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市場調査レポート
商品コード
1677376
ビデオ監視におけるAI市場:コンポーネント、テクノロジー、機能モジュール、アプリケーション、エンドユーザー、展開モード別-2025-2030年の世界予測AI in Video Surveillance Market by Component, Technology, Functionality Module, Application, End-User, Deployment Mode - Global Forecast 2025-2030 |
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カスタマイズ可能
適宜更新あり
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ビデオ監視におけるAI市場:コンポーネント、テクノロジー、機能モジュール、アプリケーション、エンドユーザー、展開モード別-2025-2030年の世界予測 |
出版日: 2025年03月09日
発行: 360iResearch
ページ情報: 英文 185 Pages
納期: 即日から翌営業日
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ビデオ監視におけるAI市場は、2024年には41億7,000万米ドルとなり、2025年には48億2,000万米ドル、CAGR15.86%で成長し、2030年には101億米ドルに達すると予測されています。
主な市場の統計 | |
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基準年 2024 | 41億7,000万米ドル |
推定年 2025 | 48億2,000万米ドル |
予測年 2030 | 101億米ドル |
CAGR(%) | 15.86% |
ビデオ監視における人工知能の出現は、セキュリティ・ソリューションの設計と導入方法を再定義しました。AIアルゴリズムとコンピュータ・ビジョンの急速な進歩は、従来のビデオ監視をスマートで予測的な、適応性の高いシステムへと変貌させました。こうした技術革新は、現在のセキュリティ業務を合理化するだけでなく、プロアクティブな脅威検知、効率的なインシデント対応、より高度な状況認識を可能にしています。
本レポートでは、AIを活用した監視の進化を検証し、これらの技術がどのように前例のないレベルの精度と効率を導入したかを捉えています。システムの堅牢性、拡張性、検知と分析の自動化が業界を牽引し、包括的なリスク管理戦略の基盤を築いた。組織がますます複雑化するセキュリティ情勢を乗り切るには、これらの動向を理解することが、十分な情報に基づいた投資や戦略的決定を行う上で極めて重要です。
急速に進化する今日の環境において、AIは性能と信頼性の新たなベンチマークを設定し続けています。技術開発者からエンドユーザーまでの利害関係者は、スケーラブルで変革的なソリューションによって従来の監視の課題を克服する上で、イノベーションが果たす役割を認識することが求められています。強化された自動化と統合された分析を通じて、ビデオ監視におけるAI革命は、公共部門と民間部門の両方が安全なコミュニティを定義する上で一歩先を維持できることを保証します。
ビデオ監視イノベーションを再定義する変革的シフト
近年、ビデオ監視の情勢は、急速な技術進歩と進化するセキュリティ・ニーズに後押しされ、変革の時期を迎えています。AIの統合は、従来の慣行を再定義し、システムの精度とリアルタイムの応答性を飛躍的に向上させる要となっています。こうした変革的シフトの核心は、技術的なものだけでなく、監視がどのようにリスクを先取りし、軽減できるかを戦略的に再考することでもあります。
情勢における顕著なシフトの一つは、データ分析とリアルタイム映像処理の融合です。この統合により、システムは複数のデータストリームを同時に分析し、異常な行動パターンを認識し、タイムリーな警告を発することができます。主に手動監視に頼っていた従来のビデオシステムは、時間の経過とともに学習し、フィードバックループを通じて改善する自動化プラットフォームに取って代わられました。その結果、システムは継続的に進化し、不正アクセスや不審な行動、あるいは微妙な環境の変化といった異常の検知に習熟するようになりました。
さらに、エッジコンピューティングの採用により、待ち時間が最小限に抑えられ、データ処理の負荷が発生源の近くで確実に行われるようになりました。これはスピードを向上させるだけでなく、集中型データハブへの依存を減らすことで、プライバシーとセキュリティを強化します。分散型処理へのシフトは、運用効率と強化されたセキュリティ・プロトコルのバランスを取るという業界のコミットメントを示すものです。
こうした変化を可能にしているのは、ハードウェア・メーカー、ソフトウェア開発者、サイバーセキュリティの専門家による強固な協力体制です。全体論的なアプローチは、技術的なブレークスルーが迅速に普及し、新しい業界標準を設定する世界の動向を推進するエコシステムを育成します。俊敏性と回復力を中心に戦略を方向転換することで、ビデオ監視業界は、現在の脅威と新たな脅威の両方に対処できる体制を整えました。
市場セグメンテーションの重要な洞察による、より明確な市場アプローチ
市場を深く掘り下げると、ビデオ監視におけるAIのさまざまな側面における微妙な需要と成長の可能性を理解するには、セグメンテーションが極めて重要であることがわかる。市場は、利用可能な機会の幅を把握するために、複数の次元でセグメンテーションされています。重要なセグメンテーションの1つは、ハードウェア、サービス、ソフトウェアに明確に区分されたコンポーネントに基づいています。ハードウェア・セグメントでは、入退室管理システム、カメラ、モニター、ストレージ・デバイスがさらに分析され、サービス・コンポーネントでは、コンサルティング・サービス、設置、メンテナンスが含まれる:ソフトウェア面では、エッジコンピューティングにおけるAI、ビデオ分析、ビデオ管理ソフトウェア・ソリューションの3つの重要な側面から分析されます。
もう一つの重要な側面は、技術に基づくセグメンテーションです。ここでは、コンピュータビジョン、ディープラーニング、エッジコンピューティング、機械学習、自然言語処理など、さまざまな先進的手法の詳細な調査が行われます。これらの技術は、スマートな監視ソリューションを提供するためのバックボーンとして機能し、システム性能と判断精度を高める上で極めて重要です。
機能性は市場セグメンテーションをさらに細分化します。機能性モジュールは、行動分析、動体検知、物体検知にわたって慎重に調査されています。これらの特定の機能により、システムはさまざまな運用シナリオに合わせてアプローチを調整することができ、各アプリケーションが最適なパフォーマンスを発揮できるようになります。機能性を重視することで、監視システムは、交通量の多い都市部や静かな産業環境など、さまざまな環境に適応することができます。
アプリケーションベースのセグメンテーションは、行動分析、群衆管理、産業モニタリング、交通モニタリングにおける展開を検討することで、さらなる洞察を提供します。このレベルのセグメンテーションは、多様な文脈における運用の有効性を理解する上で極めて重要です。エンドユーザーセグメンテーションでは、この市場が商業施設、政府機関、国土安全保障機関、産業施設、住宅環境など、幅広い分野に対応していることが示されています。いずれの場合も、その分野に関連する独自の課題や規制要件に対処するために、カスタマイズされた監視ソリューションが提供されています。
さらに、クラウド、ハイブリッド、オンプレミスの各構成に関する洞察を得るため、導入形態も調査しています。このセグメンテーションは、組織が進化するセキュリティ・ニーズに適応するために不可欠な、スケーラブルでコスト効率に優れた展開を好む傾向を反映しています。これらのセグメンテーションのレイヤーを総合すると、複雑でありながら高度に組織化された市場環境が示され、各次元がAI主導のビデオ監視の開発、商業化、運用の成功に重要な洞察をもたらしています。
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 | |
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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.