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Sensors Fusion Approach Using UAVs and Body Sensors

  • George Suciu
  • Andrei Scheianu
  • Cristina Mihaela Bălăceanu
  • Ioana Petre
  • Mihaela Dragu
  • Marius Vochin
  • Alexandru Vulpe
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 747)

Abstract

Current technological progress allows the implementation of an innovative solution that would aid the work of emergency first responder personnel. However, managing crisis situations is highly dependable on the situational awareness factors. Therefore, this paper proposes a conceptual model of a crisis management platform which integrates several technologies such as UAVs, heat cameras, toxicity sensors, and also body wearable sensors, which are capable of aggregating all the information from the above-mentioned devices. By using the proposed innovative platform, we analyze how a decrease of tragical events within the emergency sites can be achieved.

Keywords

Body sensors UAV Heat cameras Data Fusion 

Notes

Acknowledgments

This work has been supported in part by UEFISCDI Romania through projects 3DSafeguard, WINS@HI and ESTABLISH, and funded in part by European Union’s Horizon 2020 research and innovation program under grant agreement No. 777996 (SealedGRID project).

References

  1. 1.
    Tu, D.H., Esten, I.G., Sujit, P.B., Tor, A.J.: Optimization of wireless sensor network and UAV data acquisition. J. Intell. Robot. Syst. 78, 159–179 (2015)CrossRefGoogle Scholar
  2. 2.
    Purvis, K., Astrom, K., Khammash, M.: Estimation and optimal configurations for localization using cooperative UAVs. IEEE Trans. Control Syst. Technol. 16, 947–958 (2008)CrossRefGoogle Scholar
  3. 3.
    Frew, E.W., Brown, T.X.: Networking issues for small unmanned aircraft systems. J. Int. Robot. Syst. 54, 21–37 (2008)CrossRefGoogle Scholar
  4. 4.
    Ruz, J.J., Arevalo, O., Pajares, G., Cruz, J.M.: UAV trajectory planning for static and dynamic environments, Ch. 27, pp. 581–600. InTech (2009)Google Scholar
  5. 5.
    Flushing, E.F., Gambardella, L., Caro, G.D.: Search and rescue using mixed swarms of heterogeneous agents: modeling, simulation, and planning, IDSIA/USI-SUPSI, Technical report (2012)Google Scholar
  6. 6.
    Bas, V., Huub, N., Geert, B., Bart, C.: Drone technology: types, payloads, applications, frequency spectrum issues and future developments (2016)Google Scholar
  7. 7.
    Everaerts, J.: The use of Unmanned Aerial Vehicles (UAVs) for remote sensing and mappingGoogle Scholar
  8. 8.
    Maria, J.: Civil drones in the European Union, European Parliamentary Research Service (2015)Google Scholar
  9. 9.
    Silvana, P.: Swiss military drones and the border space: a critical study of the surveillance exercised by border guards, Institute of Geography, University of Neuchâtel, Neuchâtel, Switzerland (2017)Google Scholar
  10. 10.
    Tom, M.: Institute of Geography, University of Neuchâtel, Neuchâtel, Switzerland (2016)Google Scholar
  11. 11.
    Paolo, T., Massimo, S., Giacomo, D.: Towards smart farming and sustainable agriculture with drones. In: IE (Intelligent Environments) (2015)Google Scholar
  12. 12.
    Pederi, Y.A., Cheporniuk, H.S.: Unmanned aerial vehicles and new technological methods of monitoring and crop protection in precision agriculture. In: IEEE International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD) (2015)Google Scholar
  13. 13.
    HELIPSE: Border surveillance drones (UAV VTOL) (2016)Google Scholar
  14. 14.
    LIBELIUM: The first Smart Vineyard in Lebanon chooses Libelium’s technology to face the climate change. http://www.libelium.com/the-first-smart-vineyard-in-lebanon-chooses-libeliums-technology-to-face-the-climate-change/
  15. 15.
    Kaur, G., Joshi, S., Singh, G.: Food sustainability using wireless sensors networks: Waspmote and Meshlium. Int. J. Comput. Sci. Inf. Technol. 5(3), 4466–4468 (2014)Google Scholar
  16. 16.
    Zarco-Tejada, P.J., Suárez, L., Fereres, E., Berni, J.A.J.: Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Trans. Geosci. Remote Sens. 47(3), 722–738 (2009)CrossRefGoogle Scholar
  17. 17.
    Watts, A.C., Ambrosia, V.G., Hinkley, E.A.: Unmanned aircraft systems in remote sensing and scientific research: classification and considerations of use. Remote Sens. 4(6), 1671–1692 (2012)CrossRefGoogle Scholar
  18. 18.
    Aden, S.T., Bialas, J.P., Champion, Z., Levin, E., McCarty, J.L.: Low cost infrared and near infrared sensors for UAVs. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XL-1 (2014)Google Scholar
  19. 19.
    Yufu, Q., Guirong, Z., Zhaofan, Z., Ziyue, L., Jiansen, M.: Active multimodal sensor system for target recognition and tracking. Sensors 17(7), 1518 (2017). Open Access JournalCrossRefGoogle Scholar
  20. 20.
    Jouni, R., Joakim, R., Peter, S.: Accurate and reliable soldier and first responder indoor positioning: multisensor systems and cooperative localization. IEEE Wirel. Commun. 18, 10–18 (2011)Google Scholar
  21. 21.
    Francesco, N., Fabio, R.: UAV for 3D mapping applications: a review. Appl. Geomat. 6, 1–15 (2013)Google Scholar
  22. 22.
    Sonya, A.H., Mac, J.M., Peter, F., David, I., Patti, J.C.: Emergency management: exploring hard and soft data fusion modeling with unmanned aerial systems and non-governmental human intelligence mediums (2016)Google Scholar
  23. 23.
    Vishwas, R.P., Sreenatha, G.A.: Comparison of real-time online and offline neural network models for a UAV. In: Proceedings of International Joint Conference on Neural Networks (2007)Google Scholar
  24. 24.
    Elyes, B.H., Muhammad, M.A., Mickael, M., Denis, B., D’Errico, R.: Wearable Body-to-Body Networks for Critical and Rescue Operations – The CROW2 Project (2014)Google Scholar
  25. 25.
    Suciu, G., Suciu, V., Martian, A., Craciunescu, R., Vulpe, A., Marcu, I., Halunga, S., Fratu, O.: Big data, internet of things and cloud convergence–an architecture for secure e-health applications. J. Med. Syst. 39(11), 141–145 (2015)CrossRefGoogle Scholar
  26. 26.

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • George Suciu
    • 1
  • Andrei Scheianu
    • 1
  • Cristina Mihaela Bălăceanu
    • 1
  • Ioana Petre
    • 1
  • Mihaela Dragu
    • 1
  • Marius Vochin
    • 2
  • Alexandru Vulpe
    • 2
  1. 1.R&D DepartmentBEIA Consult InternationalBucharestRomania
  2. 2.Telecommunications DepartmentUniversity Politehnica of BucharestBucharestRomania

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