Author:
Nori Ruba R.,Farhan Rabah N.,Abed Safaa Hussein
Abstract
Abstract
Novel algorithm for fire detection has been introduced. CNN based System localization of fire for real time applications was proposed. Deep learning algorithms shows excellent results in a way that it accuracy reaches very high accuracy for fire image dataset. Yolo is a superior deep learning algorithm that is capable of detect and localize fires in real time. The luck of image dataset force us to limit the system in binary classification test. Proposed model was tested on dataset gathered from the internet. In this article, we built an automated alert system integrating multiple sensors and state-of-the art deep learning algorithms, which have a limited number of false positive elements and which provide our prototype robot with reasonable accuracy in real-time data and as little as possible to track and record fire events as soon as possible.
Subject
General Physics and Astronomy
Cited by
4 articles.
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1. Deep Learning-Based Fire and Smoke Detection System;2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE);2024-02-22
2. Effective and Precise Detection of Hazardous Fires from CCTV Images Using YOLOv7 Algorithm in Comparison with CNN;2023 Intelligent Computing and Control for Engineering and Business Systems (ICCEBS);2023-12-14
3. A Cyber-Physical System for Wildfire Detection and Firefighting;Future Internet;2023-07-06
4. Federated/Deep Learning in UAV Networks for Wildfire Surveillance;2023 Wireless Telecommunications Symposium (WTS);2023-04-19