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Early Fire Detection Mobile Robotic System With Hybrid Locomotion

Cilt: 8 Sayı: 4 15 Temmuz 2025
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Early Fire Detection Mobile Robotic System With Hybrid Locomotion

Öz

In this study, a mobile robotic structure with fire detection and hybrid locomotion capabilities designed and developed. The hybrid locomotion system is an adaptive three-wheeled structure, and it has been structured to provide obstacle climbing and linear motion. The paper puts forward a structure for obstacle avoidance and path planning named "Direction Based Angle Computation". The system is designed to categorize obstacles as either negligible or surmountable, with this classification determined by the height and shape of the obstacles. The objective of the "Fire Search and Find" and "Fire Detection" systems is to identify potential fire locations and calculate the associated probabilities. Experimental tests are conducted for the mechanical structure and architecture of robotic systems. The experimental test results demonstrated that the motion systems have proficiency in both rolling-climbing and linear motions. The Direction Based Angle Computation approach is a proper methodology for the tasks path planning and obstacle avoidance. The proposed fire detection algorithm with the usage of Faster R-CNN machine learning model, has been shown to determine the probability of a fire source with 93% accuracy.

Anahtar Kelimeler

Kaynakça

  1. Alqourabah H, Muneer A, Fati SM. 2021. A smart fire detection system using IoT technology with automatic water sprinklers. Int J Electr Comput Eng, 11(4).
  2. Bertram C, Evans MH, Javaid M, Stafford T, Prescott T. 2013. Sensory augmentation with distal touch: The tactile helmet project. In: Biomimetic and Biohybrid Systems, Proc Second Int Conf Living Machines, London, UK, pp: 24-35.
  3. Bruzzone L, Nodeh SE, Fanghella P. 2022. Tracked locomotion systems for ground mobile robots: A review. Machines, 10(8): 648.
  4. Buriboev AS, Rakhmanov K, Soqiyev T, Choi AJ. 2024. Improving fire detection accuracy through enhanced convolutional neural networks and contour techniques. Sensors, 24(16): 5184.
  5. Cetin AE, Dimitropoulos K, Gouverneur B, Grammalidis N, Günay O, Habiboğlu YH, Verstockt S. 2013. Video fire detection – review. Digit Signal Process, 23(6): 1827-1843.
  6. Dampage U, Bandaranayake L, Wanasinghe R, Kottahachchi K, Jayasanka B. 2022. Forest fire detection system using wireless sensor networks and machine learning. Sci Rep, 12(1): 46.
  7. Fonollosa J, Solórzano A, Marco S. 2018. Chemical sensor systems and associated algorithms for fire detection: A review. Sensors, 18(2): 553.
  8. Haukur I, Heimo T, Anders L. 2010. Industrial fires: An overview. Brandforsk Project, SP Report 2010:17, SP Tech Res Inst Sweden, Borås, Sweden, pp: 15-26.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Yangın Güvenliği Mühendisliği, Makine Tasarımı ve Makine Elemanları, Malzeme Tasarım ve Davranışları, Makine Mühendisliği (Diğer)

Bölüm

Araştırma Makalesi

Erken Görünüm Tarihi

9 Temmuz 2025

Yayımlanma Tarihi

15 Temmuz 2025

Gönderilme Tarihi

20 Nisan 2025

Kabul Tarihi

25 Mayıs 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 8 Sayı: 4

Kaynak Göster

APA
Sucuoğlu, H. S., & Böğrekci, İ. (2025). Early Fire Detection Mobile Robotic System With Hybrid Locomotion. Black Sea Journal of Engineering and Science, 8(4), 1111-1120. https://doi.org/10.34248/bsengineering.1680411
AMA
1.Sucuoğlu HS, Böğrekci İ. Early Fire Detection Mobile Robotic System With Hybrid Locomotion. BSJ Eng. Sci. 2025;8(4):1111-1120. doi:10.34248/bsengineering.1680411
Chicago
Sucuoğlu, Hilmi Saygın, ve İsmail Böğrekci. 2025. “Early Fire Detection Mobile Robotic System With Hybrid Locomotion”. Black Sea Journal of Engineering and Science 8 (4): 1111-20. https://doi.org/10.34248/bsengineering.1680411.
EndNote
Sucuoğlu HS, Böğrekci İ (01 Temmuz 2025) Early Fire Detection Mobile Robotic System With Hybrid Locomotion. Black Sea Journal of Engineering and Science 8 4 1111–1120.
IEEE
[1]H. S. Sucuoğlu ve İ. Böğrekci, “Early Fire Detection Mobile Robotic System With Hybrid Locomotion”, BSJ Eng. Sci., c. 8, sy 4, ss. 1111–1120, Tem. 2025, doi: 10.34248/bsengineering.1680411.
ISNAD
Sucuoğlu, Hilmi Saygın - Böğrekci, İsmail. “Early Fire Detection Mobile Robotic System With Hybrid Locomotion”. Black Sea Journal of Engineering and Science 8/4 (01 Temmuz 2025): 1111-1120. https://doi.org/10.34248/bsengineering.1680411.
JAMA
1.Sucuoğlu HS, Böğrekci İ. Early Fire Detection Mobile Robotic System With Hybrid Locomotion. BSJ Eng. Sci. 2025;8:1111–1120.
MLA
Sucuoğlu, Hilmi Saygın, ve İsmail Böğrekci. “Early Fire Detection Mobile Robotic System With Hybrid Locomotion”. Black Sea Journal of Engineering and Science, c. 8, sy 4, Temmuz 2025, ss. 1111-20, doi:10.34248/bsengineering.1680411.
Vancouver
1.Hilmi Saygın Sucuoğlu, İsmail Böğrekci. Early Fire Detection Mobile Robotic System With Hybrid Locomotion. BSJ Eng. Sci. 01 Temmuz 2025;8(4):1111-20. doi:10.34248/bsengineering.1680411

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