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

共 50 条

[41] Physical Activity Monitoring and Classification Using Machine Learning Techniques
Alsareii, Saeed Ali
Awais, Muhammad
Alamri, Abdulrahman Manaa
AlAsmari, Mansour Yousef
Irfan, Muhammad
Aslam, Nauman
Raza, Mohsin
[J]. LIFE-BASEL, 2022, 12 (08):
[42] An Effective Smart Water Quality Monitoring and Management System Using IoT and Machine Learning
Shanvendra Rai
Dhanasree S. Poduval
Utkarsh Anand
Vishnu Verma
Subhasish Banerjee
[J]. SN Computer Science, 5 (7)
[43] A Conceptual Framework for Cyber-Physical Quality Monitoring System using Machine Learning
Chacko, Mathew
Atul
Boddapati, Satish Babu
[J]. JORDAN JOURNAL OF MECHANICAL AND INDUSTRIAL ENGINEERING, 2022, 16 (05): : 821 - 833
[44] Air quality monitoring for Smart eHealth system using firefly optimization and support vector machine
Rahi P.
Sood S.P.
Bajaj R.
Kumar Y.
[J]. International Journal of Information Technology, 2021, 13 (5) : 1847 - 1859
[45] Air pollution prediction using machine learning techniques-An approach to replace existing monitoring stations with virtual monitoring stations
Samad, A.
Garuda, S.
Vogt, U.
Yang, B.
[J]. ATMOSPHERIC ENVIRONMENT, 2023, 310
[46] Question Answering System using Machine Learning Techniques
Dobrescu, Alexandra-Maria
Radu, Serban
[J]. VISION 2025: EDUCATION EXCELLENCE AND MANAGEMENT OF INNOVATIONS THROUGH SUSTAINABLE ECONOMIC COMPETITIVE ADVANTAGE, 2019, : 10226 - 10237
[47] ON THE DETECTION OF VOLATILE ORGANIC COMPOUNDS (VOCS) USING MACHINE LEARNING AND FTIR SPECTROSCOPY FOR AIR QUALITY MONITORING
Riad, Michael M. Y. R.
Sabry, Yasser M.
Khalil, Diaa
[J]. PROCEEDINGS OF 2019 36TH NATIONAL RADIO SCIENCE CONFERENCE (NRSC), 2019, : 386 - 392
[48] RETRACTED ARTICLE: Development of air quality monitoring (AQM) models using different machine learning approaches
C. Amuthadevi
D. S. Vijayan
Varatharajan Ramachandran
[J]. Journal of Ambient Intelligence and Humanized Computing, 2022, 13 : 33 - 33
[49] Air Quality Class Prediction Using Machine Learning Methods Based on Monitoring Data and Secondary Modeling
Liu, Qian
Cui, Bingyan
Liu, Zhen
[J]. ATMOSPHERE, 2024, 15 (05)
[50] OPTIMIZATION OF HYPER PARAMETERS IN MACHINE LEARNING TECHNIQUES FOR AIR QUALITY PREDICTIVE ANALYSIS
Patil, Basamma Umesh
Ashoka, D., V
Prakash, Ajay B., V
[J]. INTERNATIONAL JOURNAL ON INFORMATION TECHNOLOGIES AND SECURITY, 2021, 13 (03): : 73 - 86

← 1 2 3 4 5 →