From recording everything to finding what matters
For years, the primary goal of a CCTV system was to observe and store evidence. Cameras recorded, and when an incident occurred, an operator had to manually locate the relevant moment within hours of footage. Today, the landscape is changing.
Specialized manufacturers are incorporating AI-based analytics that allow images to be processed to detect specific objects, movements, or behaviors, alerting the operator when a configured event occurs.
This changes a fundamental question. It used to be: What did the camera record? Now it can also be: What is happening that requires attention?
It is important to make a distinction: Apollocom does not develop these AI algorithms. Its role is to integrate technologies from specialized manufacturers into security solutions tailored to the needs of each operation, as established by its PACT communication strategy.
What is AI video analytics?
It is the use of algorithms capable of analyzing images or video to identify previously defined characteristics or events.
For example, AXIS Object Analytics uses AI-based analytics to detect, classify, track, and count people and vehicles. It also allows for the configuration of scenarios to focus attention on specific objects or events.
Depending on the solution and configuration, analytics can help detect:
- People or vehicles in specific areas.
- Virtual line crossings.
- Loitering.
- Zone occupancy.
- Specific access events.
- Situations related to perimeter protection.
This doesn't mean a camera “understands” everything happening the way a person would. It means it can help filter vast amounts of visual information and highlight events that meet specific criteria.
The problem: no one can watch every camera all the time.
Imagine a plant with dozens or hundreds of cameras. The security center receives video from entrances, perimeters, warehouses, yards, parking lots, processing areas, and restricted zones. Even with operators at the monitors, paying simultaneous attention to every scene is practically impossible. This is where analytics can add value.
Instead of relying solely on continuous observation, the system can generate events when it detects a configured condition and direct the operator's attention to that specific scene.
Axis notes that its tools can send real-time event notifications to focus attention on objects and situations of interest. AI does not replace human decision-making. It reduces the universe that a human has to review.
How can this be applied in an industrial environment?
1. Perimeter protection
A critical facility may have extensive perimeters. Analytics can help identify movement or intrusions within configured zones and generate an alert for verification. This allows the operator to quickly review the associated video and determine the appropriate response.
2. Restricted area control
Certain spaces may be reserved for authorized personnel only. Video analytics can complement other security systems to detect presence or relevant movement within those areas.
The value increases when video does not work as an isolated system, but is integrated with access control, alarms, or other information sources. Genetec, for example, offers a security platform that unifies video surveillance, access control, license plate recognition, communications, and other functions into a single interface.
3. People and vehicles
Identifying and classifying people and vehicles can be useful in yards, entrances, internal roadways, and logistics zones. AXIS Object Analytics allows you to detect, classify, track, and count both types of objects, as well as configure actions when specific events are detected. This can help security personnel prioritize scenarios that require review.
4. Post-incident investigation
AI can also generate value after something has occurred. Manually searching for an event across multiple cameras can be very time-consuming. New tools allow the use of metadata and filters to locate relevant clips more quickly.
In 2025, Genetec announced smart investigation features for Security Center SaaS aimed at locating people or vehicles and providing context on what happened before and after an incident.
The result is significant: video stops being just an archive and becomes information that is easier to query.
Integration is just as important as detection
A camera can generate an alert. But what happens next?
If an operator has to switch to another application to check access, open a different system to verify an alarm, and then call over the radio to coordinate a response, the process remains fragmented. That is why analytics provide more value when they are part of an integrated architecture.
Genetec notes that Security Center allows you to correlate video surveillance events with other sources and manage them from a common interface; its analytics integrations can also send events to the platform to simplify management.
The goal is not to add "AI" just because it is trendy. It is to use it where it can reduce noise and facilitate decision-making.
What should you evaluate before implementing AI analytics?
Not all scenarios require the same technology. Before selecting a solution, it is advisable to define:
What do we want to detect?
Protecting a perimeter is not the same as supervising vehicle access.
Where will it operate?
Lighting, height, angles, weather, and scene characteristics can influence the quality of the results.
What should happen after a detection?
An alert only provides value if there is a response protocol in place.
Which systems must it integrate with?
CCTV, access control, intercoms, sensors, and security platforms can all be part of a broader strategy.
Axis warns, for example, that installation and scene conditions are relevant to achieving proper performance from their analytics.
Applied AI, not abstract AI
For the industry, talking about AI makes sense when it translates into a concrete use case.
- Detecting a relevant event.
- Classifying an object.
- Finding evidence more quickly.
- Prioritizing operator attention.
- Integrate an alert with other systems.
That is the approach that turns artificial intelligence into a useful tool. Apollocom works as an integrator: we analyze operational needs and can incorporate solutions from manufacturers that already have these types of capabilities.
The question, then, should not simply be: “Do we have AI?” But rather: “What operational problem do we want to solve with it?”
Frequently Asked Questions
Does AI replace a video surveillance operator?
Not necessarily. Its greatest value lies in helping to filter information, detect configured events, and direct the operator's attention toward relevant situations.
Do I need to replace all my cameras?
It depends on the platform, the cameras, and the type of analytics. Some capabilities work on compatible devices, while others can be integrated through external platforms.
Are analytics only useful for security?
No. Depending on the technology, it can also generate information regarding counts, flow, occupancy, or operational behavior.
What should be defined first?
The problem you want to solve. The technology should be selected afterward.
Conclusion
Industrial cameras are generating more and more information. The challenge is no longer just capturing video; it is ensuring that video helps identify what requires attention.
AI-based analytics can help detect, classify, and contextualize events so that security teams can work with greater focus and investigate incidents more efficiently.
But technology alone is not enough. You need to define the use case, select the right solution, integrate it with the rest of your infrastructure, and establish what should happen after each alert.
At Apollocom, we integrate video surveillance, security, and communication solutions from specialized manufacturers to address real operational needs. If you have many cameras but little ability to identify what is truly important, we can help you evaluate where analytics can add value.
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