Do AI cameras truly help businesses save costs? This is a question many business owners ask when considering implementing AI for safety monitoring or production management. Many enterprises often prioritize integrated AI cameras due to their low initial investment costs, quick installation, and lack of a need for dedicated servers.

For small-scale operations, this is a sensible choice.

However, as the system expands to include dozens of cameras—or as new requirements arise, such as PPE violation detection, hazardous zone monitoring, forklift control, or integration with PLCs and MES—the limitations of AI cameras begin to surface.

This often compels businesses to make additional investments or overhaul their system architecture just a few years after implementation.

In other words, a solution with a low initial investment cost is not necessarily the one with the lowest Total Cost of Ownership (TCO) in the long run.

Below are five common limitations of AI cameras in industrial environments that businesses should consider before investing.

I. 5 Limitations of AI Cameras in Factories

1. AI performance is constrained by camera hardware

AI cameras process images directly on the device using an integrated AI processing chip (NPU). Due to limitations in size, power capacity, and heat dissipation, the NPUs found in cameras typically offer significantly lower performance than the GPUs used in AI servers.

This results in several limitations:

• Only pre-optimized AI models can be executed.
• Deploying complex Deep Learning models is difficult.
• Processing efficiency drops when multiple objects appear in a single frame.
• Accuracy may be compromised in production environments characterized by high personnel density or significant movement.

In industrial environments, where alert-related decisions must be both accurate and timely, processing performance is a critical factor.

2. Inability to customize algorithms to specific factory needs

Every factory has its own unique operational workflows, safety standards, and monitoring requirements. PPE regulations may vary by zone, SOPs differ across production lines, and areas involving robots or AGVs require specialized safety control criteria. Furthermore, certain hazardous behaviors may be specific to particular industries or production stages.

In contrast, integrated AI cameras typically rely on algorithms and features provided by the manufacturer. Consequently, businesses may face limitations when attempting to train the AI ​​using real-world data, develop new recognition capabilities, or adjust algorithms to align with internal factory processes.

With an AI Server, AI models can be developed, optimized, and scaled to meet specific requirements. This enables the system to better adapt to actual operating conditions and the unique safety standards of each factory.

► Read more: AI CCTV Solutions for Factories From i-Soft

3. Difficulty scaling up as the number of cameras increases

Initially, a business might deploy only a few AI cameras in critical areas. However, as the system expands to 20, 50, or even 100 cameras, operation and management become significantly more complex.

With an integrated AI camera architecture, each camera functions as an independent AI processing unit—handling everything from configuration and firmware updates to device monitoring and management. As the camera count rises, the workload for IT and EHS teams increases correspondingly, particularly when the business needs to synchronize configurations or deploy new features across the entire system.

Conversely, an AI Server enables centralized processing and management of data from multiple cameras on a single platform. This allows for more convenient system management while making it easy to scale the number of cameras and add new AI applications as needs arise.

4. Challenges in integration with ERP, MES, and management systems

Modern factory AI goes beyond mere event detection and alerting; it must function as an integral part of the Smart Factory ecosystem, where data is interconnected and shared across various systems.

For instance, upon detecting a hazardous action, an AI system can signal a PLC to activate warning lights or sirens, synchronize data with the MES, log the event in the ERP, and aggregate the data on a centralized management dashboard. This enables enterprises to track safety KPIs, analyze violation trends, and assess risk levels by specific zones or timeframes.

While many integrated AI cameras focus primarily on surveillance—with connectivity often tied to specific manufacturer platforms—an AI server can serve as a centralized data processing hub. This architecture offers greater flexibility when connecting AI with PLCs, MES, ERPs, and other management systems, facilitating the step-by-step construction of a safe, intelligent, and synchronized factory ecosystem.

5. Dependence on the manufacturer for upgrades

A significant limitation of integrated AI cameras is that upgrade capabilities often depend on the manufacturer’s technology roadmap. When a business needs to add new algorithms, expand recognition functions, implement specialized features, or improve accuracy, the system may have to wait for firmware or software updates from the vendor. In some cases, if the existing hardware can no longer meet processing requirements, the business may even need to upgrade or replace the cameras.

This dependency reduces flexibility in system development and can lead to additional costs as the factory’s needs evolve over time.

In contrast, with AI servers, AI models and modules are managed centrally. Businesses can update, optimize, or add new AI applications on the same platform without necessarily altering the entire existing camera system. This makes the system more adaptable to new requirements and facilitates long-term scalability.

II. When should businesses use AI cameras?

The aforementioned limitations do not imply that AI cameras are an ineffective solution. On the contrary, for small-scale projects or basic surveillance tasks, AI cameras remain a suitable choice due to their low initial investment costs, rapid deployment, simple configuration, and the fact that they do not require a dedicated AI server.

However, when a business plans to increase its camera count, implement additional AI applications, or transition toward a Smart Factory model, long-term scalability and integration capabilities must be considered from the outset. Selecting the right AI architecture not only meets current needs but also minimizes the need for infrastructure overhauls, reduces upgrade costs, and establishes a solid foundation for future AI applications.

III. AI Server: A suitable solution for modern factories

For enterprises needing to deploy AI at scale or handle multiple use cases simultaneously, AI servers offer numerous advantages:

• Centralized management of multiple cameras.
• Utilization of existing camera systems.
• Simultaneous execution of multiple AI models.
• Customizable algorithms to meet specific requirements.
• Easy feature scalability.
• Connectivity with PLC, SCADA, MES, and ERP systems.
• Support for centralized dashboards and reporting.

This architecture is also a preferred choice for many enterprises on their journey toward building smart factories and undergoing digital transformation.

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

 

IV. Conclusion

Both integrated AI cameras and AI servers offer distinct advantages. The key is for businesses to select a solution that aligns with their current scale and future growth strategy.

If the goal is rapid deployment across just a few areas, AI cameras are an excellent choice. However, if the business aims to build a scalable AI platform that supports centralized management and integrates with production systems, an AI server is the more suitable long-term option.

Evaluating the Total Cost of Ownership (TCO), scalability, and integration requirements from the outset helps businesses avoid unnecessary additional investments down the line.

Are you considering an AI solution for your factory? Leave your details now, and i-Soft will advise you on the solution best suited to your business needs.

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