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An Internet of Things Framework to Forecast Indoor Air Quality Using Machine Learning
Rastogi K.,
Published in Springer
Volume: 1203 CCIS
Pages: 90 - 104
Good air quality is critical to healthy and productive life in the indoor environment. Quality of air inside buildings depends on several factors. Till now, it was not possible to measure and monitor indoor air quality (IAQ) through mobile phones and wireless sensors in real time, as standardized miniature sensors were not commercially available. With the introduction of wireless air quality sensors that can pair with most contemporary smartphones, it is now possible to monitor indoor environment pervasively in real time, take precautionary measures, and maintain a healthy life. In this work, we have created an IoT sensing system to monitor and analyse the time variation of carbon dioxide in a university classroom. Using the sensed data, forecast models have been developed to predict the build-up of carbon dioxide, an indicator of IAQ. © Springer Nature Singapore Pte Ltd. 2020.
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Published in Springer
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