Animal meal evaluation system, animal meal evaluation server, and animal meal evaluation method

Abstract

To improve a meal habit of an animal.SOLUTION: An animal meal evaluation system comprises: an acquisition unit for acquiring ecological information of an animal; an analysis unit for analyzing a tendency of a meal of the animal based on biological information; a detection unit for detecting a change in the tendency; and a notification unit for giving a notification of a result of the detection. In particular, the system analyzes a change in a time zone of the meal, a meal continuation time taken for a meal of one time, the frequency of meals in a predetermined period, and a meal-related behavior made during a meal or / and after the meal, and gives a notification of the change. A constitution like this allows health control and meal control of the animal to be performed efficiently and effectively.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to an animal diet evaluation system, an animal diet evaluation server, and an animal diet evaluation method.

Background Art

[0002] Conventionally, a method has been proposed in which a pet owner (for example, a cat owner) grasps the behavior of the pet by receiving behavior data for a predetermined period generated based on measurement data received by a server from a sensor attached to the pet (for example, Patent Document 1 below).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, even if the above-mentioned pet owner can grasp the behavior of the above-mentioned pet based on the above-mentioned behavior data, the pet owner cannot grasp, for example, the emotions and psychology of the pet. In particular, accurately grasping the eating tendency of an animal and optimizing the diet content as needed are very important for maintaining the health of the animal. However, with the conventional method, it is difficult to analyze in detail the specific eating habits of individual animals, and there are limitations in individual health management.

[0005] Therefore, an object of the present invention is to improve the specific eating habits of animals.

Means for Solving the Problems

[0006] According to the present invention, an acquisition unit that acquires ecological information of an animal; an analysis unit that analyzes the eating tendency of the animal from the biological information; A detection unit that detects the change in the tendency; A notification unit that notifies the detection result; An animal diet evaluation system including these is obtained.

Advantages of the Invention

[0007] According to the present invention, an animal diet evaluation system capable of analyzing the specific eating habits of an animal in detail can be obtained.

[0008] In addition, in view of the fact that there is an increasing demand for technologies that accurately evaluate the diet tendency of animals in real time and utilize it for health management, this system particularly acquires the biological information of animals, analyzes the diet tendency from the information, detects and notifies changes. Thereby, the health management and diet management of animals can be carried out efficiently and effectively.

Brief Description of the Drawings

[0009]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Modes for Carrying Out the Invention

[0010] The content of the embodiment of the present invention will be listed and described. The present invention has the following configuration. [Item 1] An acquisition unit that acquires ecological information of an animal, An analysis unit that analyzes the eating tendency of the animal from the biological information, A detection unit that detects a change in the tendency, A notification unit that notifies the detection result, An animal diet evaluation system comprising the above. [Item 2] The animal diet evaluation system according to Item 1, wherein the detection unit detects a change in the time zone of the meal. Animal diet evaluation system. [Item 3] The animal diet evaluation system according to Item 1, wherein the analysis unit analyzes the meal continuation time required for each meal, and the detection unit detects a change in the meal continuation time. Animal diet evaluation system. [Item 4] The animal diet evaluation system according to Item 1, wherein the analysis unit analyzes the number of meals within a predetermined period, and the detection unit detects a change in the number of meals. Animal diet evaluation system. [Item 5] The animal diet evaluation system according to Item 1, wherein the analysis unit analyzes the meal-related behavior performed by the animal during or after at least one of the meals, and the detection unit detects a change in the meal-related behavior. Animal diet evaluation system. [Item 6] The animal diet evaluation system according to Item 1, wherein the notification unit notifies the detection result to at least one of the owner of the animal or a veterinarian. Animal diet evaluation system. [Item 7] The animal diet evaluation system according to any one of Items 1 to 6, wherein the analysis unit generates a diet plan optimized for an individual animal based on the eating tendency of the animal. Animal diet evaluation system [Item 8] The animal diet evaluation system according to Item 7, wherein the diet plan includes information on the ingredients of the animal's feed Animal diet evaluation system [Item 9] An acquisition unit that acquires ecological information of an animal; An analysis unit that analyzes the dietary tendency of the animal from the biological information; A detection unit that detects a change in the tendency; A notification unit that notifies the detection result; An animal diet evaluation server comprising the same [Item 10] A step of acquiring ecological information of an animal; A step of analyzing the dietary tendency of the animal from the biological information; A step of detecting a change in the tendency; A step of notifying the detection result; An animal diet evaluation method comprising the same

[0011] <Details of Embodiment> Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[0012] <Embodiment 1> <Overview> The present invention relates to an animal diet evaluation system that evaluates and manages the health status and dietary tendency of an animal. In particular, it detects and estimates evaluations of food (subjective tendencies such as eating habits, likes and dislikes, and dislikes). This system includes an acquisition unit that acquires ecological information of an animal, an analysis unit that analyzes the dietary tendency of the animal from the acquired biological information, a detection unit that detects changes in the dietary tendency, and a notification unit that notifies the detection result.

[0013] In the acquisition unit, biological information such as the body temperature, heart rate, activity level, and weight of the animal is collected, and this information is transmitted to the analysis unit as the basis for analyzing the eating tendency. In the analysis unit, based on these data, the eating tendency of the animal, such as the amount of food, type of food, and frequency of meals, is analyzed in detail, providing insights into the animal's health status and nutritional situation. The detection unit, based on the analysis results, detects abnormalities and important changes in the eating tendency and passes this information to the notification unit. The notification unit notifies the detected results to relevant parties such as the owner and veterinarian, prompting necessary responses and interventions.

[0014] This system aims to improve the health and welfare of animals and provides useful information to owners and veterinarians, especially in diet management and health monitoring. Also, through the cooperation of each part, it becomes possible to respond quickly and effectively to changes in the animal's health status.

[0015] <Configuration> Figure 1 is an example of the hardware configuration of this system. This system includes a server 1 that provides services, and a weight measurement means 8, a communication terminal 2, and a user terminal 3 that are connected to the server 1 via a network such as the Internet. Also, the server 1 is connected to an analysis server 4 via a network. In Figure 1, for the sake of convenience of explanation, one weight measurement means 8, communication terminal 2, user terminal 3, and analysis server 4 are shown respectively, but a plurality of terminals of each can be connected to the network of this system.

[0016] The server 1 can provide services to the user terminal 3 via an application. The user terminal 3 can download the application from the server 1 or another server, execute this application, and access the server 1 via web page browsing software such as a browser, enabling the transmission and reception of information with the server 1 and also receiving services.

[0017] The communication terminal 2 can acquire weight data and motion measurement data by performing short-range wireless communication with the weight measurement means 8 and the acceleration sensor 5 attached to an animal, for example, a cat 6. More specifically, first, as shown in FIG. 3, a collar-shaped (or pendant-shaped) wearable device is attached to the cat 6. The wearable device incorporates an acceleration sensor and / or a temperature sensor. The weight measurement means 8 and the sensor 5 transmit data to a receiving device 7 installed in the same house through short-range wireless communication such as BLUETOOTH (registered trademark) LOW ENERGY (BLE). The receiving device 7 transfers the data to the communication terminal 2 such as a router, and the communication terminal 2 transmits the data to the server 1 via a network. Note that the weight measurement means 8 and the sensor 5 may directly transmit the data to the user terminal 3 through short-range wireless communication such as BLUETOOTH (registered trademark) LOW ENERGY (BLE). Here, as an example, the receiving device 7 can be equipped with a Linux (registered trademark)-based operating system and various sensors such as a temperature sensor for measuring the air temperature. However, it is of course also possible to use those without an operating system such as an embedded chipset, etc.

[0018] As shown in FIG. 2, the acceleration sensor 5 is a sensor that detects accelerations in three mutually orthogonal axial directions (x-axis, y-axis, z-axis directions) and is built into a collar worn on the cat's neck. As shown in FIG. 3, the front-rear direction of the cat is defined as the X direction, the left-right direction as the Y direction, and the up-down direction as the Z direction, and the collar is attached to the cat so that acceleration signals in each direction can be detected according to the cat's movement. The type of sensor is not limited to this, and any sensing device capable of acquiring information regarding the cat's movement such as a gyro sensor or a motion sensor can be adopted.

[0019] Returning to FIG. 1, the user terminal 3 may be a general-purpose computer such as a workstation or a personal computer, or may be a smartphone, a tablet, a mobile terminal, or other information terminals.

[0020] FIG. 3 is a functional block diagram of the server 1 according to the first embodiment of the present invention. Note that the illustrated configuration is an example, and other configurations may be adopted.

[0021] As shown in the figure, the server 1 is connected to a database (not shown) and constitutes a part of the system. The server 1 may be a general-purpose computer such as a workstation or a personal computer, or may be logically realized by cloud computing.

[0022] The server 1 includes at least a control unit 10, a memory 11, a storage 12, a transmission / reception unit 13, an input / output unit 14, etc., and these are electrically connected to each other through a bus 15.

[0023] The control unit 10 is an arithmetic device that controls the overall operation of the server 1, controls the transmission and reception of data between elements, and performs information processing necessary for the execution and authentication processing of applications. For example, the control unit 10 is a CPU (Central Processing Unit), and executes programs stored in the storage 12 and expanded in the memory 11 to perform each information processing.

[0024] The memory 11 includes a main memory composed of a volatile storage device such as a DRAM (Dynamic Random Access Memory), and an auxiliary memory composed of a non-volatile storage device such as a flash memory or an HDD (Hard Disc Drive). The memory 11 is used as a work area of the processor 10, and stores a BIOS (Basic Input / Output System) executed at the startup of the server 1 and various setting information.

[0025] The storage 12 stores various programs such as application programs. A database (not shown) storing data used for each process may be constructed in the storage 12.

[0026] The transceiver unit 13 connects the server 1 to the network. Note that the transceiver unit 13 may be provided with a short-range communication interface for Bluetooth (registered trademark) and BLE (Bluetooth Low Energy).

[0027] The input / output unit 14 is an information input device such as a keyboard and a mouse, and an output device such as a display.

[0028] The bus 15 is commonly connected to each of the above elements and transmits, for example, address signals, data signals, and various control signals.

[0029] FIG. 4 is a diagram showing an example of the software configuration of the server 1 of this system. The server 1 includes an acquisition unit 21, an analysis unit 21, a detection unit 23, and a notification unit 24.

[0030] <Acquisition Unit> The acquisition unit 21 has a function of acquiring ecological information of animals. The acquisition unit 21 includes sensors and devices for collecting biological data such as the body temperature, heart rate, and activity level of animals. These sensors can be directly attached to the body of the animal or installed in the living environment of the animal. For example, a collar-type sensor is used to monitor the heart rate and activity level of an animal, and the sensors installed in the sensor collect data such as the temperature and humidity of the environment.

[0031] The acquisition unit 21 according to the present embodiment may also include a camera or other visual sensors for recording the behavior patterns and eating behaviors of animals. These data are very important as basic information for analyzing the health status and eating tendencies of animals. In the health management of animals, these information can be used for optimizing the quality and quantity of food, and early detection of abnormal behaviors and health problems.

[0032] Furthermore, the acquisition unit 21 according to the present embodiment may be an animal weighing scale, which is used to periodically measure the weight of an animal and collect the data. Since changes in weight are an important indicator of an animal's health and nutritional status, this information is very valuable in analyzing the animal's dietary trends. Understanding whether an animal is maintaining a proper weight is extremely important in managing its health. Animal weighing scales are available in a variety of sizes and shapes, from those for pets kept at home to those for large animals used in zoos and farms. These weighing scales are selected according to the type and size of the animal and are designed to make it easy to measure the weight. Some advanced weighing scales may also have the function of automatically recording measurement data and transmitting the data via wireless communication.

[0033] <Analysis Department> The analysis unit 22 is responsible for analyzing the feeding habits of animals based on the collected ecological information. This part is important for processing the data obtained from the ecological information and providing insight into the feeding behavior and nutritional status of animals.

[0034] Specifically, the analysis unit 22 performs a comprehensive analysis of data such as the animal's weight, amount and type of food, activity level, body temperature, and heart rate. This analysis provides the information necessary to understand the animal's eating habits. For example, by analyzing the relationship between weight change and food amount, it is possible to evaluate whether the animal is taking in appropriate nutrition. In addition, by combining activity level data and food data, it is also possible to understand the animal's metabolic state and energy consumption pattern.

[0035] Additionally, the analysis unit 22 can utilize advanced data analysis techniques, such as machine learning algorithms, to perform more sophisticated analyses, which can detect subtle changes in an animal's dietary habits and identify deficiencies or overconsumption of certain nutrients, as described below, and can track changes in dietary habits over time and assess their impact on health status.

[0036] As dietary trends according to this embodiment, for example, information related to meals can be exemplified such as the amount of food intake, time zone, frequency, time during meals, actions during meals, actions after meals, and the like. These pieces of information may be analyzed based on the information obtained by the individual methods or combinations of the individual methods of the acquisition unit described above.

[0037] Such analysis can be performed by various methods. For example, by analyzing time-series data such as the weight, activity level, and food intake of an animal, changes in dietary trends may be captured. Furthermore, by analyzing the relationship between the pattern of weight gain or loss and the amount of food intake, it is also possible to evaluate whether the food intake is appropriate. In addition, by analyzing the relationship between biological information (biological indicators such as body temperature and heart rate) and food data, the impact of specific dietary patterns on the health of the animal can also be evaluated. For example, if there is a tendency for the heart rate to increase after a specific meal, it may be possible that the meal is causing stress.

[0038] <Detection unit> The detection unit 23 plays an important role in the animal diet evaluation system. This part has the function of detecting changes in the dietary trends of animals analyzed by the analysis unit and determining whether these changes deviate from specific criteria or patterns. Specifically, based on the normal range or established pattern regarding the dietary trends of animals, it identifies abnormal changes and trends that may affect health.

[0039] For example, when the amount of food intake of an animal suddenly decreases or an aversion to a specific food appears, the detection unit 23 detects this as an abnormal change and transmits information to the notification unit 24. This detection process enables early intervention in the health management of animals and is essential for preventing potential health problems.

[0040] The detection unit 23 evaluates these analysis results using algorithms and thresholds. This includes statistical methods, machine learning models, anomaly detection algorithms, and the like. These technologies are extremely effective for extracting meaningful patterns from large amounts of data and accurately identifying anomalies.

[0041] Furthermore, the detection unit 23 can also dynamically adjust the detection criteria according to the health status of the animal and changes in the environment. This enables more precise detection according to the characteristics and needs of individual animals, and plays an important role in protecting the welfare and health of animals.

[0042] The configuration of the detection unit will be described in more detail. The detection unit analyzes the animal's dietary records and related data to detect changes that occur during the meal time zone. This includes the meal time shifting to a different time zone than usual, the frequency of meals increasing or decreasing, or irregularities occurring in the meal rhythm. Since such changes may be due to changes in the animal's health status or stress level, or environmental factors, it is important for the detection unit to identify these changes.

[0043] Also, in the analysis unit, it may be possible to measure and analyze the time required for an animal to have one meal, that is, the meal duration. By analyzing this meal duration, the speed at which the animal eats and the pattern of eating behavior become clear. For example, it may be observed that the animal finishes the meal faster than usual, or conversely, takes longer to eat than usual. These behaviors may be indicators of the animal's health status, stress level, and even specific medical conditions. The detection unit detects the change based on the meal duration data obtained by the analysis unit. Changes in meal duration are important indicators that may affect the health of the animal. For example, if the meal duration is significantly shorter than usual, this may suggest a loss of appetite or digestive problems. Conversely, if the meal duration is abnormally long, it can also be inferred that there may be problems with chewing or ingestion.

[0044] In addition, the analysis unit may analyze the number of meals an animal has taken within a predetermined period. Through this analysis, the pattern and variation of the animal's meal frequency can be revealed, and insights into the animal's health status and behavioral habits can be obtained. For example, if the number of meals increases or decreases more than usual during a specific period, this may suggest a health problem or a change in environmental factors. The detection unit detects such changes based on the meal frequency data obtained by the analysis unit. An increase in the number of meals may be due to overeating, stress, or nutritional deficiency. On the other hand, a decrease in the number of meals may indicate loss of appetite or digestive problems. Since such changes in the number of meals have a significant impact on the animal's health status, detection and notification are very important in animal health management.

[0045] Furthermore, the analysis unit may also analyze in detail the specific behaviors exhibited by the animal during or after a meal. This meal-related behavior includes the speed of eating, the posture during the meal, the post-meal behavior pattern, etc. For example, behaviors such as finishing a meal in a hurry, being restless during the meal, or spending a long time in a specific place after the meal may be observed. These behaviors may suggest the animal's health status, stress level, digestive problems, etc. The detection unit detects such changes based on the meal-related behavior data obtained by the analysis unit. Changes in meal-related behavior are important indicators that affect the animal's health status. For example, if the behavior during the meal suddenly changes, this may be a sign of a health problem or environmental stress. Similarly, changes in the post-meal behavior pattern also provide important information related to the animal's health status.

[0046] The changes related to meals detected in this way are notified to the owner or veterinarian through the notification unit. This information is used to suggest the need for prompt intervention, environmental adjustment, and further diagnosis in animal health management and behavior monitoring. By detecting changes in meal times, it becomes possible to more meticulously support the well-being of animals and detect potential health problems at an early stage. With the addition of this function, the animal meal evaluation system of the present invention becomes a more comprehensive and effective tool in protecting the health and well-being of animals.

[0047] <Notification Unit> In the animal diet evaluation system, the notification unit 24 serves the function of transmitting the detected information to appropriate recipients. This part plays the role of notifying the owner, veterinarian, relevant care staff, etc. of the abnormalities and changes in the diet tendency of the animals identified by the detection unit 23.

[0048] The notification unit 24 makes notifications by utilizing various communication means. These include email, push notifications of the smartphone app, text messages, or alert displays on a dedicated web portal or dashboard. These communication means enable real-time information transmission and the ability to send notifications along with detailed data as needed.

[0049] The content of the notification includes the nature of the detected abnormality, details of the relevant data, and the degree of urgency, etc. For example, when a significant decrease in the animal's food intake is detected, the notification unit 24 can immediately convey that information to the owner and suggest the need for further consideration or a veterinarian's examination.

[0050] Also, the notification unit 24 can customize the notification method and frequency according to the user's settings. This enables flexible information provision according to the needs and situations of each user. A prompt and appropriate notification regarding the animal's health condition leads to early intervention and proper care, playing a crucial role in protecting the health and well-being of the animal.

[0051] <Data> Referring to FIG. 5, the data structure used in this system will be described. The data tables required for the animal diet evaluation system include a biological information table, a diet information table, a diet tendency analysis result table, and a detection result table.

[0052] The biological information table records biological information such as the body temperature, heart rate, activity level, and weight of an animal. Each record includes the animal's identification ID, the measurement date and time, and the measured values of various biological information. This table provides basic data that reflects the animal's health status and serves as the starting point for diet trend analysis.

[0053] The diet information table records details regarding the diet content, diet quantity, and frequency of an animal's meals. This table contains data such as the animal ID, meal date and time, diet content, diet quantity, and meal frequency. This data is essential for understanding the animal's diet trends and serves as the basis for detailed diet analysis by the analysis department.

[0054] The diet trend analysis result table is generated by the analysis department. This table records the analysis results of the animal's diet trends. It includes the animal ID, analysis date and time, evaluation results of the diet trend, relevant indicators, etc. This table provides insights into the animal's diet trends and serves as the basic data for the detection department to identify abnormalities and changes.

[0055] The detection result table is generated by the detection department. This table records abnormalities and changes in the animal's diet trends. Each record includes the animal ID, detected date and time, detection content, and importance of the detection. This table serves as the basis for the notification department to issue warnings and recommendations to the owner or veterinarian.

[0056] These tables play important roles in various parts of the system to continuously monitor the animal's health status and provide insights into diet management. Each table functions in cooperation to support the effective operation of the entire system.

[0057] <Flow of processing> As shown in Figures 6 and 7, the above processing can be performed in the following flow and sequence.

[0058] <Step of acquiring and transmitting biological information> The animal terminal (acquisition unit) acquires biological information such as the animal's body temperature, heart rate, activity level, and weight. These data are collected by devices such as sensors and weighing scales. The acquired biological information is transmitted to the server. In this process, the security of communication and the integrity of data are important, and appropriate encryption and data verification means are required.

[0059] <Diet trend analysis step> The server (analysis unit) analyzes the diet trend of the animal based on the received biological information. In the analysis, data such as the amount of food intake, type of food, and frequency of meals are also considered. Advanced algorithms and statistical methods are used in the analysis to gain insights into the animal's health and nutritional status. The quality of data and the accuracy of the analysis model are important at this stage.

[0060] <Detection step> The detection unit in the server uses the analysis results to detect abnormalities and changes in the diet trend. In this process, anomaly detection algorithms and threshold settings are important. Detected abnormalities include sudden changes in food intake and disruptions in the nutrient intake balance. Time series analysis and trend analysis of data are effective in enhancing the accuracy of detection.

[0061] <Notification step of detection results> The results from the detection unit are transmitted to the user terminal through the notification unit. This notification is directed to targeted individuals such as the owner or veterinarian. The forms of notification cover a wide range, including e-mails, app push notifications, SMS, etc., and can be customized according to the user's settings and situation. The speed and comprehensibility of the notification are important, and it is desirable to include detailed data and recommended countermeasures as necessary.

[0062] The "advanced algorithms and statistical methods" for analyzing the above-mentioned diet trend of animals include machine learning algorithms, time series analysis, clustering algorithms, principal component analysis (PCA), etc.

[0063] Machine learning algorithms include random forest, support vector machine (SVM), neural network, etc. These learn complex patterns from large amounts of data and are used for classifying and predicting dietary trends. Random forest is an ensemble of decision trees, SVM finds a boundary line to optimally divide data, and neural network has a structure mimicking the neurons in the human brain.

[0064] In time series analysis, ARIMA model, seasonal decomposition, trend analysis, etc. are important. These analyze the characteristics of time-dependent data and are useful for predicting future values. The ARIMA model is suitable for predicting non-stationary time series data, seasonal decomposition reveals the periodic fluctuations of data, and trend analysis captures the long-term trends of data.

[0065] Clustering algorithms include k-means method and hierarchical clustering. These classify data into natural groups. The k-means method divides data into k clusters, and hierarchical clustering creates a tree-structured cluster based on data similarity.

[0066] Principal component analysis (PCA) is used for dimensionality reduction of multivariate data. PCA captures the main trends of a dataset, reduces the number of dimensions of data while retaining important information. These algorithms and techniques are important for efficiently processing the complexity of data and extracting meaningful insights in the analysis of animals' dietary trends. The selection of an appropriate algorithm depends on the purpose of the analysis, the characteristics of the data, and the required accuracy. Utilizing advanced algorithms enables obtaining more accurate and reliable analysis results.

[0067] As described above, this system can deeply understand the dietary behavior and preferences of pets by collecting and analyzing various data related to pets' diets. Specifically, the acquisition part of the system collects data such as the amount of food a pet eats, the time required for a meal, the frequency of meals, and the behavior during and after meals, and transmits this information to the analysis part.

[0068] Based on this information, the analysis unit analyzes the pet's eating tendency and estimates the pet's preference or aversion to a specific food. For example, if changes such as a decrease in the amount of food eaten, a shortening of the meal time, or unstable behavior after eating are observed for a specific food, these suggest that the pet may not like that food.

[0069] The detection unit detects changes in diet-related data and identifies changes related to food preferences. For example, by detecting changes in eating behavior when a specific food is given or changes in the behavior pattern after eating, it is possible to estimate the pet's likes and dislikes for that food. Through the notification unit, such changes in eating tendency are notified to the owner or veterinarian.

[0070] With this information, the owner can optimize the pet's diet plan and select foods that suit the pet's preferences. Also, since food likes and dislikes are closely related to the pet's health status and nutritional intake, this information also contributes to the pet's health management and early detection of diseases. Therefore, the system of the present invention can greatly contribute to the improvement of the health and well-being of pets by estimating the pet's likes and dislikes for food.

[0071] <Embodiment 2> Using the above-described diet evaluation system, it may also be possible to generate an animal's food (pet food) and diet plan or make suggestions from a predetermined menu.

[0072] In this case, the acquisition unit of the system acquires biological information such as the pet's body temperature, heart rate, activity level, and weight. For this, sensors attached to the pet's collar or body, or sensors in the living space are used. Furthermore, information such as the pet's behavior pattern during eating and the amount of food eaten is also collected.

[0073] The acquired data is sent to the analysis unit, and the eating habits of the pet are analyzed. In this analysis, factors such as the frequency of meals, the amount of food, the behavior of the pet during meals, and the behavior after meals are considered. Additionally, a diet plan suitable for each individual pet is generated based on the pet's health condition and specific nutritional needs.

[0074] The detection unit continuously monitors changes in the pet's diet-related behavior and detects any abnormalities. For example, if the amount of food suddenly decreases or the time taken for a meal becomes shorter, these may be signs of health problems. The detected changes are reflected in the adjustment of the diet plan by the analysis unit.

[0075] The notification unit notifies the pet owner and veterinarian of information regarding the generated diet plan and the detected changes. This enables monitoring of the pet's health condition and prompt response as needed.

[0076] In this embodiment, in order to maintain and improve the health and well-being of the pet, the eating habits are precisely analyzed, and a diet plan tailored to the needs of each individual pet is provided. The pet's diet management is carried out efficiently and effectively, enabling the pet owner and veterinarian to better support the health management of the pet.

[0077] Note that the diet plan may include specific pet food ingredients, taste, smell, texture, etc. This allows for periodic improvement of the food recipe through feedback from the pet owner and continuous monitoring of eating habits, and enables adaptation to changes in the animal's preferences and health condition.

[0078] For example, the analysis unit collects data regarding the ingredients, smell, and taste of the food, and analyzes the impact on the pet's eating habits, particularly the palatability. This data includes the ratio of various nutrients and the use of flavorings. Furthermore, data such as the amount of food the animal eats, the time taken for a meal, and the frequency of meals are collected and analyzed in association with the food ingredients. At the same time, the animal's health condition and specific nutritional needs may also be considered.

[0079] Specifically, prepare an animal profile database containing basic information such as the type, age, weight, health status, and medical history of the animal, a dietary behavior database containing data such as the amount of food the animal eats, the time required for eating, the frequency of eating, and the behavior patterns during eating, and a feed ingredient database containing detailed information on the ingredients (such as protein, fat, carbohydrates, vitamins, minerals, etc.), taste, and smell of different feeds.

[0080] For example, the analysis unit associates the dietary behavior data of the animal with the feed ingredient data, conducts a dietary preference analysis to analyze which ingredients and tastes are preferred, conducts a correlation analysis with the health status to analyze the relationship between the health status of the animal and its dietary tendencies and identify the feed ingredients corresponding to specific health problems, and optimizes the nutritional balance by creating a well-balanced feed recipe based on the nutritional needs of the animal.

[0081] The system according to this embodiment may be configured to include a generation unit that performs the following outputs based on the analysis results by the analysis unit. · Customized feed recipe: Indicates the ratios of protein, fat, and carbohydrates, and the types and amounts of necessary vitamins and minerals according to the individual needs of the animal. · Dietary recommendation report: Dietary suggestions based on specific health conditions and nutritional needs. For example, it includes ingredients that are easy to digest, ingredients to avoid allergies, and calorie intake according to age and activity level. · Feedback and improvement suggestions: Suggestions for improving the feed based on feedback from the owner and updates to the recipe based on new health trends.

[0082] As described above, based on the analysis results, it may be possible to identify the recipe information of the feed that is optimal for the animal. This recipe will be designed to meet the preferences and health requirements of the animal. According to such a configuration, by providing a feed that matches the dietary tendencies of the animal, the health and well-being of the animal can be improved, and at the same time, the satisfaction of the owner can be increased.

[0083] <Modification Example> The present invention can adopt, for example, the following modification examples.

[0084] <Expansion of Biological Information Acquisition> In the acquisition unit, acquisition of biological information that has not been conventionally considered, such as the condition of an animal's skin and the brightness of its eyes, is added. As a result, it becomes possible to more comprehensively evaluate not only the eating tendency but also the overall health condition and stress level.

[0085] <Detailed Analysis of Diet Content> In the analysis unit, a detailed analysis of the nutritional components and quality of the diet is performed. This includes functions for evaluating the protein and carbohydrate content of a specific feed, the balance of vitamins and minerals, etc. As a result, it becomes possible to perform nutritional management suitable for individual animals.

[0086] <Addition of Analysis of Environmental Factors> In the analysis unit, analysis of environmental factors (such as noise, temperature, humidity, etc.) that may affect the eating behavior is added. This helps to determine whether changes in the eating tendency are due to the external environment.

[0087] <Long-Term Analysis of Behavior Patterns> In the analysis unit, a function for analyzing the eating behavior and general behavior patterns of animals over a long period is added. This makes it possible to capture changes in the eating tendency associated with seasonal variations and growth stages, and enables more accurate diet management.

[0088] <Linkage with Automatic Feeding Machine> A linkage function with an automatic feeding machine is added to the system. Based on the data obtained in the analysis unit and the detection unit, the automatic feeding machine automatically adjusts the amount and time of the animal's diet. As a result, it becomes possible to perform more precise diet management according to the needs of individual animals.

[0089] <Strengthening Linkage with Health Diagnosis> The linkage between the system and the veterinarian's diagnosis system is strengthened, and the data obtained from the diet evaluation system is directly utilized for health diagnosis. This improves the accuracy of diagnosis and enables more rapid treatment and preventive measures.

[0090] <Integration of Mobile Applications> Integrate the mobile application used by the owner with the system so that the owner can directly monitor the animal's diet data and health status from their smartphone or tablet. The system can also be enhanced to include functions where the owner can input diet records and observations through the app, and the system will incorporate these data into the analysis.

[0091] <Addition of Voice Recognition Function> Add a voice recognition function to the acquisition unit to analyze the sounds during the animal's meal (e.g., chewing sounds, drinking sounds). This function enables more detailed analysis of the animal's behavior and health status during meals.

[0092] <Utilization of Wearable Devices> Use wearable devices attached to the animal to more accurately collect biometric information such as heart rate and activity level during meals. This allows for the analysis of the animal's stress level and excitement state in relation to meals.

[0093] <Analysis of Social Behavior> Add a function to analyze the social impact on each animal's diet in an environment where multiple animals coexist. This enables the analysis of dynamics and competition in meal behaviors within the group.

[0094] <Enhancement of Learning Algorithm> Introduce an evolutionary machine learning algorithm in the analysis unit that automatically learns patterns related to the animal's diet trends and health status, and improves accuracy over time.

[0095] <Function for Monitoring Feed Quality> Add a function to the system to monitor the quality and freshness of the feed. This allows for the analysis of the impact of feed storage conditions and expiration dates on the animal's meal behavior and health. Manufacturers can utilize this data for product quality control and improvement.

[0096] <Feed Component Analysis and Recommendation System> Incorporate a system that recommends the optimal feed ingredients and composition based on the health status and dietary tendencies of animals. Manufacturers can utilize this information to develop feed recipes optimized for individual animals and provide customized feed.

[0097] <Construction of a feedback loop> Incorporate feedback from owners and veterinarians into the system to collect responses and satisfaction levels regarding the feed. This feedback is directly utilized to improve product development and marketing strategies.

[0098] <New product testing and market analysis> Test newly developed feed using the system and analyze its effects and acceptance. Capture market needs and trends and provide important data for more effective product development.

[0099] <Feed personalization and subscription model> Develop a subscription model that provides personalized feed based on the individual health status and preferences of animals. In this model, the animal's condition is monitored regularly and the feed formulation is constantly optimized.

[0100] <Monitoring function for allergic reactions> Incorporate a function into the system to monitor animals' allergic reactions to specific raw materials. This information is used to develop and improve allergen-free feed.

[0101] <Analysis tool for taste preferences> Develop a tool to collect and analyze detailed data regarding animals' taste preferences. Utilize this information to develop feed with more appealing tastes and aromas for animals.

[0102] <Development of health-promoting feed> Develop feed containing special ingredients to alleviate specific health problems in animals (e.g., joint pain, skin diseases, indigestion). Use the system to monitor and improve the effects of these products.

[0103] <Integration of Diagnostic Support System> Integrate the data of the animal diet evaluation system with the diagnostic support system of the animal hospital. As a result, the data on eating behavior can be directly utilized for health diagnosis and disease diagnosis. In particular, it is effective when changes in eating behavior may indicate early signs of disease.

[0104] <Enhanced Cooperation with Treatment Plan> When formulating an animal's treatment plan, actively utilize the information obtained from the diet evaluation system. Based on the analysis results of eating tendencies, optimize the treatment plan and diet therapy. For example, a special diet plan corresponding to specific health problems can be proposed.

[0105] <Remote Monitoring Service> The animal hospital provides a service for remotely monitoring the health status of animals. Using the diet evaluation system, regularly check the eating tendencies and health indicators of animals, and perform medical intervention as necessary.

[0106] <Disease Prevention Program> Develop a program for disease prevention, and utilize the data of the diet evaluation system to early identify animals with a high risk of specific diseases. Based on this information, recommend preventive treatments and lifestyle changes.

[0107] <Utilization as Educational Materials> Utilize the data of the diet evaluation system in educational programs and seminars for pet owners. Provide knowledge about animal health management and appropriate diets, and contribute to raising the awareness of pet owners.

[0108] The above-described embodiments are merely examples for facilitating the understanding of the present invention, and are not for limiting the interpretation of the present invention. It goes without saying that the present invention can be changed and improved without departing from its gist, and equivalents thereof are included in the present invention.

Explanation of Reference Numerals

[0109] 1 Server 2 Communication Terminal 3 User terminal 4 Analysis server 5 Sensor 6 Animal 7 Receiver 8 Weight measurement means

Claims

1. An acquisition unit that acquires ecological information of an animal, An analysis unit that analyzes the eating tendency of the animal from the biological information, A detection unit that detects a change in the tendency, A notification unit that notifies the detection result, An animal diet evaluation system comprising the above.

2. The animal diet evaluation system according to Claim 1, wherein the detection unit detects a change in the time zone of the meal. An animal diet evaluation system.

3. The animal diet evaluation system according to Claim 1, wherein the analysis unit analyzes the meal continuation time required for each meal, and the detection unit detects a change in the meal continuation time. An animal diet evaluation system.

4. The animal diet evaluation system according to Claim 1, wherein the analysis unit analyzes the number of meals in a predetermined period, and the detection unit detects a change in the number of meals. An animal diet evaluation system.

5. The animal diet evaluation system according to Claim 1, wherein the analysis unit analyzes meal-related behaviors performed by the animal during or after a meal, and the detection unit detects a change in the meal-related behavior. An animal diet evaluation system.

6. The animal diet evaluation system according to Claim 1, wherein the notification unit notifies the detection result to at least one of the owner of the animal or a veterinarian. An animal diet evaluation system.

7. The animal diet evaluation system according to any one of Claims 1 to 6, wherein the analysis unit generates a diet plan optimized for an individual animal based on the eating tendency of the animal. An animal diet evaluation system.

8. The animal diet evaluation system according to Claim 7, wherein the diet plan includes information on the components of the animal's feed. An animal diet evaluation system.

9. An acquisition unit that acquires ecological information of an animal, An analysis unit that analyzes the eating tendency of the animal from the biological information, A detection unit that detects a change in the tendency, A notification unit that notifies the detection result, An animal diet evaluation server comprising the above.

10. A step of acquiring ecological information of an animal, A step of analyzing the eating tendency of the animal from the biological information, A step of detecting a change in the tendency, A step of notifying the detection result, An animal diet evaluation method comprising the above.

Images