According to data from the Brazilian Association of Electronic Security Systems Companies (ABESE), in 2024 more than 64% of electronic security solutions available in the country used some kind of embedded artificial intelligence.
Compared to the previous year, this is a 10% growth, reflecting the high demand for this technology amidst the frank expansion of the home security segment, which moved R$ 14 billion in the same period.
For an integrator, these numbers bring a clear message: to remain competitive in the market, it is necessary to integrate AI solutions into your portfolio. And cameras with embedded artificial intelligence, also known as “AI cameras” or “smart cameras,” are among those with the highest demand.
Unlike conventional cameras, which only capture and transmit images, cameras with embedded AI can analyze images and videos in real time using artificial intelligence algorithms integrated directly into the equipment itself. That is, without relying on external servers for decision-making based on patterns and behaviors identified in the images.
Equipped with features such as object detection and classification, facial recognition, behavioral analysis, and flow counting and analysis, smart cameras are used in various sectors, such as companies, public agencies, streets, schools, and residences, for tasks such as surveillance, access control, and optimization of logistics operations, among others.
But although they bring numerous benefits, AI cameras also have important limitations, which can even make implementation unfeasible. In this article, we will discuss the pros and cons of this technology, and show how you can achieve the same results, with lower cost and more flexibility, using the AIOS platform from dtLabs.
Advantages of Surveillance Cameras With Embedded AI
The main advantage of smart cameras over traditional surveillance is the continuous, 24/7 monitoring of an environment. This alone reduces operational costs, increases monitoring effectiveness (eliminating “blind spots” caused by distractions or shift changes), and eliminates human errors.
Another benefit is the automatic and immediate response to events, which is critical in a sector where seconds can make a difference. An embedded AI camera can detect an incident and issue an alert in milliseconds, much faster than the most attentive guard, and without the “human bias” that often hinders objective decision-making.
Greater privacy is another point in favor of embedded AI solutions, when compared to entirely “cloud-based” solutions (known as Cloud AI). In these, all processing is performed remotely. Cameras stream video or raw data to servers, which execute the algorithms and subsequently return the results.
In contrast, in the embedded approach (also called Edge AI), AI processing is performed locally on the device itself, that is, much closer to the data source. As a result, images and videos from your environment do not need to travel across the internet to a remote server, reducing the risk of exposure.
Local processing also has much lower latency, since there is no need to send data to a remote server, wait for processing, and return. This is essential in applications that demand real-time decision-making, such as security, logistics tracking, or automated decisions in production environments.
Limitations of Surveillance Cameras With Embedded AI
But not everything is perfect. Cost is the biggest limitation of AI cameras: while it is possible to find some low-cost models on the market, they are generally aimed at domestic use.
Robust models suitable for professional use can cost R$10,000 or more per camera. Multiply this by the number of cameras needed in a project and the result is that the client may see value in the final solution, but the high implementation cost makes it impossible to move the project forward.
Furthermore, there are technological limitations. Simpler cameras largely have one or two AI models (usually line crossing and perimeter detection) available, and can only execute one at a time.
Even the most sophisticated equipment has a limited number of pre-installed AI models, and frequently it is not possible to add extra models or perform fine-tuning of the pre-existing ones to adapt to different scenarios. This limits implementation flexibility and even upselling opportunities.
Imagine an integrator identifies, in a client that contracted a people counting solution, the need for a facial recognition solution. If the existing cameras do not have this feature, a new hardware investment will be necessary, not to mention a solid explanation of why the client will have to replace the cameras again.
Embedded AI cameras also have limited integration capacity, generally only with other equipment and platforms from the same manufacturer or approved by them, which increases costs (by limiting choices) and restricts implementation.
Finally, there is uncertainty regarding the software update of these equipments. For a company whose business model is the sale of hardware (cameras), it makes more sense to add new features only to new models, forcing the customer to another purchase. This leaves users of older equipment using obsolete software that may no longer meet the needs of a constantly evolving market.
AIOS Brings the Advantages of Embedded AI, With the Flexibility You Need
Fortunately, there is a way to have the benefits of embedded AI cameras with the flexibility you require, for a much more accessible price. It is AIOS, dtLabs’ Edge AI and computer vision platform.
Combining hardware (the AIBox, a device created especially for processing artificial intelligence algorithms) and software (AIOS itself), the platform transforms any IP cameras you already have into smart cameras.
Each AIBox can process images from up to 16 cameras (depending on the algorithms running), drastically reducing implementation costs. And since the AIBox is installed on the same network as the IP cameras, you maintain the advantages of local processing (Edge AI), such as faster response time and greater privacy in data handling.
By using existing cameras, AIOS also reduces the cost of implementing proofs of concept (PoC) and pilots, since the integrator can demonstrate the solution’s functionality to a client without requiring them to halt operations to install new cameras. With faster validation of results, the chances of closing a deal increase.
The platform offers multiple AI models, which can be combined in sophisticated pipelines enabling the rapid implementation of sophisticated solutions for the most diverse use cases, applicable in solutions for security, productivity, access control, quality, industrial automation, agribusiness, and other areas.
AIOS offers customizable dashboards, facilitating the monitoring of the metrics that matter most to your business, and total integration flexibility, whether with popular market platforms (such as WhatsApp for instant notifications) or using our API for the development of customized integrations.
Conclusion
In summary, with AIOS you quickly expand your portfolio, meeting market demands with dozens of ready-to-use AI models, without the need to develop anything from scratch.
And with a more robust portfolio and the AI differential, it becomes easier to win large accounts and retain strategic clients.
Discover how AIOS can transform your business. Contact dtLabs today to schedule a demonstration and explore the full potential of our solution.
