Loja Arevalo, Pablo SantiagoOrellana Cordero, Marcos PatricioCedillo Orellana, Irene PriscilaLima Sigua, Juan FernandoZambrano Martinez, Jorge Luis2023-01-232023-01-232022978-303118271-61865-0929https://www.scopus.com/record/display.uri?eid=2-s2.0-85140735029&doi=10.1007%2f978-3-031-18272-3_12&origin=inward&txGid=ef2b636596fdc6c3c3dd2fcb4a67ceadNowadays, the world faces a high level of environmental pollution. This phenomenon has become a constant challenge for our society due to its negative impact on health and the increased risk of disease. Considering this problem, applications, techniques and methodologies are generated that seek to relate atmospheric pollutants to each other to predict the state of the air. On the other hand, recommendation systems are present in numerous decision-making methods to find trends in various fields. Consequently, this work presents a methodology for a recommender system that provides people with the best hours to perform outdoor activities according to the pollutants found in the environment. The results obtained were verified through an evaluation and thus be able to contribute to the creation of new recommenders based on the previous topicses-ESAir pollutantsAir qualityData miningMeteorological variablesRecommender systemsARTÍCULO DE CONFERENCIA10.1007/978-3-031-18272-3_12