The invention discloses a fire-fighting unmanned aerial vehicle autonomous patrol
system and method based on
the Internet of Things, and relates to the technical field of intelligent fire fighting, and the method comprises the steps: converging fixed
Internet of Things sensors, unmanned aerial vehicle airborne sensor
sensing data and unmanned aerial vehicle
cluster state data,
processing the data into a standardized
data set, dividing park monitoring nodes, and calculating a comprehensive risk value; constructing a weighted directed dynamic
risk map by combining the node space relationship, the distance and the environment prevailing
wind direction; simulating risk propagation based on a graph, identifying key nodes to form a key check set, determining a routine inspection set, and generating a differentiated task set; calculating task priority and execution cost, establishing a collaborative task allocation model with maximized
system overall efficiency, solving the collaborative task allocation model, and generating a task allocation scheme; the
system comprises corresponding function modules, realizes accurate
risk identification and intelligent task distribution, improves the patrol efficiency, and guarantees the
fire safety of the park.