Araştırma Makalesi
BibTex RIS Kaynak Göster

Orman Yangınlarının Tespiti İçin İnsansız Hava Aracı Geliştirilmesi

Yıl 2023, Cilt: 18 Sayı: 2, 449 - 459, 01.09.2023
https://doi.org/10.55525/tjst.1301903

Öz

Son yıllarda yangınların seyrinin belirlenmesinde, ısı noktalarının tespit edilmesinde ve müdahale yerlerinin belirlenmesinde önemli rol oynayan İnsansız Hava Araçları’ndan (İHA) elde edilen bilgiler doğrultusunda orman yangınları kontrol altına alınabilmektedir. Bu çalışmada İHA’nın, yangının bulunduğu bölgede otonom olarak konumlanarak yangını tespit etmesi durumunda, termal kamera yardımıyla yangının en yoğun sıcaklığa ulaştığı nokta belirlenmekte ve ateş topunun %100 başarı oranı ile hedefe düşürülmesi sağlanmaktadır. Bu görevi gerçekleştirmek üzere üretilecek olan İHA'nın hızlı, yük taşıma ve stabil uçuş gibi gereksinimleri de göz önünde bulundurulmuştur. İçerisindeki malzemelerin ekonomik ve uzun ömürlü olmasının yanı sıra çoğu hava koşulunda (sisli, karanlık vb.) verimli bir şekilde uçabilecektir. İHA yapımında yeterli akımı karşılamak için özgün tasarıma sahip yerli Elektronik Hız Kontrol Cihazı (ESC) üretilmiştir. Bu satın alma ile birlikte birden fazla Fırçasız DC (BLDC) motora yeterli akım göndererek gereksinimleri karşılayacak olan ESC, Radyo Kontrollü (RC) uçağımızda test edilmiş ve projeye dâhil edilmiştir.

Proje Numarası

1919B012222889

Kaynakça

  • Ucar UU, Isleyen SK. A New Solution Approach for UAV Routing Problem with Moving Target – Heterogeneous Fleet. J Polytechnic 2019; 22(4): 999 – 1016.
  • Yilmaz T, Ayranci AA, Bacanli E, Ilhan H. UAV-Assisted NOMA-Based Network with Alamouti Space-Time Block Coding. J Polytechnic 2022; 25(3): 967 - 973.
  • Ozcan O. Performance Evaluation of Bridges Under Scour by UAS Based Measurements. J Polytechnic 2019; 22(2): 385 - 391.
  • Bailon-Ruiz R, Lacroix S. Wildfire remote sensing with UAVs: A review from the autonomy point of view. In IEEE 2020 International Conference on Unmanned Aircraft Systems (ICUAS); 01-04 September 2020; Athens, Greece. New York, NY, USA: IEEE. pp. 412-420.
  • Ambrosia VG. Wegener SS, Sullivan DV, Buechel SW, Dunagan SE, Brass JA, Stoneburner J, S. Schoenun M. Demonstrating UAV-Acquired Real-Time Thermal Data over Fires. Photogramm Eng Remote Sens 2003; 69(4) 391-402.
  • Lewyckyj N, Biesemans J, Everaerts J. OSIRIS: A European Project Using A High Altitude Platform For Forest Fire Monitoring. In: Safety and Security Engineering II. Rome: Wessex Institute of Technology Press, 2007. pp. 205-213.
  • Merino L, Caballero F, Martinez-de Dios JR, Ollero A. Cooperative Fire Detection using Unmanned Aerial Vehicles. In: IEEE 2005 IEEE International Conference on Robotics and Automation; 18-22 April 2005; Barcelona, Spain. New York, NY, USA: IEEE. pp. 1884-1889.
  • Sudhakar VVS, Kumar CS, Priya V, Ravi L, Subramaniyaswamy V. Unmanned Aerial Vehicle (UAV) based Forest Fire Detection and monitoring for reducing false alarms in forest-fires. Comput Commun 2020; 149:1-16.
  • Partheepan S, Sanati F, Hassan J. Autonomous Unmanned Aerial Vehicles in Bushfire Management: Challenges and Opportunities. Drones 2023; 7(47): 1-34.
  • Masat M, Saglam HK, Ertugrul M, Korul H. The use of unmanned aerial vehicles in the detection of forest fires with a gas detection technique. NanoEra 2021; 1(1): 14-18.
  • Rahman AKZR, Sakif SMN, Sikder N, Masud M, Aljuaid H, Bairagi AK. Unmanned Aerial Vehicle Assisted Forest Fire Detection Using Deep Convolutional Neural Network. Intell. Autom Soft Comput 2022; 35(3): 3259-3277.
  • Bahhar C, Ksibi A, Ayadi M, Jamjoom MM, Ullah Z, Soufiene BO, Sakli H. Wildfire and Smoke Detection Using Staged YOLO Model and Ensemble CNN. Electronics 2013; 12(1): 1-15.
  • Barmpoutis P, Papaioannou P, Dimitropoulos K, Grammalidis N. A Review on Early Forest Fire Detection Systems Using Optical Remote Sensing. Sensors 2020; 20(22): 1-26.
  • Moumgiakmas SS, Samatas GG, Papakostas GA. Computer Vision for Fire Detection on UAVs—From Software to Hardware. Future Internet 2021; 13(8): 1-17.
  • Cory R, Tedrake R. Experiments in Fixed-Wing UAV Perching. In: AIAA Guidance, Navigation and Control Conference and Exhibit; 18-21 August 2008; Honolulu, Hawaii.
  • B. Technology, "BAYKAR Technology," . Available: https://baykartech.com/tr/orman-yanginlariyla-mucadele. .

Development of Unmanned Aerial Vehicle for Detecting the Forest Fires

Yıl 2023, Cilt: 18 Sayı: 2, 449 - 459, 01.09.2023
https://doi.org/10.55525/tjst.1301903

Öz

In recent years, forest fires can be brought under control in line with the information obtained from Unmanned Aerial Vehicles (UAVs), which play an important role in determining the progression of fires, detecting heat points and determining intervention locations. In this study, if the UAV detects the fire by autonomously positioning in the area where the fire is located, the point where the fire reaches the most intense temperature is determined with the help of the thermal camera, and it is ensured that the fireball is dropped to the target with a 100% success rate. The requirements of the UAV, which will be produced in order to realize this task, such as fast, load-carrying and stable flight are also taken into consideration. In addition to being economical and long-lasting of the materials inside, it will be able to fly efficiently in most weather conditions (foggy, dark, etc.). In the construction of the UAV, a domestic Electronic Speed Controller (ESC) with a unique design is produced to meet the sufficient current. With this acquisition, ESC, which will meet the requirements by sending sufficient current to more than one Brushless DC (BLDC) motor, has been tested on our Radio Controlled (RC) aircraft and included in the project.

Destekleyen Kurum

TÜBİTAK

Proje Numarası

1919B012222889

Teşekkür

This work is supported by TÜBİTAK 2209-A with the research project number 1919B012222889.

Kaynakça

  • Ucar UU, Isleyen SK. A New Solution Approach for UAV Routing Problem with Moving Target – Heterogeneous Fleet. J Polytechnic 2019; 22(4): 999 – 1016.
  • Yilmaz T, Ayranci AA, Bacanli E, Ilhan H. UAV-Assisted NOMA-Based Network with Alamouti Space-Time Block Coding. J Polytechnic 2022; 25(3): 967 - 973.
  • Ozcan O. Performance Evaluation of Bridges Under Scour by UAS Based Measurements. J Polytechnic 2019; 22(2): 385 - 391.
  • Bailon-Ruiz R, Lacroix S. Wildfire remote sensing with UAVs: A review from the autonomy point of view. In IEEE 2020 International Conference on Unmanned Aircraft Systems (ICUAS); 01-04 September 2020; Athens, Greece. New York, NY, USA: IEEE. pp. 412-420.
  • Ambrosia VG. Wegener SS, Sullivan DV, Buechel SW, Dunagan SE, Brass JA, Stoneburner J, S. Schoenun M. Demonstrating UAV-Acquired Real-Time Thermal Data over Fires. Photogramm Eng Remote Sens 2003; 69(4) 391-402.
  • Lewyckyj N, Biesemans J, Everaerts J. OSIRIS: A European Project Using A High Altitude Platform For Forest Fire Monitoring. In: Safety and Security Engineering II. Rome: Wessex Institute of Technology Press, 2007. pp. 205-213.
  • Merino L, Caballero F, Martinez-de Dios JR, Ollero A. Cooperative Fire Detection using Unmanned Aerial Vehicles. In: IEEE 2005 IEEE International Conference on Robotics and Automation; 18-22 April 2005; Barcelona, Spain. New York, NY, USA: IEEE. pp. 1884-1889.
  • Sudhakar VVS, Kumar CS, Priya V, Ravi L, Subramaniyaswamy V. Unmanned Aerial Vehicle (UAV) based Forest Fire Detection and monitoring for reducing false alarms in forest-fires. Comput Commun 2020; 149:1-16.
  • Partheepan S, Sanati F, Hassan J. Autonomous Unmanned Aerial Vehicles in Bushfire Management: Challenges and Opportunities. Drones 2023; 7(47): 1-34.
  • Masat M, Saglam HK, Ertugrul M, Korul H. The use of unmanned aerial vehicles in the detection of forest fires with a gas detection technique. NanoEra 2021; 1(1): 14-18.
  • Rahman AKZR, Sakif SMN, Sikder N, Masud M, Aljuaid H, Bairagi AK. Unmanned Aerial Vehicle Assisted Forest Fire Detection Using Deep Convolutional Neural Network. Intell. Autom Soft Comput 2022; 35(3): 3259-3277.
  • Bahhar C, Ksibi A, Ayadi M, Jamjoom MM, Ullah Z, Soufiene BO, Sakli H. Wildfire and Smoke Detection Using Staged YOLO Model and Ensemble CNN. Electronics 2013; 12(1): 1-15.
  • Barmpoutis P, Papaioannou P, Dimitropoulos K, Grammalidis N. A Review on Early Forest Fire Detection Systems Using Optical Remote Sensing. Sensors 2020; 20(22): 1-26.
  • Moumgiakmas SS, Samatas GG, Papakostas GA. Computer Vision for Fire Detection on UAVs—From Software to Hardware. Future Internet 2021; 13(8): 1-17.
  • Cory R, Tedrake R. Experiments in Fixed-Wing UAV Perching. In: AIAA Guidance, Navigation and Control Conference and Exhibit; 18-21 August 2008; Honolulu, Hawaii.
  • B. Technology, "BAYKAR Technology," . Available: https://baykartech.com/tr/orman-yanginlariyla-mucadele. .
Toplam 16 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Gömülü Sistemler, Otonom Araç Sistemleri
Bölüm TJST
Yazarlar

Barış Mert Kadıoğlu 0009-0001-5194-9158

Seçil Karatay 0000-0002-1942-6728

Yücel Çetinceviz 0000-0001-6834-9442

Faruk Erken 0000-0003-2048-1203

Proje Numarası 1919B012222889
Yayımlanma Tarihi 1 Eylül 2023
Gönderilme Tarihi 24 Mayıs 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 18 Sayı: 2

Kaynak Göster

APA Kadıoğlu, B. M., Karatay, S., Çetinceviz, Y., Erken, F. (2023). Development of Unmanned Aerial Vehicle for Detecting the Forest Fires. Turkish Journal of Science and Technology, 18(2), 449-459. https://doi.org/10.55525/tjst.1301903
AMA Kadıoğlu BM, Karatay S, Çetinceviz Y, Erken F. Development of Unmanned Aerial Vehicle for Detecting the Forest Fires. TJST. Eylül 2023;18(2):449-459. doi:10.55525/tjst.1301903
Chicago Kadıoğlu, Barış Mert, Seçil Karatay, Yücel Çetinceviz, ve Faruk Erken. “Development of Unmanned Aerial Vehicle for Detecting the Forest Fires”. Turkish Journal of Science and Technology 18, sy. 2 (Eylül 2023): 449-59. https://doi.org/10.55525/tjst.1301903.
EndNote Kadıoğlu BM, Karatay S, Çetinceviz Y, Erken F (01 Eylül 2023) Development of Unmanned Aerial Vehicle for Detecting the Forest Fires. Turkish Journal of Science and Technology 18 2 449–459.
IEEE B. M. Kadıoğlu, S. Karatay, Y. Çetinceviz, ve F. Erken, “Development of Unmanned Aerial Vehicle for Detecting the Forest Fires”, TJST, c. 18, sy. 2, ss. 449–459, 2023, doi: 10.55525/tjst.1301903.
ISNAD Kadıoğlu, Barış Mert vd. “Development of Unmanned Aerial Vehicle for Detecting the Forest Fires”. Turkish Journal of Science and Technology 18/2 (Eylül 2023), 449-459. https://doi.org/10.55525/tjst.1301903.
JAMA Kadıoğlu BM, Karatay S, Çetinceviz Y, Erken F. Development of Unmanned Aerial Vehicle for Detecting the Forest Fires. TJST. 2023;18:449–459.
MLA Kadıoğlu, Barış Mert vd. “Development of Unmanned Aerial Vehicle for Detecting the Forest Fires”. Turkish Journal of Science and Technology, c. 18, sy. 2, 2023, ss. 449-5, doi:10.55525/tjst.1301903.
Vancouver Kadıoğlu BM, Karatay S, Çetinceviz Y, Erken F. Development of Unmanned Aerial Vehicle for Detecting the Forest Fires. TJST. 2023;18(2):449-5.