Data reduction in the monitoring of arthropods

Abstract

The present invention relates to the generation and storage and / or transmission of images of a collection area in which one or more arthropods may be located, for the purpose of detecting, identifying and / or quantifying arthropods. The present invention also relates to a computer-implemented method, to an apparatus and to a computer program.

Description

[0001] BCS243037 FC

[0002] Data reduction in arthropod monitoring

[0003] TECHNICAL AREA

[0004] This disclosure relates to the generation, storage, and / or transmission of image recordings of a collection area in which one or more arthropods may be located, for the purpose of detecting, identifying, and / or quantifying arthropods. The subject matter of this disclosure includes a computer-implemented method, a device, and a computer program.

[0005] INTRODUCTION

[0006] W02020 / 058175A1 discloses a method, a system, and a computer program for detecting arthropods. A camera captures an image of a collection area containing one or more arthropods. The image is transmitted via a network to a computer system. On the computer system, the image can be analyzed manually and / or automatically, for example, to detect, identify, and / or count arthropods in the image.

[0007] To automatically detect, identify, and / or count arthropods in an image, the image resolution must not be too low. Furthermore, the image must not be too heavily compressed, as compression typically results in information loss and potentially introduces artifacts. The higher the image resolution and / or the lower the compression level, the larger the file size will generally be. The larger the file size, the more data must be transmitted over the network to the separate computer system.

[0008] Not every image of the collection area produced by the camera includes arthropods; that is, it is possible that images are produced and transmitted in which no arthropods are depicted.

[0009] It is also conceivable that two images are taken at different times, at which no changes have occurred or at which any changes that have occurred are irrelevant.

[0010] SUMMARY

[0011] This revelation addresses these and other aspects.

[0012] A first subject of the present disclosure is a computer-implemented method comprising the steps:

[0013] Receiving an image recording in which a collection area for arthropods is depicted,

[0014] Determining one or more reduction parameters based on the collection area depicted in the image capture,

[0015] Generating a reduced dataset using one or more reduction parameters,

[0016] Storing the reduced data set and / or transmitting the reduced data set to a separate computer system. A further subject matter of the present disclosure is a device comprising a processing unit and a memory, wherein a computer program is stored in the memory that causes the device to execute the following:

[0017] Receiving an image recording in which a collection area for arthropods is depicted,

[0018] Determining one or more reduction parameters based on the collection area depicted in the image capture,

[0019] Generating a reduced dataset using one or more reduction parameters,

[0020] Saving the reduced data set and / or transmitting the reduced data set to a separate computer system.

[0021] 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 processing unit of a computer system, causes the computer system to execute the following:

[0022] Receiving an image recording in which a collection area for arthropods is depicted,

[0023] Determining one or more reduction parameters based on the collection area depicted in the image capture,

[0024] Generating a reduced dataset using one or more reduction parameters,

[0025] Saving the reduced data set and / or transmitting the reduced data set to a separate computer system.

[0026] BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Fig. 1 shows an embodiment of the computer-implemented method of the present disclosure in the form of a flowchart.

[0028] Fig. 2 shows, by way of example and schematic representation, an embodiment of the device of the present disclosure.

[0029] DETAILED REVELATION

[0030] The subject matter of the present disclosure is explained in more detail below, without distinguishing between the subject matter of the present disclosure (method, device, computer program). Rather, the following explanations are intended to apply analogously to all subject matter of the invention, regardless of the context in which they are described (method, device, computer program).

[0031] If steps are specified in a sequence in the present description or in the claims, 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. The subject matter of the present disclosure is explained in more detail at several points with reference to drawings.The drawings depict specific embodiments with specific features and combinations of features, primarily for illustrative purposes; the present 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.

[0032] The article "ein" means "one or more," unless preceded by "nur" or "leidglich." The same applies analogously to the article "eine."

[0033] The expressions “based on” and “based on” mean “at least partly based on” unless explicitly stated otherwise.

[0034] 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”.

[0035] The present disclosure provides means for reducing data when transmitting and / or storing digital image recordings of a collection area.

[0036] The foraging area is an area that can be visited by arthropods. This can be a flat surface, such as a board, map, or similar object. It can also be the bottom of a container. It can also be a liquid in a container. It can also be a part of a plant, such as a leaf, fruit, or other plant part.

[0037] In one embodiment of the present disclosure, the collecting area is part of a trapping device for arthropods.

[0038] 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 / 058I70AI, WO2021 / 213824A1 or WO2022 / 243150A1.

[0039] In one embodiment of the present disclosure, the catching device comprises a surface provided with an adhesive, as described, for example, in WO2023 / 043871A1, WO2018 / 131853A1 or W02004 / 095919A2.

[0040] 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 that of a prism (see, e.g., EP2420695I.6).

[0041] 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 could be used to mimic a food source. 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.

[0042] If a container filled with a liquid is used, it may contain water and optionally 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. It could also be an agent to prevent algae growth (for example, a herbicide). In the case of a map or board, it may be coated with an adhesive to immobilize arthropods.

[0043] “Arthropods” are a diverse group of invertebrate animals belonging to the phylum Arthropoda.

[0044] 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).

[0045] Arthropods are divided into several groups (subphyla and classes), including insects and arachnids.

[0046] In one embodiment of the present disclosure, the term "arthropods" refers exclusively to insects and arachnids.

[0047] In another embodiment of the present disclosure, the term "arthropods" refers exclusively to insects.

[0048] In another version of the present disclosure, the term "arthropods" refers exclusively to adult insects.

[0049] In another embodiment of the present disclosure, the term "arthropods" refers exclusively to insects in the form of caterpillars.

[0050] In another embodiment of the present disclosure, the term "arthropods" refers exclusively to arachnids.

[0051] In another embodiment of the present disclosure, the term "arthropods" refers exclusively to mites.

[0052] In the first step, an image is received, in which a collection area is depicted. In other words, an image is received that shows or represents a collection area.

[0053] The term "receive" can mean that an image is transmitted from a camera or a separate computer system. The term "receive" can mean that an image is retrieved from a camera or a separate computer system. The term "receive" can mean that an image is read from a data storage device. The term "receive" can mean that an image is entered into the system of this disclosure by a user.

[0054] An "image capture" is a typically visual representation of a scene and / or one or more objects, captured or generated by the interaction of light with light-sensitive substances or sensors. The term "image capture" encompasses a wide range of formats, including but not limited to digital photographs, videos, and thermal images.

[0055] Typically, the image capture is digital. The term "digital" means that the image can be processed by a machine, usually a computer system. "Processing" refers to the familiar methods of electronic data processing (EDP).

[0056] 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. In a digital image, image content is typically represented and stored using integers. In most cases, these are two-dimensional images that are binary encoded and may be compressed. Digital images are usually raster graphics, in which the image information is stored in a uniform grid.Raster graphics consist of a grid-like arrangement of so-called image points (pixels) in the case of two-dimensional representations, or volume elements (voxels) in the case of three-dimensional representations, each assigned a color or a grayscale value. The main characteristics of a 2D raster graphic are therefore the image size (width and height measured in pixels, also commonly referred to as image resolution) and the color depth. A pixel in a digital image file is typically assigned a color or a grayscale value. The color encoding used for a pixel is defined, among other things, by the color space and the color depth. The simplest case is a binary image, in which a pixel stores a black and white value.In an image whose color is defined by the so-called RGB color space (RGB stands for the primary colors red, green, and blue), each pixel consists of three color values: one for red, one for green, and one for blue. The color of a pixel is created by superimposing (additively mixing) these three color values. Each color value is discretized into, for example, 256 distinguishable levels called tonal values, which typically range from 0 to 255. The color nuance "0" of each color channel is the darkest. If all three channels have a tonal value of 0, the corresponding pixel appears black; if all three channels have a tonal value of 255, the corresponding pixel appears white. For the sake of simplicity, this description assumes that the images in question are RGB raster graphics with a specific number of pixels. However, this assumption should in no way be considered limiting.The image processing expert understands how to apply the principles of this description to image files that are in other image formats and / or where the color values ​​are encoded differently.

[0057] The at least one image can also be one or more excerpts from a video sequence.

[0058] The at least one image capture is usually created using one or more cameras.

[0059] A "camera" is a device or system designed to capture and record images of external objects and 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) 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, conventional 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.

[0060] In one embodiment of the present disclosure, the camera is a digital camera that electrically generates two-dimensional images from light using one or more image sensors. These are typically semiconductor-based image sensors such as CCD (charge-coupled device) or 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.

[0061] The at least one camera is directed at a collection area. In other words, the at least one camera is aligned and configured to produce images of the collection area or a part thereof. The use of multiple cameras that view an object, for example, from different directions and produce images from different perspectives has the advantage of capturing depth information. One or more cameras can be a component of the device described in this disclosure.

[0062] The received image shows a collection area. This collection area may contain one or more arthropods. It is also possible that the collection area does not contain any arthropods. It is also possible that the collection area contains one or more other objects.

[0063] It is possible that more than one image is received, e.g., two, three, four, five, six, seven, eight, nine, ten, or more than ten. It is possible that received images show the collection area at different times. It is possible that received images show the collection area from different perspectives. It is possible that received images show the collection area under different exposures. It is possible that received images were taken with different sensors. It is possible that received images were taken with varying focus (e.g., focus stacking).

[0064] A reduction parameter is determined based on the (at least one) received image. More precisely, the reduction parameter is determined based on the collection area depicted in the image, in which one or more arthropods may be located.

[0065] It is possible to determine several reduction parameters based on the collection area shown in the image.

[0066] The at least one reduction parameter can specify whether and / or how a reduced dataset is generated based on the received image capture. The term "reduced" refers to the size of the dataset, i.e., the amount of data it comprises. In other words, a "reduced dataset" is a "dataset reduced in size." The size of the reduced dataset is smaller than that of a reference dataset. In one embodiment of the present disclosure, the reference dataset is the at least one received image capture, or the reference dataset comprises the at least one received image capture. In other words, in one embodiment of the present disclosure, the amount of data in the reduced dataset is less than the at least one received image capture or a reference dataset that comprises the at least one received image capture.

[0067] In one embodiment of the present disclosure, the reduced data set is or comprises one or more reduced image captures. In this case, the term "reduction" refers to the process of decreasing the size of an image capture. The result of such a reduction is a "reduced image capture." The at least one reduced image capture has a reduced size (i.e., a smaller amount of data) compared to the at least one received image capture.

[0068] The "reduction parameter" can be a parameter that specifies a reduction in the size of an image. For example, the reduction parameter can specify whether the size of an image is reduced and / or how the size of an image is reduced.

[0069] There are various ways to reduce the size of an image. Some examples are described below, without limiting the present disclosure to these examples.

[0070] One way to reduce the size of an image is to reduce its resolution. Reducing the resolution of an image typically refers to the process of decreasing the number of image elements (e.g., pixels or voxels) used to represent the image's content. This usually results in a decrease in the level of detail and / or clarity of the depicted subject, making the image appear less sharp. One way to reduce resolution is through re-sampling. This involves combining multiple image elements (e.g., pixels or voxels) into a single image element, thereby reducing the number of image elements. Various re-sampling techniques exist, such as nearest neighbor, bilinear, and bicubic interpolation, which can affect image quality in different ways.The reduction parameter can specify whether the resolution of an image is reduced, how the resolution is reduced, and / or to what extent. The resolution of an image without any arthropods can be reduced more than the resolution of an image containing one or more arthropods. Similarly, the resolution of an image containing one or more arthropods that are irrelevant and / or uninteresting to a user can be reduced more than the resolution of an image containing one or more arthropods that are relevant and / or interesting to a user. For example, an arthropod might be relevant and / or interesting to a user if it is a pest.A relevant and / or interesting arthropod is also referred to in this disclosure as a "specific arthropod". The resolution of an image that has already been analyzed to detect, locate, identify, and / or count one or more arthropods in the depicted collection area may be reduced more than the resolution of an image that has not yet been analyzed to detect, locate, identify, and / or count one or more arthropods in the depicted collection area.

[0071] Another way to reduce the size of an image is to reduce the resolution in one or more sub-areas while maintaining the resolution in other sub-areas. It is also possible to reduce the resolution to varying degrees in different sub-areas. For example, the resolution in one or more sub-areas of the image containing one or more arthropods can be left unchanged, while the resolution in one or more sub-areas containing no arthropods can be reduced. Similarly, the resolution in one or more sub-areas containing one or more arthropods can be reduced less than the resolution in one or more sub-areas containing no arthropods.The resolution of a sub-area containing one or more arthropods that are relevant and / or interesting to a user can be reduced less than the resolution of a sub-area containing no such arthropods. For example, an arthropod might be relevant and / or interesting to a user if it is a pest. The reduction parameter can specify which sub-area(s) of the image will have its resolution reduced, how the resolution will be reduced, and / or to what extent.

[0072] Another way to reduce the size of an image is to reduce the color depth (or the number of grayscale levels in grayscale images). The color depth can be reduced, or reduced more significantly, if the image contains no arthropods or no relevant / interesting ones, and / or if the image has already been analyzed to detect, locate, identify, and / or count one or more arthropods in the imaged collection area. The reduction parameter can specify whether the color depth is reduced, how the color depth of the image is reduced, and / or to what extent.

[0073] Another way to reduce the size of an image is to reduce the color depth of one or more sub-areas. The color depth can be reduced, or further reduced, in a sub-area if that sub-area contains no arthropods or no relevant / interesting arthropods, and / or if the sub-area has already been analyzed to detect, locate, identify, and / or count one or more arthropods in the imaged collection area. The reduction parameter can specify in which sub-area(s) of the image the color depth is reduced, how the color depth is reduced, and / or to what extent. Another way to reduce the size of an image is to crop and / or mask one or more parts of the image. Masking allows color / grayscale values ​​of image elements to be replaced by a fixed value (e.g.,The value zero can be replaced. Areas that do not contain any arthropods or any arthropods of interest / interest can be cropped and / or masked. The reduction parameter can specify whether one or more parts of the image are to be cropped or masked, and / or which part(s) are to be cropped or masked. Conversely, one or more areas containing one or more arthropods, or one or more relevant / interesting arthropods, can be extracted. The process of extracting relevant / interesting areas is equivalent to cropping out irrelevant / uninteresting areas.

[0074] Another way to reduce the size of an image is to compress it. The term "compression" refers to the process of reducing the amount of data required to represent image content, for example, by applying algorithms that eliminate redundancies and irrelevant information. The effectiveness of compression can be measured by the compression ratio, which indicates the extent to which the original amount of data has been reduced. An image that does not include an arthropod, or no relevant / interesting arthropod, can be compressed more than an image that does include an arthropod, or relevant / interesting arthropods.An image that has already been analyzed to detect, locate, identify, and / or count one or more arthropods in the imaged collection area can be compressed more than an image that has not yet been analyzed for this purpose. The reduction parameter can specify whether an image is compressed at all. The reduction parameter can specify whether an image is compressed lossily or losslessly. The reduction parameter can specify how an image is compressed; for example, it can specify which compression technique(s) and / or compression algorithm(s) are used to compress the image. The reduction parameter can specify a compression level.The term "compression level" refers to a setting or parameter within a compression algorithm that determines how aggressively the algorithm attempts to reduce the size of the image capture. Higher compression levels generally mean stronger compression, resulting in smaller file sizes but potentially lower image quality due to loss of detail or the introduction of compression artifacts. The reduction parameter can specify the compression ratio to be achieved. The compression ratio is a measure of the size reduction achieved by the compression process. It is usually expressed as a ratio or percentage, comparing the size of the compressed image capture to the size of the original image capture. The term "compression degree" is often used interchangeably with "compression ratio."In this revelation, the terms are used synonymously, i.e., the compression ratio can also be a compression degree.

[0075] Lossless compression algorithms reduce file size without sacrificing image quality or detail. Examples of lossless compression algorithms include:

[0076] Run-length encoding replaces sequences of image elements with identical color values ​​with a count of the repeating image elements and a single value of that image element, and is therefore recommended, for example, for compressing image recordings with large areas of uniform color values.

[0077] Huffman coding is a frequency-based coding method that assigns shorter codes to more frequent image elements and longer codes to less frequent image elements.

[0078] The LZW method (LZW: Lempel-Ziv-Welch) is a dictionary-based compression method in which character sequences (or variables that characterize image elements) are replaced by shorter, fixed-length codes contained in a dictionary created during the compression process.

[0079] The PNG image format (PNG: Portable Network Graphics) uses a combination of methods such as prediction, filtering and entropy coding (like Huffman coding) to compress image captures without loss of quality.

[0080] The Deflate method is used in the PNG image format and other formats, combining LZ77 algorithms and Huffman coding for effective lossless compression.

[0081] Lossy compression techniques achieve higher compression rates by discarding some of the image data, which can lead to a loss of quality. Examples of lossless compression algorithms include:

[0082] JPEG (Joint Photographie Experts Group) is a widely used image compression standard and uses a combination of discrete cosine transform (DCT), quantization and Huffman coding.

[0083] Instead of DCT, wavelet compression uses wavelet transformations to compress an image. It is used, for example, in JPEG 2000.

[0084] Fractal compression is based on the mathematical theory of fractals and finds self-similar parts of an image and uses them to create compression patterns.

[0085] The HEIF image format (High Efficiency Image File Format) uses the HEVC (High Efficiency Video Compression) method, also known as H.265, to compress images.

[0086] Several reduction techniques can also be combined.

[0087] Determining the reduction parameter based on the collection area depicted in the image can involve one or more of the following steps:

[0088] (i) Checking for the presence of at least one arthropod in the illustrated collection area,

[0089] (ii) Checking for the presence of at least one specific arthropod in the depicted collection area / Identifying one or more arthropods in the depicted collection area,

[0090] (iii) Counting arthropods in the illustrated collection area,

[0091] (iv) Determining the developmental stage of one or more arthropods in the illustrated collection area,

[0092] (v) Determining the size of one or more arthropods in the illustrated collection area,

[0093] (vi) Comparing a first received image with a second received image, wherein the first received image and the second received image show the collection area at different times,

[0094] (vii) Locating one or more arthropods in the illustrated collection area.

[0095] Regarding (i): It can be checked whether at least one arthropod is present in the depicted collection area. Checking for the presence of an arthropod in the collection area can be done using an object recognition method. Object detection methods are described in the prior art (see, for example, R. Girshick et al. '. Rich feature hierarchies for accurate object detection and semantic segmentation, arXiv: 1311, 2524v5; Girshick: Fast R-CNN, arXiv: 1504.08083v2; S. Ren et al.: Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, arXiv: 1506.01497v3; J. Redmon et al. '. You Only Look Once: Unified, Real-Time Object Detection, arXiv: 1506.02640v5; W. Liu et al. '. SSD: Single Shot MultiBox Detector, arXiv: 1512.02325v5; N. Carion et al. '. End-to-End Object Detection with Transformers, arXiv:2005.12872v3).

[0096] The object recognition method can be designed to indicate the presence of an arthropod without specifying the species. Alternatively, it can be designed to detect arthropods in the image and assign each detected arthropod to one of at least two classes. A class can represent a level of biological taxonomy or a combination of several levels. Different classes can represent, for example, different subclasses, superorders, orders, suborders, families, genera, and / or species of arthropods. The class to which an arthropod is assigned can indicate its developmental stage.The class to which an arthropod is assigned can indicate whether it is a beneficial organism, a pest, or a neural arthropod (one that is neither harmful nor beneficial to a given plant, or for which no harm or benefit has yet been identified). The class to which an arthropod is assigned can indicate whether it is a beneficial organism or a pest for a specific plant. The class to which an arthropod is assigned can indicate whether and / or with which pesticide the arthropod can be controlled. The class to which an arthropod is assigned can indicate whether and / or with which pesticide the arthropod cannot be controlled.

[0097] If no arthropods are present in the collection area, identification of any arthropods present in the collection area is unnecessary. If no arthropods are present in the collection area, the image capture is less relevant to the user than if one or more arthropods were present. The image size can be (significantly) reduced. The image capture can also be discarded. The image capture can be lossily compressed. The resolution and / or color depth can be reduced. The at least one reduction parameter can (a) specify that the image size is to be reduced, (b) specify one or more reduction techniques (e.g., compression techniques, Z-algorithms) with which the image capture is to be reduced, (c) specify parameters of the one or more reduction techniques (e.g., the compression level).

[0098] If one or more arthropods are present in the collection area, identification may be useful (provided the arthropod has not already been identified by the object recognition method). If one or more arthropods are present in the collection area, the image capture may be relevant and / or interesting to a user. The at least one reduction parameter can (a) specify that the image capture should not be compressed, should only be compressed slightly, or should be lossless; (b) specify one or more reduction techniques (e.g., compression techniques, Z-algorithms) with which the image capture should be reduced; (c) specify parameters of the one or more reduction techniques (e.g., the compression level); (d) specify one or more sub-areas where the image resolution and / or color depth should be reduced; (e) specify one or more sub-areas that should be cropped or masked.

[0099] Regarding (ii): It can be checked whether at least one specific arthropod is present in the depicted collection area. In other words, one or more specific arthropods can be identified in the depicted collection area. Such a specific arthropod could be one whose presence a user wants or needs to know about, for example, because it is a pest. It is possible for a user to specify which specific arthropods are relevant to them. It is also conceivable that the inventive device includes a trapping device for one or more specific arthropods, and that the trapping device itself thus already defines one or more specific arthropods.If no specific arthropod is present in the collection area, the image capture is not relevant or less relevant to a user than if one or more specific arthropods were present in the collection area. The image size can be significantly reduced. The image capture can also be discarded. The image capture can be lossily compressed. The resolution and / or color depth can be reduced. The at least one reduction parameter can (a) specify that the image size is to be reduced, (b) specify one or more reduction techniques (e.g., compression techniques, Z-algorithms) with which the image capture is to be reduced, (c) specify parameters of the one or more reduction techniques (e.g., the compression level).

[0100] If a specific arthropod or several specific arthropods are present in the collection area, the image capture may be relevant and / or interesting to a user. The at least one reduction parameter can (a) specify that the image capture should not be compressed, should only be compressed slightly, or should only be compressed losslessly, (b) specify one or more reduction techniques (e.g., compression techniques, Z-algorithms) with which the image capture should be reduced, (c) specify parameters of the one or more reduction techniques (e.g., the compression level), (d) specify one or more sub-areas where the image resolution and / or color depth should be reduced, (e) specify one or more sub-areas that should be cropped, masked, or extracted.

[0101] Regarding (iii): The number of arthropods present in the depicted collection area can be determined.

[0102] If the number of arthropods is less than a predefined threshold, the image acquisition may be considered irrelevant / uninteresting. The image acquisition may be discarded. The image acquisition may be (significantly) reduced. The image acquisition may be lossily compressed. The at least one reduction parameter may (a) specify that the size of the image acquisition is to be reduced, (b) specify one or more reduction techniques (e.g., compression techniques / algorithms) with which the image acquisition is to be reduced, (c) specify parameters of the one or more reduction techniques (e.g., the compression level).

[0103] If the number of arthropods exceeds a predefined threshold, the image may be considered relevant / interesting. The image may not be compressed, or compressed less, than if the number of arthropods were lower than the predefined threshold. The at least one reduction parameter can (a) specify that the image should not be compressed, only slightly compressed, or only losslessly compressed, (b) specify one or more reduction techniques (e.g., compression techniques, Z-algorithms) to be used to reduce the image, (c) specify parameters of the one or more reduction techniques (e.g., the compression level), (d) specify one or more areas where the image resolution and / or color depth should be reduced, or (e) specify one or more areas to be cropped or masked.

[0104] Regarding (iv): The developmental stage of one or more (specific) arthropods in the depicted collection area can be determined. The term "(specific) arthropod" means that the arthropod is any arthropod or a specific arthropod. The term "(specific) arthropod" means: "an arthropod or a specific arthropod." It is conceivable that the developmental stage of one or more arthropods or one or more specific arthropods influences whether a (specific) arthropod is of interest and / or relevant to a user. For example, a (specific) arthropod may only be considered a pest if it is in a specific developmental stage.

[0105] If no (specific) arthropod at a specific developmental stage is present in the image, the image may be considered less relevant than if it did contain a (specific) arthropod at that stage. The image may be discarded. The image may be reduced (e.g., significantly). The image may be lossily compressed. The at least one reduction parameter may (a) specify that the image size is to be reduced, (b) specify one or more reduction techniques (e.g., compression techniques, Z-algorithms) to be used to reduce the image size, or (c) specify parameters of the one or more reduction techniques (e.g., the compression level).

[0106] If at least one (specific) arthropod is present in a specific developmental stage within the image, the image may be considered relevant and / or interesting to a user. The at least one reduction parameter can (a) indicate that the image should not be compressed, only slightly compressed, or only losslessly compressed, (b) specify one or more reduction techniques (e.g., compression techniques, Z-algorithms) with which the image should be reduced, (c) specify parameters of the one or more reduction techniques (e.g., the compression level), (d) specify one or more areas where the image resolution and / or color depth should be reduced, (e) specify one or more areas that should be cropped or masked.

[0107] Regarding (v): The size of one or more (specific) arthropods in the collection area can be determined. It is conceivable that the size of one or more arthropods, or one or more specific arthropods, influences whether a (specific) arthropod is of interest and / or relevant to a user. For example, a (specific) arthropod may only be considered a pest if it exceeds or falls below a certain size threshold.

[0108] If no (specific) arthropod with a size above or below the threshold is present in the image, the image may be considered less relevant than if an arthropod with a size above or below the threshold were present. The image may be discarded. The image may be (significantly) reduced in size. The image may be lossily compressed. The at least one reduction parameter may (a) specify that the image size is to be reduced, (b) specify one or more reduction techniques (e.g., compression techniques, Z-algorithms) with which the image is to be reduced, (c) specify parameters of the one or more reduction techniques (e.g., the compression level).

[0109] If at least one (specific) arthropod with a size above or below the threshold is present in the image, the image may be considered relevant and / or interesting to a user. The at least one reduction parameter can (a) specify that the image should not be compressed, only slightly compressed, or only losslessly compressed, (b) specify one or more reduction techniques (e.g., compression techniques, Z-algorithms) with which the image should be reduced, (c) specify parameters of the one or more reduction techniques (e.g., the compression level), (d) specify one or more areas where the image resolution and / or color depth should be reduced, (e) specify one or more areas that should be cropped or masked.

[0110] Regarding (vi): At least two image acquisitions can be received; a first image acquisition and a second image acquisition, where the first and second image acquisitions typically represent the collection area at different times. The first and second image acquisitions can be compared. Changes between the first and second image acquisitions can be identified and / or quantified. These changes may influence whether the first and / or the second image acquisition is interesting and / or relevant to a user. For example, it is possible that the first and / or the second image acquisition is only interesting and / or relevant to a user if the number of (specific) arthropods has changed.It is possible that the first and / or second image capture is only interesting and / or relevant to a user if the number of (specific) arthropods has increased over time. If changes between the first and second image captures do not meet predefined criteria, the first and / or second image capture may be considered less relevant than if the changes met the predefined criteria. The first and / or second image capture can be discarded. The first and / or second image capture can be reduced (e.g., significantly). The first and / or second image capture can be lossily compressed. The at least one reduction parameter can (a) specify that the size of the image capture is to be reduced, (b) specify one or more reduction techniques (e.g.,(c) Specify compression techniques (Z-algorithms) with which the image capture is to be reduced, (c) Specify parameters of one or more reduction techniques (e.g. the compression level).

[0111] If changes between the first and second image captures correspond to predefined criteria, the first and / or second image capture may be considered interesting and / or relevant. The at least one reduction parameter can (a) specify that the image capture should not be compressed, should only be compressed slightly, or should only be compressed losslessly; (b) specify one or more reduction techniques (e.g., compression techniques, Z-algorithms) with which the image capture should be reduced; (c) specify parameters of the one or more reduction techniques (e.g., the compression level); (d) specify one or more sub-areas where the image resolution and / or color depth should be reduced; (e) specify one or more sub-areas that should be cropped or masked.

[0112] It is also possible to generate a new image based on the first and second image captures, in which the changes between the two are represented. For example, the first image capture can be subtracted from the second image capture, element by element. This subtraction typically involves the color or grayscale values ​​of the image elements. The result of this subtraction is referred to in this disclosure as a subtraction capture. It is possible that the reduced dataset includes a subtraction capture.

[0113] Regarding vii): One or more arthropods can be located within the depicted collection area. The term "locate" refers to determining the position of an arthropod in an image. Localization answers the question "where" an arthropod can be found in an image. The term "locate" can also include determining the orientation of an arthropod in the image. Localization is typically a step in object recognition (so). Localization can be achieved, for example, by specifying a bounding box around the arthropod.

[0114] A "bounding box" is a rectangular frame defined by the coordinates of its corners that encloses an object of interest (e.g., a specific arthropod) in an image. The bounding box is characterized by its position, typically specified by the coordinates of its upper left corner (xi, yi) and lower right corner (x2, yi), or alternatively by the coordinates of its center point (cx, cy) along with its width (w) and height (h). The bounding box serves as a spatial representation that delineates the object's boundaries, enabling its identification and / or analysis.

[0115] Bounding frames are frequently used to mark objects in images. It should be noted that a bounding frame does not necessarily have to be rectangular; other geometric shapes are also suitable for marking objects, such as circles, ellipses, hexagons, or other forms. In this respect, the term "bounding frame" should be interpreted broadly and is not limited to rectangular frames.

[0116] Alternatively or in addition to a bounding box, an arthropod in a photograph can also be highlighted with color. Another possibility is to highlight parts of the photograph that do not contain arthropods by displaying them in a different color, in grayscale, and / or with reduced brightness, and / or with reduced contrast, and / or with reduced color depth, thus making the arthropods stand out from the other parts of the photograph. Highlighting can also include adding a label or indicator (e.g., an arrow) pointing to a localized arthropod.

[0117] There may be other ways to mark objects. The marking can be used to show a user where one or more arthropods are depicted in the image and / or which arthropods are depicted in the image.

[0118] It is possible that different classes of arthropods are marked differently in the image. In the case of bounding boxes, for example, these may have different colors and / or borders.

[0119] In one embodiment of the present disclosure, the resolution and / or color depth within a bounding frame of a reduced image capture is higher than outside the bounding frame, wherein the bounding frame indicates the position of a (specific) arthropod.

[0120] In one embodiment of the present disclosure, a received image is reduced to the image elements within a bounding frame, the bounding frame indicating the position of a (specific) arthropod. In other words, the contents of the bounding frame (i.e., the image elements lying within the bounding frame) are extracted. In other words, those parts of the image that lie outside the bounding frame are cut out or masked.

[0121] In one embodiment of the present disclosure, one or more arthropods are located in the image and the located arthropods are identified (e.g., by assigning them to one of at least two classes). The reduced data set can include the coordinates of the one or more arthropods (position information) and / or identity information indicating which arthropod is being referred to.

[0122] The identification information can specify the type of arthropod. It can indicate whether the arthropod is beneficial, harmful, or neutral. The identification information can indicate whether the arthropod can be controlled with a plant protection product and / or which plant protection product can be used. The identification information can also indicate which plant protection products cannot be used to control the arthropod.

[0123] In a further step, a reduced dataset is generated. This reduced dataset is created based on the received image. If multiple images were received, it is possible to generate a separate reduced dataset for each image. It is also possible to combine multiple received images into a single reduced dataset.

[0124] The generation of the reduced image capture is done using one or more reduction parameters. In other words, received image captures are reduced as specified by the one or more reduction parameters.

[0125] If at least one reduction parameter specifies, for example, that a received image should be reduced, then the received image is reduced, and the result is a reduced image. The reduction technique can be a predefined technique (e.g., by a user).

[0126] If the at least one reduction parameter specifies, for example, how a received image is reduced (e.g., by reducing the resolution, reducing the color depth, cropping / extracting / masking parts of the image, or compression), the received image is reduced as specified by the at least one reduction parameter. The result is a reduced image. In one embodiment of the present disclosure, the reduced data set comprises a reduced image, wherein the reduced image is generated by reducing the received image.

[0127] In one embodiment of the present disclosure, the reduced data set includes position information, wherein the position information indicates at which position in the received image image an arthropod is depicted.

[0128] In one embodiment of the present disclosure, the reduced data set includes position information, wherein the position information indicates at which position in the received image image a specific arthropod is depicted.

[0129] In one embodiment of the present disclosure, the reduced data set includes orientation information, wherein the orientation information indicates how the arthropod depicted in the received image is oriented, i.e., e.g., how a body axis is oriented (aligned) in relation to boundaries of the received image and / or features of the collection area.

[0130] In one embodiment of the present disclosure, the reduced data set includes identity information, wherein the identity information indicates what kind of arthropod is depicted in the received image.

[0131] In one embodiment of the present disclosure, the reduced data set includes development information, wherein the development information indicates the stage of development of the arthropod depicted in the received image.

[0132] In one embodiment of the present disclosure, the reduced data set includes size information, wherein the size information indicates how large the arthropod depicted in the received image is.

[0133] In one embodiment of the present disclosure, the reduced data set includes quantity information, wherein the quantity information indicates how many arthropods are depicted in the received image.

[0134] In one embodiment of the present disclosure, the reduced data set includes quantity information, wherein the quantity information indicates how many specific arthropods (e.g., arthropods of a specific class) are depicted in the received image.

[0135] In one embodiment of the present disclosure, the reduced data set comprises a compressed image recording, wherein the compressed image recording is generated by compression of the received image recording.

[0136] In one embodiment of the present disclosure, the reduced data set comprises a reduced image capture, wherein the reduced image capture has a lower resolution and / or color depth than the received image capture.

[0137] In one embodiment of the present disclosure, the reduced data set comprises a reduced image capture, wherein the reduced image capture comprises one or more sub-areas in which the resolution and / or color depth is lower than in the received image capture, wherein the one or more sub-areas do not include / comprise an arthropod.

[0138] In one embodiment of the present disclosure, the reduced data set comprises a reduced image capture, wherein the reduced image capture comprises one or more sub-areas in which the resolution and / or color depth is lower than in the received image capture, wherein the one or more sub-areas do not comprise a specific arthropod.

[0139] In one embodiment of the present disclosure, the reduced data set comprises a reduced image capture, wherein the reduced image capture is generated by subtracting a first image capture from a second image capture, wherein the first image capture represents the capture area at a first time point in time and the second image capture represents the capture area at a second time point in time, wherein the second time point in time is temporally subsequent (i.e., later) to the first time point in time.

[0140] In one embodiment of the present disclosure, the reduced data set includes change information, wherein the change information indicates whether and / or what changes exist between a first image acquisition and a second image acquisition, wherein the first image acquisition represents the collection area at a first time point in time and the second image acquisition represents the collection area at a second time point in time, wherein the second time point in time is temporally subsequent (i.e., later) to the first time point in time.

[0141] In one embodiment of the present disclosure, the reduced data set comprises either a first image acquisition or a second image acquisition, wherein the first image acquisition can be a reduced image acquisition and the second image acquisition can be a reduced image acquisition, wherein the first image acquisition represents the collection area at a first time point in time and the second image acquisition represents the collection area at a second time point in time, wherein the second time point in time is temporally subsequent to the first time point in time (i.e. later).

[0142] The reduced data set can be stored in a data storage device. The data storage device can be a component of the device of the present disclosure. The data storage device can be connected to the device of the present disclosure (e.g., via a network).

[0143] The reduced data set can be transmitted to a separate computer system (e.g. via a network).

[0144] If the reduced dataset includes a reduced image, the reduced image can be output to a user. The reduced image can, for example, be displayed on a monitor and / or printed.

[0145] The reduced image can be further analyzed. For example, if determining one or more reduction parameters only involved checking whether an arthropod was present in the collection area, the reduced image can be used to identify one or more arthropods present in the collection area. The arthropods depicted in the reduced image can be counted. The number of specific arthropods depicted in the reduced image can be determined.

[0146] If the reduced dataset includes positional and identity information, a synthetic image can be generated based on this information. The positional information indicates the location of an arthropod within the received image. The identity information specifies the type of arthropod depicted in the received image. The synthetic image can be a synthetic representation of the collection area, in which an arthropod belonging to a defined group (e.g., subclass, superorder, order, suborder, family, genus, species, stage), defined by the identity information, is depicted at the position defined by the positional information.If the reduced dataset includes developmental information, size information, and / or orientation information, such information can be considered for representing the arborist in the synthetic image. The synthetic image can be generated, for example, by inserting an image of the corresponding arborist at the appropriate position in the synthetic image. Alternatively, the synthetic image can be generated by inputting information such as positional information, identity information, size information, developmental information, and / or orientation information as input data into a conditional generative model that has been trained to generate a synthetic image based on such input data. Such conditional generative models are described in the prior art (see, e.g., R.Rombach et al.: High-Resolution Image Synthesis with Latent Diffusion Models, arXiv:2112.10752v2; J. Ho et al.: Denoising Diffusion Probabilistic Models, arXiv:2006.11239v2; K. Preechakul et al:. Diffusion autoencoders: Toward a meaningful and decodable representation, arXiv:2111.15640v3; P. Dhariwal, A. Nichol: “Diffusion models beat GANs on image synthesis f arXiv:2105.05233v4).

[0147] Generating a synthetic image has the advantage that, compared to the received image, only a small amount of data (e.g., position and identification information) needs to be transmitted to a separate computer system. On this separate computer system, a synthetic image can then be generated based on the transmitted information, visually representing the information relevant and / or interesting to a user, which is also represented by the received image: which arthropod is located where in the collection area.In other words, instead of the received image or an image reduced based on the received image, only the information that is relevant and / or interesting to a user is transmitted; based on this information, a synthetic image and thus a visual representation of this information is then generated, which makes the information visually available to a user.

[0148] Fig. 1 shows, by way of example and schematically, an embodiment of the computer-implemented method of the present disclosure in the form of a flowchart.

[0149] The procedure (100) comprises the following steps:

[0150] (110) Receiving a photograph showing a collection area for arthropods,

[0151] (120) Determining one or more reduction parameters based on the collection area depicted in the image,

[0152] (130) Generating a reduced data set using one or more reduction parameters,

[0153] (140) Storing the reduced data set and / or transmitting the reduced data set to a separate computer system.

[0154] Another aspect of the present invention is a device. Fig. 2 shows an exemplary and schematic embodiment of such a device.

[0155] The device (1) comprises a processing unit (20) and a memory (50).

[0156] 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).

[0157] The memory (50) can be ordinary computer hardware capable of storing information such as digital image recordings (e.g., representations of the study area), 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 thereof.

[0158] 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) may include one or more near-field communication interfaces configured to connect devices using near-field communication technologies such as NFC, RFID, Bluetooth, Bluetooth LE, ZigBee, infrared (e.g., IrDA) or the like.

[0159] 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 similar. 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 similar.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.

[0160] 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 sequential, with one instruction being retrieved, loaded, and executed at a time. However, the retrieval, loading, and / or execution can also be performed in parallel.

[0161] The device may be or comprise a computer system in the form of a laptop, notebook, netbook, tablet PC, or smartphone; the device may also be a component of a camera. Likewise, one or more cameras may be part of the device.

[0162] The device typically includes a power supply unit that can supply the device with energy.

[0163] The device is typically designed for autonomous outdoor operation for a period of several days, weeks, months, or even years. Power supply means include, for example, one or more electrochemical cells, batteries, solar cells, fuel cells, and / or generators (e.g., in combination with a wind turbine).

[0164] The device can be designed to harvest electrical energy from its environment. This environmental energy can be provided in the form of light, electric fields, magnetic fields, electromagnetic fields, motion, pressure, heat, and / or other forms of energy, and can be used or "harvested" by the device. This type of electrical energy generation is known as energy harvesting. Energy harvesting refers to methods for extracting and storing minute amounts of freely available energy from the environment. This technique makes it possible to power a device throughout its entire lifespan. Energy harvesting systems typically include an energy converter, an energy management unit, and an energy storage device, usually a capacitor.The energy converter, also called a microgenerator, converts energy from the environment into electrical energy. The conversion can utilize, for example, the piezoelectric effect, the thermoelectric effect, or the photoelectric effect. Further details are described in the prior art (see, for example, http: / / www.harvesting-energy.de / and the publications listed there).

[0165] 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.

[0166] In one embodiment of the present disclosure, the device comprises a trapping device for arthropods or specific arthropods. In one embodiment of the present disclosure, the trapping device comprises the collecting area. In one embodiment of the present disclosure, the device comprises a camera. In one embodiment of the present disclosure, the camera comprises at least one camera sensor onto which the collecting area is imaged (e.g., by camera optics, which may be a component of the device).

[0167] The device of the present disclosure is configured to receive an image recording in which a collection area for arthropods is depicted, to determine one or more reduction parameters based on the collection area depicted in the image recording, to generate a reduced data set using the one or more reduction parameters, to store the reduced data set and / or to transmit it to a separate computer system.

[0168] To image the collection area on one or more image sensors of one or more cameras, 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 spectrum) is scattered / reflected from the illuminated collection area towards the camera. Daylight can be used for this purpose. However, it is also conceivable to use a lighting unit that provides defined illumination independent of daylight. This is preferably mounted to the side of the camera so that no shadow is cast by the camera onto the collection area.

[0169] The light source can be a component of the camera and / or the device.

[0170] 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 takes one or more pictures "from above".

[0171] It is conceivable that several light sources illuminate the collection area from different directions.

[0172] 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) or above 780 nm (infrared light: 780 nm to 1000 pm) is used for illumination. The image sensor and optical elements are typically adapted to the electromagnetic radiation used. The device may include a transmitter unit to transmit information via a network to a separate computer system. This information may, for example, be 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 information on the status of the device.

[0173] 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.

[0174] 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).

[0175] 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.

[0176] 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.

[0177] The computer program can be offered for download in an app store and / or on a website of the Internet.

[0178] The computer program can be loaded into the memory of the device of the present disclosure and / or may already be stored there and cause the device to perform the following steps:

[0179] Receiving an image, the image of which depicts a collection area for arthropods,

[0180] Determining one or more reduction parameters based on the collection area depicted in the image capture,

[0181] Generating a reduced dataset using one or more reduction parameters,

[0182] Saving the reduced data set and / or transmitting the reduced data set to a separate computer system.

[0183] 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 therefore part of the present technical teaching and should not be confused with the subject matter of the patent claims.

[0184] Embodiment 1: A computer-implemented method comprising the steps of: Receiving an image image wherein a collection area for arthropods is depicted in the image image,

[0185] Determining one or more reduction parameters based on the image acquisition,

[0186] Generating a reduced dataset based on the image capture using one or more reduction parameters,

[0187] Saving the reduced data set and / or transmitting the reduced data set to a separate computer system.

[0188] Embodiment 2: A computer-implemented method comprising the steps:

[0189] Receiving an image recording in which a collection area for arthropods is depicted,

[0190] Determining one or more reduction parameters based on the collection area depicted in the image capture,

[0191] Generating a reduced dataset using one or more reduction parameters,

[0192] Saving the reduced data set and / or transmitting the reduced data set to a separate computer system.

[0193] Embodiment 3: A device comprising a processing unit and a memory, wherein a computer program is stored in the memory which causes the device to execute the following:

[0194] Receiving an image recording in which a collection area for arthropods is depicted,

[0195] Determining one or more reduction parameters based on the collection area depicted in the image capture,

[0196] Generating a reduced dataset using one or more reduction parameters,

[0197] Saving the reduced data set and / or transmitting the reduced data set to a separate computer system.

[0198] Embodiment 4: A device comprising a processing unit and a memory, wherein a computer program is stored in the memory which causes the device to execute the following:

[0199] Receiving an image recording in which a collection area for arthropods is depicted,

[0200] Determining one or more reduction parameters based on the image acquisition,

[0201] Generating a reduced dataset based on the image capture using one or more reduction parameters,

[0202] Saving the reduced data set and / or transmitting the reduced data set to a separate computer system.

[0203] Embodiment 5: A non-volatile, computer-readable storage medium on which a computer program is stored which, when executed by a processing unit of a computer system, causes the computer system to execute the following:

[0204] Receiving an image in which a collection area for arthropods is depicted, determining one or more reduction parameters based on the collection area depicted in the image,

[0205] Generating a reduced dataset using one or more reduction parameters,

[0206] Saving the reduced data set and / or transmitting the reduced data set to a separate computer system.

[0207] Embodiment 6: A non-volatile, computer-readable storage medium on which a computer program is stored which, when executed by a processing unit of a computer system, causes the computer system to execute the following:

[0208] Receiving an image recording in which a collection area for arthropods is depicted,

[0209] Determining one or more reduction parameters based on the image acquisition,

[0210] Generating a reduced dataset based on the image capture using one or more reduction parameters,

[0211] Saving the reduced data set and / or transmitting the reduced data set to a separate computer system.

[0212] Embodiment 7: One of embodiments 1 to 6, wherein determining one or more reduction parameters includes:

[0213] Determine that no arthropod is depicted in the image.

[0214] Embodiment 8: One of embodiments 1 to 7, comprising determining one or more reduction parameters:

[0215] Determine that a specific arthropod is not depicted in the image.

[0216] Embodiment 9: One of embodiments 1 to 8, comprising determining one or more reduction parameters:

[0217] Determine that the number of arthropods in the image is less than a predefined threshold.

[0218] Embodiment 10: One of embodiments 1 to 9, comprising determining one or more reduction parameters:

[0219] Determine whether the size of the arthropods in the image is greater or smaller than a predefined threshold.

[0220] Embodiment 11: One of embodiments 1 to 10, comprising determining one or more reduction parameters:

[0221] Determine that no pest is depicted in the image.

[0222] Embodiment 12: One of embodiments 1 to 11, wherein determining one or more reduction parameters includes:

[0223] Determine that no specific pest is depicted in the image.

[0224] Embodiment 13: One of embodiments 1 to 12, comprising determining one or more reduction parameters:

[0225] Determine that the number of arthropods in the collection area has not increased over time.

[0226] Embodiment 14: One of embodiments 1 to 13, wherein determining one or more reduction parameters comprises: determining that the number of arthropods in the collection area has increased less over time than defined by a threshold value.

[0227] Embodiment 15: One of embodiments 1 to 14, comprising determining one or more reduction parameters:

[0228] Checking for the presence of at least one specific arthropod in the depicted collection area.

[0229] Embodiment 16: One of embodiments 1 to 15, comprising determining one or more reduction parameters:

[0230] Identifying one or more arthropods in the illustrated collection area.

[0231] Embodiment 17: One of embodiments 1 to 16, comprising determining one or more reduction parameters:

[0232] Counting arthropods in the illustrated collection area.

[0233] Embodiment 18: One of embodiments 1 to 17, comprising determining one or more reduction parameters:

[0234] Determining the developmental stage of one or more arthropods in the depicted collection area.

[0235] Embodiment 19: One of embodiments 1 to 18, comprising determining one or more reduction parameters:

[0236] Determining the size of one or more arthropods in the illustrated collection area.

[0237] Embodiment 20: One of embodiments 1 to 19, comprising determining one or more reduction parameters:

[0238] Comparing a first received image with a second received image, where the first received image and the second received image show the collection area at different times.

[0239] Embodiment 21: One of embodiments 1 to 20, comprising determining one or more reduction parameters:

[0240] Locating one or more arthropods in the imaged collection area and / or the received image, in the event that no arthropod is present in the imaged collection area: Determining one or more reduction parameters.

[0241] Embodiment 22: One of embodiments 1 to 21, comprising determining one or more reduction parameters:

[0242] Locating one or more arthropods in the depicted collection area and / or the received image,

[0243] Specify that the resolution of the portions of the image that do not represent an arthropod will be reduced.

[0244] Embodiment 23: One of embodiments 1 to 22, comprising determining one or more reduction parameters:

[0245] Locating one or more arthropods in the depicted collection area and / or the received image,

[0246] Specify that the color depth and / or the number of grayscale levels of the sub-areas of the image that do not represent an arthropod is reduced. Embodiment 24: One of embodiments 1 to 23, wherein determining one or more reduction parameters comprises:

[0247] Locating one or more arthropods in the depicted collection area and / or the received image,

[0248] Specify that parts of the image that do not represent an arthropod should be compressed, or compressed more than parts of the image that do represent an arthropod.

[0249] Embodiment 25: One of embodiments 1 to 24, comprising determining one or more reduction parameters:

[0250] Locating one or more arthropods in the depicted collection area and / or the received image,

[0251] Specify that parts of the image that do not represent an arthropod should be cropped and / or masked.

[0252] Embodiment 26: One of embodiments 1 to 25, comprising determining one or more reduction parameters:

[0253] Locating one or more arthropods in the depicted collection area and / or the received image,

[0254] Specify that parts of the image that represent an arthropod should be extracted.

[0255] Embodiment 27: One of embodiments 1 to 26, comprising determining one or more reduction parameters:

[0256] Checking for the presence of at least one specific arthropod in the depicted collection area, in the event that the specific arthropod is not present in the depicted collection area: Determining one or more reduction parameters.

[0257] Embodiment 28: One of embodiments 1 to 27, comprising determining one or more reduction parameters:

[0258] Identifying one or more arthropods in the depicted collection area, in the event that the one or more arthropods are not pests: Determining the one or more reduction parameters.

[0259] Embodiment 29: One of embodiments 1 to 28, comprising determining one or more reduction parameters:

[0260] Counting arthropods in the depicted collection area, in the event that the number of arthropods is less than a predefined threshold: Determining one or more reduction parameters.

[0261] Embodiment 30: One of embodiments 1 to 29, comprising determining one or more reduction parameters:

[0262] Determining the developmental stage of one or more arthropods in the depicted collection area, in the event that the one or more arthropods are not pests at the determined developmental stage: Determining the one or more reduction parameters. Embodiment 31: One of embodiments 1 to 30, wherein determining the one or more reduction parameters comprises:

[0263] Determining the size of one or more arthropods in the depicted collection area, in the case that the size is smaller or larger than a given threshold value: Determining one or more reduction parameters.

[0264] Embodiment 32: One of embodiments 1 to 31, comprising determining one or more reduction parameters:

[0265] Comparing a first received image with a second received image, where the first received image and the second received image show the collection area at different times, in the case that the number of arthropods has not increased over time: Determining one or more reduction parameters.

[0266] Embodiment 33: One of embodiments 1 to 32, comprising determining one or more reduction parameters:

[0267] Comparing a first received image with a second received image, where the first received image and the second received image show the collection area at different times, in the case that the number of arthropods has decreased over time or the difference between the numbers is less than a predefined threshold: Determining one or more reduction parameters.

[0268] Embodiment 34: One of embodiments 1 to 33, wherein the reduction parameter specifies that the reduced data set is generated on the basis of the image acquisition.

[0269] Embodiment 35: One of embodiments 1 to 34, wherein the reduction parameter specifies how the reduced data set is generated based on the image acquisition.

[0270] Embodiment 36: One of embodiments 1 to 35, wherein the reduction parameter specifies that the image capture is to be compressed.

[0271] Embodiment 37: One of embodiments 1 to 36, wherein the reduction parameter specifies how the image capture is to be compressed.

[0272] Embodiment 38: One of embodiments 1 to 37, wherein the reduction parameter specifies which parts of the image recording are to be compressed.

[0273] Embodiment 39: One of embodiments 1 to 38, wherein the reduction parameter specifies which sub-areas of the image recording are to be compressed and how.

[0274] Embodiment 40: One of embodiments 1 to 39, wherein the reduction parameter specifies that parts of the image capture which do not include an arthropod are cut out and / or masked.

[0275] Embodiment 41: One of embodiments 1 to 40, wherein the reduction parameter specifies that parts of the image capture which do not include a specific arthropod are cut out and / or masked.

[0276] Embodiment 42: One of embodiments 1 to 41, wherein the reduction parameter specifies that the resolution of sub-areas of the image acquisition that do not include an arthropod is to be reduced.

[0277] Embodiment 43: One of embodiments 1 to 42, wherein the reduction parameter specifies that the resolution of sub-areas of the image that do not include an arthropod is to be reduced more than the resolution of sub-areas that do include an arthropod. Embodiment 44: One of embodiments 1 to 43, wherein the reduction parameter specifies that the resolution of sub-areas of the image that do not include a specific arthropod is to be reduced.

[0278] Embodiment 45: One of embodiments 1 to 44, wherein the reduction parameter indicates that the resolution of sub-areas of the image acquisition that do not include a specific arthropod is to be reduced more than the resolution of sub-areas that do include an arthropod.

[0279] Embodiment 46: One of embodiments 1 to 45, wherein the reduction parameter specifies that the color depth and / or number of gray levels of sub-areas of the image capture that do not include an arthropod is to be reduced.

[0280] Embodiment 47: One of embodiments 1 to 46, wherein the reduction parameter specifies that the color depth and / or number of gray levels of sub-areas of the image capture that do not include a specific arthropod is to be reduced.

[0281] Embodiment 48: One of embodiments 1 to 47, wherein the reduction parameter specifies that sub-areas of the image capture that do not include an arthropod are compressed or compressed more than sub-areas that include an arthropod.

[0282] Embodiment 49: One of embodiments 1 to 48, wherein the reduction parameter specifies that sub-areas of the image capture that do not include a specific arthropod are compressed or compressed more than sub-areas that include a specific arthropod.

[0283] Embodiment 50: One of embodiments 1 to 49, wherein the reduced data set is or comprises a reduced image acquisition.

[0284] Embodiment 51: One of embodiments 1 to 50, wherein the reduced data set is or comprises a reduced image capture, wherein in the reduced image capture sub-areas that do not represent an arthropod have a lower resolution than sub-areas that represent an arthropod.

[0285] Embodiment 52: One of embodiments 1 to 51, wherein the reduced data set is or comprises a reduced image capture, wherein in the reduced image capture sub-areas that do not represent an arthropod have a lower color depth than sub-areas that represent an arthropod.

[0286] Embodiment 53: One of embodiments 1 to 52, wherein the reduced data set is or comprises a reduced image capture, wherein in the reduced image capture sub-areas that do not represent an arthropod have a lower number of gray levels than sub-areas that represent an arthropod.

[0287] Embodiment 54: One of embodiments 1 to 53, wherein the reduced data set is or comprises a reduced image capture, wherein generating the reduced image capture comprises: cutting away and / or masking sub-areas of the image capture that do not represent an arthropod.

[0288] Embodiment 55: One of embodiments 1 to 54, wherein the reduced data set is or comprises a reduced image recording, wherein the reduced image recording is characterized in that partial areas in the image recording that do not represent an arthropod are masked.

[0289] Embodiment 56: One of embodiments 1 to 55, wherein the reduced data set is or comprises a reduced image capture, wherein generating the reduced image capture comprises: extracting sub-areas from the image capture that represent one or more arthropods.

[0290] Embodiment 57: One of embodiments 1 to 56, wherein the reduced data set is or comprises a reduced image capture, wherein the reduced image capture comprises one or more sub-areas extracted from the image capture, wherein the one or more extracted sub-areas represent one or more arthropods.

[0291] Embodiment 58: One of embodiments 1 to 57, wherein the reduced data set is or comprises a compressed image recording.

[0292] Embodiment 59: One of embodiments 1 to 58, wherein the reduced data set is part of the image capture or comprises part of the image capture.

[0293] Embodiment 60: One of embodiments 1 to 59, wherein the reduced data set includes position information of one or more arthropods depicted in the image.

[0294] Embodiment 61: One of embodiments 1 to 60, wherein the reduced data set comprises identity information of one or more arthropods depicted in the image.

[0295] Embodiment 62: One of embodiments 1 to 61, wherein the reduced data set is or comprises a reduced image capture, wherein the reduced image capture is generated by reducing the received image capture.

[0296] Embodiment 63: One of embodiments 1 to 62, wherein the reduced data set includes position information, the position information indicating at which position in the received image image an arthropod is depicted.

[0297] Embodiment 64: One of embodiments 1 to 63, wherein the reduced data set includes position information, the position information indicating at which position in the received image image a specific arthropod is depicted.

[0298] Embodiment 65: One of embodiments 1 to 64, wherein the reduced data set includes orientation information, the orientation information indicating how the arthropod depicted in the received image is oriented.

[0299] Embodiment 66: One of embodiments 1 to 65, wherein the reduced data set includes identity information, the identity information indicating what kind of arthropod is depicted in the received image.

[0300] Embodiment 67: One of embodiments 1 to 66, wherein the reduced data set includes development information, the development information indicating the stage of development of the arthropod depicted in the received image.

[0301] Embodiment 68: One of embodiments 1 to 67, wherein the reduced data set includes size information, the size information indicating how large the arthropod depicted in the received image is.

[0302] Embodiment 69: One of embodiments 1 to 68, wherein the reduced data set includes quantity information, the quantity information indicating how many arthropods are depicted in the received image.

[0303] Embodiment 70: One of embodiments 1 to 69, wherein the reduced data set includes quantity information, the quantity information indicating how many specific arthropods are depicted in the received image.

[0304] Embodiment 71: One of embodiments 1 to 70, wherein the reduced data set is or comprises a compressed image recording, wherein the compressed image recording is generated by compression of the received image recording.

[0305] Embodiment 72: One of embodiments 1 to 71, wherein the reduced data set is or comprises a reduced image capture, wherein the reduced image capture has a lower resolution and / or color depth than the received image capture. Embodiment 73: One of embodiments 1 to 72, wherein the reduced data set is or comprises a reduced image capture, wherein the reduced image capture comprises one or more sub-areas in which the resolution and / or color depth is lower than in the received image capture, wherein the one or more sub-areas do not include / comprise an arthropod.

[0306] Embodiment 74: One of embodiments 1 to 73, wherein the reduced data set is or comprises a reduced image capture, wherein the reduced image capture comprises one or more sub-areas in which the resolution and / or color depth is lower than in the received image capture, wherein the one or more sub-areas do not comprise a specific arthropod.

[0307] Embodiment 75: One of embodiments 1 to 74, wherein the reduced data set is or comprises a reduced image acquisition, wherein the reduced image acquisition is generated by subtracting a first image acquisition from a second image acquisition, wherein the first image acquisition represents the collection area at a first time point and the second image acquisition represents the collection area at a second time point, wherein the second time point is temporally subsequent to the first time point.

[0308] Embodiment 76: One of embodiments 1 to 75, wherein the reduced data set includes change information, the change information indicating whether and / or which changes exist between a first image acquisition and a second image acquisition, wherein the first image acquisition represents the collection area at a first time point and the second image acquisition represents the collection area at a second time point, wherein the second time point is temporally subsequent to the first time point.

[0309] Embodiment 77: One of embodiments 1 to 76, wherein the reduced data set is or comprises either a first image acquisition or a second image acquisition, wherein the first image acquisition may be a reduced image acquisition and the second image acquisition may be a reduced image acquisition, wherein the first image acquisition represents the collection area at a first time point in time and the second image acquisition represents the collection area at a second time point in time, wherein the second time point in time is temporally subsequent to the first time point in time.

[0310] Embodiment 78: One of embodiments 1 to 77, wherein the specific arthropod is a pest.

[0311] Embodiment 79: One of embodiments 1 to 78, wherein the specific arthropod is a pest for a specific plant.

[0312] Embodiment 80: One of embodiments 1 to 79, wherein the specific arthropod is an arthropod at a specific stage of development.

[0313] Embodiment 81: One of embodiments 1 to 80, wherein the specific arthropod is an arthropod of a specific size.

[0314] Embodiment 82: One of embodiments 1 to 81, wherein the specific arthropod belongs to a specific class, subclass, superorder, order, suborder, family, genus and / or species.

[0315] Embodiment 83: One of embodiments 1 to 82, wherein the reduction parameter specifies how a reduced data set is generated on the basis of the received image recording.

[0316] Embodiment 84: One of embodiments 1 to 83, wherein the reduced data set comprises a smaller amount of data than the received image recording.

[0317] Embodiment 85: One of embodiments 1 to 84, wherein the reduced data set comprises a reduced image capture, the reduced image capture containing a smaller amount of data than the received image capture. Embodiment 86: One of embodiments 1 to 85, wherein the reduction parameter specifies how a reduced image capture is generated based on the received image capture.

[0318] Embodiment 87: One of embodiments 1 to 86, wherein the collecting area comprises means for immobilizing arthropods.

[0319] Embodiment 88: One of embodiments 1 to 87, further comprising:

[0320] Output of the reduced dataset.

[0321] Embodiment 89: One of embodiments 1 to 88, further comprising:

[0322] Transmitting the reduced data set to a separate computer system.

[0323] Embodiment 90: One of embodiments 1 to 89, further comprising:

[0324] Generating a synthetic image based on the reduced data set, wherein the reduced data set includes position information and identity information, where the position information indicates the position of an arthropod in the received image, and where the identity information indicates what type of arthropod is depicted in the received image.

[0325] Embodiment 91: One of embodiments 1 to 90, wherein the reduced data set further comprises: orientation information, wherein the orientation information indicates how an arthropod depicted in the received image is oriented.

[0326] Embodiment 92: One of embodiments 1 to 91, wherein the reduced data set further comprises: development information, wherein the development information indicates the stage of development of an arthropod depicted in the received image.

[0327] Embodiment 93: One of embodiments 1 to 92, wherein the reduced data set further comprises: size information, wherein the size information indicates how large an arthropod depicted in the received image is.

[0328] Embodiment 94: One of embodiments 1 to 93, wherein the reduced data set further comprises: quantity information, wherein the quantity information indicates how many arthropods are depicted in the received image.

[0329] Embodiment 95: One of embodiments 90 to 94, wherein the generation of the synthetic image acquisition is carried out using a conditional generative model.

[0330] Embodiment 96: One of embodiments 90 to 94, comprising generating the synthetic image capture:

[0331] Inserting an image of the arthropod at the position in the synthetic image capture.

[0332] Embodiment 97: One of embodiments 1 to 96, comprising determining one or more reduction parameters:

[0333] Checking for the presence of at least one arthropod in the depicted collection area,

[0334] Determine that no arthropod is depicted in the received image,

[0335] Setting the reduction parameter, wherein the reduction parameter specifies how and / or to what extent the received image recording is reduced, including the generation of the reduced data set:

[0336] Generating a reduced image based on the received image according to reduction parameters.

[0337] Embodiment 98: One of embodiments 1 to 97, wherein determining one or more reduction parameters comprises: checking for the presence of at least one specific arthropod in the illustrated collection area,

[0338] Determine that no specific arthropod is depicted in the received image,

[0339] Setting the reduction parameter, wherein the reduction parameter specifies how and / or to what extent the received image recording is reduced, including the generation of the reduced data set:

[0340] Generating a reduced image based on the received image according to reduction parameters.

[0341] Embodiment 99: One of embodiments 1 to 98, comprising determining one or more reduction parameters:

[0342] Checking for the presence of at least one arthropod in the depicted collection area,

[0343] Determine that at least one arthropod is depicted in the received image,

[0344] Locating at least one arthropod in the received image,

[0345] Defining one or more sub-areas in the received image, wherein the one or more sub-areas comprise the at least one arthropod, comprising the generation of the reduced data set:

[0346] Generating a reduced image based on the received image, wherein generating the reduced image includes extracting one or more specified sub-areas or cutting away or masking other sub-areas that do not correspond to the one or more specified sub-areas.

[0347] Embodiment 100: One of embodiments 1 to 99, comprising determining one or more reduction parameters:

[0348] Checking for the presence of at least one arthropod in the depicted collection area,

[0349] Determine that at least one arthropod is depicted in the received image,

[0350] Locating at least one arthropod in the received image,

[0351] Defining one or more sub-areas in the received image, wherein the one or more sub-areas do not include the at least one arthropod, comprising the generation of the reduced data set:

[0352] Generating a reduced image based on the received image, wherein generating the reduced image includes reducing the resolution and / or color depth in one or more specified sub-areas.

[0353] Embodiment 101: One of embodiments 1 to 100, comprising the generation of a reduced data set:

[0354] Reducing the resolution of the received image, at least in a sub-area, where the reduction parameter specifies how the resolution is reduced and / or to what extent the resolution is reduced and / or in which sub-area the resolution is reduced, and / or

[0355] Reducing the color depth of the received image recording, at least in a sub-area, wherein the reduction parameter specifies how the color depth is reduced and / or to what extent the color depth is reduced and / or in which sub-area the color depth is reduced, wherein generating a reduced data set includes:

[0356] Cutting away and / or masking and / or extracting one or more sub-areas of the received image recording, wherein the reduction parameter specifies which sub-areas or sub-areas are cut away, masked and / or extracted, and / or

[0357] Compressing at least a portion of the received image, where the reduction parameter specifies how and / or to what extent compression is performed and / or which portion is compressed.

[0358] Embodiment 102: One of embodiments 1 to 101, wherein the reduced data set comprises a reduced image capture, wherein the reduced image capture has a lower resolution at least in a sub-area than the received image capture, wherein the reduction parameter specifies how the resolution is reduced and / or to what extent the resolution is reduced and / or in which sub-area the resolution is reduced.

[0359] Embodiment 103: One of embodiments 1 to 102, wherein the reduced data set comprises a reduced image capture, wherein the reduced image capture has a lower color depth at least in a sub-area than the received image capture, wherein the reduction parameter specifies how the color depth is reduced and / or to what extent the color depth is reduced and / or in which sub-area the color depth is reduced.

[0360] Embodiment 104: One of embodiments 1 to 103, wherein the reduced data set comprises a reduced image capture, wherein the reduced image capture is generated by cutting away and / or masking and / or extracting one or more sub-areas of the received image capture, wherein the reduction parameter specifies which sub-area or sub-areas are cut away, masked and / or extracted.

[0361] Embodiment 105: One of embodiments 1 to 104, wherein the reduced data set comprises a compressed image capture, wherein the compressed image capture is generated by compression of the received image capture.

[0362] Embodiment 106: One of embodiments 1 to 105, wherein the reduced data set includes position information, the position information indicating at which position in the received image image an arthropod is depicted.

[0363] Embodiment 107: One of embodiments 1 to 106, wherein the reduced data set includes orientation information, the orientation information indicating how an arthropod depicted in the received image is oriented.

[0364] Embodiment 108: One of embodiments 1 to 107, wherein the reduced data set includes identity information, the identity information indicating what kind of arthropod is depicted in the received image.

[0365] Embodiment 109: One of embodiments 1 to 108, wherein the reduced data set includes development information, the development information indicating the stage of development of an arthropod depicted in the received image.

[0366] Embodiment 110: One of embodiments 1 to 109, wherein the reduced data set includes size information, wherein the size information indicates how large an arthropod depicted in the received image is.

[0367] Embodiment 111: One of embodiments 1 to 110, wherein the reduced data set includes quantity information, the quantity information indicating how many arthropods are depicted in the received image.

[0368] Embodiment 112: One of embodiments 1 to 111, wherein the reduced data set includes change information, the change information indicating whether and / or what changes exist between a first received image capture and a second received image capture, wherein the first received image capture represents the collection area at a first time point in time and the second received image capture represents the collection area at a second time point in time, wherein the second time point in time is temporally subsequent to the first time point in time.

[0369] Embodiment 113: One of embodiments 1 to 112, wherein the reduced data set comprises either a first image acquisition or a second image acquisition, wherein the first image acquisition is generated on the basis of or corresponds to a first received image acquisition and the second image acquisition is generated on the basis of or corresponds to a second received image acquisition, wherein the first received image acquisition represents the collection area at a first time point in time and the second received image acquisition represents the collection area at a second time point in time, wherein the second time point in time is temporally subsequent to the first time point in time.

[0370] Embodiment 114: One of embodiments 1 to 113, wherein the reduced data set comprises a reduced image capture, wherein the embodiment further comprises:

[0371] Output of the reduced image capture.

[0372] Embodiment 115: One of embodiments 1 to 114, comprising determining one or more reduction parameters:

[0373] Checking for the presence of an arthropod in the depicted collection area,

[0374] Determine that the received image depicts an arthropod,

[0375] Localizing the arthropod in the received image, wherein the reduced data set includes position information, the position information indicating the position of the arthropod in the received image, the reduced data set includes identity information, the identity information indicating what type of arthropod is depicted in the received image, the embodiment further comprising:

[0376] Generating a synthetic image based on position information and identity information.

[0377] Embodiment 116: One of embodiments 1 to 115, wherein the reduced data set comprises a reduced image capture, wherein receiving the image capture comprises:

[0378] Receiving a first image capture and a second image capture, wherein the first image capture represents the collection area at a first time point in time, wherein the second image capture represents the collection area at a second time point in time, comprising determining one or more reduction parameters:

[0379] Determining a change between the first image capture and the second image capture,

[0380] Determine that the change meets a predefined criterion,

[0381] Setting the reduction parameter, where the reduction parameter specifies whether the reduced image capture is generated only on the basis of the first image capture, or whether the reduced image capture is generated only on the basis of the second image capture, or whether the reduced image capture is generated on the basis of the first image capture and the second image capture.

[0382] Embodiment 117: One of embodiments 1 to 116, wherein the reduced data set comprises a reduced image capture, wherein receiving the image capture comprises:

[0383] Receiving a first image capture and a second image capture, wherein the first image capture represents the collection area at a first time point in time, wherein the second image capture represents the collection area at a second time point in time, wherein the second time point in time is temporally subordinate to the first time point in time, comprising determining one or more reduction parameters:

[0384] Determining an initial number of arthropods in the first image,

[0385] Determining a second number of arthropods in the second image,

[0386] Determine that the first number and the second number are equal, or that the absolute difference between the first number and the second number is less than a given threshold, including the generation of the reduced data set:

[0387] Generating a reduced image capture based only on the first image capture or only on the basis of the second image capture.

[0388] Embodiment 118: One of embodiments 1 to 117, wherein the collecting area is part of a trapping device for arthropods.

[0389] Embodiment 119: One of embodiments I to 118, wherein the device comprises a camera for generating the image recording.

[0390] Embodiment 120: One of embodiments 1 to 119, wherein the collection area comprises means for immobilizing arthropods.

[0391] Embodiment 121: One of embodiments 1 to 120, wherein the device comprises the collecting area.

[0392] Embodiment 122: One of embodiments 1 to 121, wherein the device is or comprises a trapping device for arthropods.

[0393] Embodiment 123: One of embodiments 1 to 122, wherein the device comprises a transmitting unit.

[0394] Embodiment 124: One of embodiments 1 to 123, wherein the device is a

[0395] The power supply unit includes a battery.

[0396] Embodiment 125: One of embodiments 1 to 124, wherein the device is a

[0397] Energy supply unit comprising, wherein the energy supply unit comprises one or more solar cells.

[0398] Embodiment 126: One of embodiments 1 to 125, wherein the device comprises a power supply unit, wherein the power supply unit comprises at least one accumulator and at least one solar cell, wherein the at least one solar cell and the at least one accumulator are connected to each other in such a way that the solar cell charges the at least one accumulator when electromagnetic radiation hits the at least one solar cell.

Claims

Patent claims 1. A computer-implemented procedure comprising the following steps: Receiving an image recording in which a collection area for arthropods is depicted, Determining one or more reduction parameters based on the image acquisition, Generating a reduced data set based on the image capture using one or more reduction parameters, where the reduced data set comprises a smaller amount of data than the received image capture. Saving the reduced data set and / or transmitting the reduced data set to a separate computer system.

2. The method according to claim 1, comprising determining one or more reduction parameters: Determine that no arthropod is depicted in the image, and / or Determine that no specific arthropod is depicted in the image, and / or determine that the number of arthropods in the image is less than a predefined threshold, and / or Determine whether the size of the arthropods in the image is greater or smaller than a predefined threshold, and / or Determine that no pest is depicted in the image, and / or Determine that no specific pest is depicted in the image, and / or Determine that the image does not depict an arthropod at a specific stage of development, and / or Determine that the image does not depict a specific arthropod at a specific stage of development, 3. The method according to claim 1 or 2, wherein the reduction parameter specifies that the reduced data set is generated based on the image capture, and / or how the reduced data set is generated based on the image capture, and / or that the image capture is to be compressed, and / or how the image capture is to be compressed.

4. The method according to any one of claims 1 to 3, comprising determining one or more reduction parameters: Locating one or more arthropods in the received image, and Specify that the resolution of the image areas that do not represent an arthropod is reduced, and / or Specify that the color depth and / or the number of grayscale levels of the image areas that do not represent an arthropod is reduced, and / or Specify that portions of the image that do not represent an arthropod are compressed, or compressed more than portions of the image that do represent an arthropod, and / or Specify that parts of the image that do not represent an arthropod are cropped and / or masked, and / or Specify that parts of the image that represent an arthropod should be extracted.

5. The method according to any one of claims 1 to 4, wherein the reduction parameter specifies which parts of the image are to be compressed, and / or which parts of the image are to be compressed and how, and / or that parts of the image that do not include an arthropod are cropped and / or masked, and / or that parts of the image that do not include a specific arthropod are cropped and / or masked, and / or that the resolution of parts of the image that do not include an arthropod is to be reduced, and / or that the resolution of parts of the image that do not include an arthropod is to be reduced more than the resolution of parts of the image that do include an arthropod, and / or that the resolution of parts of the image that do not include a specific arthropod is to be reduced, and / or that the resolution of parts of the image,that do not include a specific arthropod, is to be reduced more than the resolution of sub-areas that do include a specific arthropod, and / or that the color depth and / or number of grayscale levels of sub-areas of the image capture that do not include an arthropod is to be reduced, and / or that the color depth and / or number of grayscale levels of sub-areas of the image capture that do not include a specific arthropod is to be reduced, and / or that sub-areas of the image capture that do not include an arthropod are compressed or compressed more than sub-areas that do include an arthropod, and / or that sub-areas of the image capture that do not include a specific arthropod are compressed or compressed more than sub-areas that do include a specific arthropod.

6. The method according to any one of claims 1 to 5, wherein the reduced data set is or comprises a reduced image capture, wherein in the reduced image capture sub-areas that do not represent an arthropod have a lower resolution than sub-areas that represent an arthropod, and / or wherein in the reduced image capture sub-areas that do not represent an arthropod have a lower color depth than sub-areas that represent an arthropod, and / or wherein in the reduced image capture, sub-areas that do not represent an arthropod have a lower number of grayscale levels than sub-areas that represent an arthropod, and / or wherein generating the reduced image capture comprises: cropping and / or masking sub-areas of the image capture that do not represent an arthropod, and / or wherein the reduced image capture is characterized in that sub-areas in the image capture that do not represent an arthropod are masked, and / or wherein generating the reduced image capture comprises: extracting sub-areas from the image capture that represent one or more arthropods, and / or wherein the reduced image capture comprises one or more sub-areas extracted from the image capture, wherein the one or more extracted sub-areas represent one or more arthropods.and / or wherein the reduced dataset is or comprises a compressed image recording.

7. The method according to any one of claims 1 to 6, wherein the reduced data set comprises position information and identity information, wherein the position information indicates at which position in the received image image an arthropod is depicted, wherein the identity information indicates what kind of arthropod is depicted in the received image image, wherein the method further comprises: Generating a synthetic image of the collection area based on the reduced dataset.

8. The method according to claim 7, wherein the reduced data set further comprises orientation information and / or development information and / or size information and / or quantity information, wherein the orientation information indicates how the arthropod depicted in the received image is oriented, wherein the development information indicates the stage of development of the arthropod depicted in the received image, wherein the size information indicates how large the arthropod depicted in the received image is, and wherein the quantity information indicates how many arthropods are depicted in the received image.

9. The method according to any one of claims 1 to 8, comprising Receiving a first image capture and a second image capture, wherein the first image capture depicts a collection area for arthropods at a first time point in time, wherein the second image capture depicts the collection area at a second time point in time, the second time point being temporally subsequent to the first time point in time, Comparing the first received image with the second received image, in the event that the number of arthropods has not increased over time or has increased less than defined by a threshold: Specifying whether the reduced dataset is generated based on the first and / or the second image, and / or how the reduced dataset is generated based on the first and / or the second image, and / or that the first and / or the second image capture is to be compressed, and / or how the first and / or the second image capture is to be compressed.

10. The method according to claim 9, wherein the reduced data set is or comprises a reduced image capture, wherein the reduced image capture is generated by subtracting the first image capture from the second image capture.

11. The method according to one of claims 9 or 10, wherein the reduced data set includes change information, the change information indicating whether and / or which changes exist between the first image acquisition and the second image acquisition.

12. The method according to any one of claims 9 to 11, wherein the reduced data set is or comprises either the first image capture or the second image capture, wherein the first image capture or the second image capture may be compressed.

13. The method according to any one of claims 2 to 12, wherein the specific arthropod is a pest, and / or is a pest to a specific plant, and / or is an arthropod at a specific stage of development, and / or is an arthropod of a specific size, and / or is an arthropod belonging to a specific class, subclass, superorder, order, suborder, family, genus and / or species, and / or is an arthropod that can be controlled with a specific pesticide, and / or is an arthropod that cannot be controlled with a specific pesticide. 14: A device comprising a processing unit and a memory, wherein a computer program is stored in the memory which causes the device to perform the following: Receiving an image recording in which a collection area for arthropods is depicted, Determining one or more reduction parameters based on the collection area depicted in the image acquisition, Generating a reduced dataset using one or more reduction parameters, Saving the reduced data set and / or transmitting the reduced data set to a separate computer system.

15. Non-volatile, computer-readable storage medium on which a computer program is stored which, when executed by a processing unit of a computer system, causes the computer system to execute the method according to any one of claims 1 to 13.

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