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Air quality is a key determinant of people’s respiratory and cardiovascular health, as air pollution can increase the risk of diseases such as asthma, chronic lung diseases and cardiovascular conditions. In addition, studies have shown that prolonged exposure to air pollutants such as nitrogen dioxide (NO2) and particulate matter (PM2.5) is directly related to a shorter life expectancy.

In this regard, the increasing application of technologies such as artificial intelligence (AI) emerges as a key tool to address this problem. It has become an increasingly relevant resource, contributing significantly to the improvement of air quality and thus to the well-being of society. Artificial intelligence allows us to be able to process a large amount of information that a human is not capable of processing, and to bring systems to the optimal point of operation. Data will have an increasingly greater influence on our daily lives and will allow us to make decisions, not only at the operational level, but also at the investment level, identifying those systems whose renewal is of greater benefit.

Today, both AI and the Internet of Things (IoT) are transforming the management of ventilation systems, especially in infrastructures where environmental conditions play a crucial role. A prime example is the implementation of AI systems based on machine learning, which, being based on data, constant learning and adaptability, allow for forecasting future situations, guaranteeing real-time control of installations and facilitating efficient management of investments, ensuring adequate indoor air quality and a higher return on investment.

AI to improve air quality

An article by Guillem Peris, director of the Respira® project.

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But, in addition to facility management, it is crucial to consider efficiency, maintenance and sustainability. Proper management of the HVAC installation is essential to ensure thermal comfort, air quality and energy efficiency. Lack of proper control and optimisation can lead to serious problems, such as areas with uncomfortable temperatures and health problems due to exposure to high levels of CO2 and VOCs. Therefore, it can be stated that the key is to satisfy in a balanced way these three vectors: thermal comfort, air quality and energy efficiency, without harming one for the benefit of the others.

For example, one use case is the calculation of the dynamic occupancy of a facility. Imagine the auditorium of a hospital, where there are no people at a given moment, but an event is planned where 500 people are expected to arrive. A traditional system would heat the space up to the setpoint temperature (e.g. 22ºC) and once 500 people arrive, the temperature of the space would increase due to the heat emitted by the people, requiring the air conditioning to be switched on. An AI-based system that predicts behaviour would heat at a lower temperature, taking advantage of the fact that the temperature will rise due to people to save on heating and subsequent cooling. It would also anticipate potential air quality problems by predicting the behaviour of air quality levels based on occupancy and dwell time.

Another example – a real case in fact –, is the deployment of Respira, an intelligent air conditioning management system based on AI, in the Barcelona Metro, whose application produced an average annual energy saving in the installation of 25.1%, achieving savings of €1.7 MM the year of its application.

The future is built on informed decisions and advanced technologies, and in this respect, AI is playing an essential role in improving our quality of life and ensuring cleaner and healthier air for all.