Sensors International (Jan 2024)

Integration of carbon dioxide sensor with GNSS receiver for dynamic air quality monitoring applications

  • Lin Yola,
  • Garrin Alif Nanditho,
  • Kaito Kobayashi,
  • Dinesh Manandhar

Journal volume & issue
Vol. 5
p. 100279

Abstract

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Air pollution is a significant problem in big cities due to the rapid increase of anthropogenic activities and severe traffic congestion. Therefore, real-time and micro tools for air monitoring are urgently necessary for fast and better policy decision-making. The current city air monitoring tool is typically static and serves a macro area. This study introduces technology development to integrate the air quality sensor with the satellite-based navigation receiver. This study used a carbon dioxide (CO2) MH-Z19C sensor and real-time kinematic global navigation satellite system (RTK GNSS) U-Blox F9P with GNSS Trimble NetR9 receiver. The field air quality monitoring (CO2 observed in ppm) and the movement velocity (vehicle speed observed in km/h) were recorded on two main roads of Jakarta by using a survey vehicle. The study compares the observation results of the non-integrated system (NIS) and integrated technology system (IS). The two systems generated the CSV database (CO2 and vehicle speed); however, IS generated the automatic synchronized and error-free data output. The statistical regression analysis of CSV data (CO2 and vehicle speed) between the NIS and IS reported significant results, which means both are reliable. Still, the NIS did not require manual synchronization, with some possibility of error. The R square values show a significant gap (speed 0.99 over CO2 0.144), indicating that IS needs further development as the CO2 data varies due to technicality. The finding presents that integrating the CO2 sensor and GNSS receiver generates a more effective time synchronization process and a reliable error removal technique in developing the CSV data. This finding is a significant reference in developing the integrated satellite-based receiver system with external environmental sensors.

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