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US 2026/0237040 A1Published application
Detecting functional impairment of camera-monitored insect traps
OwnerMatthias Tempel, Fabian Christian Born +2inventors
InventorsMatthias Tempel, Fabian Christian Born, Martjin Diederik Polman, Sven Meyer zu Eißen
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Abstract
The systems, methods and computer programs disclosed herein relate to the automated recognition of functional impairments with camera-monitored insect traps using machine learning methods.
Claims17
A computer-implemented method comprising:
- receiving an image recording, wherein the received image recording shows at least part of a collection area of an insect trap;
- providing a trained machine learning model, wherein the machine learning model is configured, and has been trained on the basis of training data, to distinguish image recordings of insect traps with a functional impairment from image recordings of insect traps without a functional impairment;
- feeding the received image recording to the trained machine learning model;
- receiving information from the machine learning model, wherein the information indicates whether the image recording shows an insect trap with a functional impairment;
- and
- in the event that the received image recording shows an insect trap with a functional impairment, outputting a message that the insect trap, shown at least partially in the received image recording, has a functional impairment.
3 more elements
A computer system comprising:
- an input unit;
- a control and computing unit;
- and
- an output unit;
- wherein the control and computing unit is configured to:
- cause the input unit to receive an image recording, wherein the received image recording shows at least part of a collection area of an insect trap;
- feed the received image recording to a machine learning model, wherein the machine learning model is configured, and has been trained on the basis of training data, to distinguish image recordings of insect traps with a functional impairment from image recordings of insect traps without a functional impairment;
- receive information from the machine learning model, wherein the information indicates whether the received image recording shows an insect trap with a functional impairment;
- and
- cause the output unit to output a message, wherein the message indicates that the insect trap, shown at least partially in the received image recording, has a functional impairment when the information output by the machine learning model indicates that the received image recording shows an insect trap with a functional impairment.
7 more elements
A system comprising:
- an insect trap;
- a camera;
- a control unit;
- an analysis unit;
- a transmission unit;
- and
- an output unit,
- wherein the control unit is configured to cause the camera to generate one or more image recordings of a collection area of the insect trap,
- wherein the analysis unit is configured to feed the one or more generated image recordings to a machine learning model, wherein the machine learning model is configured, and has been trained on the basis of training data, to distinguish image recordings of insect traps with a functional impairment from image recordings of insect traps without a functional impairment,
- wherein the analysis unit is configured to receive information from the machine learning model, wherein the information indicates whether the one or more image recordings show an insect trap with a functional impairment,
- wherein the transmission unit is configured to transmit the information and/or the one or more image recordings to a separate computer system,
- wherein the output unit is configured to output the information.
9 more elements
Dependencies are inferred from the claim text.