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A Fuzzy Control Based Method for Imaging Position Decision and Its Performance Evaluation

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Advances in Internet, Data & Web Technologies (EIDWT 2024)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 193))

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Abstract

Unmanned Aerial Vehicles (UAVs) are utilized in various fields such as aerial shots, transportation, spraying chemicals in agriculture and surveys of plant growth in forestry. In particular, aerial photography by drones is used for 3D surveying. Compared to surveying from the ground, 3D surveying with a drone provides more accurate surveying and a wider area can be surveyed in a shorter period of time. Also, drones can be used to survey inaccessible areas while flying. The point cloud data obtained from 3D surveying are used in various fields such as topographical surveying, disaster assessment, and archaeological site surveying. Currently, the Structure from Motion (SfM) is the most widely used 3D surveying method in terms of technology and price. The SfM is a 3D surveying technique that uses multiple images of an object. Therefore, it is important that the captured images contain many feature points and an appropriate focal distance. In this paper, we propose a fuzzy control based imaging position decision method and 3D measurement method using 2DLiDAR. The experimental results show that the proposed system can provide 3D measurement using 2DLiDAR and can decide imaging position based on fuzzy control.

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References

  1. Mademli, I., et. al.: Challenges in autonomous UAV cinematography: an overview. In: 2018 IEEE International Conference on Multimedia And Expo (ICME), pp. 1-6 (2018)

    Google Scholar 

  2. Mademli, I., et al.: Autonomous unmanned aerial vehicles filming in dynamic unstructured outdoor environments [applications corner]. IEEE Signal Process. Mag. 36(1), 147–153 (2018)

    Article  Google Scholar 

  3. Thiels, A., et al.: Use of unmanned aerial vehicles for medical product transport. Air Med. J. 34(2), 104–108 (2015)

    Article  Google Scholar 

  4. Villa, K.D., et al.: A survey on load transportation using multirotor UAVs. J. Intell. Robot. Syst. 98, 267–296 (2020)

    Article  Google Scholar 

  5. Huang, Y., et al.: Development of a spray system for an unmanned aerial vehicle platform. Environ. Pract. 25(6), 803–809 (2009)

    Google Scholar 

  6. Faiçal, S., et al.: The use of unmanned aerial vehicles and wireless sensor networks for spraying pesticides. J. Syst. Architect. 40, 393–404 (2014)

    Article  Google Scholar 

  7. Mohan, M., et al.: UAV-supported forest regeneration: current trends, challenges and implications. Remote Sens. 13(13), 2596 (2021)

    Article  Google Scholar 

  8. de Castro, I., et al.: UAVs for vegetation monitoring: overview and recent scientific contributions. Remote Sens. 13(11), 2139 (2021)

    Article  Google Scholar 

  9. Shvetsova, S., et al.: Safety when flying unmanned aerial vehicles at transport infrastructure facilities. Transp. Res. Procedia., 141-145 (2015)

    Google Scholar 

  10. Jofré-Briceño, C., et al.: Implementation of facility management for port infrastructure through the use of UAVS, photogrammetry and BIM. Sensors 21(19), 6686 (2021)

    Article  Google Scholar 

  11. Qazi, S., et al.: UAV based real time video surveillance over 4G LTE. In: 2015 International Conference on Open Source Systems & Technologies (ICOSST), vol. 13, no. 11, pp. 141-145 (2015)

    Google Scholar 

  12. Anwar, N., et al.: Construction monitoring and reporting using drones and unmanned aerial vehicles (UAVs). In: The Tenth International Conference on Construction in the 21st Century (CITC-10), vol. 8, no. 3, pp. 2-4 (2018)

    Google Scholar 

  13. Li, Y., et al.: Applications of multirotor drone technologies in construction management. Int. J. Constr. Manag. 19(5), 401–412 (2019)

    Google Scholar 

  14. Irizarry, J., et al.: Exploratory study of potential applications of unmanned aerial systems for construction management tasks. J. Manag. Eng. 32(3), 05016001 (2016)

    Article  Google Scholar 

  15. Bustamante, M., et al.: Design and construction of a UAV VTOL in ducted-fan and tilt-rotor configuration. In: 2019 16th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), pp. 1-6 (2019)

    Google Scholar 

  16. Zong, J., et al.: Evaluation and comparison of hybrid wing VTOL UAV with four different electric propulsion systems. Aerospace 8(9), 256 (2021)

    Article  Google Scholar 

  17. Akter, R., et al.: CNN-SSDI: convolution neural network inspired surveillance system for UAVs detection and identification. Comput. Netw. 201, 108519 (2021)

    Article  Google Scholar 

  18. Benjdira, B., et al.: Car detection using unmanned aerial vehicles: comparison between faster R-CNN and YOLOV3. In: 2019 1st International Conference on Unmanned Vehicle Systems-Oman (UVS), pp. 1-6 (2019)

    Google Scholar 

  19. Kanellakis, C., et al.: Survey on computer vision for UAVs: current developments and trends. J. Intell. Robot. Syst. 87, 141–168 (2017)

    Article  Google Scholar 

  20. Bouguettaya, A., et al.: A review on early wildfire detection from unmanned aerial vehicles using deep learning-based computer vision algorithms. Signal Process. 190, 108309 (2022)

    Article  Google Scholar 

  21. Cazzato, D., et al.: Survey of computer vision methods for 2D object detection from unmanned aerial vehicles. J. Imaging 6(8), 78 (2020)

    Article  Google Scholar 

  22. Saito, N., et. al.: Approach of fuzzy theory and hill climbing based recommender for schedule of life. In: Proceedings of LifeTech-2020, pp. 368-369 (2020)

    Google Scholar 

  23. Ozera, K., et al.: A fuzzy approach for secure clustering in MANETs: effects of distance parameter on system performance. In: Proceedings of IEEE WAINA-2017, pp. 251-258 (2017)

    Google Scholar 

  24. Elmazi, D., et al.: Selection of secure actors in wireless sensor and actor networks using fuzzy logic. In: Proceedings of BWCCA-2015, pp. 125-131 (2015)

    Google Scholar 

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Acknowledgement

This work was supported by JSPS KAKENHI Grant Number 20K19793.

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Authors and Affiliations

  1. Graduate School of Engineering, Okayama University of Science (OUS), 1-1 Ridaicho, Kita-ku, Okayama, 700-0005, Japan

    Chihiro Yukawa, Yuki Nagai & Kyohei Wakabayashi

  2. Department of Information and Computer Engineering, Okayama University of Science (OUS), 1-1 Ridaicho, Kita-ku, Okayama-shi, 700-0005, Japan

    Tetsuya Oda

  3. Department of Informention and Communication Engineering, Fukuoka Institute of Technology, 3-30-1 Wajiro-Higashi-ku, Fukuoka, 811-0295, Japan

    Leonard Barolli

Authors
  1. Chihiro Yukawa
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  2. Tetsuya Oda
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  3. Yuki Nagai
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  4. Kyohei Wakabayashi
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  5. Leonard Barolli
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Corresponding author

Correspondence to Tetsuya Oda .

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Editors and Affiliations

  1. Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

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Yukawa, C., Oda, T., Nagai, Y., Wakabayashi, K., Barolli, L. (2024). A Fuzzy Control Based Method for Imaging Position Decision and Its Performance Evaluation. In: Barolli, L. (eds) Advances in Internet, Data & Web Technologies. EIDWT 2024. Lecture Notes on Data Engineering and Communications Technologies, vol 193. Springer, Cham. https://doi.org/10.1007/978-3-031-53555-0_45

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