Autors: Marinov, M. B., Topalov, I. P., Ganev, B. T., Geva, E. E., Galabov, V. T.
Title: UAVs based particulate matter pollution monitoring
Keywords: air quality, environmental monitoring, unmanned aerial vehic

Abstract: Technologies using Unmanned Aerial Vehicles (UAVs) have been the subject of research for many years now. They are increasingly used in a number of public and private projects. UAVs with their mobility and ability to fly at different altitudes can compensate for some shortcomings in the wireless sensor network and offer an alternative approach to data harvesting. With their help, it is easy to allow spatial research of different areas/spaces. This is particularly important in the study of air pollution, which changes sharply even over relatively short distances in the horizontal and vertical directions. In the present study is presented a research of possibilities for application of a new instrument for studying the air quality at different altitudes, which is accessible to a wide range of users. The approach is based on using cheap UAVs and low-cost air quality sensors. This paper shows the relevance of a customized, off the shelf UAV equipped with mobile monitoring devices as an effe

References

  1. S. Hayat, E. Yanmaz and R. Muzaffar, "Survey on unmanned aerial vehicle networks for civil applications: A communications view- point," IEEECommunications Surveys and Tutorials, vol. Quarter 4, 2016.
  2. "OPC-N3 Particle Monitor, Technical Specification," Alphasens Alphasense Ltd, Sensor Technology House, Great Notley, UK, March 2019.
  3. P. Haas, C. Balistreri, P. Pontelandolfo, G.Triscone, H. Pekoz and A. Pignatiello, "Development of an unmanned aerial vehicle UAV for air quality measurements in urban areas," in 32nd AIAA Applied Aerodynamics Conference,(AIAA 2014-2272), 2014.
  4. G. M. Bolla et al., "ARIA: Air Pollutants Monitoring Using UAVs,"," in 2018 5th IEEE International Workshop on Metrology for AeroSpace (MetroAeroSpace), Rome, 2018.
  5. M. Alvarado, F. Gonzalez, P. Erskine, D. Cliff and D. Heuff, "A Methodology to Monitor Airborne PM10 Dust Particles Using a Small Unmanned Aerial Vehicle," Sensors, vol. 17, no. 2, 2017.
  6. F. G. Toro and A. Tsourdos, UAVBased Remote Sensing, Vol. 1 - 2, May 2019.
  7. A. I. Ivanov, A Basic Course of Fluid Mechanics, (in Bulgarian), Sofia: Avangard Prima, 2016, p. 542.
  8. "Computational Fluid Dynamics Software," SimScale , 2019. [Online]. Available: https://www.simscale.com/product/cfd/.
  9. Babaan, J. B.; Ballori, J. P.; Tamondong, A. M.; Ramos, R. V.; Ostrea, P. M., "Estimation of pm2.5 vertical distribution using customized UAV and mobile sensors in Brgy. up campus, Diliman, Quezon city," Int. Arch. Photogramm. Remote Sens. Spatial Inf..
  10. S.-L. von der Weiden, F. Drewnick and S. and Borrmann, "Particle Loss Calculator – a new software tool for the assessment of the performance of aerosol inlet systems," Atmos. Meas. Tech., vol. 2, no. 2, pp. 479-494, 2009.

Issue

28th International Scientific Conference Electronics, ET 2019, pp. 1-4, 2019, Bulgaria, IEEE, DOI 10.1109/ET.2019.8878586

Copyright IEEE

Цитирания (Citation/s):
1. Vazquez-Carmona, Esther & Vasquez-Gomez, Juan. Sistema electrónico para el monitoreo de gases de efecto invernadero utilizando internet de las cosas y vehı́culos aéreos no tripulados. 10.13140/RG.2.2.15858.53443 - 2019 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
2. D. Nikolov, B. Ganev, M. B. Marinov and N. Nikolov, "Smart Sensor Node for Distributed Noise Monitoring," 2020 XXIX International Scientific Conference Electronics (ET), Sozopol, Bulgaria, pp. 1-4, doi: 10.1109/ET50336.2020.9238169 - 2020 - в издания, индексирани в Scopus или Web of Science
3. Z. Han, X. Zhu and L. Xu, "Scheduling Rechargeable UAVs for Long Time Barrier Coverage," 2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS), Hong Kong, 2020, pp. 282-289, doi: 10.1109/ICPADS51040.2020.00046 - 2020 - в издания, индексирани в Scopus или Web of Science
4. Chodorek, A.; Chodorek, R.R.; Sitek, P. UAV-Based and WebRTC-Based Open Universal Framework to Monitor Urban and Industrial Areas. Sensors 2021, 21, 4061. https://doi.org/10.3390/s21124061 - 2021 - в издания, индексирани в Scopus или Web of Science
5. Ming, Z. , Huang, H. A 3d vision cone based method for collision free navigation of a quadcopter UAV among moving obstacles, (2021) Drones, - 2021 - в издания, индексирани в Scopus или Web of Science
6. Ganev, B., Marinov, M.B., Nikolov, D., Ivanov, A., High-resolution Particulate Matter Monitoring and Mapping in Urban Environments, 12th National Conference with International Participation, ELECTRONICA 2021 - Proceedings 9513728 - 2021 - в издания, индексирани в Scopus или Web of Science
7. Chodorek, A., Chodorek, R.R., Yastrebov, A., The Prototype Monitoring System for Pollution Sensing and Online Visualization with the Use of a UAV and a WebRTC-Based Platform, Sensors 22(4),1578 - 2022 - в издания, индексирани в Scopus или Web of Science
8. Rajesh K, Ch LR, Varaprasad G, Muralikrishnan S. A cellular IoT based sensor system for atmospheric studies using UAVs. In: SPICES 2022 - IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems; 2022. p. 263-7. DOI: 10.1109/SPICES52834.2022.9774182 - 2022 - в издания, индексирани в Scopus или Web of Science
9. Velichkova R., Pushkarov M., Simova I., (...), Pavlova Y., Alexandrov A., Harnessing the Energy of Moving Water to Generate Electricity in Bulgaria, Green Energy and Technology, pp. 129-164. - 2023 - в издания, индексирани в Scopus или Web of Science

Вид: постер/презентация в международен форум, публикация в реферирано издание, индексирана в Scopus и Web of Science