A decision support model for unmanned aerial vehicles assisted disaster response using AHP-TOPSIS method

Abstract

The main objective of disaster response is to secure lives and livelihoods at first. To achieve that, policymakers need accurate information regarding disaster areas to make a quick decision right after the disaster. Especially at a large scale disaster, it is much more important to respond to it quickly due to the number of affected people. In the uncertain atmosphere of the disaster, decision-makers can utilize UAS (Unmanned Aerial Systems) to gather instant images of the disaster area for Search and Rescue Mission (SAR) and damage assessment. Also, it will be used as a communication tool between emergency units and the command center. This paper discusses the usage of UAS in a possible İstanbul earthquake. Considering the damages that may occur after a possible Istanbul earthquake, 5 criteria have been determined, these criteria have been weighted within the Analytical Hierarchy Process (AHP) method, and the Technique for Order-Preference by Similarity to Ideal Solution (TOPSIS) method has prioritized the districts of Istanbul according to these criteria. With the help of this ranking, when the Istanbul earthquake occurs, if a different duty was not given to UASs, it was tried to be determined which districts should first look for the UAS's SAR mission.

Keywords

• UAS
• Disaster response
• Earthquake
• AHP
• TOPSIS

İnsansız hava araçları destekli afet müdahalesi için bir karar destek modeli: AHP-TOPSIS metodu

Öz

Afete müdahalenin temel amacı, öncelikle yaşamları ve geçim kaynaklarını güvence altına almaktır. Bunu başarmak için, politika yapıcıların afetten hemen sonra hızlı bir karar verebilmeleri için afet alanlarıyla ilgili doğru bilgiye ihtiyaçları vardır. Özellikle büyük çaplı bir felakette, etkilenen insan sayısı nedeniyle buna hızlı bir şekilde cevap vermek çok daha önemlidir. Felaketin belirsiz atmosferinde karar vericiler, Arama ve Kurtarma Misyonu (AKM) ve hasar değerlendirmesi için felaket alanının anlık görüntülerini toplamak için İHA'ı (İnsansız Hava Sistemleri) kullanabilirler. Ayrıca acil durum birimleri ile komuta merkezi arasında bir iletişim aracı olarak kullanılacaktır. Bu makale olası bir İstanbul depreminde UAS kullanımını tartışmaktadır. Olası bir İstanbul depreminden sonra meydana gelebilecek zararlar göz önüne alındığında, 5 kriter belirlenmiş, bu kriterler AHP (Analitic Hierarchy Process) yöntemi içinde tartılmış ve TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions) yöntemi kullanılmıştır. İstanbul ilçelerini bu kriterlere göre önceliklendirmiştir. Bu sıralamanın yardımıyla, İstanbul depremi meydana geldiğinde, IHA'lara farklı bir görev verilmemişse, hangi bölgelerin ilk önce İHA'ın AKM misyonunu araması gerektiği belirlenmeye çalışılmıştır.

Anahtar Kelimeler

• Arama ve Kurtarma
• Felaket Müdahalesi
• Deprem
• AHP
• TOPSIS

Kaynakça

1. Karlsruhe Institute of Technology. "Natural disasters since 1900: Over 8 million deaths, 7 trillion US dollars." ScienceDaily. ScienceDaily, 18 April 2016. .
2. Gutierrez, D., 2008. Natural disasters up more than 400 percent in two decades. Natural News. June 5.
3. A. Tiwari. The Capacity Crisis in Disaster Risk Management. Springer International Publishing Switzerland, 2015, ISBN 978-3-319-09405-2
4. M.Erdelj, E. Natalizio, UAV-Assisted Disaster Management: Applications and Open Issues, International Conference on Computing, Networking and Communications (ICNC),2016. DOI:10.1109/ICCNC.2016.7440563
5. E. Spiers, Chemical Warfare, Springer, 2016. DOI https://doi.org/10.1007/978-3-319-51664-6
6. Türkiye Cumhuriyeti İstanbul İli Sismik Mikro-Bölgeleme Dahil Afet Önleme/Azaltma Temel Planı Çalışması, Eylül 2002, http://www.ibb.gov.tr/sites/akom/documents/JICA-TUR.pdf
7. Liu, P., Chen, A. Y., Huang, Y. N., Han, J. Y., Lai, J. S., Kang, S. C., Wu, T. H., Wen, M. C. & Tsai, M. (2014) A review of rotorcraft unmanned aerial vehicle (uav) developments and applications in civil engineering, Smart Structures and Systems, 13(6), 1065-1094. DOI: http://dx.doi.org/10.12989/sss.2014.13.6.1065
8. Camara, D. (2014) Cavalry to the rescue: Drones fleet to help rescuers operations over disasters scenarios, IEEE Conference on Antenna Measurements & Applications (CAMA), 16-19 November, Antibes Juan-les-Pins, France DOI: 10.1109/CAMA.2014.7003421

9. Bravo, R. & Leiras, A. (2015) Literature review of the application of uavs in humanitarian relief, XXXV Encontro Nacional de Engenharia de Producao, 13-16 October, Fortaleza, Brazil, 1-15.
10. Quaritsch, M., Kruggl, K., Wischounig-Strucl, D., Bhattacharya, S., Shah, M. & Rinner, B. (2010) Networked uavs as aerial sensor network for disaster management applications, Elektrotechnik&Informationstechnik DOI:https://doi.org/10.1007/s00502-010-0717-2
11. Mukherjee, A., Chakraborty, S., Azar, A. T., Bhattacharyay, S. K., Chatterjee, B. & Dey, N. (2014) Unmanned aerial system for post disaster identification, International Conference on Circuits, Communication, Control and Computing (I4C), 21-22 November, Bangalore, India DOI: 10.1109/CIMCA.2014.7057799 Tuna, G., Nefzi, B. & Conte, G. (2014) Unmanned aerial vehicle-aided communications system for disaster recovery, Journal of Network and Computer Applications, 41, 27-36. DOI: 10.1016/j.jnca.2013.10.002
12. Luo, C., Nightingale, J., Asemota, E. & Grecos, C. (2015) A uav-cloud system for disaster sensing applications, Vehicular Technology Conference (VTC Spring), 11-14 May, Glasgow, Scotland DOI: 10.1109/VTCSpring.2015.7145656
13. Restas, A. (2015) Drone applications for supporting disaster management, World Journal of Engineering and Technology doi: 10.4236/wjet.2015.33C047.
14. Lee, J., Huang, R., Vaughn, A., Xiao, X., Hedrick, J. K., Zennaro, M. & Sengupta, R. (2003) Strategies of path-planning for a uav to track a ground vehicle, AINS Conference.
15. Gencer, C., Aydoğan, E. K. & Kocabaş, S. İnsansız hava araçlarının rota planlaması için bir karar destek sistemi, Savunma Bilimleri Dergisi, (2009 8/1). https://dergipark.org.tr/tr/pub/khosbd/issue/19230/204343
16. Mufalli, F., Batta, R. & Nagi, R. (2012) Simultaneous sensor selection and routing of unmanned aerial vehicles for complex mission plans, Computers&Operations Research, https://doi.org/10.1016/j.cor.2012.02.010
17. Ercan, C. & Gencer, C. (2013) An integer programming model for the heterogeneous uav fleet routing problems”, Savunma Bilimleri Dergisi, 12(2), 119-144. https://dergipark.org.tr/tr/download/article-file/180237
18. Cabreira, Taua & Di Franco, Carmelo & Ferreira Jr, Paulo. (2018). Energy-Aware Spiral Coverage Path Planning for UAV Photogrammetric Applications. IEEE Robotics and Automation Letters. PP. 1-1. DOI: 10.1109/LRA.2018.2854967.
19. Yakıcı, E. (2016) Solving location and routing problem for uavs, Computers&Industrial Engineering, 102, 294-301. https://doi.org/10.1016/j.cie.2016.10.029
20. Mersheeva, Vera & Friedrich, Gerhard. (2012). Routing for Continuous Monitoring by Multiple Micro UAVs in Disaster Scenarios. Frontiers in Artificial Intelligence and Applications. 242. 10.3233/978-1-61499-098-7-588.
21. Nedjati, A., Vizvari, B. & Izbirak, G. Post-earthquake response by small UAV helicopters. Nat Hazards 80, 1669–1688 (2016). https://doi.org/10.1007/s11069-015-2046-6
22. Macintyre, Anthony & Barbera, Joseph & Smith, Edward. (2006). Surviving collapsed structure entrapment after earthquakes: A "time-to-rescue" analysis. Prehospital and disaster medicine. 21. 4-17; discussion 18. DOI:10.1017/S1049023X00003253.
23. Cavdur, Fatih& Köse Küçük Merve & Sebatlı Asli.(2016). Allocation of temporary disaster response facilities under demand uncertainty: An earthquake case study. International Journal of Disaster Risk Reduction. 159-166. https://doi.org/10.1016/j.ijdrr.2016.08.009
24. Saaty, R., W. (1987). The analytic hierarchy process-what it is and how it is used. Mathematical Modelling.161-176. https://doi.org/10.1016/0270-0255(87)90473-8
25. Badri, M. (2001). A combined AHP-GP model for quality control systems. International Journal of Production Economics. 72. 27-40. 10.1016/S0925-5273(00)00077-3.
26. Dağdeviren, M. (2008). Decision making in equipment selection: An integrated approach with AHP and PROMETHEE. Journal of Intelligent Manufacturing, 19, 397–406. DOI: 10.1007/s10845-008-0091-7
27. Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications, A State of the Art Survey. New York: Springer-Verlag. DOI: 10.1007/978-3-642-48318-9
28. Wang, Y. M., & Elhag, T. M. S. (2006). Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert Systems with Applications, 31, 309–319. https://doi.org/10.1016/j.eswa.2005.09.040