Computer Vision is one of the many options offered by Artificial Intelligence.
Lately, artificial intelligence is one of the main investments that companies from different sectors are making.
It is about obtaining predictive models or data analysis.
Therefore, the benefits of using Computer Vision are very broad, and, of course, are available to everyone.
But, in order to implement artificial intelligence in an organization, in this case, Computer Vision, it is necessary to take some previous steps.
How to prepare a correct data architecture?
As we commented, for any business to be able to implement Computer Vision in its company, it must:
First, be able to apply an adequate Artificial Intelligence.
That is to say, it must prepare a correct data architecture, which allows to unify information from different origins and expand the potential of our models.
Thus, it will be possible to integrate databases from the different departments of the company, information from social networks, live events that can nourish our knowledge, etc.
In this way, you will be able to understand well the company’s context and be able to have that competitive advantage.
Therefore, the relevant data that will allow us to make the right business decisions.
Also, it will be possible to work with all of them in different geographical locations.
This would help us to implement our Artificial Intelligence models.
But what if that information comes from images? How do we work with it to improve our analysis?
It will be possible thanks to Computer Vision.
Computer Vision, the AI for working with images
What is Computer Vision?
Computer Vision is the scientific field that allows machines to be able to understand and analyze images and videos.
Let’s take a look at the uses of Computer Vision:
- Detection of people or objects:
- If we implement a camera system we can be able to detect the different elements that the camera visualizes.
- For example, in a factory to detect if a person is in a restricted area,
- or whether a certain part in the production line is valid or not.
- Facial recognition.
- We can recognize people’s faces in order to restrict access to some place.
- for example to unlock technological devices.
- Important to be based on AI Responsible.
- Spatial analysis.
- We can analyze the space visualized by a camera in order to calculate distances, trajectories…
- Also, the objects in those spaces.
- All this allows Computer Vision to help to implement intelligent systems.
- In this way, it offers security and analytics to our business.
- But another question arises, how do we make all the information available?
Unify everything, the key to correct analysis.
Therefore, if we have been able to integrate a correct data architecture, we will be able to analyze data from different origins.
Also, something key, is that it will be of different nature (such as images and videos).
Therefore, if in our data analysis we are able to add the results that Computer Vision offers us, we will be able to make decisions that are much more aligned with the context of our company.
Let’s look at some examples:
- Capacity analysis in stores:
- Computer Vision makes it possible to detect the number of people in the store.
- In addition, it will be possible to determine how many people have approached a specific place in the store.
- If this data obtained is unified with data from turnover or marketing campaigns, you will be able to obtain clear indicators of how that campaign affects the actual turnover.
- Detection of invalid parts in a factory.
- Computer Vision makes it possible to classify correct and defective parts on an assembly line.
- Thus, it can detect if any element of the part is not correct.
- Therefore, it should be removed from the assembly line to avoid future problems.
- This allows safety in the chain, as well as speed in the quality process.
- In addition, to obtain this information and store it correctly, allowing the development of an analysis in which both the suppliers’ databases and the tracking and treatment of the part in previous steps come into play.
- Therefore, it will be possible to create indicators to optimize processes.
- In addition, economic decisions can be made regarding future purchases.
- Space optimization.
- Warehouses must ensure a correct optimization of each storage space they have.
- With Computer Vision you can analyze the empty space in different areas and determine how many meters are free each day.
- That is, through spatial analysis.
- Therefore, if this information is unified with the orders that the Supply Chain department, its periodicity, it will be possible to optimize the orders in time and form.
- Also, the space to achieve a correct purchasing and management process.
Therefore, these examples, and many more, show us the capacity that Computer Vision.
That, together with a good data architecture, offers opportunities to draw conclusions and make decisions appropriate to the business context.
Therefore, by developing Artificial Intelligence models and data architectures, optimal results will be achieved quickly.
In this way, the organizations that implement it will offer a great competitive advantage.
Would you be interested in learning more about Computer Vision and see all the possibilities it offers for your business? At Bravent, we want to help you grow.
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