AI Video Search in Modern Surveillance

NGÀY ĐĂNG 29/12/2025

Võ Hồng Tiên

In a modern Security Operations Center (SOC), incident response speed and video investigation accuracy are crucial to operational efficiency. However, with large-scale camera systems, manually reviewing hours of video from multiple cameras and timestamps remains a common challenge for security teams.

Intelligent Search VMS, also known as AI video search, was developed to address this problem by applying artificial intelligence to automate the forensic video investigation process, helping SOCs shorten investigation time from hours to just minutes.

What is Intelligent Search VMS?

Intelligent Search VMS is an intelligent search feature in a Video Management System (VMS) that applies AI (artificial intelligence) and advanced video analysis to help operators search, trace, and investigate video events faster and more accurately than traditional manual review methods.

How does Intelligent Search work?

In a VMS (Vehicle Monitoring System) integrated with Intelligent Search, AI will:

• Analyze video in real time or post-audit: Identify people, vehicles, objects, detect movement direction, entry/exit of areas, and assign metadata to each frame.
• Store metadata alongside video for faster searching without fast-forwarding, and expandable to systems with multiple cameras and sites.
• Operators can: Perform flexible searches using natural language (AI video search), directly select objects in video, or search by similarity characteristics (similarity search).

How is Intelligent Search different from traditional video search?

Traditional surveillance systems only allow video searching based on time, camera, or motion, forcing operators to manually review and scan large amounts of video data. This process is time-consuming, heavily reliant on human intervention, and prone to missing important events.

Intelligent Search uses AI to analyze video, transforming raw image data into structured information (objects, behaviors, relationships). As a result, users can quickly search by content, trace events more accurately and consistently, and significantly reduce manual workload.

Here are the core differences:

• Search by content, not just by time.
• Faster and more accurate incident investigation.
• Reduced human reliance, standardized operations.
• Easily scalable for SOCs and large-scale surveillance systems.

The Role of AI Video Search in Modern Surveillance

In the context of increasingly large-scale and complex camera systems, AI Video Search plays a key role in upgrading traditional surveillance to intelligent surveillance. This technology helps organizations effectively utilize video data, enhance response capabilities, and optimize security operations.

Transforming Raw Video into Valuable Data

In traditional camera systems, video is simply raw image data, primarily used for playback after an incident has occurred. As the system scales up, this approach quickly reveals its limitations: difficult to search, time-consuming, and heavily reliant on human intervention.

AI Video Search addresses this problem by transforming raw video into structured and exploitable data, laying the foundation for intelligent surveillance and efficient operation. Specifically:

• AI-based frame analysis: AI uses computer vision to identify people, vehicles, objects, and behaviors within each video frame.
• Structured metadata creation: Each object and event is assigned metadata such as object type, time, camera location, direction of movement, and in/out relationships.
• Transforming video into searchable data: Video combined with metadata allows for object and contextual searching, eliminating the need for time-lapse tracking.

Enhancing event detection and tracing capabilities

AI Video Search helps surveillance systems detect and trace events accurately and early, even in environments with multiple cameras and complex data streams. Specifically, the implementation is as follows:

• Contextual object and event detection: AI identifies people, vehicles, and behaviors instead of just detecting movement, helping to pinpoint the specific event of interest.
• Object tracking across multiple cameras: Thanks to object tracking and similarity search, the system can track the same object across multiple camera angles and lighting conditions.

Entry/exit detection allows for a clear timeline of the object's movement.

Speed up incident response and resolution:

• AI significantly shortens the time from incident detection to resolution, especially in continuously operating Security Operations Center (SOC) environments. Specifically:
• AI automatically filters video data, displaying only clips relevant to the incident context, saving operators time from watching irrelevant videos.
• Instead of rewinding hours of video, operators can quickly identify: when the incident occurred, the involved objects, and the extent of the impact. AI helps highlight critical events, allowing SOCs to focus resources on situations requiring immediate response.

Reduced Human Load, Increased Accuracy

In traditional surveillance models, monitoring and reviewing large volumes of video relies heavily on human operators, leading to operational overload and the risk of missing important events. AI Video Search is designed to optimize the role of operators through automated video analysis, thereby improving accuracy and consistency in surveillance. Specifically:

• Automatically filters video data, retaining only relevant events, objects, or behaviors, significantly reducing the amount of video that needs to be manually reviewed.
• Ensures consistent search results unaffected by fatigue or subjectivity, AI provides stable results across shifts and between different operators.
• Provides quick suggestions and search results, while humans focus on contextual assessment and final processing decisions.

Standardizing Surveillance Operations

Over-reliance on individual experience in operations can lead to inconsistent processes, especially with multiple shifts, operators, or locations. AI Video Search plays a crucial role in standardizing surveillance and video investigation processes. Specifically:

• Establishing a unified search process.
• Increasing reproducibility in incident investigations.
• Supporting training and operational transfer.
• Synchronizing operations in a multi-site environment.

Optimizing Costs and Investment Efficiency

• Maximizing the use of existing camera systems increases the value of existing infrastructure.
• Reducing long-term operating costs through the automation of video search and investigation processes.
• Improving incident handling efficiency and enhancing the investment efficiency of surveillance infrastructure.
• Supporting flexible scalability reduces additional investment costs as the number of cameras increases.

Foundation for a Smart Security Ecosystem

In modern surveillance, camera systems no longer operate independently but need to be connected and coordinated with other security platforms.

• Connecting and sharing data between systems helps form a comprehensive security picture, instead of fragmented systems.
• Supports proactive monitoring and multi-dimensional analysis.
• A platform for flexible expansion suitable for Smart Building and Smart City architectures.
• Standardizing data and processes helps: Easier access, inspection, and reporting; compliance with risk management and compliance requirements; and enhanced transparency in security operations.

Operational Value for Security Operations Centers

In the Security Operations Center model, efficiency depends not only on the number of cameras or personnel, but on the ability to detect, analyze, respond to, and investigate incidents quickly and with high accuracy. AI Video Search has become a core component helping SOCs upgrade from passive monitoring to proactive, data-driven operations.

Shortening the Incident Lifecycle

AI Video Search helps SOCs optimize the entire incident lifecycle, significantly shortening incident response time compared to manual video review methods. Specifically:

• Rapidly detects relevant events based on objects and context.
• Accurately identifies the time, location, and extent of impact.
• Continuously tracks objects across multiple cameras.
• Aggregates data for investigation and reporting.

Standardizes SOC operational processes

In multi-shift and multi-personnel SOCs, differences in experience can easily lead to inconsistent response results. AI Video Search supports:

• Establishing standardized search and investigation procedures.
• Ensuring consistent results across operators.
• Easier development of SOPs, playbooks, and incident response checklists.

This helps the SOC operate stably, measurably, and scalably.

Optimized and increased personnel efficiency

AI plays a role in filtering and prioritizing information:

• Automatically removes irrelevant videos.
• Only displays events with operational value.
• Reduces operator's continuous monitoring time.

Enhances real-time response capabilities.

When integrated with VMS and other security systems:

• Video events are directly linked to alerts.
• The SOC has a complete incident picture from the outset.
• Faster, more accurate response decisions.

Supports forensic video investigation and compliance.

AI Video Search provides a foundation for post-incident investigations, which is especially important for SOCs in industrial parks, critical infrastructure, seaports, and airports.

• Fast, structured data retrieval.
• Clear, easily verifiable event timeline.
• Serves reporting, auditing, and legal requirements.

Optimize SOC operating costs

• Reduce the need for increased personnel based on the number of cameras.
• Maximize the utilization of existing camera infrastructure.
• Expandable platform for AI and advanced analytics.

KPS - Smart Surveillance and Security Solutions Partner in Vietnam

With a focus on developing smart surveillance systems and modern security operations, KPS provides comprehensive solutions based on VMS, AI Video Search, and advanced video analytics, helping customers maximize the value of video data in surveillance and SOC operations. 

KPS is designed to meet the criteria of high reliability, security, scalability, and suitability for long-term operation, fulfilling the requirements of large-scale security systems and critical infrastructure.

With practical experience in consulting, designing, and implementing systems, KPS partners with investors, IT Managers, Security Managers, and System Integrators throughout the entire project lifecycle – from building surveillance architecture and integrating AI Video Search to operating and optimizing the SOC. KPS solutions have been and are being applied in many fields such as industrial parks, seaports, transportation, energy, smart cities, and critical security projects.

Through the combination of AI camera technology, intelligent video analytics, and standardized operational processes, KPS helps organizations enhance their security response capabilities, optimize investment efficiency, and gradually transition from traditional surveillance to intelligent surveillance in the AI era.

Not limited to just one brand, KPS is a distributor and implementer of surveillance and security solutions from many leading technology companies such as i-PRO, Bosch, CNB, and many other international partners in the security field. The solutions are carefully selected and optimized.