AI Camera: Future Trends and Breakthrough Applications

NGÀY ĐĂNG 30/01/2026

Võ Hồng Tiên

In Vietnam, many security projects share a common paradox: the number of cameras continues to increase, yet surveillance effectiveness does not improve proportionally. Systems remain heavily dependent on human operators, false alarms occur frequently, and incidents are often detected only after they have already happened. Surveillance systems primarily serve as tools for post-incident recording. Operators are forced to review hours of video footage to find evidence, while the majority of collected data carries little to no operational value.

From Traditional CCTV Systems to AI Cameras: Where Does the Difference Lie?

As deployment scales expand—from factories and commercial centers to entire urban areas—traditional camera systems increasingly reveal their limitations. The emergence of AI cameras represents not merely a technological upgrade, but a fundamental transformation in how surveillance systems operate and create value.

So where does the real difference lie?

The most significant distinction between traditional surveillance camera systems and AI cameras does not lie in resolution or camera quantity, but in how visual data is processed. AI cameras mark a critical shift—from passive video recording to proactive data analysis and understanding.

Operating Methodology

Traditional cameras simply record pixels and store raw video footage for later review. All decisions depend on human intervention after an incident has already occurred.

In contrast, AI cameras function as intelligent processors at the edge, capable of analyzing images in real time, identifying objects, and triggering responses at the moment an event occurs.

Object Recognition Capability

Legacy systems detect only pixel changes, making them highly susceptible to triggers from lighting variations, shadows, weather conditions, or insects—leading to frequent false alarms.

AI cameras can accurately classify objects such as people, vehicles, and animals. As a result, the system focuses only on events that truly matter from a security or operational perspective.

Accuracy and Alert Effectiveness

Powered by deep learning algorithms, AI-enabled cameras can filter out most irrelevant disturbances, reducing false alarms by 80–90% compared to traditional systems.

Instead of triggering alerts for any motion, the system raises alarms only when suspicious behaviors are detected according to predefined scenarios (e.g., intrusion outside permitted hours, wrong-way movement, abnormal vehicle stopping).

Security Nature: From Reactive to Proactive

Unlike traditional cameras, AI cameras are designed for proactive security, with capabilities such as:

• Early risk detection
• Immediate deterrent activation (strobe lights, sirens, voice warnings)
• Incident prevention before real damage occurs

Intelligent Data Management and Search

Rather than manually scrubbing through hours of video footage to locate a specific moment, AI cameras significantly shorten incident handling and decision-making time. They enable:

• Attribute-based search (person, license plate, clothing color, time)
• Rapid filtering of critical events
• Visual reports such as heatmaps, people counting, and behavior statistics

Extended Value Beyond Security

Traditional camera systems are almost exclusively used for security purposes. AI cameras, however, extend into operations and business intelligence through applications such as:

• Facial recognition-based attendance and access control
• Customer demographic analysis (age, gender)
• Operational optimization in retail, parking facilities, and urban traffic systems

Practical Deployment of AI Cameras in Urban Traffic Management

In Vietnam, AI camera applications have entered large-scale real-world operation in major cities such as Ho Chi Minh City and Hanoi. Recorded results show that the technology not only supports authorities in traffic management but also significantly improves public compliance with traffic regulations.

Automated Surveillance System in Ho Chi Minh City

By the end of 2025, Ho Chi Minh City had established a wide-area intelligent traffic surveillance network, integrating specialized cameras capable of automatic violation detection and recording. According to reports from the Traffic Police Department (PC08), the system has delivered breakthrough initial results in traffic safety management.

Notably, the city’s smart traffic infrastructure focuses not only on scale, but also on device quality and edge-level data processing capabilities (Edge AI).

Violation Detection Statistics

• From September 1, 2025 to November 2025, AI camera systems detected approximately 5,898 traffic violations and issued notifications to vehicle owners for enforcement.
• Earlier, within just over one month from early September, 31 AI cameras installed at key intersections recorded approximately 3,143 violations, primarily red-light running, lane violations, and speeding.

Operational Camera Infrastructure Scale

• The city operates over 1,200 traffic surveillance cameras, including 31 AI cameras dedicated to automated violation detection connected to the central control system.
• The system also includes 530 area-monitoring cameras, 9 automatic speed-measurement cameras, and 47 cameras invested by the Ministry of Public Security, forming a multi-layer surveillance network.

AI cameras in Ho Chi Minh City not only detect violations but also generate transparent data for automated enforcement, partially replacing manual monitoring. The growing number of detected violations reflects the objectification of enforcement processes and significantly supports traffic police operations under high traffic density conditions.

Hanoi – Expansion Model and Results After One Month

Similarly, Hanoi deployed approximately 1,837 AI cameras across 25 major roads and 195 key intersections starting December 13, 2025. By January 12, 2026—after just one month of operation—the system recorded 6,351 violations with sufficient legal evidence for automated penalty notices, including:

• 66.36% red-light violations
• 32.32% helmet-related violations
• Other violations such as lane misuse and illegal parking

AI-driven traffic signal control and surveillance reduced average travel time at certain intersections by 20%–36.8% and increased traffic throughput at congestion hotspots by 8%–18.88%, significantly alleviating congestion.

Most notably, clear behavioral changes were observed among road users. At AI-monitored intersections and road segments, common violations such as lane encroachment, red-light running, and illegal stopping dropped sharply compared to previous periods.

Next-Phase Development Direction in Hanoi

• Deep integration with telecommunications infrastructure from major providers such as VNPT, MobiFone, and Viettel
• Development of AI software capable of extracting value from existing conventional camera systems
• Expansion of monitoring coverage to suburban road networks
• Direct integration with traffic signal systems for real-time adaptive traffic control based on vehicle density and AI analytics

Future Trends of AI Cameras

From Passive Recording to AI Agents – Active Actors

Next-generation AI cameras will not only detect and alert but also analyze complex contextual situations and propose optimal response strategies for human operators.

Natural Language Video Search

By removing technical barriers in video data exploitation, users can search video footage using natural language queries such as:

• “Find a person wearing a blue shirt entering the server room after 10 PM”
• “Show vehicles stopping in the wrong lane during peak hours”

Edge AI as the Infrastructure Standard

Edge AI adoption will continue to accelerate due to:

• Reduced latency for real-time scenarios
• Data retention at the source, enhancing privacy
• Reduced dependency on cloud infrastructure

Sensor Fusion

AI cameras will no longer rely solely on visual input. Future systems will integrate:

• Optical cameras
• Thermal cameras
• AI-enabled microphones for abnormal sound detection
• Short-range radar / LiDAR

AI-powered Image Signal Processing (ISP)

This approach enhances AI accuracy and reduces recognition errors under challenging conditions.

AI Cameras & Digital Twins

• Real-time understanding of human movement flows
• Optimization of traffic, energy, and spatial usage
• Simulation of operational scenarios prior to deployment

This marks the transition from object recognition to behavior and contextual understanding.

Green AI

Meeting sustainability requirements through:

• Lightweight AI models (TinyML)
• Low power consumption
• Battery or solar-powered operation

Hybrid Cloud Infrastructure – Edge & 5G/6G

• Edge AI: instant processing and response
• Cloud AI: long-term training and analytics
• 5G/6G: ultra-low-latency connectivity for massive device ecosystems

From Product to Platform

AI cameras are evolving from standalone products into comprehensive technology platforms.

Privacy-by-Design as a Mandatory Standard

Future AI camera technologies will embed privacy protection directly into system architecture.

Video Analytics as Big Data

Video analytics will become a major data source for governance and strategic decision-making.

Multi-modal AI

AI cameras will function as intelligent nodes within the broader AI–IoT ecosystem.

KPS – Total Security Solution Provider

With over 15 years of experience deploying security and surveillance systems across factories, industrial zones, commercial complexes, and urban infrastructure, KPS approaches cameras not as standalone recording devices, but as intelligent sensing layers within an integrated security ecosystem.

KPS is an authorized distributor and implementation partner of leading global camera and surveillance platforms such as i-PRO, Bosch, and CNB, alongside solutions for Video Analytics, AI Cameras, VMS, and system integration. Through deep integration between cameras, access control, intrusion and fire alarm systems, public address systems, and centralized management platforms, KPS enables owners to transition from passive surveillance to data-driven, AI-powered proactive security.

Beyond equipment supply, KPS partners with investors and facility managers throughout the entire project lifecycle—from camera architecture consulting and technology selection to deployment, operation, optimization, and scalable expansion. This approach ensures long-term stability, flexibility, and performance for AI camera systems that meet future security, operational, and data governance requirements.

Contact KPS for consultation tailored to your project’s real operational needs.