Forest fire early warning method and system based on fuzzy Bayesian network

Abstract

The invention discloses a forest fire early warning method and system based on a fuzzy Bayesian network and belongs to the fire-fighting safety field. The method comprises the following steps that anunmanned aerial vehicle is equipped with a plurality of sensors to inspect a forest along a set route, senses data of a driving area in real time and sends the data to a ground station; the ground station combines the number of local sunny days and the number of flammable plants to carry out stage treatment on flammable grades, and carries out early judgment of fire warning according to temperature, humidity, smoke and gas information; the ground station receives the data of each sensor, then uses a fuzzy Bayesian network to process the sensor data, and calculates and acquires a fire occurrence probability; when the probability of the fire is high, the ground station sends a fire warning signal, whether there is the fire, a real-time situation of the fire and location information to a forest management center; and when the probability of the fire is low, the unmanned aerial vehicle flies at the same height along the set route. In the invention, a fuzzy Bayesian network algorithm is used to process the sensor data, the fire probability can be accurately calculated so that correlation personnel can accurately acquire a fire condition at first time.

Description

technical field [0001] The invention relates to the field of fire safety, in particular to a forest fire early warning method and system based on a fuzzy Bayesian network. Background technique [0002] The definition of forest fire is: in the forest area, the sudden burning of large forest trees that are out of human control, and the spread speed is very fast. Forest fire prevention is an important part of China's disaster prevention and reduction. It is of great significance to the protection of forest resources and the development of a good ecological environment, and has a major impact on China's energy development. [0003] Forest fire monitoring mainly adopts the methods of manual observation, remote video monitoring, satellite remote sensing and drone patrolling. The artificial lookout method is to set up lookout posts at the commanding heights, and the on-duty personnel are on duty 24 hours a day. Due to human negligence and negligence, many fires will not be detecte...

AI Technical Summary

Problems solved by technology

Since the infrared thermal imager relies on temperature difference imaging, and the temperature difference of the general target is not large, the contrast of the infrared thermal image is low, which makes the ability to distinguish details worse, and the target cannot be seen clearly through transparent obstacles; while the commonly used camera video image processing method Failure to precisely identify the possibility or occurrence of a fire

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