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вул. Інститутська 11, м. Хмельницький, 29016

МОБІЛЬНА БЕЗДРОТОВА СИСТЕМА ДЛЯ АНАЛІЗУ ЯКОСТІ ПОВІТРЯ

MOBILE WIRELESS SYSTEM FOR AIR QUALITY ANALYSIS

Сторінки: 184-191. Номер: №6, 2019 (279)
Автори:
А.В. КОВАЛЬ, А.Г. ТКАЧУК, М.С. ГРИНЕВИЧ
Державний університет «Житомирська політехніка»
Т.Л. КОВАЛЬ
Житомирський національний агроекологічний університет
A.V. KOVAL, A.H. TKACHUK, M.S. HRYNEVYCH
State University «Zhytomyr Polytechnic»
T.L. KOVAL
Zhytomyr National Agroecological University
DOI: https://www.doi.org/10.31891/2307-5732-2019-279-6-184-191
Рецензія/Peer review : 03.11.2019 р.
Надрукована/Printed : 14.01.2020 р.

Анотація мовою оригіналу

У роботі розглянуто реалізацію одного зі способів моніторингу та аналізу якості повітря з використанням безпілотного літального апарата. В результаті аналізу отриманих експериментальних даних було обрано основу для даної системи та проведено ряд досліджень.
Ключові слова: БПЛА, якість повітря, система моніторингу, мобільна система.

Розширена анотація англійською мовою

The purpose of this work is to develop an automated system for air quality monitoring and analysis based on the mini unmanned aerial vehicle. An automated mobile wireless air quality monitoring system has been developed as an alternative way of finding contaminants to replace ground based systems. It provides more flexible use than terrestrial systems. The main task is to improve and create an alternative system that will perform the same tasks as terrestrial systems, but will be faster and able to work in inaccessible places. The system collects pollution data and searches for gas leaks in various potentially hazardous locations. This system is compact, lightweight, capable of being mounted on any unmanned aerial vehicle, capable of operating in the absence of GPS signal and capable of rapid deployment and piloting by operator or offline without endangering human life. This project is a system based on a conventional commercial unmanned aerial vehicle of any model, equipped with a gas concentration sensor and controlled by the Robot Operating System (ROS). In the course of this project all problems related to stability of measurement data were solved. The system is now capable of providing consistently high quality measurement. Some measurement experiments are needed to study the relationship between the distance from a gas source to the measurement system and the measured gas concentration. The influence of UAV parameters, such as battery level, on the measurement values is investigated.
Keywords: UAV, air quality, monitoring system, mobile system.

References

  1. Vachtsevanos G. J., Valavanis K. P. (2014) Handbook of Unmanned Aerial Vehicles. (Springer Publishing Company).
  2. Koval A., Irigoyen E. (2017) Mobile Wireless System for Outdoor Air Quality Monitoring. In: Graña M., López-Guede J., Etxaniz O., Herrero Á., Quintián H., Corchado E. (eds) International Joint Conference SOCO’16-CISIS’16-ICEUTE’16. ICEUTE 2016, SOCO 2016, CISIS 2016. Advances in Intelligent Systems and Computing, vol 527. Springer, Cham.
  3. Quigley M., Conley K., Gerkey B., Faust J., Foote T., Leibs J., Wheeler R., Ng A.Y. (2009) Ros: an open-source robot operating system. In: ICRA Workshop on Open Source Software, vol. 3, p. 5.
  4. Mani Monajjemi. Ardrone autonomy. Mani Monajjemi (2015). URL: https://ardrone-autonomy.readthedocs.io/en/latest/installation.html.
  5. Repository for the tum_ardrone ROS package, implementing autonomous flight with PTAM-based visual navigation for the Parrot AR. Drone (2014). URL: http://wiki.ros.org/tum_ardrone.
  6. Adam A. How to Calibrate a Monocular Camera (2017). URL: http://wiki.ros.org/camera_calibration/Tutorials/MonocularCalibration.
  7. Grey C. Tutorial for calibrating the camera (2013). URL: http://wiki.ros.org/ethzasl_ptam/Tutorials/camera_calibration.
  8. Arduino Yún. 2017. URL: https://store.arduino.cc/arduino-yun.
  9. Sensor Humidity SHT1x datasheet (2010). URL: Rethttps://cdn.sparkfun.com/datasheets/Sensors/Pressure/Sensirion_Humidity_SHT1x_Datasheet_V5.pdf.
  10. ROS Tutorials (2017). URL: http://wiki.ros.org/ROS/Tutorials.
  11. Hongrong H., Jürgen S. Tum_simulator (2014). URL: http://wiki.ros.org/tum_simulator.
  12. GeoJSON (2016). URL: http://geojson.org/.
  13. Drone Developer Guide (2012). URL: https://jpchanson.github.io/ARdrone/ParrotDevGuide.pdf.
  14. Github with code of the project (2017). URL: https://github.com/OlehQWERTY/QT_AR_Drone_App.git.
  15. OpenGL Overview. URL: https://www.opengl.org/about/

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