Forest smoke and fire real-time monitoring system and method based on robust multi-view

Abstract

The invention discloses a forest smoke and fire real-time monitoring method based on robust multi-view, and belongs to the technical field of forest smoke and fire safety monitoring. The method comprises the following steps: firstly, uniformly arranging forest smoke and fire data collection modules in a forest, and each forest smoke and fire data collection module comprising a forest smoke and fire image data collector; setting a robust multi-view detection module on a background server; inputting forest smoke and fire image data to the background server through a data transmission module by the forest smoke and fire data collection modules; and finally, enabling a robust multi-view detection module located on the background server to process and detect the input forest smoke and fire image data so as to judge whether a smoke and fire accident exists in the forest or not. The robustness multi-view detection module in the method is high in robustness, the forest smoke and fire accidentscan be monitored in real time, the monitoring precision is high, and high expandability is achieved.

Description

technical field [0001] The invention belongs to the technical field of forest pyrotechnic monitoring, and in particular relates to a robust multi-angle-based forest pyrotechnic real-time monitoring system and method. Background technique [0002] Forest is an important natural resource, which has a very close relationship with human beings. Its contribution to human beings is diverse. It not only provides various timber and economic plants, but also a source of many foods. However, in recent years, my country's forest resources have continued to increase. decrease, resulting in serious consequences. [0003] In the fields of face recognition, text classification and pattern recognition, Support Vector Machine (SVM, Support Vector Machine) is a supervised learning classifier, which constructs the best hyperplane by maximizing the distance between different hyperplanes for classification. While effectively dealing with linear inseparable problems, the regularization term is us...

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Problems solved by technology

[0022] In order to overcome the shortcomings of low forest firework monitoring accuracy and lack of scalability in the prior art, the present invention provides a robust multi-view forest firework real

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