LAVA-COUNT, the analytics used by the security system to provide business and statistical data
Lanaccess > Analytics > LAVA-COUNT, the analytics used by the security system to provide business and statistical data
  • Posted by: Demelsa Gonzalez

Companies are increasingly looking for technology solutions that help security personnel detect more incidents faster so they can resolve all of them sooner. But they have also realized that the video surveillance system can also provide very interesting data that affects other departments of the organization.

To do this, they use video surveillance systems with Artificial Intelligence Deep Learning . One of the tools with the greatest potential to provide relevant data to company management is LAVA-COUNT by Lanaccess .

LAVA-COUNT is one of the new Deep Learning video analytics algorithms   developed by the Lanaccess R&D team.

What is LAVA-COUNT and what does it offer to companies?

LAVA-COUNT is an analytic that includes a pack of algorithms based on neural networks that offers the possibility of viewing people and vehicle counting data in an intuitive dashboard for data exploitation through a powerful Business Intelligence (BI Xplorer).

Thanks to this analytics, the system obtains anonymous information on the flow, behavior and segmentation of objects (both people and vehicles).

This information makes it possible to control different situations such as traffic flow and influx in a space, queue analysis, occupancy density, dwell time and tailgating events (when an individual accesses restricted spaces by closely following others). authorized personnel).

Why does a company need LAVA-COUNT analytics?

Lanaccess’s exclusive analytics offer specific functionalities that are useful for any company that wants to maintain the security of a space.

LAVA-COUNT allows you to define 10 different areas and lines to analyze for each channel and detects the presence of people or vehicles in the areas, lines and configuration rules:

  • When the vehicle or the person’s body cannot be fully seen in the image.
  • In those situations in which the person is partially covered, crouched, crawling, walking or running, among others.
  • In the circumstances of low light and night events thanks to cameras with IR.

In addition, this exclusive solution with Deep Learning does not confuse reflections or shadows with people or vehicles, detects and tracks people thanks to thermal cameras and avoids cameras having to be previously calibrated.

With directional line crossing, the solution allows you to draw three types of lines, bidirectional, directional or group crossing. Bidirectional lines increment the counter when a person crosses the line in any direction, while directional lines increment the counter when an individual crosses the line in a particular direction. With group crossing or tailgating , the counter is increased when more than one person has crossed a line.

With double line crossing, the system increments the counter when a person has crossed the double line that was previously drawn.

Each of these rules sends information to the system that the business managers can later analyze through the Business Intelligence BI Xplorer tool, thanks to this solution it allows those responsible to take action, knowing, for example, that on Mondays at 1:00 p.m.: 00 there is a lot of influx in the metro station near the university and that is why the entrance to the station must be regulated so as not to cause risk situations, or that on Thursdays at 15:00 in the shopping center many people gather in the area of ​​young fashion and that point must be reinforced, or that in the bank branch the bulk of the users first withdraw money from the ATM and then enter to make arrangements with the employees.

Lanaccess provides companies with Deep Learning analytics such as LAVA-COUNT to improve their video surveillance systems and protect their assets and users as much as possible, but also to optimize company management and thus be able to provide a better service to their customers.

 

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