casa 18: e3

Research Article

Air Quality Monitoring Systems with Multiple Data Sources for Ho Chi Minh City

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  • @ARTICLE{10.4108/eai.24-5-2021.169971,
        author={Cuong Pham-Quoc and Tran Ngoc Thinh and Trong Nhan Le and Phan Hien Vu and Tan Long Le and Kha Huynh Hoang},
        title={Air Quality Monitoring Systems with Multiple Data Sources for Ho Chi Minh City},
        journal={EAI Endorsed Transactions on Context-aware Systems and Applications: Online First},
        volume={},
        number={},
        publisher={EAI},
        journal_a={CASA},
        year={2021},
        month={5},
        keywords={Air quality index, air pollution, smart city, fine particulate matter, remote sensing images},
        doi={10.4108/eai.24-5-2021.169971}
    }
    
  • Cuong Pham-Quoc
    Tran Ngoc Thinh
    Trong Nhan Le
    Phan Hien Vu
    Tan Long Le
    Kha Huynh Hoang
    Year: 2021
    Air Quality Monitoring Systems with Multiple Data Sources for Ho Chi Minh City
    CASA
    EAI
    DOI: 10.4108/eai.24-5-2021.169971
Cuong Pham-Quoc1,2,*, Tran Ngoc Thinh1,2, Trong Nhan Le1,2, Phan Hien Vu2,3, Tan Long Le1,2, Kha Huynh Hoang1,2
  • 1: Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet, District 10, Ho Chi Minh City, Vietnam
  • 2: Vietnam National University – Ho Chi Minh City, Thu Duc District, Ho Chi Minh City, Vietnam
  • 3: International University – VNU-HCM, Thu Duc District, Ho Chi Minh City, Vietnam
*Contact email: cuongpham@hcmut.edu.vn

Abstract

In this paper, we present our proposed air quality monitoring system with multiple data sources for smart cities. We deploy our system in one of the biggest cities in Vietnam, Ho Chi Minh City. The proposed system uses data collected by our sensors and extracted from remote sensing images. The system also allows users to contribute by provide alerts through a portal. With data collected from sensors, we can provide exact values of fundamental parameters for calculating air quality index (AQI) while data extracted from remote sensing images help governors estimate the AQI values in surrounding areas without sensors deployed. This estimation although cannot provide exact information as sensors, it helps us to quickly understand AQI in an extremely large area with low cost. Along with these data sources, notifications from users also allow governors to react unawareness problems faster. Experimental results show the error (difference) between our systems and commercial devices is less than 24% for sensoring system and less than 9% for remote sensing images estimation. The sensoring system presented in this paper is low-energy consumption when using only 900mW in average.