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Item type:Publication, An air quality monitoring and forecasting system for Lima city with low-cost sensors and artificial intelligence models(Frontiers Media S.A., 2022-07-07)Monitoring air quality is very important in urban areas to alert the citizens about the risks posed by the air they breathe. However, implementing conventional monitoring networks may be unfeasible in developing countries due to its high costs. In addition, it is important for the citizen to have current and future air information in the place where he is, to avoid overexposure. In the present work, we describe a low-cost solution deployed in Lima city that is composed of low-cost IoT stations, Artificial Intelligence models, and a web application that can deliver predicted air quality information in a graphical way (pollution maps). In a series of experiments, we assessed the quality of the temporal and spatial prediction. The error levels were satisfactory when compared to reference methods. Our proposal is a cost-effective solution that can help identify high-risk areas of exposure to airborne pollutants and can be replicated in places where there are no resources to implement reference networks. - Some of the metrics are blocked by yourconsent settings
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Item type:Publication, Assessment of the level of knowledge on artificial intelligence in a sample of university professors: A descriptive study(Editorial Salud, Ciencia y Tecnologia, 2024-01-01)the knowledge of artificial intelligence (AI) by university professors provides them with the ability to effectively integrate these innovative technological tools, resulting in a significant improvement in the quality of the teaching and learning process. to assess the level of knowledge about AI in a sample of Peruvian university professors. Methods: quantitative study, non-experimental design and descriptive cross-sectional type. The sample consisted of 55 university professors of both sexes who were administered a questionnaire to assess their level of knowledge about AI, which had adequate metric properties. Results: the level of knowledge about AI was low for 41,8 % of professors, regular for 40 %, and high for 18,2 %. This indicates that there is a significant gap in the knowledge of university professors about AI and its application in education, which could limit their ability to fully leverage AI tools and applications in the educational environment and could affect the quality and effectiveness of teaching. Likewise, it was determined that age and self-perception of digital competencies of professors were significantly associated with their level of knowledge about AI (p<0,05). Conclusions: peruvian university professors are characterized by presenting a low level of knowledge about AI. Therefore, it is recommended to implement training and professional development programs focused on artificial intelligence, in order to update and improve their skills in this field.