In recent years, AI cameras have emerged as a prominent trend in industrial surveillance. Many enterprises seek to leverage artificial intelligence to enhance workplace safety, ensure quality control, and optimize production operations. However, when exploring these options, managers often face a common dilemma: should they invest in integrated AI cameras or an AI server system?

While both are referred to as “AI cameras” and offer object recognition and surveillance capabilities, their system architectures, scalability, and application scopes differ significantly.

An unsuitable choice can lead to various issues for the enterprise, such as:

• Difficulty scaling the system as the number of cameras increases.
• AI capabilities failing to address specific factory requirements.
• Inability to integrate with PLC, SCADA, or MES systems.
• The need to replace equipment when new requirements arise.
• Escalating investment costs during system expansion.

This article provides a detailed analysis of the differences between integrated AI cameras and AI server systems, helping enterprises select the solution that best aligns with their current needs and future growth strategies.

I. Understanding Integrated AI Cameras

1. What is an integrated AI camera?

An integrated AI camera (or Edge AI camera) is a camera equipped with a built-in AI chip. The entire process of image recognition and processing takes place directly on the camera itself, eliminating the need for a separate AI server.

Currently, many major camera manufacturers offer models with built-in basic AI features, such as:

• Human detection
• Vehicle detection
• Intrusion detection
• Virtual line crossing detection
• Motion detection
• People counting

Thanks to their on-device processing capabilities, AI cameras offer advantages such as rapid deployment, simple configuration, and suitability for basic surveillance applications.

2. How does an AI camera work?

A typical AI camera follows this process:

1. The camera captures images.
2. An AI chip inside the camera analyzes each frame.
3. The AI ​​identifies objects such as people or vehicles.
4. Upon detecting a pre-configured event, the camera sends an alert.

The entire process takes place directly on the camera, without the need to transmit data to an AI server for processing. This is why this solution is also known as Edge AI.

3. Advantages of AI-integrated cameras

For simple or small-scale applications, AI cameras offer several benefits, such as:

• Low initial investment cost: no need to invest in dedicated GPU or AI servers.
• Rapid deployment: simply install and configure the camera to start using it.
• Suitability for small-scale systems: ideal for offices, shops, small warehouses, or specific areas requiring surveillance.
• Reduced data transmission traffic: since AI processing occurs directly on the camera, the volume of data transmitted to the central system is significantly reduced.

4. Limitations of AI cameras in factories

While well-suited for basic applications, AI cameras begin to reveal significant limitations when deployed in large-scale factories or when multiple AI tasks must be performed simultaneously.

4.1. AI capabilities constrained by camera hardware

The AI ​​processing capability of an integrated AI camera depends directly on the performance of the chip embedded within the device. Due to limited computational resources, there are constraints on the number and complexity of AI algorithms that can run concurrently on a single camera.

For instance, an AI camera might be designed to handle tasks such as PPE inspection, intrusion detection, or human recognition. However, when multiple complex AI models need to run simultaneously on the same video stream, processing performance can become a limiting factor. This is a particularly important consideration in factory environments, where a single area may require the monitoring of multiple safety risks at once, rather than the execution of just one isolated detection function.

4.2. Scalability challenges

With integrated AI cameras, each unit functions as an independent AI processing device. While configuration and management are relatively simple when a system comprises only a few cameras, the complexity increases significantly as a business scales up—for instance, expanding from 5 to 50 cameras—because the number of AI devices requiring management grows in tandem.

This makes configuring, maintaining, updating, and synchronizing AI algorithms across the entire system more complicated. In particular, deploying a new feature or adjusting an algorithm may require the technical team to perform tasks on multiple individual devices rather than managing everything centrally via a single platform.

4.3. Limited customization

Integrated AI cameras typically support only the AI ​​algorithms and features provided by the manufacturer. Consequently, the ability to customize the system to meet a specific business’s unique needs may be restricted. When a factory has specialized requirements, the business may struggle to train the AI ​​using real-world data, add new recognition capabilities, or optimize AI models to align with specific production workflows and safety standards.

This is a significant limitation for factories with complex operational processes or unique safety monitoring requirements, as the AI ​​system needs to adapt to the actual operating environment rather than relying solely on pre-installed algorithms.

4.4. Integration challenges

Integrated AI cameras typically focus on surveillance, recognition, and alert functions performed directly on the device. Consequently, when a business needs to connect AI data with other factory systems—such as PLC, SCADA, MES, ERP, or proprietary management dashboards—integration capabilities may be limited and dependent on the specific platforms supported by the manufacturer.

This can pose an obstacle when a business aims to incorporate AI camera data into its production management ecosystem and Smart Factory infrastructure, where systems must interconnect and exchange data seamlessly.

4.5. When is an AI camera the right choice?

AI cameras remain an effective choice if the business has the following requirements:

• Deployment in only a few specific areas.
• Fewer than 5–10 cameras.
• Need for only basic AI applications.
• No requirement for algorithm customization.
• No need for integration with factory management systems.

In these scenarios, AI cameras enable rapid deployment at a reasonable investment cost.

II. What is an AI Server?

While AI cameras process data locally on each unit (Edge AI), an AI Server utilizes a high-performance central server to process imagery from the entire camera system within a factory. Instead of operating independently, all video data is transmitted to the AI ​​Server. There, AI models simultaneously analyze multiple video streams, recognize behaviors, assess risk levels, and issue real-time alerts. This architecture enables businesses to easily manage the system centrally, scale operations, and deploy complex AI applications that would be difficult for integrated AI cameras to handle.

1. How does an AI Server work?

An AI Server system typically consists of four main components:

• IP ​​Cameras: These capture images in areas requiring surveillance, allowing businesses to leverage existing camera systems without needing a complete replacement.
• AI Server: This acts as the “brain” of the entire system. It utilizes dedicated GPUs for real-time image processing and can simultaneously run multiple AI models—such as PPE detection, unsafe behavior recognition, forklift safety monitoring, robot safety zone monitoring, hazard zone entry/exit detection, fall detection, Skeleton AI, and Bounding Box analysis.
• Dashboard: All alerts are centralized on a single dashboard, enabling managers to monitor the entire factory, review event history, analyze statistics, and evaluate safety KPIs.
• Alert System: The AI ​​Server can integrate with warning lights, sirens, PLCs, barriers, SCADA, MES, and ERP systems to create a proactive alert network.

2. Why are AI servers becoming a trend in smart factories?

As the number of cameras increases, businesses require more than just “cameras that can see”; they need an AI platform capable of management and scalability over time. This is why many factories are shifting from standalone AI cameras to an AI server architecture.

Key benefits of AI servers include:

• Centralized management of dozens to hundreds of cameras.
• Deployment of multiple AI applications on a single platform.
• Ease of updating and upgrading AI models.
• No dependency on a specific camera manufacturer.
• Easy integration with production management systems.

This architecture is also the choice of many enterprises as they build their smart factories.

3. Comparison of AI Cameras and AI Servers

Below are key criteria that businesses should consider when selecting an AI solution for their factories.

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The comparison table reveals that AI cameras and AI servers are not directly competing solutions but rather serve distinct needs. If a business requires the deployment of only a few cameras with basic recognition functions, AI cameras are a logical choice due to their low investment cost and rapid implementation.

However, as the system scales up or the business requires multiple simultaneous AI applications, the limitations of AI cameras become apparent. Managing numerous independent cameras, expanding features, or customizing systems to fit production workflows can become complex and costly.

In such scenarios, AI servers offer distinct advantages through centralized processing, flexible scalability, and deep integration with factory management systems. They also provide a suitable foundation for businesses to incrementally build a Smart Factory model and develop further AI applications in the future.

III. When should you choose AI cameras? When should you choose an AI server?

There is no one-size-fits-all solution for every business. The choice between AI cameras and an AI server depends on the scale of the facility, deployment objectives, and future development plans. Below are some typical scenarios.

1. When are AI cameras the right choice?

AI-integrated cameras are suitable if the business:

• Needs to deploy only 1–10 cameras.
• Wants to monitor a few specific, isolated areas.
• Requires only basic AI features, such as person, vehicle, or intrusion detection.
• Has no need to customize AI algorithms.
• Does not require integration with PLC, SCADA, MES, or ERP systems.
• Wants a quick deployment with low initial investment costs.

For small-scale projects, AI cameras can effectively meet monitoring needs while offering a reasonable return on investment.

2. When should you choose an AI Server?

An AI Server is the right choice when a business aims for an AI system that offers scalability and centralized management. This solution is particularly suitable if the factory:

• Has more than 10–20 cameras or multiple areas requiring surveillance.
• Wishes to leverage its existing camera system.
• Needs to deploy multiple AI applications simultaneously, such as PPE detection, hazard zone monitoring, forklift safety, robot safety, or Skeleton AI.
• Wants to customize AI capabilities to fit specific operational workflows.
• Requires integration with PLC, SCADA, MES, or ERP systems.
• Plans to expand the system in the future.
• Aims to build an AI platform to support a Smart Factory.

In these scenarios, an AI Server helps businesses reduce long-term upgrade costs while making it easy to add new AI modules as needs evolve.

IV. Case Study: Scaling an AI System at an FMCG Plant

Consider an FMCG plant that initially sought only to monitor hard hat usage in the packaging area. In Phase 1, the company deployed six cameras equipped with AI for PPE compliance checks; at this scale, the AI ​​cameras were sufficient to meet requirements. After approximately one year, the company expanded the project to include the following new requirements:

• Safety monitoring for the robotic palletizer area.
• Forklift monitoring in the finished goods warehouse.
• Detection of personnel entering hazardous zones.
• Monitoring the distance between personnel and robots.
• Data logging for EHS reporting.
• A centralized dashboard for the entire plant.

At this stage, relying on standalone AI cameras presented significant limitations: each camera ran a different algorithm, making synchronized management and updates difficult; data integration across areas was challenging; and system expansion became complex and costly.

In contrast, an AI Server architecture allows the company to simply add new AI modules to the existing platform without replacing the entire camera system. This is why many enterprises choose an AI Server solution from the outset when planning for long-term Smart Factory development.

► Watch video about Safety AI CCTV from i-Soft:

V. Checklist: Which solution suits your business?

If you are considering implementing AI CCTV, try answering the questions below.

1. How many cameras need to be deployed at the factory?

• Fewer than 10 cameras.
• 10–50 cameras.
• More than 50 cameras.

2. Does the business want to leverage its existing camera system?

If the answer is “Yes,” an AI Server allows you to utilize existing infrastructure and reduce investment costs.

3. Do you need to solve just one AI use case or multiple ones simultaneously?

Examples:

• PPE detection
• Forklift safety
• Robot safety
• Hazardous area monitoring
• Fall detection
• Smoking detection

If multiple AI applications are required simultaneously, an AI Server offers greater scalability.

4. Are there plans to add more cameras or expand to other factories in the future?

If so, the business should consider a scalable AI platform rather than one that merely meets current needs.

5. Is a centralized management dashboard required?

If the business wants to monitor the entire system via a single interface, an AI Server is the suitable choice.

6. Is integration with PLC, SCADA, or MES systems required?

If the AI ​​needs to interact with operational processes or trigger automated alerts, an AI Server is better suited for the task.

7. Does the business have specific safety protocols?

Examples:

• Specific PPE requirements.
• Specific SOPs.
• Area-specific regulations.

An AI Server can be customized to meet these specific requirements.

8. What is the business’s objective?

To solve only an immediate, specific problem? Or should an AI platform be built to serve Smart Factories for the years to come?

The answer to this question will determine the most suitable solution.

VI. Conclusion

Both AI cameras and AI servers offer value in smart surveillance, yet they cater to different needs. If a business requires only basic AI features on a small scale, AI cameras represent an economical and easy-to-deploy option. Conversely, if the goal is to build a scalable AI system that supports centralized management and integrates with production infrastructure, an AI server serves as a more suitable foundation for a long-term digital transformation strategy.

The key lies not in choosing the “most powerful” technology, but in selecting the solution that best aligns with the business’s current situation and future development direction.

VII. Schedule a free consultation with i-Soft

Not sure whether your business should use AI cameras or an AI server? i-Soft’s team of experts is here to assist you with:

• Assessing your existing camera system.
• Analyzing your factory’s specific needs.
• Advising on the appropriate AI architecture.
• Proposing a phased implementation roadmap.
• Conducting live demonstrations on your business’s camera system.

Contact i-Soft today for a free consultation and to select the best AI CCTV solution for your factory.

i-Soft Joint Stock Company – specializing in providing factory digitalization software solutions

► Address: 115 N2 Road, Long Truong Ward, Ho Chi Minh City, Vietnam
► Hotline: 0989 739 488
► Email: info@i-soft.com.vn

Frequently Asked Questions (FAQ)

1. Can AI cameras replace AI Servers?

No. AI cameras and AI Servers serve different scales and needs. AI cameras are suitable for smaller systems, whereas AI Servers are ideal for factories requiring centralized management and long-term scalability.

2. Does an AI Server require replacing existing cameras?

No. i-Soft’s AI Server can integrate with a wide range of popular IP cameras available on the market.

3. Can an AI Server handle multiple AI tasks simultaneously?

Yes. The system supports multiple concurrent modules, such as PPE detection, hazardous area monitoring, forklift safety, robot safety, fall detection, and various other applications.

4. When should one switch from AI cameras to an AI Server?

When the number of cameras increases, AI requirements become more diverse, or the business needs to integrate with PLC, SCADA, MES, and other management systems.

5. Is the AI ​​Server suitable for Smart Factories?

Yes. The AI ​​Server architecture is designed to support scalability, centralized management, and integration with smart manufacturing ecosystems.

6. Does i-Soft provide site surveys and demonstrations?

Yes. i-Soft’s engineering team conducts site surveys, assesses requirements, and proposes suitable solutions prior to implementation.