Air Quality Monitoring Intelling System Using Machine Learning Techniques

被引：8

作者：

Rosero-Montalvo, Paul D. ^{[1
,2
]}

Caraguay-Procel, Jorge A. ^{[1
]}

Jaramillo, Edgar D. ^{[1
]}

Michilena-Calderon, Jaime M. ^{[1
]}

Umaquinga-Criollo, Ana C. ^{[1
]}

Mediavilla-Valverde, Mario ^{[1
]}

Ruiz, Miguel A. ^{[2
]}

Beltran, Luis A. ^{[2
]}

Peluffo-Ordonez, D. H.

机构：

[1] Univ Tecn Norte, Ibarra, Ecuador

[2] Inst Tecnol Super 17 Julio, Urcuqui, Ecuador

来源：

PROCEEDINGS 3RD INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS AND COMPUTER SCIENCE (INCISCOS 2018) | 2018年

关键词：

air quality; monitoring system; intelligent system;

D O I：

10.1109/INCISCOS.2018.00019

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Environment monitoring is so important because it is based on the first right of people, life and health. For this reason, this system monitoring air quality with different sensor nodes in the Ibarra that evaluate the parameters of CO2, NOx, UV Light, Temperature and Humidity. The data analysis through machine learning algorithms allow the system to classify autonomously if a certain geographical location is exceeding the established emission limits of gases. As a result, the k-Nearest Neighbor algorithm presented a great classification performance when selecting the most contaminated sectors.

引用

页码：75 / 80

页数：6

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