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Control systems Capacity: 2 effective Ways to control it.

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Since the beginning of the Pandemic, a new word was installed in the everyday vocabulary of all who frequent trade, retail, restaurants, grocery stores, or any place with confined spaces and limited capacity: the system capacity control.

The capacity is defined as the maximum capacity of people that can fit in a place or enclosure. And along with the re-opening of the trade, control the capacity became one of the most important aspects to take care of the safety of customers and employees.

There are mainly 2 alternative systems to perform an efficient capacity control.

The first is to count the people entering and leaving of a place, so by the difference to get the capacity in real-time. The second system, is to take instant photos of all over the place, and from algorithms with artificial intelligence, to detect the people in the pictures and narratives.

Count the people entering and leaving of a place, and control the capacity for differences is the control system of capacity ideal for large surfaces, such as shopping Malls, Supermarkets and Multitiendas. In this way, devices that are installed in the doors are synchronized to bring an added control in real-time.

One of the aspects that have to be considered when implementing this type of system capacity control, is the error in the count.

There is no system that is able to count people entering and leaving with 0% error. Traditionally you will find all the solutions in the market converge to a 98% accuracy. But this precision is in the people counting.

If during a day entering and leaving 15,000 people, a 2% error in the count of people are 300 people. If the maximum capacity is about 5,000 people, 300 people on 5,000 imply a 6% error. This potential error on the capacity, it is still tolerable.

On the other hand, if we are controlling the capacity into a smaller space, but high-flow, the reality will be different. Suppose that we have a space of bounded surface where the maximum capacity is 50 people, and the daily flow are 5,000. In this case, a 2% error in the count of people would be 100 people. However, 100 people over 50, which is the maximum capacity, we are given a 200% error potential. That is to say, to tell people in areas of high flow and low maximum capacity would not be an effective system.

For these cases, the best solution would be to cover the surface of the place with cameras, and get snapshots every 10 seconds. An algorithm with artificial intelligence must be able to identify people, differentiating customers of partners.

In this way, despite the fact that it can continue to exist is an error determining which people in around 5%, the maximum error will be 3 people on the 50 allowed. With this system, capacity control, do not drag the error count throughout the day and keeps under control the error with respect to the maximum capacity.

We hope with this article to have been able to clarify many of the doubts that come to us permanently about the different systems of capacity control effective that are available in the market.

If you need an accessory to be able to implement a control system in terms of capacity within your venue, and being able to know what are the types of técnologias feasible for the control of your physical space , you can communicate info@inxbg.com.

 

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