There are many companies that use Artificial Intelligence for their services or applications, but do we know how it really works? Artificial Intelligence is a combination of algorithms that allows machines to have an intelligent behavior to act appropriately for different situations.
Evolution of technologies
Thanks to the constant development of technology and the large amounts of data available to us today, material detection problems can be solved, even if they are much more complex today than in the past. Surely hardware or software are words familiar to everyone; when we talk about hardware, we refer to robots or other types of automation, while software refers to vision and artificial intelligence.
Artificial Intelligence is composed of two major branches: Machine Learning and Deep Learning. What do these terms mean and what are the differences between them?
- Machine Learning is a subset of Artificial Intelligence where people train machines to recognize patterns based on data and make their predictions.
- Deep Learning is a subset of Machine Learning where the machine can reason and draw its own conclusions by learning on its own. Deep Learning also recognizes patterns like Machine Learning, the difference is that they are more complex problems for the machines, for that reason, it is necessary to train the neural networks in a deeper way.
What technologies do we use in PICVISA?
Currently, the technology used by PICVISA is Artificial Intelligence together with Machine Vision. The basis of machine vision is that it makes decisions based on image analysis; the algorithm identifies patterns in these, which allow the classification of different classes of objects within a heterogeneous flow. Currently, one of the technologies that gives the best results in classification and detection of objects in images is Deep Learning.
Deep Learning is a type of Machine Learning that consists of establishing basic parameters on the data we are interested in and, based on these, training the machine through automatic learning in which it manages to recognize different patterns using many layers of processing. This technology can be used with RGB color cameras, which provide information about what the image is, or cameras with near infrared spectroscopy (NIR) sensors that, on the other hand, tell us what type of material the object is made of.
A promising future?
With technology advancing by leaps and bounds and the recycling industry evolving at a stratospheric rate, in a few years Artificial Intelligence will make it possible for robots to adapt to changes without having to learn in advance which objects to dispose of.
Thanks to Deep Learning, we can automate the process much more and also increase the purity of recyclable materials. Looking ahead, AI will continue to push the boundaries in the recycling industry and offer a wide range of sorting possibilities that will allow us to recover materials we had never imagined.
At PICVISA we lead the market in optical sorters for waste recycling; our robots are versatile, flexible, and efficient. In addition, our optical sorting technology improves product quality, maximizes throughput, and increases efficiency, as well as reducing labor costs. Thanks to our vision and artificial intelligence solutions, we help companies to be more competitive by reducing their costs and improving their productivity.
In PICVISA we have been helping recycling plants to increase their productivity with Machine Vision and Artificial Intelligence solutions for more than 20 years. Visit our website and learn more about PICVISA’s optical sorters.