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Unmanned Aerial Vehicles for Disaster Management

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Geological Disaster Monitoring Based on Sensor Networks

Part of the book series: Springer Natural Hazards ((SPRINGERNAT))

Abstract

This chapter highlights the communication and network technologies that contribute to UAV disaster management systems, surveys the latest development of UAV-assisted disaster management applications, including early warning system, search and rescue, data gathering, emergency communication, and logistics, and presents our preliminary work to demonstrate the benefits and challenges of UAV systems for emergency communication. Finally, we discuss the characteristics and design challenges of UAV disaster management systems.

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References

  1. Ruckversicherungs-Gesellschaft M (2015) Loss events worldwide 1980–2014. Geo Risks Research, NatCatSERVICE

    Google Scholar 

  2. nd MR (2018) The 10 most significant natural disasters worldwide by death toll from 1980 to 2016. Statista. Available at https://www.statista.com/statistics/268029/natural-disasters-by-death-toll-since-1980/. Accessed 5 Feb 2018

  3. nd MR (2018) The 10 biggest natural disasters worldwide by economic damage from 1980 to 2016 (in billion U.S. dollars). Statista. Available at https://www.statista.com/statistics/268126/biggest-natural-disasters-by-economic-damage-since-1980/. Accessed 5 Feb 2018

  4. Erdelj M, Natalizio E, Chowdhury KR, Akyildiz IF (2017) Help from the sky: leveraging uavs for disaster management. IEEE Pervasive Comput 16(1):24–32

    Article  Google Scholar 

  5. Government of Nepal Ministry of Home Affairs (2015) Nepal disaster report

    Google Scholar 

  6. Hein D et al (2017) An integrated rapid mapping systems for disaster management. Int Arch Photogram Remote Sens Spatial Inf Sci vol XLII-1/W1

    Google Scholar 

  7. Gupta L et al (2016) Survey of important issues in UAV communication networks. IEEE Commun Surv Tutorials 18(2)

    Google Scholar 

  8. Rakesh MT (2016) Study on Google‘s loon project. Int J Adv Res Comput Eng Technol (IJARCET) 5(5)

    Google Scholar 

  9. Sathyanarayanan Chandrasekharan et al (2016) Designing and implementing future aerial communication networks. IEEE Commun Mag 54(5)

    Google Scholar 

  10. Wang Y et al (2014) Three-dimensional wireless sensor networks: geo-metric approaches for topology and routing design. In: The art of wireless sensor networks, signals and communication technology. Springer, Berlin, p 367–409

    Google Scholar 

  11. Luo C, Parr G, McClean SI, Peoples C, Wang X (2015) Hybrid demodulate-forward relay protocol for two-way relay channels. IEEE Trans Wireless Commun 14(8):4328–4341

    Article  Google Scholar 

  12. Rosati S, Krużelecki K, Heitz G, Floreano D, Rimoldi B (2016) Dynamic routing for flying ad hoc networks. IEEE Trans Veh Technol 65(3):1690–1700

    Article  Google Scholar 

  13. Ullah H, McClean S, Nixon P, Parr G, Luo C (2017) An optimal UAV deployment algorithm for bridging communication. In: 15th international conference on ITS telecommunications (ITST), pp 1–7

    Google Scholar 

  14. Mozaffari M, Saad W, Bennis M, Debbah M (2016) Unmanned aerial vehicle with underlaid device-to-device communications: performance and tradeoffs. IEEE Trans Wireless Commun 15(6):3949–3963

    Article  Google Scholar 

  15. Jagun K, Hailes S (2014) Scheduling UAVs to bridge communications in delay-tolerant networks using real-time scheduling analysis techniques. In: System integration (SII), 2014 IEEE/SICE international symposium on 2014, pp 363–369

    Google Scholar 

  16. Luo C, McClean SI, Parr G, Wang Q, Wang X, Grecos C (2014) A communication model to decouple the path planning and connectivity optimization and support cooperative sensing. IEEE Trans Veh Technol 63(8):3985–3997

    Article  Google Scholar 

  17. Morgenthaler S, Braun T, Zhongliang Z, Staub T, Anwander M (2012) UAVNet: A mobile wireless mesh network using unmanned aerial vehicles. In: Globecom Workshops (GC Wkshps), 2012 IEEE, pp 1603–1608

    Google Scholar 

  18. Ponda SS, Johnson LB, Kopeikin AN, Han-Lim C, How JP (2012) Distributed planning strategies to ensure network connectivity for dynamic heterogeneous teams. IEEE J Sel Areas Commun 30(5):861–869

    Article  Google Scholar 

  19. Palat RC, Annamalau A, Reed JR (2005) Cooperative relaying for ad hoc ground networks using swarm UAVs. IEEE Military communications conference (MILCOM), pp 1588–1594, 17–20 Oct 2005

    Google Scholar 

  20. Charlesworth PB (2014) Using non-cooperative games to coordinate communications UAVs. In: Globecom Workshops (GC Wkshps), pp 1463–1468

    Google Scholar 

  21. Chandrashekar K, Dekhordi MR, Baras JS (2004) Providing full connectivity in large ad hoc networks by dynamic placement of aerial platforms. IEEE Military communications conference (MILCOM), pp 1429–1436, 31 Oct–3 Nov 2004

    Google Scholar 

  22. Heimfarth T, de Araujo JP (2014) Using unmanned aerial vehicle to connect disjoint segments of wireless sensor network. In: IEEE 28th international conference on advanced information networking and applications, pp 907–914

    Google Scholar 

  23. Zhu M, Liu F, Cai Z, Xu M (2015) Maintaining connectivity of MANETs through multiple unmanned aerial vehicles. Mathematical Problems in Engineering, vol 2015, p 14

    Google Scholar 

  24. Heimfarth T, de Araujo JP, Giacomin JC (2014) Unmanned aerial vehicle as data mule for connecting disjoint segments of wireless sensor network with unbalanced traffic. In: IEEE 17th international symposium on object/component/service-oriented real-time distributed computing, pp 246–252

    Google Scholar 

  25. Marinho MAM, de Freitas EP, de Costa JPCL, de Almeida ALF, de Sousa RT (2013) Using cooperative MIMO techniques and UAV relay networks to support connectivity in sparse wireless sensor networks. In: International conference on computing, management and telecommunications (ComManTel), pp 49–54, 21–24 Jan 2013

    Google Scholar 

  26. Guillen-Perez A, Sanchez-Iborra R, Cano MD, Sanchez-Aarnoutse JC, Garcia-Haro J (2016) WiFi networks on drones. In: 2016 ITU kaleidoscope: ICTs for a sustainable world (ITU WT), pp 1–8

    Google Scholar 

  27. Asadpour M, Giustiniano D, Hummel KA, Heimlicher S (2013) Characterizing 802.11n aerial communication. Presented at the proceedings of the second ACM MobiHoc workshop on airborne networks and communications, Bangalore, India

    Google Scholar 

  28. Yanmaz E, Yahyanejad S, Rinner B, Hellwagner H, Bettstetter C (2018) Drone networks: communications, coordination, and sensing. Ad Hoc Netw vol 68, pp 1–15

    Google Scholar 

  29. Ullah H, Abu-Tair M, McClean S, Nixon P, Parr G, Luo C (2017) An unmanned aerial vehicle based wireless network for bridging communication. In: The 14th international symposium on pervasive systems, algorithms and networks, pp 179–184

    Google Scholar 

  30. Ullah H, Abu-Tair M, McClean S, Nixon P, Parr G, Luo C (2018) UAV-based wireless network for bridging communication using IEEE 802.11 protocols. Submitted to IEEE journal on selected areas in communications (JSAC), Special issue on airborne communication networks

    Google Scholar 

  31. Andre T et al (2015) Application-driven design of aerial communication networks. IEEE Commun Mag 52(5):129–137

    Article  Google Scholar 

  32. George SM et al (2010) DistressNet: a wireless ad hoc and sensor network architecture for situation management in disaster response. IEEE Commun Mag 48(3):128–136

    Article  Google Scholar 

  33. Shengli Fu et al (2015) Spotlight: UAVs for disaster area communication. HDIAC Spotlight

    Google Scholar 

  34. Wu Q et al (2018) Joint trajectory and communication design for multi-UAV enabled wireless networks. IEEE Trans Wireless Commun 17(3):2109–2121

    Article  Google Scholar 

  35. Gurkan Tuna et al (2012) Design strategies of unmanned aerial vehicle-aided communication for disaster recovery. In: 9th IEEE international conference on high capacity optical networks and enabling technologies (HONET)

    Google Scholar 

  36. Sonia Waharte et al (2010) Supporting search and rescue operations with UAVs. In: 2010 international conference on emerging security technologies (EST)

    Google Scholar 

  37. Silvagni Mario et al (2016) Multipurpose UAV for search and rescue operations in mountain avalanche events. Geomatics Nat Hazards Risk 8(1):18–33

    Article  Google Scholar 

  38. Swiss foundation for mine action (2016) Simulation—drones for search and rescue in emergency response simulation

    Google Scholar 

  39. Zhang J et al (2016) Flooding disaster oriented USV & UAV system development & demonstration. In: IEEE-Oceans

    Google Scholar 

  40. Kakooei M et al (2017) Fusion of satellite, aircraft, and UAV data for automatic disaster damage assessment. J Remote Sens 38(8)

    Google Scholar 

  41. Corrado C et al (2017) Data fusion and unmanned aerial vehicles (UAVs) for first responders. In: 2017 IEEE international symposium on technologies for homeland security (HST)

    Google Scholar 

  42. Jiang X, Ren P, Luo C (2016) A sensor self-aware distributed consensus filter for simultaneous localization and tracking. Cognitive Comput 8(5):828–838

    Article  Google Scholar 

  43. Gong Y, Luo C, Chen Z (2012) Two-path succussive relaying with hybrid demodulate and forward. IEEE Trans Veh Technol 61(5):2044–2053

    Google Scholar 

  44. Raptopoulos A (2013) No Roads? There is a Drone for That. TED Conference

    Google Scholar 

  45. Carlsson JG et al (2017) Coordinated logistics with a truck and a drone, Inform

    Google Scholar 

  46. Luo C, Casaseca-de-la-Higuera P, McClean S, Parr G, Ren P (2018) Characterisation of received signal strength perturbations using allan variance. IEEE Trans Aerosp Electron Syst 54(2):873–889

    Google Scholar 

  47. Morgenthaler S, Braun T, Zhao Z, Staub T, Anwander M (2012) UAVNet: A mobile wireless mesh network using unmanned aerial vehicles. In: Proc IEEE GLOBECOM Workshop-WiUAV, pp 1603–1608

    Google Scholar 

  48. Luo C, Wang Q, Wang X, Grecos C, Yang R, Ren P (2013) Exploiting selection diversity and recovering spectrum loss in wireless sensor networks with directional antennas. Globecom, 2013 IEEE, Atlanta, Georgia, 9–13 Dec 2013

    Google Scholar 

  49. Luo C, Nightingale J, Asemota E, Grecos C (2015) A UAV-cloud system for disaster sensing applications. In: IEEE 81st vehicular technology conference (VTC Spring), Glasgow, 11–14 May 2015

    Google Scholar 

  50. Luo C, McClean SI, Parr G, Teacy L, De Nardi R (2013) UAV position estimation and collision avoidance using the extended kalman filter. IEEE Trans Veh Technol 62(6):2749–2762

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. University of Exeter, Exeter, UK

    Chunbo Luo, Wang Miao & Geyong Min

  2. University of Ulster, Coleraine, UK

    Hanif Ullah & Sally McClean

  3. University of East Anglia, Norwich, UK

    Gerard Parr

Authors
  1. Chunbo Luo
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  2. Wang Miao
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  3. Hanif Ullah
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  4. Sally McClean
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  5. Gerard Parr
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  6. Geyong Min
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Corresponding author

Correspondence to Chunbo Luo .

Editor information

Editors and Affiliations

  1. Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, United Kingdom

    Tariq S. Durrani

  2. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  3. Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, United Kingdom

    Sheila M Forbes

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Luo, C., Miao, W., Ullah, H., McClean, S., Parr, G., Min, G. (2019). Unmanned Aerial Vehicles for Disaster Management. In: Durrani, T., Wang, W., Forbes, S. (eds) Geological Disaster Monitoring Based on Sensor Networks. Springer Natural Hazards. Springer, Singapore. https://doi.org/10.1007/978-981-13-0992-2_7

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