Experimental Analysis of Robust Forest Fire Detection for Sustainability

Qurban A. Memon, Bethel Wodajo, Aryam Alshamsi, Shaikha Alshamsi, Amna Alshebli

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The incidence and severity of wildfires are rising due to climate change and global warming, which might have a growing effect on the Sustainable Development Goals. This research study looks on the creation of a prototype for fire detection in farmlands in GCC nations. After talking about how technology is progressing in this area, a methodology is proposed that speeds up fire detection by combining two techniques: sensor networks installed in fields and a UAV-based system for aerial fire detection. Each of these methods is explained in full, including its technology, operating system, and circuit schematics. Results from tests conducted on this functional prototype are presented to show the efficacy of this strategy.

Original languageEnglish
Title of host publicationICCTA 2023 - 2023 9th International Conference on Computer Technology Applications
PublisherAssociation for Computing Machinery
Number of pages6
ISBN (Electronic)9781450399579
Publication statusPublished - May 10 2023
Event9th International Conference on Computer Technology Applications, ICCTA 2023 - Vienna, Austria
Duration: May 10 2023May 12 2023

Publication series

NameACM International Conference Proceeding Series


Conference9th International Conference on Computer Technology Applications, ICCTA 2023


  • Ecological balance
  • Fire sensor network
  • Machine learning
  • UAV

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software


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