Smart pet door

Abstract

The invention relates to a door (1000) for an animal, preferably a pet, such as cats, dogs or the like, in particular an animal flap, preferably a cat flap, which has a housing (1100, 1200, 1300), a flap (1400) with a lock, and electronics (1500) with a first sensor, preferably a camera, which is configured to perform at least one of the following functions, in particular during the day and / or night: a) animal recognition to identify the animal; and / or b) prey recognition, in order to identify prey of the animal; and / or c) a health assessment to determine the health and / or well-being of the animal; and / or d) foreign animal detection to identify another animal.

Description

[0001] The present invention relates to an intelligent animal door and an application program for such an animal door.

[0002] Pet doors, such as cat or dog doors, are generally known.

[0003] A cat flap (also called a cat door, or, in slightly larger models, a dog door or dog flap) is a passageway for cats, dogs, or similar animals, allowing them to enter and leave premises such as houses, apartments, or indoor spaces independently of humans. These flaps are typically installed in doors, windows, or masonry.

[0004] Nowadays, there are pet doors that recognize your own pet using a chip, thus preventing access by other animals, such as cats or other animals, such as raccoons.

[0005] Animal doors typically consist of a simple flap that swings in one or two directions and is mounted in a frame. The frame is also referred to as the housing.

[0006] Many pet doors also feature a mechanism, a so-called 4-way lock, that regulates access through the pet door. A slider or lever allows you to adjust the direction in which the door opens. This allows you to set the door to be completely closed, open to both sides, or open to only one side, so that a pet can only enter or only exit.

[0007] Furthermore, controlled pet doors are increasingly being used. The animal in question wears, for example, a collar with an infrared transmitter, a magnetic key, or an implanted RFID transponder. A corresponding receiver in the pet door then only grants access to appropriately equipped or authorized animals. This prevents unauthorized animals from using the pet door.

[0008] A disadvantage of previously known animal flaps is, for example, that the animals can enter the premises even with live prey and / or cannot enter the premises at all if they lose their collar and electronic identification.

[0009] The object of the present invention is therefore to provide an intelligent animal door that addresses the above-mentioned problems and is in particular designed to perform animal detection and / or prey detection and / or health detection.

[0010] According to the invention, a door for an animal, preferably a pet such as a cat, dog or the like, in particular an animal flap, preferably a cat flap, is proposed, comprising a housing, a flap with a locking mechanism, and electronics with a first sensor, preferably a camera, which is configured to perform at least one of the following functions, in particular during the day and / or at night: animal detection to recognize the animal and / or prey detection to recognize prey of the animal; and / or health detection to recognize the health of the animal; and / or foreign animal detection to identify another animal.

[0011] Such doors are also known as pet doors. The pet door described herein is preferably designed as a cat or dog door, i.e., for cats, dogs, or the like.

[0012] The animal flap essentially consists of a frame, a flap with a locking mechanism and electronics designed to operate the locking mechanism, in particular so that the flap is closed, open or open in one direction.

[0013] The housing is preferably designed as a multi-part frame and includes, for example, two covers and optionally a spacer that is arranged between the two covers.

[0014] Thanks to its multi-part design, the pet flap described herein can be retrofitted into any opening, be it in a wall, a front door, an apartment door, or the like. The pet flap is installed, for example, by placing the first cover against the opening from the outside and screwing the second cover to the first from the inside.

[0015] Preferably, the first cover is the one located on the outside, and the second cover is the one located on the inside, i.e., facing into the space. The covers are thus mounted against the opening from one side of the opening. The housing therefore has an outer (first) cover and an inner (second) cover, with the inner cover extending into the space and the outer cover being located outside the space.

[0016] Preferably, the covers and the optional spacer have corresponding mounting openings by means of which the elements can be assembled to form the housing or frame. For example, the housing or frame can be assembled using screw or snap-fit ​​connections.

[0017] Preferably, the covers or spacers are made of weather- and UV-resistant PVC or other polymer.

[0018] In a particularly preferred embodiment, the covers or the spacer are also designed to be scratch-resistant.

[0019] The flap is designed, for example, as a double or single flap. Preferably, the flap(s) are movably, and in particular pivotably, mounted in the housing. This can be achieved, for example, by means of a pivot axis in the form of pins, which are arranged at the upper end of the flap and rotatably mounted in the housing. In one embodiment, for example, a first flap is arranged in the first cover and a second flap is arranged in the second cover. In another embodiment, exactly one flap is provided, for example, centrally in the area of ​​the spacer.

[0020] Preferably, the flap is made of weather- and UV-resistant PVC or another polymer and / or is transparent or translucent, in particular so that the animal can see through it. Preferably, the flap is scratch-resistant.

[0021] The flap's locking mechanism is specifically designed to hold the flap in a predetermined position, closing the opening to and / or from the premises. For this purpose, the locking mechanism can, for example, comprise a mechanical, electrical, or electromechanical mechanism, preferably controlled electronically. The electronics themselves can calculate corresponding control commands from sensor data, receive them via a push button attached to the housing, or via a corresponding app. Preferably, the push button is located on the second cover, i.e., the cover facing inwards.

[0022] The locking mechanism can therefore be controlled automatically by the electronics and corresponding sensors, as well as manually by the user, for example by pressing a button or via an app.

[0023] The locking mechanism can be engaged and disengaged electronically or manually by the user, for example, via a push button or an app. For instance, the user may have locked the flap using the push button, preventing any animal from entering the room. If the user's pet then approaches the flap from outside, the electronic system uses a camera to identify the pet and unlocks the flap, allowing the pet to enter. The flap is then relocked electronically.

[0024] Preferably, the locking mechanism is designed as an electromechanical locking mechanism, in particular in the form of a 4-way locking mechanism.

[0025] The electronics, for example, consist of a computing unit and a multitude of interfaces and include at least one sensor which is configured to perform one of the functions described a) to d) herein, in particular animal detection, prey detection, health detection and / or foreign animal detection.

[0026] Health detection serves primarily to assess the health and / or well-being of the animal, for example, based on facial and / or movement recognition. For instance, certain characteristics of the animal, such as the distance between the eyes, ear position, or gait, are analyzed to evaluate its health and / or well-being.

[0027] Preferably, the electronics have at least one connection to a push button with which the locking of the flap can be actuated, an interface to the sensor and optionally further interfaces if further sensors are present, as well as further interfaces for example for an app or a database described herein.

[0028] Preferably, the electronics comprise at least two sensors to perform the functions described in a) to d) herein.

[0029] Preferably, the electronics are arranged within the frame, in particular in such a way that the electronics are protected from dust and water.

[0030] The sensor(s) can be of any design, provided they are suitable for performing one of the functions a) to d). For example, the sensor could be a camera, such as a photo or video camera, or a TOF (time-of-flight) sensor, a PMD (photonic mixing device) sensor, or the like.

[0031] Preferably, the sensor(s) are configured as a camera, in particular a digital camera. The camera is set up to capture individual images and / or videos. Where images are mentioned herein, these are individual images and / or frames from videos.

[0032] Optionally, infrared lighting can also be provided to ensure suitable night photography. It is specifically recommended that the infrared lighting only be activated at dusk and / or in darkness.

[0033] Preferably, the electronics have two cameras. A first camera, preferably arranged above the flap, and a second camera, preferably arranged below the flap.

[0034] Preferably, the first camera is arranged in the first cover and the second camera in the second cover, i.e., the cover that is arranged inside, with both cameras facing outwards to perform one of the functions described a) to d) herein.

[0035] Preferably, the camera(s) are subjected to image processing after the fact, thereby improving or optimizing image quality. This image processing can be performed either by the electronics of the pet door (edge) or externally (remotely), for example via a cloud service.

[0036] In the event that the image quality is too poor even after processing, i.e., too blurry, overexposed, or the like, it is suggested to create a new image using the camera.

[0037] The first camera is preferably positioned centrally above the flap and in the first cover, i.e., the cover that faces outwards.

[0038] The first camera is directed outwards in particular to perform one of the functions a) to d) outside the premises.

[0039] By positioning the first camera above the flap, it is particularly well-suited to capturing the animal's face. The first camera therefore essentially records the animal from above.

[0040] Preferably, the first camera has a wide-angle lens and is designed to take pictures of an animal both during the day and at night, especially regardless of weather conditions and / or twilight.

[0041] The first camera is also ideally suited for taking infrared images of an animal at night or at dusk. This can be achieved, for example, by the camera not having an infrared filter. The first camera is therefore optimized for night vision and specifically designed for capturing infrared radiation. For this purpose, the camera may, for instance, have an optical filter that is transparent to infrared light, enabling the effective capture and processing of infrared radiation.

[0042] Alternatively or additionally, the camera can be equipped with a highly sensitive image sensor that is specifically optimized for capturing images in low light conditions and in the near-infrared range.

[0043] The second camera is preferably positioned centrally below the flap and in the second cover, i.e., the cover facing inwards. The second camera is specifically directed outwards to perform one of the functions a) to d) outside the premises.

[0044] The positioning of the second camera, particularly below the flap, makes it especially well-suited to capturing the animal's mouth and its prey. Essentially, the second camera records the animal from below.

[0045] If the first and second cameras are positioned offset from each other, such an arrangement also allows for a perspective shot of the animal, which can be used, for example, to recognize the animal's facial features.

[0046] It is particularly advantageous if the second camera is positioned lower in the room than the first camera, especially so that when the animal approaches the flap from the outside, the second camera is further away from the animal than the first camera.

[0047] Preferably, the second camera has a wide-angle lens and is designed to capture images of an animal during the day and / or at night. Specifically, this camera is also equipped to take infrared images of an animal. This can be achieved, for example, by not having an infrared filter. The second camera is therefore optimized for night vision and specifically designed to detect infrared radiation. For this purpose, it can, for instance, have an optical filter that is transparent to infrared light, enabling the effective detection and processing of infrared radiation.

[0048] Alternatively or additionally, the camera can be equipped with a highly sensitive image sensor that is specifically optimized for capturing images in low light conditions and in the near-infrared range.

[0049] The use of cameras allows access based solely on the animal's appearance. This eliminates the need for the familiar RFID-chip collar, and the animal can still enter the premises even if it has lost its collar, for example, during a fight with another animal.

[0050] Preferably, the door, in particular the animal flap, also has other elements, such as a rubber seal for the housing, a brush seal for the flap, a power and / or battery connection for the electronics, a mounting adapter for the hole cover, cover glasses, preferably made of plastic, for infrared light from the cameras and / or speakers on PCB.

[0051] Alternatively or additionally, infrared lighting, for example in the form of infrared LEDs, is arranged on the housing, especially to increase the image quality for the first and / or second camera.

[0052] Alternatively or additionally, the animal flap or housing has a loudspeaker, buzzer or the like, in particular to give acoustic feedback to the animal or the user.

[0053] Preferably, the electronics are powered by a battery and / or a rechargeable battery and / or a power connection, for example an alternating current and / or direct current connection.

[0054] Preferably, the electronics include, for example, a microcontroller or a processor configured to execute a KL algorithm, a corresponding AI algorithm, a working memory configured to process images, non-volatile memory for an operating system and / or the storage of biometric data and / or for a neural network, and a power supply, for example in the form of a cable or a battery.

[0055] Alternatively or additionally, the electronics have a WLAN interface, a WLAN module or the like to configure the flap (open, closed) using an app or to update the software of the electronics.

[0056] Preferably, LEDs are also provided, particularly for emitting warning and / or indicator signals. In a particularly preferred embodiment, infrared LEDs are also provided, for example, on both sides of the first and / or second camera, to improve image quality for twilight and / or night photography. Preferably, the LEDs are located behind covers.

[0057] Preferably, a control panel is also provided, particularly on the second cover in an upper area. The control panel includes, for example, several push buttons with which the user can activate certain functions, such as locking the flap and / or animal detection and / or prey detection and / or another function of the animal flap or electronics.

[0058] Preferably, the door also has a motion sensor configured to activate the first sensor.

[0059] Preferably, the motion sensor is also configured to activate other sensors, such as the first and second cameras described herein.

[0060] The use of the motion sensor allows the electronics to remain in a sleep mode (standby) until the motion sensor detects movement and then activates certain and / or all functions of the electronics.

[0061] The motion sensor therefore ensures, in particular, that the energy consumption of the electronics is kept as low as possible.

[0062] Preferably, the motion sensor is designed as a passive infrared motion sensor, in particular comprising one or more pyroelectric sensors, a Fresnel lens for focusing the infrared radiation and corresponding signal processing.

[0063] Preferably, the electronics are configured to lock and / or unlock the flap based on one of the functions described a) to d) herein and / or to output a signal or information about it, for example via an app to a user or to a cloud.

[0064] For example, the electronics recognize the animal and then unlock the flap so the animal can enter the premises. Alternatively, the electronics may recognize that the animal has prey in its mouth and keep the flap locked.

[0065] Preferably, animal detection is carried out using and / or a) artificial intelligence or b) a neural network.

[0066] Preferably, the housing includes a first cover that incorporates the first sensor for performing animal detection.

[0067] The first sensor is preferably designed as a camera and is located centrally above the flap in the first cover, i.e., the cover that faces outwards.

[0068] The first sensor enables the electronics to perform animal recognition, for example by creating a digital image of the animal and subsequently evaluating its corresponding biometric data. If the biometric data of the image of the animal in front of the flap matches the user's stored biometric data for their animal, the flap is unlocked.

[0069] Alternatively, animal detection can also be carried out by another or a second camera, which is preferably located centrally below the flap in one or the second cover.

[0070] Animal recognition can be performed by the electronics themselves, i.e., on device, or by other electronics, i.e., remotely.

[0071] Preferably, animal identification is performed on-site (edge) using biometric data; that is, the animal's biometric data is captured by the camera and compared with previously stored data. If the comparison is successful, the flap is unlocked. If the comparison is unsuccessful, the flap remains closed.

[0072] Preferably, the housing includes a second cover which has a second sensor to perform prey detection, for example by generating a digital recording of the animal and subsequent evaluation using object recognition, which is based, for example, on a neural network.

[0073] The second sensor is preferably designed as a camera and is located centrally below the flap in the second cover, i.e., the cover that faces inwards.

[0074] Prey detection is preferably carried out using electronics (edge), especially to identify the animal's prey as quickly as possible.

[0075] In one embodiment, prey detection serves only to identify whether the user's animal is carrying prey, i.e., simple prey detection. In another embodiment, prey classification is also performed – it determines not only "if" but also "what" the animal is carrying.

[0076] Prey detection is preferably carried out by means of and / or using a) artificial intelligence or b) a neural network.

[0077] It is therefore specifically proposed that a camera be used to take a picture of the animal and that this picture be analyzed using artificial intelligence or a neural network. This can be done, for example, using so-called feature extraction. If the quality of the picture is not particularly good, it is further proposed to optimize the image quality using software or similar methods.

[0078] Preferably the housing comprises a first cover and a second cover, wherein the first cover has the first sensor and the second cover has a second sensor, in particular to perform health detection.

[0079] It is therefore specifically proposed here that health detection be carried out using at least two sensors. Preferably, the sensors are designed as cameras and enable perspective recording. Alternatively, health detection can also be carried out with only one camera that is configured to take perspective recordings.

[0080] Health assessment is preferably performed remotely, for example on a server or in the cloud. Furthermore, it is suggested that image series be used for health assessment; that is, multiple images from different times, for example over several days, are used to evaluate the animal's health status.

[0081] To determine an animal's state of health, various characteristics can be used, such as facial features, coat color, ear position, eye position, and eye cloudiness. In particular, facial features, ear position, and eye cloudiness can be used to detect signs of pain or suffering.

[0082] Preferably, health detection is carried out using pain detection based on object tracking and / or artificial intelligence and / or deep learning and / or a database.

[0083] Health assessment is therefore primarily based on pain detection, which is mainly AI-based. Alternatively and / or additionally, health assessment relies on so-called "feline grimace scale" (FGS) indicators.

[0084] According to the invention, a computer program product is further proposed, in particular for a door, as described herein.

[0085] The computer program product includes, for example, commands which, when executed on a computer, cause it to perform animal detection and / or health detection and / or prey detection and / or foreign animal detection for a door described herein.

[0086] Alternatively and / or additionally, the computer program product includes commands which, when executed on a computer, cause it to send and / or receive a push notification, send and / or receive an alarm, monitor (track) the health of an animal, provide a selection of images taken by a camera of the door described herein, collect statistics on the health of the animal, open and / or close the flap, and monitor or query the status (open / closed) of the flap.

[0087] According to the invention, a database, in particular a decentralized and / or AI-based database, is further proposed which is set up to provide data for a computer program product as described herein and / or to exchange data with an animal flap described herein.

[0088] In particular, the database is run as a cloud and / or set up to edit images, process images, process image sequences, execute AI algorithms, for example for health and / or pain detection, store and / or process images from cameras or from animal detection and / or prey detection and / or health detection and / or foreign animal detection.

[0089] Preferably, the data in the database as well as the communication with the database, for example via an app, should be encrypted.

[0090] Preferably, the database is also set up so that authorized third parties can access the database, the data, and the algorithms, such as verified veterinarians or verified veterinary medical systems.

[0091] Preferably, the AI ​​algorithms on the database can be trained externally and / or updated.

[0092] An interface is a part of an electrical system that serves for communication. The term originates from the natural sciences and refers to the physical phase boundary between two states of a medium. It metaphorically describes the property of a system as a black box, of which only the "surface" is visible; communication is only possible via this surface. Two adjacent black boxes can only communicate with each other if their surfaces "match." The word also implies an "intermediate layer": for the two boxes involved, it is irrelevant how the other internally processes the messages and how the responses are generated. The description of the boundary is part of the boundary itself, and the black boxes only need to know the side facing them to ensure communication. This corresponds to the Latin etymology of the word, inter "between" and facies "appearance," "form," from the English word face.

[0093] When analyzing any given "system" as a whole, one would "dissect" this system into subsystems. The points of contact or connection between these subsystems (through which communication takes place) then represent the interfaces. Using these interfaces, the subsystems can be reassembled into a larger whole. They then serve as seams.

[0094] An application programming interface (API), also known as an application programming interface, is a part of a software system that allows other programs to connect to it. Unlike a binary interface (ABI), an API defines only the program connection at the source code level. Providing such an interface typically includes detailed documentation of the interface functions and their parameters, either in print or as an electronic document.

[0095] Besides accessing databases or hardware such as hard drives or graphics cards, a programming interface can also enable or simplify the creation of graphical user interface components. For example, the Windows Application Programming Interface (WAPI) of the Windows operating system allows external companies to develop software for this operating system.

[0096] Nowadays, many online services also provide programming interfaces; these are then called web services. In a broader sense, the interface of any library is referred to as a programming interface. This type of functional programming interface should be distinguished from the many other interfaces used in programming—for example, the parameters that are agreed upon and passed when calling subroutines.

[0097] Artificial intelligence (AI) is a subfield of computer science that deals with the automation of intelligent behavior and machine learning. The term is difficult to define, as there is already a lack of a precise definition of intelligence itself. One attempt at defining intelligence is that it is the property that enables a being to act appropriately and proactively in its environment; this includes the ability to perceive environmental data, i.e., to have sensory impressions and react to them, to receive, process, and store information as knowledge, to understand and generate language, to solve problems, and to achieve goals. Practical successes of AI are quickly integrated into application areas and then no longer fall under the umbrella of AI.

[0098] In this context, a neural network refers specifically to an artificial neural network. Artificial neural networks, also known as ANNs, are networks of artificial neurons inspired by the networks formed by biological neurons in the brain. An ANN is formed by interconnected artificial neurons, typically organized in layers. ANNs are used in machine learning. They enable computers to solve problems that are too complex to be described with rules, but for which there is a wealth of data that can serve as examples of the desired solution. ANNs form the basis for deep learning, which has allowed for significant advances in the analysis of large datasets since 2006. Successful applications of deep learning include image recognition and speech recognition.KNNs are the subject of research in both machine learning, a subfield of artificial intelligence, and interdisciplinary neuroinformatics. Replicating a biological neural network of neurons is more the domain of computational neuroscience.

[0099] To improve camera image quality, image editing can be performed after the camera has taken the picture. Image editing involves modifying photos, negatives, slides, or digital images. It differs from image processing, which involves manipulating the content of images. Image editing is often used to correct errors that can occur during photography or other image capture processes. These include over- and underexposure, blurriness, low contrast, image noise, red-eye, and converging lines. These errors often make images appear too dark, too bright, too blurry, or otherwise flawed. The causes can include technical problems or poor quality of the recording equipment (digital camera, lens, scanner), incorrect operation, unfavorable working conditions, or inadequate source material.The two images on the right illustrate some image editing possibilities: The top image appears overexposed, has a color cast, the text is blurry, the object shows a light reflection at the top and is off-center. The bottom, corrected, and now color-corrected image, on the other hand, looks much clearer and sharper. This is because the subject is emphasized, as it is larger, corrected for distortion, and centered in the frame; the aspect ratio has also been slightly adjusted.

[0100] Object recognition is a subfield of image processing, or computer vision, where the goal is to identify individual objects within images. An image is divided into regions that form meaningful units, which are then further analyzed for specific features to assign the image region to a class of objects. Preliminary object recognition usually follows this pattern: Divide an image into smaller, fixed-sized sections (windows) and then apply a classification algorithm to each window. While it is relatively easy for us humans to assign individual objects, such as a poodle or a German Shepherd, to an abstract category—in this case, the category "dog"—it is extremely difficult to teach a computer to do this. This task becomes increasingly challenging as more classes of objects need to be identified. Therefore, a specific algorithm is typically applied to the image, which, for example,can only recognize faces.

[0101] The present invention is explained in more detail below with reference to the accompanying figures. Fig. Figure 1 shows an animal flap in one embodiment in one view. Fig. Figure 2 shows a first view of a cover for an animal flap. Fig. Figure 3 shows an animal flap in a third view. Fig. Figure 4 shows an animal flap in one embodiment in a further view. Fig. 5 shows animal detection. Fig. Figure 6 shows prey detection. Fig. 7 indicates a health detection. Fig. Figure 8 shows the process of animal detection. Fig. Figure 9 shows the process of prey detection. Fig. Figure 10 shows the process of a health screening.

[0102] Fig. Figure 1 shows an animal flap 1000 in one embodiment.

[0103] The animal flap 1000 includes a first cover 1100, an optional spacer 1200, a second cover 1300 and a flap 1400.

[0104] The first cover 1100, the spacer 1200 and the second cover 1300 together form the housing.

[0105] In the middle of the housing is an opening which is covered by the flap 1400.

[0106] The flap 1400 is pivotably mounted in the housing by means of two pins arranged at the upper end of the flap, in particular so that an animal, preferably a cat, can pass through the opening if the flap is unlocked.

[0107] Preferably, the second cover 1300 has a control panel 1350 with which the user can control the locking of the flap 1400.

[0108] Fig. Figure 2 shows a first cover 1100 of an animal flap 1000, in particular as in Fig. 1 shown.

[0109] The first cover 1100 is essentially designed like a square frame with rounded corners and has an opening in the middle through which an animal, especially a cat, can pass.

[0110] Within the first cover 1100, in particular in the middle of the sides, mounting openings 1110 are provided, by means of which the first cover 1100 and the second cover 1300 can be screwed to the housing around an opening in a wall, door or the like.

[0111] Furthermore, the first cover 1100 has a first camera 1510 above its opening (in the installed state above the flap 1400), by means of which the functions described herein a) to d) can be carried out.

[0112] In addition to the camera 1510, there is also an aperture 1512 arranged to the right and left of it, behind which an LED is located, for example to give warning signals and / or emit infrared light.

[0113] Fig. Figure 3 shows a second cover 1300 of an animal flap 1000, in particular as in Fig. 1 shown.

[0114] The second cover 1300 is essentially designed like a square frame with rounded corners and has an opening in the middle through which an animal, especially a cat, can pass.

[0115] Within the second cover 1300, particularly in the center of the sides, mounting openings 1310 are provided, which serve as complementary mounting openings to the mounting opening 1110, as shown in Fig. 2 shown, are designed to screw the second cover 1300 to the first cover 1100 to the housing.

[0116] Furthermore, the second cover 1300 has a second camera 1520 below its opening (in the installed state below the flap 1400), by means of which the functions described a) to d) herein can be carried out.

[0117] In addition to the camera 1520, there is also an aperture 1522 arranged to the right and left of it, behind which an LED is located, for example to give warning signals and / or emit infrared light.

[0118] The second cover 1300 also includes a spacer 1200, which is an integral part of the second cover. Alternatively, the spacer 1200 can also be an integral part of the first cover 1100 or a separate component.

[0119] Fig. Figure 4 shows an animal flap in one embodiment, in particular when the first cover 1100, as in Fig. 2 shown, and the second cover 1300, as in Fig. 3 shown, which are joined together to form the housing.

[0120] Both the first camera 1510, which is housed in the first cover 1100, and the second camera 1520, which is housed in the second cover 1300, have the same recording direction, namely outwards, i.e. in the direction of the first cover 1100, which is located outside the premises.

[0121] The first camera 1510 and the second camera 1520 are positioned offset from each other in the recording direction, specifically such that the upper camera 1510 is further forward in the recording direction than the lower camera 1520. This results in the second camera 1520 being further away from the animal than the first camera 1510. Consequently, the second camera 1520 has a longer recording time, which can be used to process the data from the second camera 1520 for more complex calculations and / or for remote processing, for example, on a server.

[0122] Fig. Figure 5 shows animal recognition, in particular using the example of a cat, via object recognition.

[0123] Animal recognition is carried out, for example, using the first camera. For this purpose, the first camera 1510 generates an image of the animal, for example, a cat 2000 standing in front of the cat flap.

[0124] The cat is then identified using object recognition. If it is the user's cat, the lock opens. If it is a strange cat or another animal, the flap remains closed.

[0125] Object recognition is a subfield of image processing, or computer vision, where the goal is to identify individual objects in images. An image is divided into regions or pixels that form meaningful units. These units are then further analyzed for specific features in order to assign the image region or pixels to a class of objects.

[0126] Animal recognition is carried out, for example, by the electronics and the first camera.

[0127] In this case, for example, the interpupillary distance of 2100, defined by pixels 14 and 17, is used to identify the animal. However, other and / or multiple characteristics can also be used to identify the animal.

[0128] Fig. Figure 6 shows prey detection, in particular using the example of a cat in 2000, by means of object recognition.

[0129] Although individual pixels 1,2 of the cat 2000 can be recognized, the image region 2200(B) in which, for example, the pixels of the mouth or the mouth characteristics would have to be identified, is obscured.

[0130] From this, it is deduced that the animal has something in its mouth, which is most likely prey 7000, and the flap remains locked accordingly, and a warning signal is issued to the animal via LEDs.

[0131] Fig. Figure 7 shows a health detection process, particularly using the example of a cat, via object recognition.

[0132] Health detection is performed, for example, using the first and second cameras. The first camera, 1510, takes a picture of the animal, for example, a cat, 2000, standing in front of the cat flap. The second camera, 1520, also takes a picture simultaneously.

[0133] The images thus generated are then superimposed using software, so that a perspective evaluation of the facial features can be carried out based on image points 1, ..., 7, in particular based on facial features based on image points 1, ..., 7.

[0134] It is therefore specifically proposed that, in the context of health detection using object recognition, the facial features of the cat 2000 be analyzed.

[0135] The facial features recorded in this way can then be saved and / or compared with previously saved facial features. If the cat's facial features change over time, this can be used as an indication that the cat's health is changing, particularly deteriorating.

[0136] Fig. Figure 8 shows the process of animal detection 3000.

[0137] For animal detection, for example, the first camera 1510 and / or the second camera 1520 of the animal flap 1000 is used, especially as described in the Fig. Shown 1 to 4.

[0138] In the first step (3100), an image of the animal is taken using a camera, specifically the first camera. This can be done, for example, by activating the first camera and optionally an infrared light with a motion sensor, and then taking an image of the animal with the camera.

[0139] In the next step, this image is segmented 3200 times using object recognition, and then specific features are extracted from the image, such as those shown in the... Fig. 5 or Fig. 6 shown.

[0140] Subsequently, the extracted characteristics are classified in a further step 3300, for example using a biometric database in which the data of the user's animal is stored.

[0141] In the next step, a decision algorithm (3400) is used to determine whether the animal belongs to the user or is someone else's. This can be done, for example, by comparing the extracted characteristics with a database containing the relevant characteristics of the user's animal, such as coat color, eye spacing, or similar data. Preferably, this process is performed by the electronics of the pet door itself (edge).

[0142] If the photographed animal belongs to the user, the flap opens ("open"). If the photographed animal belongs to someone else, the flap remains closed ("closed").

[0143] Additionally, the user can be informed about the process and / or the process can be saved, in particular this includes the image captured by the camera.

[0144] Optionally, a warning signal, such as a visual and / or acoustic signal, can even be issued, especially if it is not the user's animal, i.e., a stranger's animal.

[0145] The animal recognition system described herein can also be used to locate missing animals, for example, by comparing the images captured by the animal recognition system with a database of missing animals. It is therefore also suggested that the door be used for the detection of foreign animals or missing animals, and that any found animals be reported accordingly.

[0146] Fig. Figure 9 shows the process of prey detection 4000.

[0147] Prey detection 4000 is preferred over animal detection 3000, as in Fig. As shown in section 7, this process is subsequent. This means, in particular, that prey recognition is only carried out once the user's animal has been identified ("animal=yes").

[0148] In a first step 4100, an image of the animal is provided; for this purpose, for example, the image from animal recognition 3100 can be used and / or a new image can be taken using the first and / or second camera.

[0149] In the next step, this image is segmented using object recognition (4200), and then specific features are extracted from the image, such as those shown in the... Fig. 5 or Fig. Figure 6 shows that prey recognition focuses particularly on the segment of the image that relates to the animal's mouth.

[0150] Subsequently, the extracted features are classified in a next step (4300) using a neural network for prey. This neural network was trained, for example, using extensive image data of prey animals and the "ground truth" technique. Preferably, this process is performed by the electronics of the animal flap itself (edge).

[0151] In the next step, 4400, a decision algorithm is used to assess whether the animal is carrying prey or not.

[0152] If the animal is not carrying prey, the flap is opened ("open"). If the animal is carrying prey, the flap remains closed ("closed").

[0153] Optionally, a warning signal can be issued to the animal if it is carrying prey, for example a visual and / or acoustic signal.

[0154] Additionally, the user can be informed about the process and / or the process can be saved, in particular this also includes the image captured by the camera.

[0155] Fig. Figure 10 shows the process of a health screening 5000.

[0156] The health detection 5000 is preferably performed independently of the animal and / or prey detection. However, the health detection is only carried out for the user's animal.

[0157] The health detection 5000 is preferably performed after the animal detection 3000. This means, in particular, that prey detection is only carried out once the user's animal has been identified ("animal=yes").

[0158] Furthermore, the health detection system 5000 is preferably based on perspective images using two cameras, as is particularly evident in... Fig. 7 shown.

[0159] In a first step 5100, an image of the animal is provided; for this purpose, for example, the image from animal recognition 3100 can be used and / or a new image can be taken using the first and second cameras, especially in the form of a perspective view.

[0160] In the next step, this image is segmented 5200 times using object recognition, and then specific features are extracted from the image, such as in the Fig. 6 shown.

[0161] Health assessment relies primarily on the so-called "feline grimace scale" (FGS) indicator. This means that specific features are extracted, which can then be used to run an FGS algorithm, such as ear position, eye area, jaw tension, whisker changes, or similar characteristics. Alternatively or additionally, another algorithm can be used, such as a landmark-based approach that focuses on specific landmarks.

[0162] Subsequently, the extracted features are classified in a next step using a neural network for prey based on a deep learning model. This neural network was trained, for example, using extensive image data of animals and the "ground truth" technique. Features crucial for the FGS algorithm, such as ear position, eye area, mouth tension, whisker changes, and the like, were labeled accordingly.

[0163] In the next step 5400, the process is then repeated and / or compared with already generated data, in particular so that the health detection is based on image series of the animal and a final assessment, a health assessment, can be carried out.

[0164] The assessment can be based, for example, on a health factor and / or stored data and / or an analysis of changes over time. For example, it may be observed that the FGS indicators deteriorate over time, indicating poor health.

[0165] Other visual health indicators can also be used for assessment, such as coat condition, pupil dilation, tongue position, tail posture, or the like.

[0166] These image series and / or health data may have been generated and / or stored over several days, weeks, or months. Step 5400 is preferably performed using an external database 6000 or in the cloud (remotely).

[0167] If the health monitoring system detects a deterioration in the animal's health, a corresponding alarm is issued, for example as a push notification to a corresponding app.

[0168] The health monitoring system proposed here offers continuous, and notably non-invasive, monitoring of the animal. The animal's health can therefore be assessed without stressing it, as would be the case, for example, during a visit to the veterinarian.

[0169] The data obtained through health detection can also be used to assist the veterinarian in assessing the animal and / or supporting the veterinarian's treatment decisions.

[0170] Furthermore, health detection offers a time- and cost-effective alternative for ongoing health assessment of the animal.

[0171] Furthermore, diseases in animals can be detected at an early stage using neural networks or AI. Reference symbol list 1, 2, ... pixels 1000 pet doors, especially cat doors 1100 first cover, especially for the outside 1110 Mounting opening 1200 spacers 1300 second cover, especially for the inside 1310 Mounting opening 1350 Control panel 1400 flap 1500 Electronics 1510 first camera 1512 Aperture including LED 1520 second camera 1522 Cover including LED 1530 network connection 2000 animals, especially cats 2100 characteristics, especially of a cat 2200 facial features, especially of a cat 2200(B) Area of ​​facial features 3000 animal recognition 4000 prey detection 5000 health detection 6000 Cloud 7000 loot

Claims

[1] Door (1000) for an animal, preferably a pet, such as cats, dogs or the like, in particular an animal flap, preferably a cat flap, comprising: - a case (1100, 1200, 1300), - a flap (1400) with a locking mechanism, and - an electronics (1500) with a first sensor, preferably a camera, which is configured to perform at least one of the following functions, especially during the day and / or night: a) animal recognition to identify the animal; and / or b) prey recognition, in order to identify prey of the animal; and / or c) a health assessment to determine the health and / or well-being of the animal; and / or d) foreign animal detection to identify another animal. [2] Door (1000) according to claim 1, wherein - has a motion sensor configured to activate the first sensor. [3] Door (1000) according to claim 1 or 2, further comprising: - the electronics are set up to lock and / or unlock the flap and / or output a signal and / or information based on one of the functions a) to d). [4] Door (1000) according to one of the preceding claims, wherein - the housing includes a first cover (1300) which has the first sensor to perform animal detection. [5] Door (1000) according to one of the preceding claims, wherein - the housing includes a second cover (1300) which has a second sensor to perform prey detection. [6] Door (1000) according to claim 5, wherein - Prey detection is carried out using: a) an artificial intelligence; and / or b) a neural network. [7] Door (1000) according to one of the preceding claims, wherein - the housing comprises a first cover and a second cover, the first cover having the first sensor and the second cover having a second sensor to perform health detection. [8] Door (1000) according to claim 7, wherein - Health detection is carried out using pain detection based on object tracking and / or artificial intelligence and / or deep learning and / or a database. [9] Computer program product for a door, comprising commands which, when executed on a computer, cause the computer to perform animal detection and / or health detection and / or prey detection and / or foreign animal detection for a door according to any one of claims 1 to 8. [10] Database, in particular a decentralized and / or AI-based database, which is set up to provide data for a computer program product according to claim 9.

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