Intelligent pest monitoring optimal interval discrimination method

By constructing a set of control response event segments and event-protected resampling rules, and optimizing the monitoring interval, the problems of high resource consumption and incomplete control response of field intelligent pest monitoring equipment were solved, achieving efficient coverage and accurate control of pest population change trends.

CN122451672APending Publication Date: 2026-07-24江西省经济作物研究所
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Patent Information

Application Number
CN202610896967.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-06-22
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Existing field-based intelligent pest monitoring equipment consumes a lot of resources under long-term operation conditions and is difficult to adapt to different pest population stages and equipment resource status, resulting in incomplete recording of control response event segments and affecting the judgment of control windows.

Method used

By constructing a set of event segments for prevention and control response, a set of candidate monitoring intervals is generated. Then, an event-protected resampling rule is used to process the resampling window, and monitoring quality indicators are calculated to optimize the optimal monitoring interval to meet resource constraints and prevention and control response requirements.

Benefits of technology

It enables efficient coverage of pest population change trends under resource constraints, ensures complete recording of control response event segments, and improves the accuracy of control window judgment and equipment resource utilization efficiency.

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Abstract

The invention relates to the technical field of intelligent pest monitoring, in particular to an intelligent pest monitoring optimal interval judgment method, which comprises the following steps of: acquiring continuous trapping counting data of target pests and constructing an original monitoring sequence; forming a prevention response event section set including trigger starting time, section peak time and section releasing time according to the prevention threshold; generating a candidate monitoring interval set based on a preset minimum sampling interval, an allowable maximum monitoring interval and a prevention and control response allowable time limit, and executing event protection type resampling on each candidate interval; calculating an information loss degree, a trend fidelity, a resource consumption degree, a prevention event coverage rate, a prevention response delay penalty degree and a stage transfer retention degree, and screening and determining an optimal monitoring interval under the constraint of an edge resource budget. According to the method, equipment energy consumption and communication and storage resource consumption can be reduced while prevention and control event coverage and response timeliness are ensured.
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