سابِق|تال

Development and applications of the UAV remote sensing network based on the intelligent UAV base station

  • role： First author第一作者
  • Affiliation：

    Guangdong Provincial Key Laboratory of Remote Sensing and GIS Application, Guangdong Provincial Public Laboratory of Geospatial Information Technology and Application,Guangzhou Institute of Geography, Guangdong Academy of Sciences,Guangzhou 510070, China

    Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China

  • Email：jingwl@lreis.ac.cn
  • Introduction：荆文龙，研究方向为遥感人工智能研究与应用。E-mail： jingwl@lreis.ac.cn
JING Wenglong12,  
  • Affiliation：

    Guangdong Provincial Key Laboratory of Remote Sensing and GIS Application, Guangdong Provincial Public Laboratory of Geospatial Information Technology and Application,Guangzhou Institute of Geography, Guangdong Academy of Sciences,Guangzhou 510070, China

    Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China

ZHOU Chenghu12,  
  • role： Corresponding author通信作者
  • Affiliation：

    Guangdong Provincial Key Laboratory of Remote Sensing and GIS Application, Guangdong Provincial Public Laboratory of Geospatial Information Technology and Application,Guangzhou Institute of Geography, Guangdong Academy of Sciences,Guangzhou 510070, China

    Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China

  • Email：liyong@gdas.ac.cn
  • Introduction：李勇，研究方向为无人机遥感技术及应用。E-mail： liyong@gdas.ac.cn
LI Yong12*,  
  • Affiliation：

    Guangdong Provincial Key Laboratory of Remote Sensing and GIS Application, Guangdong Provincial Public Laboratory of Geospatial Information Technology and Application,Guangzhou Institute of Geography, Guangdong Academy of Sciences,Guangzhou 510070, China

    Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China

YANG Ji12,  
  • Affiliation：

    Guangzhou iMapCloud Intelligent Technology Co.Ltd, Guangzhou 510070, China

PAN Yifeng3,  
  • Affiliation：

    Guangdong Provincial Key Laboratory of Remote Sensing and GIS Application, Guangdong Provincial Public Laboratory of Geospatial Information Technology and Application,Guangzhou Institute of Geography, Guangdong Academy of Sciences,Guangzhou 510070, China

    Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China

    Guangzhou iMapCloud Intelligent Technology Co.Ltd, Guangzhou 510070, China

HUANG Wumeng123,  
  • Affiliation：

    Guangdong Provincial Key Laboratory of Remote Sensing and GIS Application, Guangdong Provincial Public Laboratory of Geospatial Information Technology and Application,Guangzhou Institute of Geography, Guangdong Academy of Sciences,Guangzhou 510070, China

    Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China

DENG Yingbin12,  
  • Affiliation：

    Guangzhou iMapCloud Intelligent Technology Co.Ltd, Guangzhou 510070, China

ZHAO Xiaodan3

ملخص

Unmanned Aerial Vehicles (UAVs) could flexibly and efficiently observe land surface and obtain surface information at very high frequency and resolutions. In recent years, UAV technology has been greatly improved and the UAVs are increasingly applied in large amount of civilian fields. The UAV Remote Sensing (UAVRS) is a comprehensive technology composed of UAV flying aircraft, light remote sensing payload, satellite positioning device, remote-control system, communication technology and application technology. An UAVRS system is mainly composed of UAV platform, load system, ground control and data transmission system and image processing system. With the popularity of civilian UAV products and the development of UAV remote sensing payload, UAVRS also shows an explosive growth trend in various industries. However, the short battery life and limited coverage of the civilian drones are one of the key factors restricting the UAVRS applications. Besides, although the application of UAVs in various industries and fields continues to deepen, most of them are single-type applications in a certain discipline or industry. The 5G technology and wireless communication technology advance and will give rise to the UAVRS applications in terms of “networking”, “IoT”, and “real-time”, as well as cross-domain and convergence application. The modern cities are highly complex and sociotechnical. They comprise people and communities interacting with one another and with objects (e.g., roads, buildings) within a range of urban settings or contexts. It is extremely difficult to monitor and manage such complex sociotechnical systems. The monitoring and mapping of pollutions, traffic, infrastructures are great challenges in rapidly changing cities, and especially gained increasing attentions of citizens and are putting great stresses on policy makers and urban planners. Theoretical and practical efforts to create better city monitoring and management systems have a long history. In the 21st century, we recognize and conceive “creative”, “smart” and “knowledge” cities, in which the multidisciplinary Information and Information and Communication Technology (ICT) has played a vital role. The Internet of Things (IoT) promotes the development of the smart cities. However, in various urban domains, the cities equipped with a sensor-based web, or a cyber-physical information infrastructure, are far from sufficient to help policy makers or citizens to get a full understanding of the real time or near real time city conditions. To this end, due to their mobility, autonomous operation, and communication/processing capabilities, UAVs are envisaged in many smart city application domains. In this article, we describe a technology of air-ground collaborative low-altitude UAV remote sensing network system. The system composes of intelligent UAV, the UAV base station (drone-in box) and operation system. The UAV remote sensing network can provide high-frequency and real-time observations of the land surface. Based on the UAV remote sensing network, we constructed a comprehensive application for urban governance. An UAVRS network composed of eight UAV base stations was deployed in Danzao Town, Foshan City. Connected through 5G network, the UAVRS network advances the UAV inspection frequency, spatial coverage, and response time. It provides revolutionary and intelligent services for local agents and departments of water affairs, environment protection, public security, urban management, and emergency. The UAVRS network system in Danzao is expected to develop a real-world smart city paradigm that could be copied and migrated to other towns across the country.

مفهوم

UAV;UAV base station;UAV remote sensing network;air-ground collaborate

References

  1. 1.
    Abdelmaboud A. 2021. The internet of drones: requirements, taxonomy, recent advances, and challenges of research trends. Sensors, 21(17): 5718
  2. 2.
    Alam S, Natesha B V, Ashwin T S and Guddeti R M R. 2019. UAV based cost-effective real-time abnormal event detection using edge computing. Multimedia Tools and Applications, 78(24): 35119-35134
  3. 3.
    Barthélemy J, Verstaevel N, Forehead H and Perez P. 2019. Edge-computing video analytics for real-time traffic monitoring in a smart city. Sensors, 19(9): 2048
  4. 4.
    Bergkvist A, Burnett D C, Jennings C and Narayanan A. 2012. WebRTC 1.0: Real-Time Communication Between Browsers. W3C
  5. 5.
    Chen N C, Xiao C J, Yang C and Wang W. 2020. Technology and application of the fusion service of geospatial sensor web. Journal of Geo-Information Science, 22(1): 11-20
  6. 6.
    Colomina I and Molina P. 2014. Unmanned aerial systems for photogrammetry and remote sensing: a review. ISPRS Journal of Photogrammetry and Remote Sensing, 92: 79-97
  7. 7.
    Fan B K and Zhang R Y. 2017. Unmanned aircraft system and artificial intelligence. Geomatics and Information Science of Wuhan University, 42(11): 1523-1529
  8. 8.
    Fielding R. 1999. Hypertext Transfer Protocol-HTTP/1.1. RFC 2616
  9. 9.
    Ge X J, Huang B, Yuan Z J, Wang D D, Wang Q Q, Chen J C and Xie Z Y. 2022. Temporal and spatial variation characteristics and source analysis of agricultural non-point source pollution load in Guangdong during the past 20 years. Environmental Science, 43(6): 3118-3127
  10. 10.
    Gharibi M, Boutaba R and Waslander S L. 2016. Internet of drones. IEEE Access, 4: 1148-1162
  11. 11.
    Gien M. 1978. A file transfer protocol (FTP). Computer Networks, 2(4/5): 312-319
  12. 12.
    Guo Q H, Hu T Y, Liu J, Jin S C, Xiao Q, Yang G J, Gao X L, Xu Q, Xie P H, Peng C G and Yan L. 2021. Advances in light weight unmanned aerial vehicle remote sensing and major industrial applications. Progress in Geography, 40(9): 1550-1569
  13. 13.
    Gupta L, Jain R and Vaszkun G. 2016. Survey of important issues in UAV communication networks. IEEE Communications Surveys and Tutorials, 18(2): 1123-1152
  14. 14.
    Li D R and Li M. 2014. Research advance and application prospect of unmanned aerial vehicle remote sensing system. Geomatics and Information Science of Wuhan University, 39(5): 505-513, 540
  15. 15.
    Li D R, Wnag M and Hu F. 2009. Utilizing Chinese high-resolution satellite images for inspection of unauthorized constructions in Beijing. Chinese Science Bulletin, 54(14): 2524-2534
  16. 16.
    Liang S Y, Wu H, Zhen L, Hua Q Z, Garg S, Kaddoum G, Hassan M M and Yu K P. 2022. Dge YOLO: real-time intelligent object detection system based on edge-cloud cooperation in autonomous vehicles. IEEE Transactions on Intelligent Transportation Systems, 23(12): 25345-25360
  17. 17.
    Liao X H, Huang Y H and Xu C C. 2021. Views on the study of low-altitude airspace resources for UAV applications. Acta Geographica Sinica, 76(11): 2607-2620
  18. 18.
    Liao X H, Xiao Q and Zhang H. 2019. UAV remote sensing: popularization and expand application development trend. Journal of Remote Sensing, 23(6): 1046-1052
  19. 19.
    Liao X H, Zhou C H, Su F Z, Lu H Y, Yue H Y and Gou J P. 2016. The mass innovation era of UAV remote sensing. Journal of Geo-Information Science, 18(11): 1439-1447
  20. 20.
    Liu J W, Chen P F, Lu M and Liao X H. 2021. Unmanned aerial vehicle airports for verification of common products from China High-resolution Earth Observation System (CHEOS). Acta Geographica Sinica, 76(11): 2621-2631
  21. 21.
    Liu Y H, Guo J P and Wei Q S. 2012. Urban green space landscape patterns and thermal environment investigations based on computational fluid dynamics. Acta Ecologica Sinica, 32(6): 1951-1959
  22. 22.
    Liu Y M, Deng R R, Qin Y, Cao B, Liang Y H, Liu Y F, Tian J L and Wang S L. 2019. Rapid estimation of bathymetry from multispectral imagery without in situ bathymetry data. Applied Optics, 58(27): 7538-7551
  23. 23.
    Lu M, Liao X H, Yue H Y, Huang S F, Xu C C, Lu H Y and Bai Y Q. 2019. Determining the distribution of unmanned aerial vehicles airports for the emergency monitoring of floods in China. Journal of Geo-Information Science, 21(6): 854-864
  24. 24.
    Nex F, Armenakis C, Cramer M, Cucci D A, Gerke M, Honkavaara E, Kukko A, Persello C and Skaloud J. 2022. UAV in the advent of the twenties: where we stand and what is next. ISPRS Journal of Photogrammetry and Remote Sensing, 184: 215-242
  25. 25.
    Parmar H and Thornburgh M. 2012. Real-time messaging protocol (rtmp) specification. Adobe Specifications, December
  26. 26.
    Peng B F, Chen Z F, Li J H, Luo W J, Gan J and Zeng R L. 2018. Monitoring water quality of Dongting Lake region based on GF-1 image. Geographical Research, 37(9): 1683-1691
  27. 27.
    Redmon J, Divvala S, Girshick R and Farhadi A. 2016. You only look once: unified, real-time object detection//Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas: IEEE
  28. 28.
    Shan J L, Li X N, Zhang J, Li Q, Tan L T, Ding C Z and Liang P X. 2019. Ources and prevention and control measures of agricultural non-point source pollution in Foshan City, Guangdong Province. Agricultural Engineering Technology, 39(17): 43-44
  29. 29.
    Shi W S, Cao J, Zhang Q, Li Y H Z and Xu L Y. 2016. Edge computing: vision and challenges. IEEE Internet of Things Journal, 3(5): 637-646
  30. 30.
    Standard O. 2019. MQTT Version 5.0. Retrieved June, 22: 2020
  31. 31.
    U.S. Army 2010. Unmanned Aircraft Systems Roadmap, 2010-2035. 609874047. U.S. Army UAS Center of Excellence
  32. 32.
    Wang D, Yang C, Zheng Y H, Xiao X Y, Zhao L and Chen Z H. 2021. Estimation of mitigation effect of sponge city reconstruction on heat island effect. Resources and Environment in the Yangtze Basin, 30(4): 968-975
  33. 33.
    Wang K, Fu Y R, Peng X Y, Zuo Z Q, Yi L and Huang S B. 2017. Overview of UAV low altitude remote sensing technology and application in typical industries. Bulletin of Surveying and Mapping, (S1): 79-83
  34. 34.
    Wen J G, Xiao Q, Liu Q H and Zhou Y. 2007. Extraction of chlorophyll-a concentration based on spectral unmixing model in taihu lake water. Scientia Geographica Sinica, 27(1): 92-97
  35. 35.
    Xu C C, Ye H P, Yue H Y, Tan X and Liao X H. 2020. Iterative construction of UAV low-altitude air route network in an urbanized region: theoretical system and technical roadmap. Acta Geographica Sinica, 75(5): 917-930
  36. 36.
    Xu R S, Kong G T and LI G H. 2007. Current situation and prevention countermeasures of agricultural non-point source pollution in Nanhai District, Foshan City. Guangdong Agricultural Sciences, (1): 72-73.
  37. 37.
    Yang G J, Liu J G, Zhao C J, Li Z H, Huang Y B, Yu H Y, Xu B, Zhu D M, Zhang X Y, Zhang R Y, Feng H K, Zhao X Q, Li Z H, Li H L and Yang H. 2017. Unmanned aerial vehicle remote sensing for field-based crop phenotyping: current status and perspectives. Frontiers in Plant Science, 8: 1111
  38. 38.
    Zeng Y, Lyu J B and Zhang R. 2019. Cellular-connected UAV: potential, challenges, and promising technologies. IEEE Wireless Communications, 26(1): 120-127
  39. 39.
    Zhang C S, Liu Z J, Yang S W and Zuo Z Q. 2017. Data acquisition and processing for large UAV in inspecting transmission lines and its key technologies. Bulletin of Surveying and Mapping, S1: 136-139, 163
  40. 40.
    Zhang H D, Wang L Q, Tian T and Yin J H. 2021. A Review of unmanned aerial vehicle low-altitude remote sensing (UAV-LARS) use in agricultural monitoring in China. Remote Sensing, 13(6): 1221
  41. 41.
    Zhang J X, Liu F and Wang J. 2021. Review of the light-weighted and small UAV system for aerial photography and remote sensing. National Remote Sensing Bulletin, 25(3): 708-724

قراءة النص الكامل

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website