Autors: Mihaylova, P., Manolova, A. H., Georgieva, P.
Title: Data analytics for home air quality monitoring
Keywords: Air quality monitoring, Analytics systems, Auto encoders, High complexity, Humidity and temperatures, Indoor air quality, Intelligent data processing, Temperature and humidities

Abstract: Modern air quality monitoring systems are characterised by high complexity and costs. The expensive embedded units such as sensor arrays, processors, power blocks, displays and communication units make them less appropriate for small indoor spaces. In this paper we demonstrate that two widely available, in private houses, sensors (for Humidity and Temperature) are promising alternative, to the expensive indoor air quality solutions, provided with intelligent data processing tools. Our findings suggest that neural network based data analytics system can learn to discriminate unusual indoor gases from normal home air components based only on temperature and humidity measurements.



    Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, 4th EAI International Conference on Future Access Enablers of Ubiquitous and Intelligent Infrastructures, FABULOUS 2019. Sofia, Bulgaria, 28 March 2019 through 29 March 2019, vol. 283, pp. 79-88, 2019, Switzerland, Springer, DOI 10.1007/978-3-030-23976-3_8, ISSN: 18678211

    Copyright Springer

    Вид: пленарен доклад в международен форум, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus