The outbreak of fire is a problem that occurs everywhere, and the damage produced by fires and other incidences of this sort is immense both to nature and to people. Vision-based fire detection systems have garnered significant appeal compared to more conventional sensor-based systems. However, using image processing technology to identify objects is highly laborious. In this study, we explored the use of image processing to detect fires and presented a PSO-based k-means clustering strategy. Later, the new approach is compared to current fire detection systems, and testing findings demonstrate that the proposed methodology has superior accuracy.
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Jain et al. (2023) studied this question.
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