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.