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dc.contributor.authorGupta, Karunesh Kumar-
dc.date.accessioned2023-02-28T10:01:02Z-
dc.date.available2023-02-28T10:01:02Z-
dc.date.issued2020-
dc.identifier.urihttps://ieeexplore.ieee.org/document/9376497-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9383-
dc.description.abstractWith the advent of technology, more and more aspects of our lives are being digitized. Hence, eventually, there will be a need for sensor-based networks for creating sustainable living conditions. This paper aims to describe the implementation and application of an Air Quality monitoring and analysis network(AQMAN) capable of monitoring different air quality parameters which could then be used to predict the sustainability of a locality at the expense of precision. The network employs various Machine Learning algorithms for forecasting the parameters on multiple time granularity. A method for constructing a Geo-spatial graph of the parameter's concentration has also been discussed in the later sections. The paper takes a more pragmatic approach of making the system cheaper, reliable, scalable and accessible.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectEEEen_US
dc.subjectSoft Sensorsen_US
dc.subjectAir Quality Index(AQI)en_US
dc.subjectInternet of Things(IoT)en_US
dc.subjectLong Short Term Memory(LSTM) unitsen_US
dc.titleAir Quality Monitoring and Analysis Networken_US
dc.typeArticleen_US
Appears in Collections:Department of Electrical and Electronics Engineering

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