Knowledge for improving indoor air quality and health

What is KHealthInAir?

K-HEALTHinAIR is an interdisciplinary research project that aims to increase knowledge about chemical and biological indoor air pollutants affecting human health, and to provide solutions for more accurate monitoring and improvement of indoor air quality.

The project will leverage on a novel artificial intelligence algorithm and advanced data analysis to identify the determinants, their sources, and the potential health risks of indoor air quality.

A rigorous research action based on data collected through real-life scenarios, public health surveillance, and particularly vulnerable groups such as high-risk outpatients, elderly people, pregnant women, and children, will investigate the holistic correlations between indoor air quality characterization and its harmful effects on health.

K-HEALTHinAIR will

Deliver a new pragmatic knowledge base focused on easy identification of the main pathologies, associated body burdens, and health effects related to the presence of indoor polluting substances or their harmful combinations

Allow easy consultation of the knowledge generated by the project through a completely open-access platform developed according to the principles of usability, convenience, and simplicity

Provide user-friendly and affordable IAQ monitoring solutions, technological IAQ treatment solutions, and guidelines for IAQ improvement

Our latest news

Events

Indoor Air Quality in Schools: From Pilot Experience to Policy Action

6 March 2026

News

PRESS RELEASE: Exposure to CO2 of students in secondary schools in Poland – K-HEALTHinAIR’s Polish pilot insights

Air Quality in Schools Matters: K-HEALTHinAIR Project Findings Highlight the Need for More Effective Classroom Ventilation   Lodz, Poland, 14 Jul...
15 July 2026

PRESS RELEASE: Barcelona pilot shows how home air-quality sensors and hybrid care can protect high-risk respiratory patients

In Barcelona, K-HEALTHinAIR researchers combined low-cost sensors in patients' homes with a nurse-led, digitally enabled care model to detect risk ear...
15 July 2026

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