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  Authors

Dr.N.Sai Sindhuri,SK.Jasmin

  Keywords

forest fire, detection, smoke alert, computer vision, yolo model, deep learning.

  Abstract


The performance of Yolo V8 when compared to traditional approaches such as infrared imaging has been thoroughly studied and documented. Studies have found that the algorithm is more accurate in detecting fires before they become too severe or spread too far, allowing for quicker response times from firefighting units. For solving this problem, we developed a detection model called upgraded-YOLO based on the state-of-the-art object detection method of YOLOv8. The proposed model is able to perform real-time object detection. Firstly, the data will be collected and data labelling is performed. Unlike other objects detection models that divide image into multiple regions and perform object detection on multiple regions, YOLOv8 performs object detection on entire image in one forward pass through the network. This makes it fast and efficient for real time applications. A comparative study with several contemporary object detectors proved that the Upgraded-YOLO performed better. Therefore, the proposed detection technology can be deployed in a monitoring center in order to protect a strategic installation even in low-visibility conditions.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2306821

  Paper ID - 240379

  Author type - Indian Author

  Page Number(s) - g971-g976

  Pubished in - Volume 11 | Issue 6 | June 2023

  DOI (Digital Object Identifier) -   

  No Of Downloads - 110

  Author Country - India, 524137, NELLORE, NELLORE, 524137, Science and Technology

  Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Published Paper PDF : - http://www.ijcrt.org/papers/IJCRT2306821

  Published Paper URL: : - http://ijcrt.org/viewfull.php?&p_id=IJCRT2306821

  Published Paper PDF Downlaod: - download.php?file=IJCRT2306821

  Cite this article

Dr.N.Sai Sindhuri,SK.Jasmin,   "FIRE AND SMOKE DETECTION IN FOREST USING YOLOV8", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 6, pp.g971-g976, June 2023, Available at :http://www.ijcrt.org/papers/IJCRT2306821.pdf

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