Monitoring of arthropods

Abstract

The present disclosure relates to the monitoring of arthropods on the basis of captured images. The subject matter of the present disclosure includes a computer-implemented method, a computer system, a computer program, and a device.

Description

[0001] BCS243043 FC

[0002] Monitoring arthropods

[0003] TECHNICAL AREA

[0004] The present revelation deals with the monitoring of arthropods based on image recordings.

[0005] The subject matter of the present disclosure is a computer-implemented method, a computer system, a computer program and a device.

[0006] INTRODUCTION

[0007] Approximately two-thirds of currently known animal species belong to the arthropods (phylum Arthropoda), 85% of which are insects. A significant proportion of arthropods are phytophagous: these animals feed on plants and can impair growth, cause damage through sucking and feeding, and transmit viral diseases. This can lead to, for example, substantial losses in yield and quality in crop cultivation.

[0008] W02020 / 058175A1 discloses a device and a method for detecting arthropods in a region where plants grow, using a camera.

[0009] US2009 / 153659A1 discloses a system and a method for detecting and classifying objects in images, such as insects and other arthropods.

[0010] WO2023 / 239794A1 discloses systems and methods for monitoring arthropod vectors and for creating projective or predictive models.

[0011] W02013 / 079601A1 discloses a system and a method for monitoring plants and / or infestation of plants with pests during storage.

[0012] In modern agriculture, the detection and identification of pests within agriculturally used areas plays an important role.

[0013] SUMMARY

[0014] This revelation addresses these and other aspects.

[0015] A first subject matter of the present disclosure is a computer-implemented method for configuring a device for monitoring arthropods in an area where crops are cultivated. The method comprises the steps:

[0016] - Receiving and / or obtaining application information relating to the device for monitoring arthropods, wherein the device comprises an arthropod trap or means for connecting the device to an arthropod trap, wherein the application information specifies the crops, the area, the arthropods and / or the trap,

[0017] - Configuring the device based on the application information. Another subject of the present disclosure is a computer system comprising a control unit,

[0018] - wherein the control unit is configured to determine and / or receive application information relating to a device for monitoring arthropods in an area where crops are grown, by means of a receiving unit, wherein the device comprises an arthropod trap or means for connecting the device to an arthropod trap, wherein the application information specifies the crops, the area, the arthropods and / or the trap,

[0019] - wherein the control unit is configured to configure the device based on the application information and / or to initiate a configuration of the device.

[0020] Another subject of the present disclosure is a non-volatile, computer-readable storage medium on which a computer program is stored which, when executed by a computer system, causes the computer system to perform the following steps:

[0021] - Receiving and / or obtaining application information relating to the device for monitoring arthropods, wherein the device comprises an arthropod trap or means for connecting the device to an arthropod trap, wherein the application information specifies the crops, the area, the arthropods and / or the trap,

[0022] - Configuring the device based on the application information and / or initiating a configuration of the device based on the application information.

[0023] Another subject of the present disclosure is a device for monitoring arthropods in an area where crops are grown, comprising a camera and a control unit,

[0024] - wherein the control unit is configured to receive and / or determine application information and to configure the device based on the application information and / or to initiate a configuration of the device based on the application information.

[0025] Further items can be found in the detailed revelation and the drawings.

[0026] BRIEF DESCRIPTION OF THE DRAWINGS Fig. 1 shows an exemplary and schematic embodiment of the computer-implemented method of the present disclosure.

[0027] Fig. 2 shows an exemplary and schematic embodiment of the computer system of the present disclosure.

[0028] Fig. 3 shows an example and schematic of a device for monitoring arthropods and how it is produced from various components.

[0029] DETAILED REVELATION

[0030] The subject matter of this disclosure is explained in more detail below, without distinguishing between the subject matter of this disclosure (process, computer system, computer program, device). Rather, the following explanations are intended to apply analogously to all subject matter of the disclosure, regardless of the context in which they are described (process, computer system, computer program, device). In other words, features described in relation to one subject matter apply analogously to all other subjects.

[0031] If the present description or the claims specify steps in a sequence, this does not necessarily mean that the disclosure is limited to the specified sequence. Rather, it is conceivable that the steps could also be carried out in a different sequence or even in parallel with one another, unless, for example, one step builds upon another, which requires that the building step be carried out subsequently (this will become clear in the specific case). The specified sequences are therefore exemplary embodiments of the present disclosure.

[0032] The subject matter of this disclosure is further explained in some places with reference to drawings. These drawings depict specific embodiments with specific features and combinations of features, primarily for illustrative purposes; this disclosure should not be understood as being limited to the features and combinations of features shown in the drawings. Furthermore, statements made in the description of the drawings with regard to features and combinations of features are intended to be generally applicable, that is, transferable to other embodiments and not limited to the embodiments shown.

[0033] The article "ein" means "one or more," unless preceded by "nur" or "lemiglich." The same applies analogously to the article "eine."

[0034] The expressions ‘based on’ and ‘based on’ mean ‘at least partly based on’, unless explicitly stated otherwise.

[0035] The term “or” is not to be understood as an exclusive “or”, i.e. the expression “A or B” includes “A”, “B” as well as “A and B”.

[0036] The terms used in this disclosure have the meaning they have in the prior art, in particular in the prior art cited in this disclosure, unless otherwise stated.

[0037] One subject matter of the present disclosure is a computer-implemented method for configuring a device. The device is a device for monitoring arthropods in an area where crops are cultivated.

[0038] “Arthropods” are a diverse group of invertebrate animals belonging to the phylum Arthropoda.

[0039] Arthropods play an important role in ecosystems as pollinators, decomposers, and / or as part of the food web. They can also be of economic importance, both beneficial (e.g., pollination, silk production) and detrimental (e.g., as pests in agriculture, vectors of diseases).

[0040] Arthropods are divided into several groups (subphyla and classes), including insects and arachnids.

[0041] In one embodiment of the present disclosure, the term "arthropods" refers exclusively to insects and arachnids.

[0042] In another embodiment of the present disclosure, the term "arthropods" refers exclusively to insects.

[0043] In another embodiment of the present disclosure, the term "arthropods" refers exclusively to adult insects.

[0044] In another embodiment of the present disclosure, the term "arthropods" refers exclusively to insects in the form of caterpillars.

[0045] In another embodiment of the present disclosure, the term "arthropods" refers exclusively to arachnids.

[0046] In another embodiment of the present disclosure, the term "arthropods" refers exclusively to mites.

[0047] In another embodiment of the present disclosure, the term "arthropods" refers exclusively to pests of the crops grown in the area.

[0048] The term "monitoring" usually means that the presence of one or more arthropods in an area where crops are or are to be grown can be detected with the aid of the device of the present disclosure.

[0049] The term "crop" refers to a plant that is intentionally cultivated through human intervention and / or used by humans. A "crop" encompasses any plant that is deliberately grown and / or cultivated by humans for food, animal feed, fiber, timber, fragrances, medicinal, hygienic, and / or other economic purposes. These plants are typically specifically selected and managed to produce a yield or harvest, and they can include a wide variety of species, such as cereals, fruits, vegetables, oilseeds, and fiber crops. Parts of the cultivated crop may be suitable for human and / or animal consumption. Ornamental plants and algae also fall under the term "crop." The term "crop" also includes seeds that are sown to enable a plant to grow.

[0050] In one embodiment of the present disclosure, the term "crop crop" also includes cover crops. A cover crop is a plant primarily planted to control soil erosion, fertility, ecological status, water, weeds, pests, diseases, biodiversity, and / or wildlife. Cover crops are generally not grown for direct harvesting but instead benefit the soil and / or subsequent crops. They are typically planted during the off-season and / or between regular crop plantings. Cover crops can help prevent soil erosion, improve soil health, increase organic matter content, suppress weeds, and / or reduce the need for synthetic fertilizers and / or pesticides. In addition, they can promote biodiversity, provide habitat for beneficial insects, and / or contribute to overall sustainable agricultural practices.Common cover crops include pulses such as clover and vetch, grasses such as rye and oats, and various other species, depending on the specific agricultural objectives and / or local conditions.

[0051] The area where the crops are grown can be a field (e.g. outdoors), a greenhouse, a polytunnel, a plantation, or any other area where crops are (or can be) grown.

[0052] The device of the present disclosure comprises a catching device for arthropods or can be mechanically connected to a catching device.

[0053] The trapping device includes a collection area. The collection area is an area accessible to arthropods. It can be a flat surface, such as a board, map, or similar object. It can be the bottom of a container. It can be a liquid within a container. It can be a part of a plant, such as a leaf, fruit, or other plant part.

[0054] In one embodiment of the present disclosure, the catching device comprises a container filled with a liquid, e.g. a catching tray, as described in W02020 / 058175A1, W02020 / 058170A1, WO2021 / 213824A1 or WO2022 / 243150A1.

[0055] In one embodiment of the present disclosure, the trapping device comprises a surface provided with an adhesive, as described, for example, in WO2023 / 043871A1, WO2018 / 131853 Al, W02004 / 095919A2 or EP24206951.6. Such a trapping device is also referred to in this disclosure as an adhesive trap.

[0056] In one embodiment of the present disclosure, the trapping device comprises a tent-like frame that defines an interior space into which arthropods can enter. Such trapping devices are also known as delta traps (see, e.g., WO2018 / 078638A1); however, they can have shapes other than a prism (see, e.g., EP24206951.6). Such a trapping device is a special type of adhesive trap, since such delta traps are usually provided with a card or panel coated with an adhesive. This special type is characterized in that the card or panel coated with the adhesive is enclosed in a housing to protect it from environmental influences (e.g., precipitation, contamination, and the like). Otherwise, an adhesive trap can also be open (e.g., at the top).

[0057] As an attractant, the collection area can be colored (e.g., yellow or red) to attract specific arthropods. In addition to or instead of color, other attractants can be used. For example, a pheromone or scent that mimics a food source could be used. Another possibility is the use of a source of electromagnetic radiation in the infrared, visible, and / or ultraviolet range to attract (specific) arthropods. Sounds that imitate, for example, mating males and / or females are also conceivable. Finally, special patterns that mimic, for example, a plant are another option.

[0058] If a container filled with a liquid is used, it can be filled with water and optionally with one or more additives. Such an additive could be, for example, a surfactant to reduce surface tension. It could also be an attractant to lure (specific) arthropods. Or it could be an agent to prevent algae growth (for example, a herbicide).

[0059] The device may include one (or more) catching devices for arthropods. Such a catching device may be an integral part of the device of the present disclosure.

[0060] The device can also be configured to be mechanically connected to one or more catching devices. The device can include means for mechanically connecting it to a catching device. In one embodiment, connecting means are provided for a reversible mechanical connection of the device to a catching device.

[0061] “Reversible” means that the connection between the device and the catch can be broken without leaving any trace of the device and catch ever being connected.

[0062] In one embodiment, the device is designed so that it can be reversibly connected to different types of catching devices.

[0063] In one embodiment, the device is configured to have connecting elements compatible with those of a catch tray and an adhesive trap, while the catch tray and the adhesive trap have connecting elements compatible with those of the device. In another embodiment, the connecting elements of the catch tray and the adhesive trap are identical.

[0064] “Compatible” means that the connecting elements of the device can be reversibly connected to the connecting elements of the trap tray and the glue trap, so that when connected in this way the device and the trap tray or the device and the glue trap form a system for monitoring arthropods.

[0065] In one embodiment, the device is designed such that a mechanical connection between the device and the catching device also establishes an electrical contact between the device and the catching device (see, for example, EP24205469.0, the contents of which are to be fully incorporated into this description by reference).

[0066] The device includes means for generating images. These are usually one or more cameras.

[0067] A "camera" is a device or system designed to capture and record images of objects and / or phenomena. A camera uses, for example, electromagnetic radiation, sound waves, or other physical processes that can be visually represented. The camera converts received signals (e.g., optical or acoustic) into other signals (e.g., electrical) and / or data that can be stored, processed, displayed, and / or transmitted. The term "camera" encompasses devices that operate with all media or technologies, including analog and digital, optical, electronic, chemical, or other methods of image capture.The term "camera" encompasses a wide range of devices including, but not limited to, still cameras, video cameras, thermal imaging cameras, radar systems, ultrasound imaging devices, electron microscopes and all future technologies that can perform the function of image acquisition.

[0068] In one embodiment, the camera is an optical camera. In another embodiment of the present disclosure, the camera is a digital camera that generates two-dimensional images from light electrically using one or more image sensors. These are typically semiconductor-based image sensors such as CCD (CCD = charge-coupled device) or CMOS (CMOS = complementary metal-oxide semiconductor) sensors. Optical elements such as lenses, apertures, and the like serve to achieve the sharpest possible image of arthropods in the collecting area on the image sensor. A digital camera is configured to produce digital images.

[0069] Digital images can be processed, edited, and reproduced using computer systems and programs, as well as converted into standardized data formats such as JPEG (Joint Photographic Experts Group graphics format), PNG (Portable Network Graphics), or SVG (Scalable Vector Graphics). Digital images can be visualized using suitable display devices, such as computer monitors, projectors, and / or printers.

[0070] The camera can be pointed at the collection area of ​​the trap. In other words, the camera can be positioned to capture images of the collection area or a part of it.

[0071] The camera can be used to generate digital images of the collection area or a part thereof. The generated images can be used (i) to detect whether one or more arthropods are present in the imaged collection area (arthropod detection), (ii) to determine the position of an arthropod within the image (arthropod localization), (iii) to count arthropods in the imaged collection area, and / or (iv) to identify arthropods, i.e., to determine which arthropod species it is (e.g., subclass, superorder, order, suborder, family, genus, species, stage, beneficial organism, pest).

[0072] To image the collection area on one or more image sensors, a light source is required to illuminate the collection area so that light (electromagnetic radiation in the infrared, visible and / or ultraviolet range of the electromagnetic spectrum) is scattered / reflected from the illuminated collection area towards the camera.

[0073] Daylight can be used for this purpose.

[0074] The device can also include one or more light sources. Such a lighting unit provides defined illumination independent of daylight. For example, such a lighting unit can be mounted to the side of the camera and illuminate the collection area from there, so that the camera does not cast a shadow on the collection area.

[0075] It is also conceivable to position a light source below and / or next to the collection area, illuminating the collection area "from below" and / or "from the side", while a camera produces one or more images "from above".

[0076] It is conceivable that several light sources illuminate the collection area from different directions. The terms "light" and "illumination" are not intended to imply that the spectral range is limited to visible light (approximately 380 nm to approximately 780 nm). It is equally conceivable that electromagnetic radiation with a wavelength below 380 nm (ultraviolet light: 100 nm to 380 nm) and / or above 780 nm (infrared light: 780 nm to 1000 pm) is used for illumination. The image sensor and the optical elements of the camera are typically adapted to the electromagnetic radiation used.

[0077] The device includes a control unit.

[0078] The control unit serves to control the electrical / electronic components of the device and to coordinate the data flows between different components of the device.

[0079] The control unit typically comprises a processor, program memory, and main memory. The control unit may also include non-volatile data storage, such as semiconductor memory, which can be used to store images, measurements, analysis models, computer programs (software), and / or analysis results.

[0080] The control unit can be configured to use the camera to capture images of the collection area. The control unit can be configured to cause the camera to capture images of the collection area. The control unit can be configured to cause the camera to capture one or more images of the collection area at defined times and / or intervals and / or upon the occurrence of defined events. The control unit can be configured to transmit images, measurements, analysis results, geocoordinates, and / or other information to a separate computer system using a transmitter. The control unit can be configured to receive images from the camera and / or retrieve images from the camera and / or read images from a data storage device, which may be an integral part of the device.The control unit can be configured to receive data and / or commands and / or software updates using a receiving unit.

[0081] The control unit can be configured to detect, locate, count and / or identify arthropods depicted in images.

[0082] The detection, localization, counting, and / or identification of arthropods in images of the collection area can be achieved, for example, using a trained machine learning model. Such a machine learning model can be configured and trained to detect, localize, count, and / or identify arthropods depicted in images. Details on the automated detection, localization, counting and / or identification of arthropods in images are described in publications on this topic (see, for example: DCK Amarathunga et al.: Methods of Insect Image Capture and Classification: A Systematic Literature Review, Smart Agricultural Technology, Volume 1, 2021, 100023; C. Zhu et al.: Insect Identification and Counting in Stored Grain: Image Processing Approach and Application Embedded in Smartphones, Mob. Inf. Syst. 2018, 5491706: 1-5, W02020058175A1, W02020058170A1).

[0083] Such a "machine learning model" can be understood as a computer-implemented data processing architecture. The model can receive input data and deliver output data based on this input data and model parameters. Through training, the model can learn a relationship between the input data and the output data. During training, model parameters can be adjusted to deliver a desired output for a given input.

[0084] When training such a model, it is presented with training data from which it can learn. The trained machine learning model is the result of the training process. In addition to input data, the training data includes the correct output data (target data) that the model is to generate based on the input data. During training, patterns are recognized that map the input data to the target data.

[0085] During the training process, the input data for the training data is fed into the model, and the model generates output data. This output data is then compared to the target data. Model parameters are modified to reduce the deviations between the output and target data to a (defined) minimum. To modify the model parameters with a view to reducing these deviations, an optimization method such as gradient descent can be used.

[0086] The deviations can be quantified using a loss function. Such a function can be used to calculate the loss for a given pair of output and target data. The goal of the training process can be to modify (adjust) the parameters of the machine learning model so that the loss is reduced to a (defined) minimum for all pairs in the training dataset. Reducing the errors by modifying model parameters can be achieved using an optimization method (e.g., a gradient descent method).

[0087] If the output and target data are numbers, for example, the error function can be the absolute difference between these numbers. In this case, a large absolute error may mean that one or more model parameters need to be changed significantly.

[0088] For output data in the form of vectors, difference metrics between vectors such as the mean squared error, a cosine distance, a norm of the difference vector such as a Euclidean distance, a Chebyshev distance, an Lp norm of a difference vector, a weighted norm or another type of difference metric of two vectors can be chosen as the error function.

[0089] For higher-dimensional outputs, such as two-dimensional, three-dimensional, or even higher-dimensional outputs, an element-wise difference metric can be used. Alternatively or additionally, the output data can be transformed before calculating an error value, for example, into a one-dimensional vector.

[0090] Training can be terminated when a stop criterion is met. Such a stop criterion could be, for example: a predefined maximum number of training steps / cycles / epochs has been performed, deviations between output data and target data can no longer be reduced by changing the model parameters, and / or a predefined minimum error function has been reached.

[0091] A machine learning model configured to detect arthropods in an image can be trained, for example, on a large number of images containing collection areas with and without arthropods. The training data thus includes not only the images themselves but also information about whether or not an arthropod is present in each image. This information can be used as target data when training the model. The images can be fed to the machine learning model sequentially, and the model can generate an output for each image indicating whether or not an arthropod is present. This output can then be compared to the target data. Discrepancies can be reduced by modifying model parameters.

[0092] A machine learning model configured to identify arthropods in an image can be trained, for example, on a large number of images depicting areas containing specific arthropods. The training data therefore includes not only the images themselves but also information about which specific arthropods are present in each image. This information can be used as target data when training the model. The images can be fed to the machine learning model sequentially, and the model can generate an output for each image indicating which specific arthropod is present. This output can then be compared to the target data. Discrepancies can be reduced by modifying model parameters.

[0093] A machine learning model configured to locate arthropods in an image can be trained, for example, on a large number of images depicting areas where arthropods are present. For each image, there is information indicating where an arthropod is located within the image. This information can be used as target data when training the model. The images can be fed to the machine learning model sequentially, and the model can generate an output for each image indicating where an arthropod is located. This output can then be compared to the target data. Discrepancies can be reduced by modifying model parameters.

[0094] A machine learning model configured to count arthropods in an image can be trained, for example, on a large number of images depicting areas containing arthropods. For each image, a second image can exist in which an arthropod is marked, for example, by a bounding box. This information can be used as target data when training the model. Alternatively, the coordinates of the bounding boxes can be used as target data. Images without bounding boxes can be fed to the machine learning model sequentially, and the model can be trained to generate bounding boxes and / or predict their coordinates. The output can then be compared to the target data. Discrepancies can be reduced by modifying model parameters.Once the model is trained, the number of bounding frames generated or predicted by the trained model indicates the number of arthropods depicted in the image.

[0095] The methods described here for training machine learning models are merely examples. Numerous other methods and variations exist (see, for example, DCK Amarathunga et al.: Methods of Insect Image Capture and Classification: A Systematic Literature Review, Smart Agricultural Technology, Volume 1, 2021, 100023; C. Zhu et al.: Insect Identification and Counting in Stored Grain: Image Processing Approach and Application Embedded in Smartphones, Mob. Inf. Syst. 2018, 5491706: 1-5, W02020058175A1, W02020058170A1). The device includes a power supply. It is typically designed for autonomous outdoor operation for a period of several days, weeks, months, or even years. The means of energy supply include, for example, one or more electrochemical cells, accumulators, solar cells, fuel cells and / or generators (e.g. in combination with a wind turbine).

[0096] In one embodiment, the device comprises one or more solar cells and one or more accumulators for power supply. The at least one solar cell and the at least one accumulator are connected in such a way that the solar cell charges the accumulator when electromagnetic radiation (e.g., sunlight) strikes the at least one solar cell.

[0097] The device may include a transmitting unit to send information over a network to a separate computer system. This information may include, for example, images of the collection area. This information may also include the results of an analysis of an image, such as the number of arthropods depicted in an image, identified species, and / or messages regarding the status of the device.

[0098] The transmitting unit can be designed to transmit information via a mobile network (e.g., GSM: Global System for Mobile Communications, GPRS: General Packet Radio Service, UMTS: Universal Mobile Telecommunications System, LTE: Long Term Evolution), via a WLAN (Wireless Local Area Network), via Bluetooth, via DECT (Digital Enhanced Cordless Telecommunications), via a Low Power Wide Area Network (LPWAN or LPN) such as a NarrowBand IoT network, and / or via a combination of different transmission methods.

[0099] The transmitting unit can be designed to transmit information via a short-range radio connection (e.g., Bluetooth) to a base station, from which the information is then forwarded via cable and / or a long-range radio connection (e.g., a mobile network).

[0100] In one embodiment of the present disclosure, the transmitting unit comprises a modem and an antenna for transmitting information via a GSM, GPRS, 2G, 3G, LTE, 4G, 5G, 6G mobile network or via another mobile network.

[0101] The device may include a receiving unit to receive information over a network. This information may include software updates, status queries, application information, configuration information, and / or other / additional information.

[0102] The receiving unit can be designed to receive information via a mobile network.

[0103] The transmitting unit and the receiving unit can be components of a transmitting and receiving unit.

[0104] In one embodiment of the present disclosure, the device comprises a transmitting and receiving unit with which information can be received and transmitted via a GSM, GPRS, 2G, 3G, LTE, 4G, 5G, 6G mobile network or via another mobile network. In one embodiment of the present disclosure, the device can be adapted to various use cases. Adapting the device to a use case is also referred to in this description as "configuring" or "configuring".

[0105] By configuring the device, it can be set up to monitor specific arthropods, for example to detect, locate, identify and / or count them.

[0106] By configuring the device, it can be set up to monitor arthropods in a specific area.

[0107] By configuring the device, it can be set up to monitor arthropods under specific conditions.

[0108] By configuring the device, it can be set up to monitor arthropods using a specific capture device.

[0109] Configuration typically occurs during the initial startup of the device. The device's control unit can be configured to initiate a configuration mode upon initial startup, i.e., to put the device into a configuration mode. Initial startup can mean that the device is switched on for the first time by a user (e.g., an end customer). It is also possible for a user to manually put the device into configuration mode. This can be done, for example, by entering a command. In configuration mode, the device can receive and / or determine application information. The control unit can be configured to receive application information from the user via input devices. The control unit can also be configured to determine the device's position, for example, using a GPS receiver.In configuration mode, the control unit can be configured to determine the date. In configuration mode, the control unit can be configured to cause the camera to take an image. The image can show the collection area. The image can show an optical marker. In configuration mode, the control unit can be configured to configure the device based on application information. In configuration mode, the control unit can be configured to cause the transmitter to send application information over a network to a separate computer system. In configuration mode, the control unit can be configured to receive configuration information from the separate computer system via the receiver. In configuration mode, the control unit can be configured to configure the device based on the configuration information.

[0110] The control unit can be configured to put the device into an operating state after configuration. This operating state can be characterized by the device monitoring arthropods in a crop cultivation area according to the configuration. Monitoring arthropods in the operating state can include generating images of the collection area. Monitoring arthropods in the operating state can include detecting, locating, identifying, and / or counting arthropods in images. Monitoring arthropods in the operating state can include transmitting images and / or results of image analysis to the separate computer system.

[0111] Configuration is based on application information. This information specifies the use case. It can specify the crops grown in the area where the device is used or intended to be used. It can also specify the area where the device is used or intended to be used. Furthermore, it can specify the arthropods to be monitored by the device. Finally, it can specify the trapping device used to monitor the arthropods.

[0112] In one embodiment of the present disclosure, the application information includes arthropod information. The arthropod information specifies the arthropods to be monitored. In other words, the arthropod information specifies the arthropods that are commonly found in the area where the crops are or are intended to be grown. In other words, the arthropod information specifies the arthropods that are expected or may be found in the area. In other words, the arthropod information specifies the arthropods that are expected or may be found in the collection area of ​​the trapping device. In other words, the arthropod information specifies the arthropods that are or may be captured in the images of the collection area.

[0113] The arthropod information can specify which subclass, superorder, order, suborder, family, genus and / or species the (expected) arthropods belong to.

[0114] The arthropod information can specify the stage of development the (expected) arthropods are in.

[0115] Based on the arthropod information, a model for detecting, locating, identifying and / or counting arthropods in images of the collection area can be selected.

[0116] It is possible that several models exist, trained on different training data. It is possible that different models were trained on images showing different arthropods. The model whose training data included images of the specified arthropods can be selected. The model that is best suited or most likely to detect, locate, identify, and / or count the specific arthropods present in the area can be chosen.

[0117] The model can be configured to detect, locate, identify, and / or count arthropods in images of the collection area. The model may include configurable parameters. These parameters can be adjusted to suit the specific arthropods being analyzed, for example, to achieve optimal results.

[0118] For example, the arthropods can be used to determine how images of the collection area are pre-processed and / or edited before being fed to the model for detection, localization, identification and / or counting.

[0119] The term "preprocessing" describes a range of techniques that can be applied to prepare image captures (e.g., raw images) before they are passed to a machine learning model. The purpose of preprocessing is to improve image quality, reduce noise, and / or extract relevant features. Typical steps in preprocessing an image capture include image scaling (i.e., adjusting the image size to ensure a uniform input dimension for the model), normalization (i.e., adjusting the values ​​of the image elements to bring them within a specific range), noise reduction (e.g., by applying filters such as median filters or Gaussian filters), contrast adjustment (e.g., improving the image contrast through techniques like histogram normalization to increase feature visibility), and segmentation.Separation of the image capture into relevant areas or objects to facilitate analysis) and / or color space conversion (i.e., conversion of the image capture into a different color space (e.g., from RGB to HSV or LAB) to better capture certain features and / or facilitate processing).

[0120] The arthropod information can be used to determine when and / or how frequently the device's camera takes pictures of the collection area.

[0121] Some arthropods are more active at certain times of day or night. The camera can be configured to take images, or to take a larger number of images, or to take images more frequently during the times when these specified arthropods are typically active.

[0122] The image resolution can be determined based on the arthropod information. The image resolution can be adjusted to the specific arthropods being studied. For example, a lower resolution can be set for larger arthropods than for smaller ones.

[0123] The magnification for image capture can be set based on the arthropod information. It is conceivable that the camera is configured to capture magnified views of the collection area as images, for example, using one or more objects. The magnification can be adjusted to the specified arthropods. For instance, a lower magnification can be set for larger arthropods than for smaller ones.

[0124] Based on the arthropod information, further camera parameters can be set, which, for example, lead to the sharpest, most detailed, and / or highest-contrast image of arthropods on the camera's image sensor. Such camera parameters include, for example, exposure time, aperture, ISO value, white balance, exposure compensation, image format, scene mode, and / or image stabilization.

[0125] The arthropod information can be used to determine whether and / or how the collection area is illuminated.

[0126] The arthropod information can be used to determine the intensity with which the collection area is illuminated.

[0127] Based on the arthropod information, it can be determined which spectral range is used to illuminate the collection area. The spectral range, i.e., the wavelength range of the electromagnetic radiation emitted by the illumination unit, can be adapted to the specified arthropods. It is conceivable that dark, black-appearing arthropods are more easily detected in a different spectral range than light and / or white-appearing, green-appearing, or brown-appearing arthropods.

[0128] The arthropod information can therefore be used to determine whether a

[0129] The lighting unit is switched on during the production of images, which lighting unit is switched on, when one or more lighting units are switched on, and at what times and / or at what time intervals one or more lighting units are switched on.

[0130] In addition to illuminating the collection area, one or more lighting units can also be used to attract specific arthropods. Here, too, the lighting can be configured accordingly based on information about the arthropods.

[0131] The arthropods to be monitored can also be specified indirectly based on the cultivated / to-be-cultivated crops, the area in which the crops are cultivated and / or the trapping device used.

[0132] In one embodiment of the present disclosure, the application information includes crop information. This crop information can specify which crop is cultivated in the area. From the crop, it can be deduced which arthropods are to be expected in the collection area, namely those arthropods that typically appear when the crop is cultivated. These may, for example, be pests of the crop. A user may be interested in knowing whether such pests appear in the area where the user cultivates the crop. If the presence of such pests in the area is detected by means of the device of the present disclosure, the user can take measures to control the pests.

[0133] The crop information can specify which subclass, superorder, order, suborder, family, genus and / or species the crop grown in the area belongs to.

[0134] The crop information can specify the stage of development the crop is in.

[0135] Based on the crop information, a model for detecting, locating, identifying and / or counting arthropods in images of the collection area can be selected.

[0136] The crop information can be used to determine when and / or how frequently the device's camera takes pictures of the collection area.

[0137] The resolution of the images can be determined based on the crop information.

[0138] The information on the crop plants can be used to determine whether and / or how the collection area is illuminated.

[0139] The intensity with which the collection area is illuminated can be determined based on the information about the crop plants.

[0140] Based on the crop information, it can be determined which spectral range is used to illuminate the collection area.

[0141] Based on the crop information, it can be determined whether a lighting unit is switched on during image acquisition, which lighting unit is switched on, when one or more lighting units are switched on, and at what times and / or time intervals one or more lighting units are switched on. In one embodiment of the present disclosure, the application information includes capture device information.

[0142] Trapping device information can specify whether the trap is equipped with an attractant (e.g., a pheromone) and / or which attractant it uses. Specifying the attractant allows us to deduce which arthropods can be expected in the collection area—namely, those arthropods that are attracted by the attractant. Trapping device information can also specify the color of the collection area. The color of the collection area can act as an attractant to lure specific arthropods and thus influence which arthropods enter the collection area. Attractants can influence how frequently arthropods enter the collection area and / or how many arthropods enter the collection area within a defined period (e.g., per day or per week), as attractants specifically draw arthropods into the collection area.The color of the collection area can also influence the depiction and / or appearance of arthropods in an image of the collection area.

[0143] This allows, for example, the selection of one or more models for detecting, locating, identifying, and / or counting arthropods in images of the collection area based on the capture device information; the determination of when and / or how frequently the device's camera takes images of the collection area; the determination of the image resolution; the determination of whether and / or how the collection area is illuminated; the determination of the illumination intensity; the determination of which spectral range is used to illuminate the collection area; the determination of whether an illumination unit is switched on when images are taken; which illumination unit is switched on; when one or more illumination units are switched on; and at what times and / or intervals one or more illumination units are switched on.

[0144] - Camera parameters are set, and / or

[0145] - Maintenance and / or cleaning intervals will be determined.

[0146] Capture device information can specify the type of capture device used. This can indicate whether it is a sticky trap, a liquid-filled trap, the distance of the capture area from the camera's image sensor and / or lens, the size of the capture area, and / or its shape.

[0147] It is possible that the camera of the device needs to be, or should be, adapted to the specific trapping device. It is possible that different trapping devices have different distances between the camera's image sensor and the collection area, and the focus needs to be, or should be, adjusted accordingly. It is possible that the type of focusing (e.g., autofocus or fixed focal length) needs to be, or should be, adapted to the trapping device. It is possible that a different type of focusing will produce better results (e.g., sharper images of arthropods) with a water-filled trap than with a glue trap. It is possible that the size and / or shape of the collection area varies between different trapping devices, and the area captured by the camera needs to be, or should be, adjusted.

[0148] The focus and / or focusing method of the camera can be determined based on the trap information. The size of the collection area captured by the camera can also be determined based on this information. Furthermore, other camera parameters can be set using the trap information to create an image of arthropods that enables and / or improves automatic detection, localization, identification, and / or counting of these arthropods. Such camera parameters include, for example, shutter speed, aperture, ISO value, white balance, exposure compensation, image format, scene mode, and / or image stabilization.

[0149] It is possible that the lighting unit needs to be, or should be, adapted to the specific trapping device. It is possible that one or more lighting units are present, emitting electromagnetic radiation from different spectral ranges. It is possible that the spectral range and / or intensity of the electromagnetic radiation can or should be adapted to the color of the trapping area, for example, to create a high contrast between the arthropods and the surrounding area.

[0150] The information from the trapping device can therefore be used to determine the type of lighting, the intensity of the lighting and / or the spectral range of the lighting.

[0151] The type of trapping device can influence how exposed the collection area is to environmental factors. It can also affect how quickly and / or severely the collection area becomes contaminated. An open-topped sticky trap will become contaminated faster and / or more heavily than a delta trap. A collection area coated with an adhesive will become contaminated faster and / or more heavily than one without. The type of liquid in a collection tray can also influence the type, severity, and speed of contamination. A liquid containing an anti-algaecide will be less susceptible to algae growth than a liquid without an anti-algaecide. Therefore, the trapping device information can be used to determine maintenance and / or cleaning intervals.The device can be configured to send a notification of upcoming cleaning to a separate computer system at or shortly before the end of a maintenance and / or cleaning interval. The device can also be configured to clean the collection area itself at the end of a maintenance and / or cleaning interval.

[0152] In one embodiment of the present disclosure, the application information includes area information. The area information can specify the area in which the crops are cultivated (e.g., outdoors, in a greenhouse, in a polytunnel). The area can influence which arthropods appear in the area and / or how many arthropods typically enter the area or the collection area per unit of time (e.g., per day or per week). The area can influence the environmental influences to which the device is exposed. The area can influence how heavily and / or quickly the collection area becomes contaminated.Based on the area information, for example, one or more models can be selected for detecting, locating, identifying and / or counting arthropods in images of the collection area, it can be determined when and / or how frequently the device's camera takes images of the collection area, the resolution of the images can be determined, whether and / or how the collection area is illuminated can be determined, the intensity with which the collection area is illuminated can be determined, the spectral range used to illuminate the collection area can be determined, it can be determined whether a lighting unit is switched on when images are taken, which lighting unit is switched on, when one or more lighting units are switched on, and at what times and / or intervals one or more lighting units are switched on.

[0153] - Camera parameters are set, and / or

[0154] - Maintenance and / or cleaning intervals will be determined.

[0155] The application information can be entered into the device by a user via input devices (e.g. a keyboard, a computer mouse, a microphone).

[0156] The device can be configured to configure itself based on the application information.

[0157] It is also conceivable that the device is configured wholly or partially by a separate computer system.

[0158] It is possible for the device to be connected to a separate computer system, which then configures the device based on the application information. The connection can be established via a cable or wirelessly, for example, via a cellular network. In such a case, the application information must reach the separate computer system. Alternatively, the user can enter the application information into the separate computer system. It is also possible for the user to enter the application information into a first computer system, and for the application information and / or configuration information derived from it to be transmitted from the first computer system to a second computer system configured to configure the device.

[0159] The device can be configured through a software update and / or an update of software parameters.

[0160] It is possible that a separate computer system (e.g., the second computer system described above) causes the device to perform the configuration, either wholly or partially.

[0161] The application information can be determined fully or partially automatically. "Automatically" means without human intervention. The device may be configured to recognize which capture device is present. For example, the capture device and the device may be two separate units that can be mechanically connected to form an arthropod monitoring system. The capture device and the device may have connecting means that allow such a mechanical connection. These connecting means may have electrical contacts. When the device is mechanically connected to a capture device, an electrical connection is established between the device and the capture device.It is possible that the device is configured to detect, via the electrical contact, what type of catch device the device is connected to.

[0162] There are numerous ways to achieve such recognition.

[0163] In resistance coding, different types of locking devices have different electrical resistances. The device measures this resistance as a recognition component to determine which locking device it is connected to.

[0164] Capacitors with different capacitance values ​​can be connected to the electrical contacts of various traps. When connected, the device measures the capacitance, similar to the resistance coding method, to identify the trap.

[0165] By designing the mechanical connection with a unique configuration of pins and contacts (e.g., different number of pins, different pin arrangements and / or use of pins of different lengths), the device can determine the type of connected trapping device based on the pins that make contact.

[0166] It is also possible for interception devices to include an RFID transponder (RFID: radio frequency identification). The RFID transponder can be active (i.e., include a source of electrical energy). In one embodiment of the present disclosure, the RFID transponder is passive, i.e., it does not have its own source of electrical energy but is supplied with electrical energy by induction from the device. The device can be configured to read the RFID transponder at predefined times and / or at predefined intervals and / or upon the occurrence of defined events, thereby determining which interception device is present. The type of interception device can be stored as information in a data memory of the RFID transponder.

[0167] It is also possible for the device and the trap to exchange data in a connected state via digital communication protocols such as I2C, SPI, or UART. In this case, one component (e.g., the trap) can send a unique identification code to the other component (e.g., the device).

[0168] It is also possible to integrate an optical recognition system. When the components are connected, an optical marker (e.g., a QR code or barcode) on the capture device can be read by an optical sensor on the device (e.g., the camera). The optical marker can, for example, be placed in the collection area.

[0169] The device can configure itself using the automatically determined trap information. It is also possible for the device to be configured to transmit the automatically determined trap information to a separate computer system, which then configures the device.

[0170] The color, shape, and / or size of the collection area can be automatically determined from an image of the collection area. The device can be configured to generate an initial image of the collection area. For example, the device can be configured to generate such an initial image when the device is connected to a capture device and / or is first switched on. The device can be configured to analyze the initial image and determine the color, shape, and / or size of the collection area. The device can be configured to automatically configure itself based on the color, shape, and / or size of the collection area. The device can be configured to transmit the initial image and / or the automatically determined capture device information to a separate computer system.The separate computer system can be configured to analyze the initial image acquisition to determine the color, shape, and / or size of the collection area. The separate computer system can also be configured to configure the device based on the transmitted and / or determined capture device information.

[0171] It is also possible that the color and / or shape and / or size of the collection area is specific to the trapping device and that further information can be derived from the color and / or shape and / or size of the collection area, such as what type of trapping device it is, in what area it is (e.g., usually) used, for which arthropods it is intended and / or for which crops it is (e.g., usually) used.

[0172] Similarly, when using an attractant (e.g., a pheromone), it is possible that such an attractant is positioned in, above, below, or in the immediate vicinity of the collection area, making it visible in the initial image. Information about the presence or absence of the attractant (e.g., in the form of a capsule, gel, coating, or the like) in the image can be used to configure the device.

[0173] It is also possible for the device's position to be determined automatically. From the device's position (e.g., in the form of geocoordinates), it may be possible to deduce the area in which the device is used, which crops are cultivated in that area, and / or which arthropods are likely to be present.

[0174] The device can be configured to determine its position using a GPS receiver. The GPS receiver can be an integral part of the device and / or a separate unit.

[0175] A GPS receiver (GPS: Global Positioning System) is part of a satellite navigation system used to determine position. A satellite navigation system is based on satellites that continuously transmit their current position and the precise time using coded radio signals. From the signal travel times, a receiver (referred to in this description as the GPS receiver) can calculate its own position and speed. Well-known satellite navigation systems include NAVSTAR GPS, GLONASS, Galileo, and BeiDou. Since the abbreviation GPS (Global Positioning System) has become established in everyday language as a generic term for all satellite navigation systems, this description uses the term GPS as a collective term for all positioning systems.The term "GPS receiver" should therefore not be understood as limiting it to the GPS satellite navigation system; it should also include receivers of other satellite navigation systems. The device's position can also be derived from the (mobile) cell in which the device is located. In mobile communications, the simplest method of location determination relies on knowing the cell in which a transmitting unit is located. Since, for example, a switched-on mobile phone is connected to a base station, the mobile phone's position can be assigned to at least one cell (cell ID). Similarly, the position of a device, including a transmitting unit, can be equated with the cell to which the transmitting unit is connected. Using GSM (Global System for Mobile Communications), the location of a transmitting unit can be determined to within several hundred meters.In cities, the location can be determined with an accuracy of 100 to 500 meters; in rural areas, the radius increases to 10 kilometers or more. Combining the Cell ID information with the TA parameter (TA: Timing Advance) further improves accuracy. The higher this value, the farther the transmitting unit is from the base station. The EOTD method (EOTD: Enhanced Observed Time Difference) allows for even more precise location tracking of a transmitting unit. This method determines the time-of-flight differences of the signals between the transmitting unit and multiple receiving units.

[0176] Other methods of position determination are described in the prior art (see e.g. DE10029137A1, DE102010041548A1, DE102012214203A1, DE102015121384A1, DE102016225886A1, US2015119086A1).

[0177] Another automatically determined application piece of information can be the date and / or the season. The time, alone or in combination with the geocoordinates, can provide information about which arthropods are to be expected and / or what stage of development they are in.

[0178] In one embodiment of the present disclosure, the device is or comprises an IoT device.

[0179] "IoT" is the abbreviation for "Internet of Things," which in German means "Internet of Things." The Internet of Things (IoT) refers to a network of devices that are connected to the internet and can collect, exchange, and / or process data.

[0180] An "IoT device" is a uniquely identifiable electronic computing device configured to transmit, receive, process, and / or respond to data over a network without the need for human-to-human or human-to-computer interaction. An "IoT device" is typically equipped with computer chips, sensors, and communication hardware that enable it to collect, send, and / or receive data from its environment and / or other devices. An IoT device operates autonomously within an Internet of Things (IoT) ecosystem, which comprises networked IoT devices that communicate and / or interact via the internet and / or other network infrastructures. An IoT device is characterized by its ability to operate with minimal human intervention, utilizing embedded software, sensors, and network connectivity to perform its defined functions.

[0181] In one embodiment of the present disclosure, the IoT device is a component of the arthropod monitoring system of the present disclosure. Another component may be a capture device. In one embodiment of the present disclosure, the IoT device comprises the camera, the control unit, the transmitter, the receiver, the power supply unit, optionally one or more illumination units, and optionally a GPS receiver.

[0182] In one embodiment of the present disclosure, the IoT device comprises a housing into which the electrical and / or electronic components are placed. The housing protects the electrical / electronic components from moisture, contamination, and / or sunlight. The housing ensures that no arthropods or other organisms can enter the interior of the housing.

[0183] In one embodiment of the present disclosure, the housing comprises connecting means with which the IoT device can be mechanically connected to a collection tray. The connecting means ensure a defined alignment of the camera relative to the collection area of ​​the collection device.

[0184] In one embodiment, the mechanical connection is reversible, meaning it can be loosened and renewed.

[0185] In one embodiment, the IoT device is designed to be reversibly connected to different types of trapping devices.

[0186] In one embodiment of the present disclosure, the device of the present disclosure comprises a unique identifier. In one embodiment of the present disclosure, the unique identifier is attached to the device in the form of an optically readable code. The code may be printed and / or affixed and / or engraved and / or stamped and / or applied to the device by means of a laser and / or in another way and / or incorporated into or attached to the device.

[0187] The optically readable code can be a barcode and / or a 2D code (e.g. a QR code or a Data Matrix code).

[0188] The optically readable code typically includes a unique identifier by which the device can be uniquely addressed in a network to which the device may be connected.

[0189] In one embodiment of the present disclosure, the optically readable code comprises a link (e.g., in the form of a Uniform Resource Locator (URL)) to a website. A user can capture the optically readable code with a camera of a mobile computing system (e.g., a smartphone or a tablet computer). The optically readable code can direct the user via the link to the website, where the user can register and / or configure the device and / or initiate the configuration of the device.

[0190] In one embodiment, the user is prompted on the internet page to enter and / or specify application information.

[0191] Based on the application information, a separate computer system, which has access to the application information entered and / or specified by the user, can configure and / or initiate the configuration of the device. The separate computer system can be configured to contact the device via a network connection (e.g., a cellular network) and transmit the application information to the device. The separate computer system can be configured to configure the device via the network connection based on the application information. The separate computer system can be configured to transmit configuration information to the device via the network connection, based on which the device can configure itself.

[0192] As previously described, the configuration of the device can include one or more of the following steps:

[0193] Selecting one or more models for detecting, locating, identifying and / or counting arthropods in images of the collection area,

[0194] - Determine when and / or how frequently the device's camera takes pictures of the collection area,

[0195] - Setting the resolution of the images,

[0196] - Determine whether and / or how the collection area is illuminated,

[0197] - Determine which spectral range is used to illuminate the collecting area,

[0198] - Determine whether a lighting unit is switched on when images are taken, which lighting unit is switched on, when one or more lighting units are switched on, and at what times and / or at what intervals one or more lighting units are switched on,

[0199] - Establishing a maintenance and / or cleaning interval,

[0200] - Setting a focus / focusing mode,

[0201] - Setting camera parameters such as magnification, resolution, exposure time, aperture, ISO value, white balance, exposure compensation, image format, scene mode and / or image stabilizer.

[0202] Once the device is configured, it can be put into operation. It can be configured to operate at defined times and / or intervals and / or upon the occurrence of defined events.

[0203] (i) To produce images of the collection area according to the configuration and / or

[0204] (ii) to analyze image recordings according to the configuration and / or

[0205] (iii) To detect, locate, identify and / or count arthropods in the images according to the configuration and / or

[0206] (iv) To transmit images and / or analysis results and / or notices relating to the maintenance and / or cleaning of the device to a separate computer system in accordance with the configuration.

[0207] Further embodiments are disclosed below. These embodiments are not necessarily subject matter that falls under patent protection. As is known to those skilled in the art in patent law, the scope of protection of a patent is defined by the patent claims. The description and the drawings are to be used to interpret the patent claims. The embodiments described below are part of the description and not of the patent claims. The following embodiments are intended to give the reader guidance on how various features described in this disclosure can be combined. They are thus part of the present technical teaching and should not be confused with the subject matter of the patent claims. Embodiment 1: Computer-implemented method for configuring a device for monitoring arthropods in an area where crops are cultivated, comprising:

[0208] - Receiving and / or obtaining application information relating to the device for monitoring arthropods, wherein the device comprises an arthropod trap or means for connecting the device to an arthropod trap, wherein the application information specifies the crops, the area, the arthropods and / or the trap,

[0209] - Configure the device based on the application information.

[0210] Embodiment 2: Method according to embodiment 1, wherein the

[0211] Application information and arthropod information are or include.

[0212] Embodiment 3: Method according to embodiment 2, wherein the

[0213] Arthropod information: Specify arthropods that occur in the area.

[0214] Embodiment 4: Method according to one of embodiments 2 or 3, wherein the arthropod information specifies those arthropods that are monitored by the device.

[0215] Embodiment 5: Method according to one of embodiments 2 to 4, wherein the arthropod information specifies which subclass, superorder, order, suborder, family, genus and / or species the arthropods to be monitored belong to.

[0216] Embodiment 6: Method according to one of embodiments 2 to 5, wherein the arthropod information specifies arthropods that are pests of the crops.

[0217] Embodiment 7: Method according to one of embodiments 2 to 6, wherein the arthropod information specifies the stage of development of the arthropods to be monitored.

[0218] Embodiment 8: Method according to one of embodiments 2 to 7, wherein the configuration of the device is based on the arthropod information, and wherein the configuration of the device comprises:

[0219] - Selecting a model for detecting, locating, identifying and / or counting arthropods in images of the collection area and / or

[0220] Configuring a model to detect, locate, identify and / or count arthropods in images of the collection area and / or

[0221] - Determine how the image captures will be pre-processed before being applied to a model for detecting, locating, identifying and / or counting arthropods.

[0222] Embodiment 9: Method according to any of embodiments 1 to 8, wherein the application information is or includes crop information, the crop information specifying the crops to be incorporated into the area.

[0223] Embodiment 10: A method according to any one of embodiments 1 to 9, wherein the application information is or includes trap information, the trap information specifying the trap. Embodiment 11: A method according to embodiment 10, wherein the trap information specifies whether the trap comprises an adhesive trap or a liquid-filled trap tray.

[0224] Embodiment 12: Method according to embodiment 10 or 11, wherein the trap information specifies whether the trap is equipped with an attractant and / or with which attractant the trap is equipped.

[0225] Embodiment 13: Method according to one of embodiments 10 to 12, wherein the trapping device information specifies whether the trapping device comprises an adhesive trap or a trapping tray filled with a liquid.

[0226] Embodiment 14: Method according to one of embodiments 10 to 13, wherein the trap information specifies the color in which a collection area for arthropods of the trap is designed.

[0227] Embodiment 15: Method according to one of embodiments 10 to 14, wherein the capture device information specifies how far the capture area is from a lens of a camera and / or an image sensor of the camera.

[0228] Embodiment 16: Method according to one of embodiments 10 to 15, wherein the capture device information specifies the size of the collection area.

[0229] Embodiment 17: Method according to one of embodiments 10 to 16, wherein the trapping device information specifies the shape of the collection area.

[0230] Embodiment 18: Method according to one of embodiments 10 to 17, wherein the catching device information specifies with which liquid the catching device designed as a catching tray is filled.

[0231] Embodiment 19: Method according to one of embodiments 11 to 18, wherein the catching device information specifies whether and / or which additive the liquid in the catching tray comprises.

[0232] Embodiment 20: Method according to any of embodiments 1 to 19, wherein the application information is or includes area information, the area information specifying the area.

[0233] Embodiment 21: Method according to embodiment 20, wherein the area information specifies whether the crops are grown outdoors, in a polytunnel or in a greenhouse.

[0234] Embodiment 22: Method according to one of embodiments 1 to 21, wherein configuring the device comprises:

[0235] Selecting a model for detecting, locating, identifying and / or counting arthropods based on application information.

[0236] Embodiment 23: Method according to one of embodiments 1 to 22, wherein the trapping device comprises a collecting area for arthropods, wherein the device comprises a camera for generating images of the collecting area.

[0237] Embodiment 24: Method according to embodiment 23, wherein configuring the device comprises: - Determining at what times and / or at what time intervals the camera of the device generates images of the collection area.

[0238] Embodiment 25: Method according to one of embodiments 23 or 24, wherein configuring the device comprises:

[0239] - Setting a resolution for the image captures of the collection area.

[0240] Embodiment 26: Method according to one of embodiments 1 to 25, wherein the device and / or the trapping device includes a lighting unit for illuminating the collection area.

[0241] Embodiment 27: Method according to embodiment 26, wherein configuring the device includes:

[0242] - Defining a spectral range and / or intensity of electromagnetic radiation emitted by the lighting unit to illuminate the collecting area.

[0243] Embodiment 28: Method according to one of embodiments 1 to 27, wherein the trapping device comprises a collecting area for arthropods, wherein the device comprises a camera for generating images of the collecting area, wherein the device comprises one or more lighting units for illuminating the collecting area, wherein configuring the device comprises:

[0244] - Specify whether a lighting unit is switched on when images are taken and / or which lighting unit is switched on and / or when one or more lighting units are switched on and / or at what times and / or at what intervals one or more lighting units are switched on.

[0245] Embodiment 29: Method according to one of embodiments 1 to 28, wherein configuring the device comprises:

[0246] - Establishing a maintenance and / or cleaning interval for one or more components of the device.

[0247] Embodiment 30: Method according to one of embodiments 1 to 29, wherein the trapping device comprises a collecting area for arthropods, wherein the device comprises a camera for generating images of the collecting area, and wherein configuring the device comprises:

[0248] - Setting a magnification and / or a resolution and / or a focus and / or a focus mode and / or an exposure time and / or an aperture and / or an ISO value and / or a white balance and / or an exposure compensation and / or an image format and / or a scene mode and / or an image stabilizer.

[0249] Embodiment 31: Method according to one of embodiments 1 to 30, wherein the application information is provided by a user.

[0250] Embodiment 32: A method according to any one of embodiments 1 to 31, wherein the application information is determined automatically. Embodiment 33: A method according to any one of embodiments 1 to 32, wherein the receiving and / or determination of application information takes place in a configuration mode.

[0251] Embodiment 34: Method according to one of embodiments 1 to 33, wherein the configuration of the device is carried out in a configuration mode.

[0252] Embodiment 35: Method according to one of embodiments 33 or 34, wherein the configuration mode is a mode in which the device is during initial startup and / or into which the device switches in response to user input and / or into which the device switches upon the occurrence of an event.

[0253] Embodiment 36: Method according to one of embodiments 33 to 35, wherein the device switches to an operating mode after completion of the configuration.

[0254] Embodiment 37: Method according to one of embodiments 1 to 36, further comprising:

[0255] - Monitoring the arthropods according to the configuration.

[0256] Embodiment 38: Method according to one of embodiments 1 to 37, further comprising:

[0257] - Generating images of the collection area according to the configuration and / or analyzing the generated images according to the configuration and / or detecting, locating, identifying and / or counting arthropods in the images according to the configuration and / or

[0258] - Transmitting image recordings and / or analysis results and / or maintenance and / or cleaning notifications for the device to a separate computer system according to the configuration.

[0259] Embodiment 39: Method according to one of embodiments 1 to 38, wherein configuring the device comprises one or more of the following steps:

[0260] Selecting one or more models for detecting, locating, identifying and / or counting arthropods in images of the collection area,

[0261] - Determine when and / or how frequently the device's camera takes pictures of the collection area,

[0262] - Setting the resolution and / or magnification of the images,

[0263] - Defining preprocessing steps for preprocessing the image recordings,

[0264] - Determine whether and / or how the collection area is illuminated,

[0265] - Determine which spectral range is used to illuminate the collecting area,

[0266] - Determine whether a lighting unit is switched on when images are taken, which lighting unit is switched on, when one or more lighting units are switched on, and at what times and / or at what intervals one or more lighting units are switched on,

[0267] - Setting a maintenance and / or cleaning interval, - Setting a focus / focusing mode,

[0268] - Setting camera parameters such as magnification, resolution, exposure time, aperture, ISO value, white balance, exposure compensation, image format, scene mode and / or image stabilizer.

[0269] Embodiment 40: Computer system comprising means for carrying out the method according to one of embodiments 1 to 39.

[0270] Embodiment 41: Computer system, wherein the computer system is configured to execute the method according to one of embodiments 1 to 39.

[0271] Embodiment 42: Computer system comprising a processing unit and a memory, wherein a computer program is loaded into the memory that causes the processing unit to execute the method according to one of embodiments 1 to 39.

[0272] Embodiment 43: Computer system comprising a receiving unit

[0273] - and a control unit,

[0274] - wherein the control unit is configured to receive and / or determine application information relating to a device for monitoring arthropods in an area where crops are grown, by means of the receiving unit, wherein the device comprises an arthropod trap or means for connecting the device to an arthropod trap, wherein the application information specifies the crops, the area, the arthropods and / or the trap,

[0275] - wherein the control unit is configured to configure the device based on the application information and / or to initiate a configuration of the device.

[0276] Embodiment 44: Computer system according to one of the embodiments, characterized by one or more features of embodiments 1 to 43.

[0277] Embodiment 45: Device comprising the computer system according to one of embodiments 40 to 44.

[0278] Embodiment 46: Device for monitoring arthropods comprising a camera and a control unit,

[0279] - wherein the control unit is configured to receive and / or determine application information and to configure the device based on the application information and / or to initiate a configuration of the device based on the application information.

[0280] Embodiment 47: Device according to one of embodiments 45 or 46, wherein the control unit is configured to put the device into a configuration mode upon initial commissioning of the device and / or in response to user input and / or upon the occurrence of an event.

[0281] Embodiment 48: Device according to embodiments 45 to 47, wherein the control unit is configured to receive and / or determine application information in configuration mode.

[0282] Embodiment 49: Device according to one of embodiments 45 to 48, wherein the control unit is configured to receive application information via input means from a user in configuration mode.

[0283] Embodiment 50: Device according to one of embodiments 45 to 49, wherein the control unit is configured to cause the camera to produce an image in configuration mode, the image showing the collection area.

[0284] Embodiment 51: Device according to one of embodiments 45 to 50, wherein the control unit is configured to determine the color and / or shape and / or size of the collection area from the image of the collection area in configuration mode.

[0285] Embodiment 52: Device according to one of embodiments 45 to 51, wherein the control unit is configured to configure the device in configuration mode based on the color and / or shape and / or size of the collection area.

[0286] Embodiment 53: Device according to one of embodiments 45 to 52, wherein the control unit is configured to identify an attractant in the collection area in configuration mode based on image acquisition.

[0287] Embodiment 54: Device according to embodiment 53, wherein the control unit is configured to configure the device in configuration mode based on the identified attractant.

[0288] Embodiment 55: Device according to one of embodiments 45 to 54, further comprising a catching device for arthropods or means for connecting the device to a catching device for arthropods.

[0289] Embodiment 56: Device according to embodiment 55, wherein the control unit is configured in configuration mode to cause the camera to produce an image capture, wherein the image capture shows an optical marker, the optical marker indicating what type of capture device it is.

[0290] Embodiment 57: Device according to embodiment 56, wherein the control unit is configured to configure the device on the basis of the optical marker in configuration mode.

[0291] Embodiment 58: Device according to one of embodiments 45 to 57, wherein the control unit is configured to determine the position of the device in configuration mode.

[0292] Embodiment 59: Device according to embodiment 58, wherein the control unit is configured to configure the device in configuration mode based on the determined position.

[0293] Embodiment 60: Device according to one of embodiments 45 to 59, wherein the control unit is configured to determine the current date in configuration mode. Embodiment 61: Device according to embodiment 60, wherein the control unit is configured to configure the device based on the current date in configuration mode.

[0294] Embodiment 62: Device according to one of embodiments 45 to 61, wherein the control unit is configured to configure the device in configuration mode based on the application information.

[0295] Embodiment 63: Device according to one of embodiments 45 to 62, wherein the device further comprises a transmitting unit.

[0296] Embodiment 64: Device according to embodiment 63, wherein the control unit is configured to cause the transmitting unit, in configuration mode, to transmit application information to a separate computer system.

[0297] Embodiment 65: Device according to one of embodiments 45 to 66, wherein the device further comprises a receiving unit.

[0298] Embodiment 66: Device according to embodiment 65, wherein the control unit is configured to cause the receiving unit to receive configuration information from the separate computer system in configuration mode.

[0299] Embodiment 67: Device according to embodiment 66, wherein the control unit is configured to configure the device according to the configuration information.

[0300] Embodiment 68: Device according to one of embodiments 45 to 67, wherein the control unit is configured to move the device from configuration mode to operating mode after configuration of the device.

[0301] Embodiment 69: Device according to embodiment 68, wherein the control unit is configured to monitor arthropods in an area where crops are grown, in operating mode according to the configuration.

[0302] Embodiment 70: Device according to one of embodiments 45 to 69, wherein the control unit is configured to cause the camera, in operating mode, to produce one or more image recordings of the collection area at defined times and / or at defined time intervals and / or upon the occurrence of defined events.

[0303] Embodiment 71: Device according to one of embodiments 45 to 70, wherein the control unit is configured to analyze image recordings in operating mode.

[0304] Embodiment 72: Device according to embodiment 71, wherein the analysis includes detecting and / or locating and / or identifying and / or counting arthropods in the image recordings.

[0305] Embodiment 73: Device according to one of embodiments 45 to 72, wherein the control unit is configured to transmit image recordings generated in operating mode to a separate computer system.

[0306] Embodiment 74: Device according to one of embodiments 45 to 73, wherein the control unit is configured to transmit information on detected, localized, identified arthropods and / or the number of arthropods in image recordings to a separate computer system in operating mode.

[0307] Embodiment 75: Device according to one of embodiments 45 to 74, further comprising means for connecting the device to a trapping device for arthropods. Embodiment 76: Device according to embodiment 75, wherein the means for connecting establish an electrical contact between the device and the trapping device.

[0308] Embodiment 77: Device according to embodiment 76, wherein the control unit is configured to detect, on the basis of the electrical contact, which trapping device the device is connected to.

[0309] Embodiment 78: Device according to embodiment 77, wherein the control unit is configured to configure the device based on the information about which catch device the device is connected to.

[0310] Embodiment 79: Device according to one of embodiments 76 to 77, wherein the control unit is configured to identify, in configuration mode via the electrical contact, the catch device to which the device is connected, and to configure the device on the basis of the identified catch device.

[0311] Embodiment 80: Device according to embodiment 79, wherein the identification of the trapping device is carried out by means of a resistance coding.

[0312] Embodiment 81: Device according to embodiment 79, wherein the identification of the trapping device is based on a capacity.

[0313] Embodiment 82: Device according to embodiment 79, wherein the identification of the trapping device is based on pins, an arrangement of pins, a number of pins and / or a length of pins, wherein the pins establish the electrical contact between the device and the trapping device.

[0314] Embodiment 83: Device according to embodiment 79, wherein the identification of the trapping device is based on information stored in an RFID transponder of the trapping device.

[0315] Embodiment 84: Device according to one of embodiments 45 to 83, wherein the application information specifies the application case.

[0316] Embodiment 85: Device according to one of embodiments 45 to 84, wherein the application information specifies the crops that are grown in the area in which the device is used or is intended to be used.

[0317] Embodiment 86: Device according to one of embodiments 45 to 85, wherein the application information specifies the area in which the device is used or is intended to be used.

[0318] Embodiment 87: Device according to one of embodiments 45 to 86, wherein the application information specifies the arthropods to be monitored by means of the device.

[0319] Embodiment 88: Device according to one of embodiments 45 to 87, wherein the application information specifies the catching device used to monitor the arthropods.

[0320] Embodiment 89: Device according to one of embodiments 45 to 88, wherein the application information includes one or more of the following:

[0321] Arthropod information, wherein arthropod information specifies the arthropods to be monitored; crop information, wherein crop information specifies which crop is grown in the area;

[0322] - Capture device information, wherein the capture device information specifies the capture device for immobilizing the arthropods,

[0323] Area information, where the area information specifies the area in which the arthropods are monitored.

[0324] Embodiment 90: Device according to one of embodiments 45 to 89, wherein configuring the device comprises one or more of the following steps:

[0325] Selecting one or more models for detecting, locating, identifying and / or counting arthropods in images of the collection area,

[0326] - Determine when and / or how frequently the device's camera takes pictures of the collection area,

[0327] - Setting the resolution and / or magnification of the images,

[0328] - Defining preprocessing steps for preprocessing the image recordings,

[0329] - Determine whether and / or how the collection area is illuminated,

[0330] - Determine which spectral range is used to illuminate the collecting area,

[0331] - Determine whether a lighting unit is switched on when images are taken, which lighting unit is switched on, when one or more lighting units are switched on, and at what times and / or at what intervals one or more lighting units are switched on,

[0332] - Establishing a maintenance and / or cleaning interval,

[0333] - Setting a focus / focusing mode,

[0334] - Setting camera parameters such as magnification, resolution, exposure time, aperture, ISO value, white balance, exposure compensation, image format, scene mode and / or image stabilizer.

[0335] Embodiment 91: Device according to one of embodiments 45 to 90, wherein the control unit is configured to operate the device in operating mode according to the configuration.

[0336] Embodiment 92: Device according to embodiment 91, wherein operating the device comprises operating it at defined times and / or at defined time intervals and / or upon the occurrence of defined events.

[0337] (v) To produce images of the collection area according to the configuration and / or

[0338] (vi) to analyze image recordings according to the configuration and / or

[0339] (vii) To detect, locate, identify and / or count arthropods in the image data according to the configuration and / or

[0340] (viii) To transmit images and / or analysis results and / or maintenance and / or cleaning instructions for the device to a separate computer system according to the configuration. Embodiment 93: Device according to any one of embodiments 45 to 92, comprising one or more features of embodiments 1 to 44.

[0341] Embodiment 94: Non-volatile, computer-readable storage medium on which a computer program is stored which, when executed by a computer system, causes the computer system to perform the following steps:

[0342] Receiving application information concerning a device for monitoring arthropods in an area where crops are grown, wherein the device comprises an arthropod trapping device, wherein the application information specifies the crops, the area, the arthropods and / or the trapping device.

[0343] - Configuring the device based on the application information and / or initiating a configuration of the device based on the application information.

[0344] Embodiment 95: Storage medium according to embodiment, wherein the computer system is the computer system of embodiments 40 to 44.

[0345] Embodiment 96: Storage medium according to one of embodiments 94 or 95, wherein the computer system is part of the device according to one of embodiments 45 to 93.

[0346] Embodiment 97: Storage medium according to one of embodiments 94 to 96, wherein the computer program causes the computer system to execute the method according to one of claims 1 to 44.

[0347] Embodiment 98: Storage medium according to one of embodiments 94 to 97, comprising one or more features of embodiments 1 to 93.

[0348] Fig. 1 shows an exemplary and schematic embodiment of the computer-implemented method of the present disclosure. The method (100) comprises the steps:

[0349] (110) Receiving and / or obtaining application information relating to a device for monitoring arthropods, wherein the device comprises an arthropod trap or means for connecting the device to an arthropod trap, wherein the application information specifies the crops, the area, the arthropods and / or the trap,

[0350] (120) Configure the device based on the application information.

[0351] Another subject of the present disclosure is a computer system.

[0352] A "computer system" is an electronic data processing system that processes data using programmable instructions. Such a system typically comprises a "computer," the unit containing a processor for performing logical operations, as well as peripherals.

[0353] In computer technology, "peripherals" refers to all devices connected to a computer that serve to control the computer and / or as input and output devices. Examples include monitors (screens), mice, keyboards, data storage devices, cameras, microphones, speakers, status indicators, etc. Internal ports and expansion cards are also considered peripherals in computer technology. Modern computer systems are often categorized into desktop PCs, portable PCs, laptops, notebooks, netbooks, and tablet PCs, as well as handheld devices (e.g., smartphones); all of these systems can be used to implement the invention.

[0354] The term "computer" should be interpreted broadly and include any type of electronic device with data processing capabilities, including, as a non-restrictive example, personal computers, servers, embedded cores, communication devices, processors (e.g., digital signal processor (DSP), microcontroller, field-programmable gate array (FPGA), application-specific integrated circuit (ASIC), etc.) and other electronic computing devices.

[0355] The term "processing," as used above, is intended to encompass any type of calculation, manipulation, or transformation of data that is represented as physical, e.g., electronic, phenomena and that can occur or be stored, e.g., in registers and / or memory of at least one computer or processor. The term "processor" encompasses a single processing unit or a multitude of such distributed or remote units.

[0356] The computer system of the present disclosure can be a component of the device of the present disclosure. The computer system can be a separate computer system independent of the device, which can be connected to the device, for example, via a network.

[0357] The computer system includes a receiver unit.

[0358] - and a control unit,

[0359] - wherein the receiving unit is configured to receive application information relating to a device for monitoring arthropods in an area where crops are grown, wherein the device comprises an arthropod trapping device, wherein the application information specifies the crops, the area, the arthropods and / or the trapping device,

[0360] - wherein the control unit is configured to configure the device based on the application information and / or to initiate a configuration of the device.

[0361] Fig. 2 shows an exemplary and schematic embodiment of the computer system of the present disclosure.

[0362] The computer system (1) comprises a processing unit (20) and a memory (50). The processing unit (20) and the memory (50) can together form a control unit according to the present device.

[0363] The processing unit (20) may comprise one or more processors alone or in combination with one or more memories. The processing unit (20) may be ordinary computer hardware capable of processing information such as digital images, computer programs, and / or other digital information. The processing unit (20) typically consists of an arrangement of electronic circuits, some of which may be implemented as an integrated circuit or as several interconnected integrated circuits (an integrated circuit is sometimes referred to as a "chip"). The processing unit (20) may be configured to execute computer programs, which may be stored in memory (50).

[0364] The memory (50) can be ordinary computer hardware capable of storing information such as digital images, data, computer programs, and / or other digital information, either temporarily and / or permanently. The memory (50) can include volatile and / or non-volatile memory and can be permanently installed or removable. Examples of suitable memory include RAM (Random Access Memory), ROM (Read-Only Memory), a hard disk, flash memory, or a combination of the above.

[0365] In addition to the memory (50), the processing unit (20) can also be connected to one or more interfaces (11, 12, 30, 41, 42) to display, transmit, and / or receive information. The interfaces can include one or more communication interfaces (41, 42) and / or one or more user interfaces (11, 12, 30). The one or more communication interfaces (41, 42) can be configured to send and / or receive information, e.g., to and / or from a camera, other computer systems, networks, data storage devices, or the like. The one or more communication interfaces (41, 42) can be configured to transmit and / or receive information via physical (wired) and / or wireless communication links. The one or more communication interfaces (41, 42) can include one or more interfaces for connecting to a network, e.g.,using technologies such as mobile phone, Wi-Fi, satellite, cable, DSL, fiber optic and / or the like. In some examples, the one or more communication interfaces (41, 42) can be one or more.

[0366] Near-field communication interfaces include devices configured to connect to near-field communication technologies such as NFC, RFID, Bluetooth, Bluetooth LE, ZigBee, infrared (e.g., IrDA), or similar technologies.

[0367] The user interfaces (11, 12, 30) may include a display (30). A display (30) may be configured to show information to a user. Suitable examples include a liquid crystal display (LCD), a light-emitting diode (LED) display, a plasma display (PDP), or the like. The user input interface(s) (11, 12) may be wired or wireless and may be configured to receive information from a user into the computer system (1), for example, for processing, storage, and / or display. Suitable examples of user input interfaces (11, 12) include a microphone, an image or video recording device (e.g., a camera), a keyboard or keypad, a joystick, a touch-sensitive surface (separate from or integrated into a touchscreen), or the like.In some examples, the user interfaces may include automatic identification and data capture (AIDC) technology for machine-readable information. This could include barcodes, radio frequency identification (RFID), magnetic stripes, optical character recognition (OCR), integrated circuit cards (ICC), and similar technologies. The user interfaces may also include one or more interfaces for communication with peripheral devices such as printers and / or cameras, and the like.

[0368] One or more computer programs (60) can be stored in memory (50) and executed by the processing unit (20), which is programmed to perform the functions described in this description. The retrieval, loading, and execution of instructions from the computer program (60) can be performed sequentially, with one instruction being retrieved, loaded, and executed at a time. However, the retrieval, loading, and / or execution can also be performed in parallel.

[0369] The present invention also relates to a computer program. Such a computer program can be stored on a non-volatile data carrier such as a CD, a DVD, a USB stick, or another medium for storing data.

[0370] The computer program can be offered for download in an app store and / or on a website of the Internet.

[0371] The computer program causes a computer system, in whose memory it is loaded, to perform the following steps:

[0372] Receiving application information concerning a device for monitoring arthropods in an area where crops are grown, wherein the device comprises an arthropod trapping device, wherein the application information specifies the crops, the area, the arthropods and / or the trapping device.

[0373] - Configuring the device based on the application information and / or initiating a configuration of the device based on the application information.

[0374] Fig. 3 shows an example and schematic of a device for monitoring arthropods and how it is produced from various components.

[0375] Fig. 3(a) shows an example of attaching an enclosure (20) to a holding device (30). Spacers (40) are attached to / present on the holding device (30); the spacers (40) can be part of the holding device (30) or a separate component. The spacers (40) ensure a defined distance between an image sensor of a camera and a collection area for arthropods.

[0376] Fig. 3(b) shows an example of how a structure comprising a housing (20), a holding device (30), and spacers (40) is mounted on a base body (10). The base body (10) includes a receiving surface (11) on which an adhesive-coated sheet can be placed. This adhesive-coated sheet acts as a collection area for arthropods. Arthropods that come into contact with the adhesive-coated sheet are immobilized by the adhesive. The base body (10), the housing (20), the holding device (30), and the spacers (40), together with the adhesive-coated sheet, form a trapping device for arthropods.

[0377] Figures 3(c) and 3(d) show by way of example how the assembly from Figure 3(b) is connected to the base body (10). For this purpose, the tabs (24-1, 24-2) shown in Figure 3(a) are inserted into corresponding slots in the base body (10). Figures 3(c) and 3(d) further show that an IoT device (50) is inserted into the holding device (30). The holding device (30) thus provides means for reversibly connecting the IoT device (50) to the catch device.

[0378] The IoT device (50) typically comprises a camera for generating images of the collection area and a control unit. The control unit is configured, in configuration mode, to receive and / or determine application information and, based on this information, to configure the IoT device and / or initiate a configuration of the device. In operating mode, the control unit is configured to cause the camera to generate images of the collection area according to the configuration and / or to analyze generated images according to the configuration and / or to detect, locate, identify, and / or count arthropods in the generated images according to the configuration and / or to transmit image data and / or analysis results and / or messages for maintenance and / or cleaning of the device according to the configuration to a separate computer system.

Claims

Patent claims 1. Computer-implemented method for configuring a device for monitoring arthropods in an area where crops are grown, comprising: - Receiving and / or obtaining application information relating to the device for monitoring arthropods, wherein the device comprises an arthropod trap or means for connecting the device to an arthropod trap, wherein the application information specifies the crops, the area, the arthropods and / or the trap, - Configure the device based on the application information.

2. Method according to claim 1, wherein the application information Arthropod information is or includes, wherein the arthropod information specifies arthropods that are monitored by the device, and / or - Crop information is or includes, where the crop information specifies the crops, and / or - Capture device information is or includes, wherein the capture device information specifies the capture device, and / or Scope information is or includes, where the scope information specifies the scope.

3. Method according to claim 2, wherein the arthropod information specifies, - to which subclass, superorder, order, suborder, family, genus and / or species the arthropods to be monitored belong and / or whether the arthropods to be monitored are pests of the crops and / or what kind of pests they are, and / or - at what stage of development the arthropods to be monitored are.

4. Method according to one of claims 2 or 3, wherein the crop information specifies, - to which subclass, superorder, order, suborder, family, genus and / or species the cultivated crop in the area belongs and / or - at what stage of development the crops are.

5. Method according to any one of claims 2 to 4, wherein the catch device information specifies, whether the trapping device includes a glue trap or a liquid-filled trapping tray and / or whether the trapping device is equipped with an attractant and / or what attractant the trapping device is equipped with and / or - the color of the arthropod collection area of ​​the trapping device and / or the distance of the collection area from a camera lens and / or image sensor, and / or - how large the collection area is and / or - what form the collection area has, and / or - with which liquid the collection device designed as a collection tray is filled and / or whether the liquid in the collection tray contains an additive and / or which additive the liquid in the collection tray contains.

6. Method according to any one of claims 2 to 5, wherein the area information specifies whether the crops are grown outdoors, in a polytunnel or in a greenhouse.

7. Method according to any one of claims 1 to 6, wherein the application information includes: the position of the device in the form of geocoordinates and / or the current date.

8. A method according to any one of claims 1 to 7, wherein the trapping device comprises a collection area for arthropods and / or the device comprises a camera for generating images of the collection area, wherein configuring the device comprises one or more of the following steps: Selecting one or more models for detecting, locating, identifying and / or counting arthropods in images of the collection area, - Determine when and / or how frequently the device's camera takes pictures of the collection area, - Setting the resolution and / or magnification of the images, - Defining preprocessing steps for preprocessing the image recordings, - Determine whether and / or how the collection area is illuminated, - Determine which spectral range is used to illuminate the collecting area, - Determine whether a lighting unit is switched on when images are taken, which lighting unit is switched on, when one or more lighting units are switched on, and at what times. and / or at what intervals one or more lighting units are switched on, - Establishing a maintenance and / or cleaning interval, - Setting a focus / focusing mode, - Setting camera parameters such as magnification, resolution, exposure time, aperture, ISO value, white balance, exposure compensation, image format, scene mode and / or image stabilizer.

9. Method according to any one of claims 1 to 8, wherein the device comprises a transmitting unit, further comprising: - Generating images of the collection area according to the configuration and / or analyzing the generated images according to the configuration and / or detecting, locating, identifying and / or counting arthropods in the images according to the configuration and / or - Transmitting image recordings and / or analysis results and / or maintenance and / or cleaning notifications for the device to a separate computer system according to the configuration.

10. A method according to any one of claims 1 to 9, wherein the receiving and / or determination of application information and the configuration of the device take place in a configuration mode, wherein the configuration mode is a mode in which the device is during initial commissioning and / or into which the device switches in response to user input and / or into which the device switches upon the occurrence of an event, wherein the device switches to an operating mode after completion of the configuration, wherein the operating mode is characterized in that the device is operated according to the configuration.

11. Device for monitoring arthropods in an area where crops are grown, comprising: a camera, an arthropod trap or means for connecting the device to an arthropod trap and a control unit, - wherein the control unit is configured to receive and / or determine application information and to configure the device based on the application information and / or to initiate a configuration of the device based on the application information.

12. Device according to claim 11, wherein the control unit is configured, upon initial commissioning of the device and / or in response to user input and / or upon the occurrence of an event, to put the device into a configuration mode, to receive and / or determine application information in configuration mode, to configure the device in accordance with the application information in configuration mode, to put the device into an operating mode after configuration of the device, and to operate the device in operating mode in accordance with the configuration.

13. Device according to one of claims 11 or 12, wherein the control unit is configured in configuration mode to receive application information via input means from a user and to configure the device based on the received application information, and / or to cause the camera to produce an image, wherein the image shows a collecting area for arthropods, to determine the color and / or shape and / or size of the collecting area from the image of the collecting area, and to configure the device based on the color and / or shape and / or size of the collecting area, and / or to cause the camera to produce an image, wherein the image shows a collecting area for arthropods, to identify an attractant in the collecting area based on the image, and to configure the device based on the identified attractant, and / or to cause the camera to produce an image, wherein the image shows an optical marker, wherein the optical marker indicates,to determine what type of trap is being used, and to configure the device based on the information about what type of trap is being used, and / or to determine the position of the device and to configure the device based on the determined position, and / or to determine the current date and to configure the device based on the current date.

14. Device according to any one of claims 11 to 13, wherein the application information comprises one or more of the following: Arthropod information, wherein arthropod information specifies the arthropods to be monitored, Crop information, where the crop information specifies which crop is grown in the area, - Capture device information, wherein the capture device information specifies the capture device for immobilizing the arthropods, Area information, wherein the area information specifies the area in which the arthropods are monitored, wherein configuring the device comprises one or more of the following steps: Selecting one or more models for detecting, locating, identifying and / or counting arthropods in images of the collection area, - Determine when and / or how frequently the device's camera takes pictures of the collection area, - Setting the resolution and / or magnification of the images, - Defining preprocessing steps for preprocessing the image recordings, - Determine whether and / or how the collection area is illuminated, - Determine which spectral range is used to illuminate the collecting area, - Determine whether a lighting unit is switched on when images are taken, which lighting unit is switched on, when one or more lighting units are switched on, and at what times and / or at what intervals one or more lighting units are switched on, - Establishing a maintenance and / or cleaning interval, - Setting a focus / focusing mode, - Setting camera parameters such as magnification, resolution, exposure time, aperture, ISO value, white balance, exposure compensation, image format, scene mode and / or image stabilizer.

15. Non-volatile, computer-readable storage medium on which a computer program is stored which, when executed by a computer system, causes the computer system to execute the method according to any one of claims 1 to 12.

Images