AI improves the quality of life: thanks to technology, people receive feedback faster, use quality services, spend less energy on routine and, as a result, can devote more time to what interests them. When used correctly, neural networks are capable of saudi arabia phone number globally transforming urban spaces. How exactly they are integrated and what this gives is described in the article.
Concept and main technologies of artificial intelligence
Artificial intelligence is the ability of a computer system to solve problems and perform actions that require intelligent thinking. These include learning, data analysis, speech recognition, decision making, and other complex cognitive functions. AI is based on several key technologies: machine learning, neural networks, and big data processing.
Machine learning is a method that allows computers to learn from incoming information. A model is built on a large amount of input data, analyzes it, and forms predictions or decisions. All this happens without the need for explicit programming at each stage. Another technology, neural networks, are multi-level systems that can automatically learn and adapt. Their use allows solving problems related to image, speech, and text recognition.
An integral part of AI is also the processing of Big Data. Modern cities generate colossal amounts of information - from traffic and resource consumption to population information. It is difficult for a person to cope with such volumes, but a machine can do it 24/7 without getting tired. Being able to process huge amounts of received data, artificial intelligence can use them to solve complex problems in the urban environment.
Development
By using various electronic devices integrated into the city infrastructure, it is possible to collect a huge amount of information about the population, energy consumption, traffic and other aspects of city life. Based on this data, artificial intelligence creates the most accurate and effective models of city management.
Efficient use of resources
AI skills in scanning data, analyzing peak energy usage times, and predicting maximum costs have been successfully applied to government buildings in Suwon, South Korea. After optimization, energy efficiency increased by 30%, administrative costs were reduced by 50%, and carbon emissions were reduced by 35%.
Another example is the Google Sunroof service, which uses AI to analyze solar energy available on the roofs of buildings. The system calculates how much money a user can save on it, allowing both residents and organizations to assess the potential of installing solar panels and their efficiency in a specific location. As a result, energy is used more rationally and the load on traditional sources is reduced.
There are a number of developments in Russia as well. For example, a solution in the field of environmental monitoring created by a team from the Perm campus allows predicting the dynamics of movement of harmful substances in the air and assessing the most probable point of emission. Thus, the use of modern technologies also helps to follow the ESG agenda, which is extremely relevant in our time .
Architecture and urban design
AI-powered tools for architects and designers are already commonplace. Floor plans, 3D models, and even complete building designs can all be generated using neural networks. They are used to create designs that are aesthetically pleasing, functional, and sustainable. PromeAI, Leonardo.Ai, ArchiVinci, Gendo, Architectures, Autodesk Forma are just a few of the generators that generate such solutions. There are platforms for almost every task. For example, NVIDIA's The AI System helps integrate styles and shapes in architectural sketches, while The Living's "Hy-Fi" at MoMA PS1 helps optimize building shapes for environmental parameters.
Artificial intelligence also helps designers. For example, the Ant Road Planner pedestrian modeling system developed by ITMO University simulates pedestrian behavior in a specific area, thereby allowing to predict traffic routes and build an optimal layout of paths to avoid the emergence of spontaneous paths. Another example is the use of AI in multi-variant design. Thus, if earlier an engineer could spend weeks on calculating and designing complex hydraulic systems, neural networks allow to do the same work in a matter of minutes, analyzing many options and offering optimal solutions.