We have all heard about artificial intelligence and its capabilities: news about innovative developments,
Briefly about AI
Artificial intelligence is a range of technologies andalgorithms that are capable of imitating some cognitive functions inherent in humans. However, it is important to understand that AI technology is far from the “superbrain” it is often associated with. It is still just a technology that does not have consciousness, cannot think and reason like a person.
However, there are a number of tasks that are close in cognitive characteristics to human thinking. These are the ones that are successfully solved by artificial intelligence, and they are usually called “AI problems.”
These tasks include:
- Computer vision and object recognition: You can show the algorithm a photo or video stream, from which the program will select data and perform a classification.
- Speech synthesis recognition: algorithms convert speech signals into digital information, which the program also classifies.
- Working with a stream of various information, including “natural language” data: applicable when you have a large database.
- Decision Support: Algorithms generate a decision function.
All these tasks are the main directions inimplementation of AI elements. And all of them are already being actively integrated into our daily lives: from automated assistants on websites to “smart” cameras on city streets.
AI in ecology
AI is relevant and effective for many industries, the development of education and even culture. But it also significantly influences the transformation of the environmental sphere.
Already at waste processing plantsThere are robots that help sort waste. The technology is being implemented in systems for monitoring and analyzing air, water bodies and soils. And each of us can meet “eco-friendly” AI, for example, at automatic recycling collection points.
In general, it is impossible to single out any specifics of AIspecifically in ecology. With its help, you can significantly reduce costs, which is important for any business. Thus, when a real person is replaced by a “machine” in a recycling collection system, the entire process is automated, and the cost of servicing the devices is reduced.
How to train AI to recognize recyclables
Pattern recognition is one of the mostcommon AI tasks. The most suitable solution for this problem is convolutional neural networks - a computer program model that is closest to how a person recognizes objects in reality. The “layers” of such a network are similar to the layers of the retina.
A neural network is a simplified model of operationhuman brain. Its basic elements - neurons - have a large number of connections and relationships, which are usually grouped into layers. Each connection of neurons is assigned a certain force of influence - weight. Input data to the network is supplied to the first layer, then it is distributed to the next layers in accordance with the current weight of the relationships. The final result can be obtained from the last layer of the neural network.
Training a convolutional neural network consists ofselecting the weight of neuron connections in order to obtain the correct result as a result of its work on the last layer of the network. In the case of recognizing recyclable materials, two problems are solved: segmentation - determining the area in the photo with the object and classification, understanding what kind of object it is. Therefore, in this case, two sequentially operating neural networks are used: the first receives an image as an input and outputs the contours of the found objects, and the second sequentially processes the found contours and returns the belonging of each contour to a certain class of objects.
Submitting a set of examples (images) “as input”called “supervised learning.” This process requires a large number of photographs in which the necessary objects are circled and labeled. When teaching technology in a recycling machine, you will need to collect more than 50,000 images of objects.
By showing a large number of images “at the input” andBy measuring the quality of their “output”, it is possible to build and select specific neurons in the network. If the hypotheses for the selection of neurons turn out to be correct, the network is trained, then the error is gradually minimized. Ideally, as a result of training, the network should accurately recognize the images that were loaded into it and identify similar images.
Nuances of recognition
Crumpled plastic bottles, twisted aluminum cans, wet waste paper - how can AI understand which recyclables can be recycled and what fractions it can be divided into?
When teaching AI technology, it is important to includethe human factor, because it will be people who will load the recyclables, who for the most part will not care about the quality of the waste being handed over. Let us clarify that quality here means purified recyclable materials that are suitable for processing.
To keep different scenarios in mind and preparetechnology, the developers include among the downloaded sample images those same “damaged” objects. So, AI can learn to recognize the same plastic bottles in any of their forms. For example, a bottle has a characteristic cap or a certain texture, which is fixed with a network.
The fractions of supplied raw materials are determined by external forms, standards, and textures. And based on the stored data of fraction weight categories, you can calculate, for example, wet waste paper.
In the future, the technology is trained in the processwork: when he sees real objects rented out by people. Operators process incoming new data, select the necessary images and adjust the network.
AI is becoming universal over timea tool that helps optimize various areas of production and our lives. In ecology, this is the ability to respond in a timely manner to certain circumstances, reduce costs and minimize errors that may be made due to the human factor in work.
However, like any technology, AI requirescontinuous improvement. Thus, in the field of recycling collection, additional training of smart devices occurs regularly. Time will tell to what extent AI can improve ecological processes and improve the environment on a global scale. But it is already clear that the use of artificial intelligence is one of the effective steps towards our green future.
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