looking, and resilient in the face of evolving security challenges.
The report delves into recent significant developments in the AI in Video Surveillance Market, highlighting leading vendors and their innovative profiles. These include Agent Video Intelligence Ltd., AllGoVision Technologies Pvt Ltd, Avigilon Corporation by Motorola Solutions, Inc., Axis Communications AB, Calipsa Ltd., Canon Inc., Cognitec Systems GmbH, Dahua Technology Co., Ltd., Digital Barriers plc, FLIR Systems, Inc., Genetec Inc., Gorilla Technology Group Inc., Hangzhou Hikvision Digital Technology Co., Ltd., Hanwha Group, Honeywell International Inc., Huawei Technologies Co., Ltd., IC Realtime LLC, Infinova Corporation, Intellivision Technologies Corp., MOBOTIX AG, NEC Corporation, Panasonic Corporation, Robert Bosch GmbH, SenseTime Group Limited, Sony Corporation, Turing AI, Verint Systems Inc., Vivint, Inc., and VIVOTEK Inc.. Actionable Recommendations for Industry Leaders Aiming for Tomorrow's Security Solutions
For decision-makers and innovators in the AI in video surveillance space, a few strategic recommendations can pave the way for sustained excellence and competitive advantage. First, invest robustly in research and development to enhance core algorithms behind AI-based analytics. Emphasis on areas like deep learning and computer vision will not only improve detection accuracy but also increase system adaptability. Coupled with edge computing to minimize latency in real-time analysis, this focus will create a full-spectrum solution capable of responding decisively to numerous security threats.
Adopting a modular approach towards system design is equally critical. A modular architecture allows for seamless integration of new technologies while safeguarding existing investments. Embracing cloud, hybrid, or on-premise deployment modes based on operational needs can enhance scalability and offer tailored solutions for diverse end-user requirements. Industry players should ensure that system updates and continuous training of AI models occur regularly, enabling systems to remain effective in the face of evolving threat patterns.
Moreover, collaboration is paramount. Form strategic alliances with technology partners and industry consortia to pool knowledge, share best practices, and foster innovation. A concerted focus on interoperability between systems and devices will ensure that security solutions can function synergistically across diverse platforms. This approach is essential when facing next-generation challenges that require a unified, cross-functional response.
In parallel, market players are encouraged to invest in customer education and structured support systems. Enhancing user understanding of AI capabilities, deploying intuitive interfaces, and delivering dedicated training programs can significantly improve user adoption and overall satisfaction, hence driving both retention and expansion of market share.
Embracing a data-centric approach is another critical recommendation. The integration of vast datasets with advanced analytics can uncover insights that drive predictive assessments and dynamic responses. Regular data audits and adherence to regulatory frameworks will further build trust among stakeholders and end-users, laying the groundwork for sustained success in an increasingly competitive market.
Finally, agile decision-making coupled with strategic long-term planning is essential. The ability to rapidly adapt in response to cybersecurity challenges and market shifts will define the leaders in this field. With a clear roadmap for innovation, industry leaders can secure a future where intelligent video surveillance not only meets but exceeds modern security expectations.
Conclusion: Shaping a Resilient and Intelligent Security Tomorrow
In conclusion, the evolution of AI in video surveillance is a testament to the power of technology in redefining security paradigms. The comprehensive analysis presented here underscores that the convergence of innovative software, robust hardware infrastructures, and intelligent service models is reshaping the global surveillance landscape. By integrating transformative technologies like deep learning, computer vision, and edge computing, the industry unlocks new dimensions of operational efficiency and proactive threat detection.
This in-depth exploration of segmentation-from component and technology to functionality, application, end-user, and deployment mode-reveals that the market is both complex and highly adaptive. The insights into regional trends highlight that while the Americas, Europe, the Middle East & Africa, and Asia-Pacific each have unique market dynamics, the global challenge remains consistent: to implement smarter, more reliable, and scalable surveillance solutions.
Additionally, the review of key companies affirms that a competitive and innovative marketplace is thriving. Companies across the spectrum are setting benchmarks and driving progress through strategic investments and collaborations. Their contributions are critical in the evolving landscape where smart surveillance solutions become increasingly nuanced and indispensable.
Looking forward, the recommendations provided offer a clear pathway for maintaining momentum in research, system optimization, and stakeholder collaboration. With an emphasis on interoperability, continuous innovation, and agile response strategies, industry players can navigate the transforming security landscape with confidence. Ultimately, the intelligent integration of AI in video surveillance is not merely about technology deployment-it is about forging resilient, adaptive, and future-ready security ecosystems.