Improvement of air pollution prediction in a smart city and its correlation   with weather conditions using metrological big data

TALAT ZAREE; ALI REZA HONARVAR

Makale detayları

Improvement of air pollution prediction in a smart city and its correlation with weather conditions using metrological big data

Yazarlar:

TALAT ZAREE | ALI REZA HONARVAR

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 3, pp.1302-1313

Belge Tipi:

Makale

Yayın Tarihi:

5/2018

Belge Dili:

Türkçe

Document ID (Org No.):

2000735082

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

Smart cities are an important concept for urban   development. This concept addresses many current critical urban problems   including traffic and environmental pollution. As utilization of the   Internet of things and technology in smart cities increases, large volumes   of big data are generated and collected by sensors embedded at different   places in the city, which present a real-time display of what is happening   throughout the city at all times. Such data should be processed and analyzed   as a response to ensure effectiveness and improvement in quality of provided   services; correct use and analysis of such data is valuable. Big data mining   is the most effective method for analyzing such data. In this paper, aiming   to increase speed and accuracy in predicting real levels of air pollution,   its location, and effects of weather conditions on density of air pollution,   a K-means clustering algorithm using the Mahout library is used as a big   data mining tool on datasets of a city pulse project. Results of this study   show that temperature, low air pressure, relative increase in moisture, and   wind speed are causes of low pollution density at the cleanest point of the   city. The SSE evaluation metric shows the high speed of this clustering   method for big data, and results obtained from employing RMSE = 0.632 and   MSE = 0.488 statistical measures indicate the high efficiency and accuracy   of the proposed method in predicting air pollution.

Makale detayları

Improvement of air pollution prediction in a smart city and its correlation with weather conditions using metrological big data

Yazarlar: TALAT ZAREE | ALI REZA HONARVAR

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 3, pp.1302-1313

Belge Tipi: Makale

Yayın Tarihi: 5/2018

Belge Dili: Türkçe

Document ID (Org No.): 2000735082

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

TALAT ZAREE | ALI REZA HONARVAR

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 3, pp.1302-1313

Belge Tipi:

Makale

Yayın Tarihi:

5/2018

Belge Dili:

Türkçe

Document ID (Org No.):

2000735082

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632