Unmanned aerial vehicle monitoring and early warning method, computing device, storage medium and early warning system

By obtaining drone flight data in real time and using position prediction and abnormal behavior detection models, we can discover the risk that drone may deviate from the route in advance, solving the problem of insufficient timeliness in the existing technology, and improving the early warning of drone monitoring system ability.

CN119296289APending Publication Date: 2025-01-10AUTEL INTELLIGENT AUTOMOBILE CORP LTD
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Patent Information

Application Number
CN202411341931.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-09-25
Publication Date
2025-01-10

AI Technical Summary

Technical Problem

The existing drone monitoring system cannot detect the risk of drone flight deviation in advance, and the timeliness is insufficient, so preventive measures cannot be taken in advance.

Method used

By obtaining real-time flight data of the drone, use the position prediction model to predict future locations, and determine whether it is in the preset latitude and longitude fence. If it is not there, an early warning will be triggered; at the same time, use the abnormal behavior detection model to detect the abnormal score of the predicted location, if Above the threshold, triggering an early warning.

Benefits of technology

Real-time prediction of the drone's flight trajectory and early detection of potential deviation risks are achieved, improving the timeliness of the system, and users can take preventive measures before problems occur to ensure flight safety.

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Abstract

The invention relates to the technical field of unmanned aerial vehicle warning, and discloses an unmanned aerial vehicle monitoring and early warning method, computing equipment, a storage medium and an early warning system. The method comprises the steps that flight data, collected by a sensor in real time, of an unmanned aerial vehicle are acquired, the flight data are time series data, and the flight data comprise the longitude and the latitude in position coordinates of the unmanned aerial vehicle; inputting the flight data into a position prediction model to obtain a predicted position of the unmanned aerial vehicle in future time, the predicted position including longitude and latitude; whether the predicted position is in a preset longitude and latitude fence is judged, and the longitude and latitude fence is set according to a set route of the unmanned aerial vehicle; if the predicted position is not in the longitude and latitude fence, determining that the unmanned aerial vehicle deviates from a set route; early warning is triggered when it is determined that the unmanned aerial vehicle deviates from the set route. According to the invention, the timeliness of route deviation monitoring and early warning of the unmanned aerial vehicle is improved.
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Citation Information

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