Forest fire monitoring system with autonomous learning ability

Abstract

The invention discloses a forest fire monitoring system with the autonomous learning ability. By means of a forest fire monitoring technology of a seamless fusion intelligent network nerve model, andby combining professional knowledge of forest management and forest fire prevention experience, a forest fire prevention intelligent monitoring early warning and emergency command system is built, andthe functions in multiple aspects of automatic monitoring of forest video, accurate smoke and fire recognition, precise fire point positioning, fire spreading trend deduction, auxiliary decision making of a suppression command, evaluation after fire and the like, a complete service chain of forest fire prevention is built, and various individual needs of users are met in a targeted mode. By monitoring temperature information, light intensity information, humidity information, wind direction information and the like of the forest scene in real time, the monitored data is input into the networknerve model for parameter analysis, whether detected parameters are within a safety range or not is judged, and then whether the risk of unknown fire exists in the forest or not is monitored in realtime.

Description

technical field [0001] The invention relates to the technical field of forest fires, in particular to a forest fire monitoring system with self-learning ability. Background technique [0002] Forest fire is the most dangerous enemy of the forest and the most terrible disaster of forestry. It will bring the most harmful and devastating consequences to the forest. Forest fires not only burn the forests and harm the animals in the forests, but also reduce the regeneration capacity of the forests, cause soil barrenness and damage the forest's ability to conserve water, and even lead to an imbalance in the ecological environment. Although science in today's world is advancing with each passing day, human beings have not yet made great progress in subduing forest fires; therefore, forest fire prevention and detection are more realistic than extinguishing them. [0003] The forest fire monitoring system in the prior art does not monitor the on-site environmental information of the...

AI Technical Summary

Problems solved by technology

Forest fires not only burn the entire forest and harm the animals in the forest, but also reduce the regeneration ability of the forest, cause soil barrenness and damage the function of the forest to conserve water, and even lead to the imbalance of the ecological environment

Although science in today's world is advancing with each passing day, human beings have not yet made great progress in subduing forest fires; therefore, prevention and detection of forest fires are more practical than extinguishing them

[0003] The forest fire monitoring system in the prior art does not monitor the on-site environmental information of the forest in real time, so the data collected for the on-site environmental information of the forest is not accurate enough to effectively control the occurrence of fires

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