Fresh food environment information-based quality prediction device and method

Abstract

The present invention provides a fresh food environment information-based quality prediction device and method. The fresh food environment information-based quality prediction device and method according to an embodiment of the present invention includes: a quality prediction model determination unit for determining at least one quality prediction model from among a plurality of quality prediction models to estimate a quality index of at least one food material and fresh food to be sold that is cooked using said food material; a quality prediction unit for predicting, by using the quality prediction model, the quality index of the fresh food and the food material on the basis of the passage of time or a temperature change in consideration of at least one of a type of the food material and an environment factor according to a processing process in a space in which the food material is processed; and a display unit for displaying the quality index of the fresh food and the food material predicted on the basis of the passage of time or the temperature change so as to be monitored.

Description

Device and method for predicting quality based on fresh food environment information

[0001] The present invention relates to a device and method for predicting the quality of fresh food, and more particularly, to a device and method for predicting the quality of fresh food by taking into account not only food materials but also environmental factors related to the food materials.

[0002] Maintaining freshness is crucial for fresh food. In particular, fresh food, which is made up of a variety of ingredients and prepared before being sold, undergoes various storage, handling, cooking, and distribution processes. Therefore, consumers have no way of knowing the freshness or sanitary conditions of fresh food before opening the package.

[0003] Additionally, when a hygiene problem such as food poisoning occurs in fresh food, it is very difficult to trace which process of fresh food the problem occurred in.

[0004] Furthermore, for fresh food products sold in the form of meal kits that go through a variety of food preparation processes, it is nearly impossible to determine at which stage among storage, preparation, simple cooking, and sale the cause of quality deterioration occurred.

[0005] Accordingly, there is a need for a food quality monitoring device that can monitor the quality of fresh food in real time by reflecting environmental factors during the food ingredients and cooking process of fresh food.

[0006] The present invention is intended to solve the above problems, and provides a quality prediction device and method based on fresh food environment information capable of predicting quality indicators of fresh food by reflecting environmental factors in the food ingredients and cooking process of fresh food.

[0007] The tasks of the present invention are not limited to the tasks mentioned above, and other tasks not mentioned will be clearly understood by those skilled in the art from the description below.

[0008] In a quality prediction device based on fresh food environment information according to one embodiment of the present invention,

[0009] A quality prediction model determination unit for determining at least one quality prediction model among a plurality of quality prediction models to estimate quality indicators of at least one food ingredient and fresh food to be cooked and sold using the food ingredient;

[0010] A quality prediction unit that predicts the quality indicators of the food material and the fresh food based on the passage of time or temperature change by considering at least one of the types of the food material and environmental factors according to the processing process in the space where the food material is processed using the quality prediction model; and

[0011] It includes a display unit that displays the quality indicators of the food material and the fresh food predicted based on the passage of time or change in temperature so that they can be monitored.

[0012] Preferably,

[0013] The above quality indicator is characterized in that it is expressed as the number of microorganisms in the food material or the fresh food.

[0014] Preferably,

[0015] The above processing process includes a storage step after receiving the food material, a preparation step of the food material, a storage step after preparation of the food material, a cooking step of the food material, and a sales waiting step of the fresh food.

[0016] The above quality prediction model is characterized by predicting quality indicators of the food material or the fresh food at each stage of the processing process.

[0017] Preferably,

[0018] The quality prediction model applied to at least one step of the above processing process is characterized in that it can predict the number of microorganisms in the food material or the fresh food that changes through at least one environmental factor.

[0019] Preferably,

[0020] The above environmental factors include at least one of the temperature of the space, a cooking tool for cooking the food material, a storage container for storing the food material or the fresh food, and a packaging container for packaging the food material or the fresh food.

[0021] Preferably,

[0022] The above quality prediction model receives at least one of the type of the food ingredient, the time of receipt of the food ingredient, the storage time and storage temperature of the food ingredient, and the mixing ratio of the food ingredient as a prediction parameter, and outputs the quality index according to the passage of time or change in temperature.

[0023] A quality prediction method based on fresh food environment information executed on at least one processor according to another embodiment of the present invention,

[0024] A quality prediction model determination step for determining at least one quality prediction model among a plurality of quality prediction models to estimate quality indicators of at least one food ingredient and fresh food to be cooked and sold using the food ingredient;

[0025] An input receiving step of receiving at least one of the type of the food material, the time of receipt of the food material, the storage time and storage temperature of the food material, and the mixing ratio of the food material as a prediction parameter into the determined quality prediction model;

[0026] A quality prediction step for predicting the quality indicators of the food material and the fresh food according to the passage of time or change in temperature by considering at least one of the types of the food material and environmental factors according to the processing process in the space where the food material is processed using the quality prediction model; and

[0027] It includes a display step for displaying the quality indicators of the food material and the fresh food predicted based on the passage of time or change in temperature using a display unit so that they can be monitored.

[0028] Preferably,

[0029] The above quality indicator is characterized in that it is expressed as the number of microorganisms in the food material or the fresh food.

[0030] Preferably,

[0031] The above processing process includes a storage step after receiving the food material, a preparation step of the food material, a storage step after preparation of the food material, a cooking step of the food material, and a sales waiting step of the fresh food.

[0032] The above quality prediction step includes a step of predicting a quality indicator of the food material or the fresh food at each step of the processing process using the quality prediction model.

[0033] Preferably,

[0034] The quality prediction model applied to at least one step of the above processing process is characterized in that it can predict the number of microorganisms in the food material or the fresh food that changes through at least one environmental factor.

[0035] Preferably,

[0036] The above environmental factors include at least one of the temperature of the space, a cooking tool for cooking the food material, a storage container for storing the food material or the fresh food, and a packaging container for packaging the food material or the fresh food.

[0037] Specific details of other embodiments are included in the detailed description and drawings.

[0038] According to the fresh food environment information-based quality prediction device and method according to the present invention, when a sanitary problem such as food poisoning occurs in fresh food, it is possible to trace back to which process of the fresh food the problem occurred.

[0039] According to the fresh food environment information-based quality prediction device and method according to the present invention, it is possible to monitor the quality status and identify risk factors by predicting the number of microorganisms in food from the time of receipt of food ingredients until delivery to consumers.

[0040] According to the fresh food environment information-based quality prediction device and method according to the present invention, it is possible to trace the cause of quality deterioration for each individual environmental factor and for each food material.

[0041] However, the effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

[0042] FIG. 1 is a schematic diagram illustrating the configuration of a quality prediction device based on fresh food environment information according to one embodiment of the present invention.

[0043] FIG. 2 is a schematic diagram illustrating an embodiment of a system capable of real-time quality monitoring of fresh food, including a quality prediction device based on fresh food environment information of FIG. 1.

[0044] FIG. 3 is a drawing summarizing quality prediction-related information according to a processing process of a quality prediction device based on fresh food environment information according to one embodiment of the present invention.

[0045] FIG. 4 is a diagram illustrating an example of quality indicators of food materials and fresh food predicted using a quality prediction device based on fresh food environment information according to one embodiment of the present invention.

[0046] FIG. 5 is a diagram illustrating a flowchart of a quality prediction method based on fresh food environment information according to one embodiment of the present invention.

[0047] FIG. 6 is a diagram illustrating an exemplary computing device that may implement devices and / or systems according to various embodiments of the present invention.

[0048]

[0049] The advantages and features of the present invention, and the methods for achieving them, will become clearer with reference to the embodiments described in detail below together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and may be implemented in various different forms. These embodiments are provided only to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention, and the present invention is defined only by the scope of the claims. Like reference numerals designate like elements throughout the specification.

[0050] Embodiments described herein will be described with reference to cross-sectional and / or plan views, which are ideal illustrations of the present invention. In the drawings, the thicknesses of components are exaggerated for the purpose of effectively explaining the technical contents. Accordingly, the components illustrated in the drawings have a schematic nature, and the shapes of the components illustrated in the drawings are intended to illustrate specific forms of the components and are not intended to limit the scope of the invention. Although terms such as first, second, and third are used to describe various components in various embodiments of the present specification, these components should not be limited by such terms. These terms are used only to distinguish one component from another. The embodiments described and illustrated herein also include complementary embodiments thereof.

[0051] The terminology used herein is for the purpose of describing embodiments only and is not intended to limit the present invention. In this specification, the singular also includes the plural unless specifically stated otherwise. As used herein, the terms "comprises" and / or "comprising" do not exclude the presence or addition of one or more other components, steps, operations, and / or elements to the mentioned components, steps, operations, and / or elements.

[0052] Unless otherwise defined, all terms (including technical and scientific terms) used herein may be used in their common sense to those of ordinary skill in the art to which the present invention pertains. Furthermore, terms defined in commonly used dictionaries are not to be interpreted ideally or excessively unless explicitly and specifically defined otherwise.

[0053] Hereinafter, with reference to the drawings, the concept of the present invention and embodiments thereof will be described in detail.

[0054]

[0055] FIG. 1 is a schematic diagram illustrating the configuration of a quality prediction device based on fresh food environment information according to one embodiment of the present invention.

[0056] A quality prediction device (100) based on fresh food environment information according to one embodiment of the present invention includes a quality prediction model determination unit (110), a quality prediction unit (120), and a display unit (130).

[0057] The quality prediction model determination unit (110) determines at least one quality prediction model among a plurality of quality prediction models to estimate the quality index of at least one food ingredient and fresh food to be cooked and sold using the food ingredient.

[0058] In the present invention, the quality indicator of fresh food is expressed as the number of microorganisms in food materials or fresh food.

[0059] For example, types of food microorganisms include bacteria, fungus, yeast, and viruses.

[0060] Of particular interest in this invention is microbial risk assessment. Risk refers to the economic loss of food caused by contamination and proliferation of harmful microorganisms such as bacteria, mold, yeast, and viruses, which affect the quality and preservation of fresh food, as well as health risks resulting from ingestion of toxic metabolites produced by these harmful microorganisms.

[0061] Conventional food hazard assessments simply predicted the number of microorganisms (e.g., bacteria) according to temperature changes.

[0062] In contrast, the fresh food environment information-based quality prediction device (100) of the present invention can provide more accurate fresh food freshness information to consumers by predicting the number of microorganisms by considering all food ingredients constituting fresh food and environmental factors involved in the cooking process or processing of the food ingredients and displaying the predicted result.

[0063] The quality prediction unit (120) uses a quality prediction model to predict the quality indicators of food materials and fresh food based on the passage of time or temperature change by considering at least one of the environmental factors according to the type of food material and the processing process in the space where the food material is processed.

[0064] In one embodiment, the quality prediction model receives as input at least one of the type of food material, the time of receipt of the food material, the storage time and storage temperature of the food material, and the mixing ratio of the food material as a prediction parameter, and outputs a quality index according to the passage of time or change in temperature.

[0065] In one embodiment of the present invention, the space for processing food ingredients may refer to a kitchen. The space for processing food ingredients may refer to a shared kitchen for food manufacturing. A shared kitchen for food manufacturing may be equipped with all the necessary equipment for the production and packaging of fresh produce. A shared kitchen for manufacturing refers to a single, undivided space shared by multiple businesses for food manufacturing and processing. Representative domestic shared kitchen companies include WeCook.

[0066] The food processing process of the present invention includes a storage stage after receiving the food ingredients, a preparation stage, a storage stage after preparation, a cooking stage, and a sales stage for fresh food. The processing process may refer to a cooking process for preparing fresh food in a shared kitchen.

[0067] In one embodiment, the step of preparing food may mean washing the food and performing physical processing such as cutting.

[0068] In one embodiment, the cooking step of the food material means performing chemical processing of the food material, which may mean cooking the food material by adding seasoning or applying heat to produce fresh food.

[0069] In one embodiment of the present invention, the quality prediction model is characterized by predicting quality indicators of food materials or fresh food at each stage of the processing process.

[0070] In one embodiment of the present invention, the environmental factor includes at least one of the temperature of a space such as a shared kitchen where food is processed or prepared, cooking utensils where food is prepared, storage containers where food or fresh food is stored, and packaging containers where food or fresh food is packaged.

[0071] Environmental factors may additionally include the hygiene conditions of workers handling food, such as their hands or work clothes.

[0072] The display unit (130) displays the quality indicators of food ingredients and fresh food predicted based on the passage of time or temperature change so that they can be monitored.

[0073] The quality prediction model determination unit (110) and the quality prediction unit (120) of the fresh food environment information-based quality prediction device (100) of the present invention can be implemented in a computer device (e.g., a server), and can be implemented in the form of any one of hardware, software, a combination of hardware and software, and firmware.

[0074] The display unit (130) can display a predicted quality indicator as shown in FIG. 4.

[0075]

[0076] FIG. 2 is a schematic diagram illustrating an embodiment of a system capable of real-time quality monitoring of fresh food, including a quality prediction device based on fresh food environment information of FIG. 1.

[0077] The system (200) capable of real-time quality monitoring of fresh food of the present invention can provide relevant information so that consumers can know whether fresh food sold at a sales counter is safe, i.e., whether harmful microorganisms have grown in the fresh food without the consumers having to open the fresh food packaging.

[0078] A system (200) capable of real-time quality monitoring of fresh food according to one embodiment of the present invention includes a quality prediction device (220) based on fresh food environment information.

[0079] In a system (200) capable of real-time quality monitoring of fresh food as illustrated in FIG. 2, fresh food (210), a quality prediction device (220), and a consumer terminal (230) can be connected to each other through a network (240).

[0080] Although not shown in FIG. 2, a system (200) capable of real-time quality monitoring of fresh food may additionally include an administrator terminal (not shown).

[0081] Fresh food (210) may include a sensor tag (210), an RFID tag (212), and an IoT interface (213).

[0082] The sensor tag (210) attached to the fresh food (210) may be composed of multiple units, but only one is illustrated in FIG. 2 for simplicity.

[0083] The sensor tag (210) senses environmental information (e.g., temperature, humidity) in real time while fresh food is being transported or waiting to be sold at a sales counter.

[0084] Environmental information sensed by the sensor tag (210) is transmitted to a quality prediction device (220) based on fresh food environmental information through an IoT interface (213).

[0085] The quality prediction device (220) uses environmental information sensed by the sensor tag (210) through a communication unit (not shown) to predict the quality indicators of food materials and fresh food based on the passage of time or temperature change.

[0086] The quality indicators of fresh food predicted by the quality prediction unit of the quality prediction device (220) are transmitted to the IoT interface (213) of the fresh food (210) through the network (240).

[0087] The quality indicators of fresh food predicted by the fresh food environment information-based quality prediction device (220) can be automatically updated to the RFID tag (212).

[0088] FIG. 2 illustrates an example in which the quality indicators of fresh food predicted by the quality prediction device (220) are automatically updated to the RFID tag (212).

[0089] In another embodiment, the quality indicator of fresh food predicted by the quality prediction device (220) is transmitted to a manager terminal (not shown) and can be stored in an RFID tag (212) of fresh food (210) using an RFID writer of the manager terminal.

[0090] By reading the quality indicator of fresh food stored in the RFID tag (212) through an RFID reader (not shown) of a consumer terminal (230), the consumer can know the predicted quality indicator (e.g., number of microorganisms) of the fresh food (210).

[0091] In another embodiment, the display installed on the sales counter may be configured to display quality indicators of fresh food stored in the RFID tag (212).

[0092]

[0093] FIG. 3 is a drawing summarizing quality prediction-related information according to a processing process of a quality prediction device based on fresh food environment information according to one embodiment of the present invention.

[0094] In one embodiment of the present invention, the quality prediction model is characterized by predicting quality indicators of food ingredients or fresh food at each stage of a processing process or a shared kitchen process.

[0095] In the present invention, the processing process or shared kitchen process for processing food materials includes a storage step after receiving food materials, a preparation step for food materials, a storage step after preparation of food materials, a cooking step for food materials, and a sales waiting step for fresh food.

[0096] The quality prediction device of the present invention reflects the temperature value of each food ingredient constituting fresh food in the storage stage (310) after receipt of the food ingredient, according to the storage type such as refrigeration, freezing, or room temperature, and presents a quality index result according to time / temperature.

[0097] In one embodiment, in the storage step (310) after receipt of food materials, the quality prediction device selects the Gompertz (@Risk) analysis model.

[0098] The quality prediction device of the present invention considers the food ingredients being stored and kitchen environmental factors related to the food ingredient handling, such as hands, cutting boards, knives, and bowls, in the food ingredient handling step (320), and derives changes in quality indicators before and after the food ingredient handling.

[0099] In one embodiment, in the food handling step (320), the quality prediction device selects a microbiology-based model.

[0100] The quality prediction device of the present invention presents a quality index over time by considering the temperature inside a shared kitchen for food materials that have been prepared in the post-preparation storage step (330).

[0101] In one embodiment, in the post-processing storage step (330) of the food material, the quality prediction device selects the Gompertz (@Risk) analysis model.

[0102] The quality prediction device of the present invention presents quality indicator changes before and after cooking for food ingredients that have been prepared in the cooking step (340) and quality factors for hands and cooking tools, which are cooking environment factors.

[0103] In one embodiment, the quality prediction device selects a microbiology-based model in the cooking step (340) of the food material.

[0104] The quality prediction device of the present invention presents a quality index according to time / temperature by considering the kitchen environment temperature where the food is served, such as a serving bowl or packaging, which is a serving environment factor for the food that has been cooked and the serving environment factor in the fresh food sales waiting stage (350).

[0105] In one embodiment, in the fresh food sales waiting stage (350), the quality prediction device selects the Gompertz (@Risk) analysis model.

[0106] An example of a quality prediction model for estimating quality indicators of fresh food is the Gompertz model. The Gompertz analysis model uses the @Risk tool to predict quality indicators or bacterial counts.

[0107] The Gompertz model is used to predict quality indicators or bacterial counts in the storage stage after receiving food materials (310), the storage stage after handling food materials (330), and the sales waiting stage of fresh food (350).

[0108] The Gompertz model is calculated using a linear model that represents the rate of bacterial change over time at each temperature for each food ingredient.

[0109] For example, in the storage step (310) after receiving food materials, the number of bacteria before storage, the storage time, and the storage temperature are used to predict the number of bacteria after n hours using the Gompertz formula (1).

[0110] Formula (1)

[0111] Here, A is the log value of the initial number of cells, C is the log value difference between the initial number of cells and the maximum number of cells, B is the growth rate at time M, M is the time at which the growth rate reaches its maximum, and n is the storage time.

[0112] The Gompertz model can predict microbial populations over time and temperature.

[0113] The Gompertz model uses data from measurements of microorganisms at various temperatures, and if this is difficult, the combase tool is used to generate the data.

[0114] Once the data is ready, we use the Graph Pad Prism tool to calculate C, B, and M, and then complete the Gompertz model through secondary modeling.

[0115] The Gompertz model requires that the temperature range to be predicted be within the range of the prepared data.

[0116] Another example of a quality prediction model for estimating quality indicators of fresh food is a predictive microbiology-based model.

[0117] Microbiology-based models predict quality indicators by considering environmental factors from both pre- and post-cooking perspectives.

[0118] Microbiology-based models do not significantly account for changes over time and temperature, and focus on pathogen flow through the medium during cooking to predict microbial populations.

[0119] Microbiology-based models are used to predict quality indicators at the food handling stage (320) and the food cooking stage (340).

[0120] The number of microorganisms or bacteria in the food material handling step (320) can be predicted using the following equation (2). That is, the initial number of bacteria in the food material is multiplied by the washing rate, the initial number of bacteria in the cooking utensils used is multiplied by the transfer rate, and then the products are added together to predict the quality indicator after the handling step, i.e. the number of bacteria.

[0121] Formula (2)

[0122] The number of microorganisms or bacteria in the cooking stage (340) of food ingredients can be predicted using the following equation (3). That is, the number of bacteria after the cooking stage, i.e., the finished product, is predicted by adding the product of the initial number of bacteria in the food ingredients multiplied by the initial number of bacteria in the cooking utensils used and the transfer rate.

[0123] Formula (3)

[0124] Microbiology-based models can predict the number of microorganisms in food or fresh food products as a function of at least one environmental factor.

[0125] A quality prediction device based on fresh food environment information according to one embodiment of the present invention is characterized in that it can monitor the quality status and check risk factors in advance by predicting the number of microorganisms in fresh food from the time of receipt of food materials until delivery to consumers.

[0126] A quality prediction device based on fresh food environment information according to one embodiment of the present invention can display the quality status (number of microorganisms) according to the receipt of food ingredients in a shared kitchen and the entire cooking process and time in the form of a graph or a score.

[0127]

[0128] FIG. 4 is a diagram illustrating an example of quality indicators of food materials and fresh food predicted using a quality prediction device based on fresh food environment information according to one embodiment of the present invention.

[0129] Figure 4 is a diagram illustrating the time series of quality indicators of food materials and fresh food predicted using a quality prediction model.

[0130] As illustrated in Figure 4, the quality indicators are predicted and illustrated for each step in the processing process in the space where food materials are processed or in the shared kitchen process.

[0131] The graph of quality indicators shown in Figure 4 is shown as an example to show the trend of increase and decrease in quality indicators, and the number of microorganisms refers to the number of microorganisms per unit area of ​​food materials or manufactured fresh food.

[0132] In the storage stage (410) after receiving the food materials, the quality prediction model predicts an increase of approximately 0.5 from 2 to 2.5 over 1-5 hours.

[0133] In the food handling step (420), the quality prediction model predicts the number of microorganisms to be less than 2 per unit area for 5-6 hours after washing the food.

[0134] In the post-processing storage stage (430), the quality prediction model predicts that the microbial count will increase again over a period of 6-11 hours. The microbial count immediately prior to the cooking stage is approximately 2.5.

[0135] At the cooking stage (440) of the food material, the quality prediction model predicts that the number of microorganisms increases to 3 over 11-12 hours.

[0136] The results predicted by the quality prediction model in the sales waiting stage (450) of fresh food show that the number of microorganisms per unit area continues to increase over time.

[0137] In Fig. 4, the subject of quality prediction from the storage stage (410) to the food preparation stage (440) is food, but the subject of quality prediction in the sales waiting stage (450) is fresh food.

[0138] In FIG. 4, the results of predicting quality indices for one food ingredient from the storage stage (410) to the cooking stage (440) of the food ingredient are shown, but in the case of multiple fresh food ingredients, the results of quality indices for each food ingredient can all be shown in the form of a graph.

[0139]

[0140] FIG. 5 is a diagram illustrating a flowchart of a quality prediction method based on fresh food environment information according to one embodiment of the present invention.

[0141] A quality prediction method based on fresh food environment information executed on at least one processor according to another embodiment of the present invention includes a quality prediction model determination step (S510), an input reception step (S520), a quality prediction step (S530), and a display step (S540).

[0142] The quality prediction model determination step (S510) determines at least one quality prediction model among a plurality of quality prediction models to estimate quality indicators of at least one food ingredient and fresh food to be cooked and sold using the food ingredient.

[0143] In one embodiment, the quality prediction model may include a Gompertz prediction model and a microbiology prediction-based model.

[0144] The input reception step (S520) receives at least one of the type of food material, the time of receipt of food material, the storage time and temperature of food material, and the mixing ratio of food material as a prediction parameter for the determined quality prediction model.

[0145] The quality prediction step (S530) uses a quality prediction model to predict the quality indicators of food ingredients and fresh food according to changes in time or temperature by considering at least one of the types of food ingredients and environmental factors according to the processing process in the space where the food ingredients are processed or the shared kitchen process.

[0146] In one embodiment, the environmental factors include at least one of the temperature of the food processing space or shared kitchen, cooking utensils for preparing the food, storage containers for storing the food or fresh food, and packaging containers for packaging the food or fresh food.

[0147] In one embodiment, the quality prediction step includes predicting quality indicators of the food ingredient or fresh food at each step of the processing process or shared kitchen process using the determined quality prediction model.

[0148] The display step (S540) displays the quality indicators of the food ingredients and fresh food predicted based on the passage of time or temperature change using the display unit so that they can be monitored.

[0149] In one embodiment, the quality indicator or quality value is characterized by being expressed as the number of microorganisms in the food material or fresh food.

[0150] In one embodiment, the processing process or shared kitchen process includes a storage step after receiving food ingredients, a preparation step of food ingredients, a storage step after preparation of food ingredients, a cooking step of food ingredients, and a sale-ready step of fresh food.

[0151] In one embodiment, a quality prediction model (e.g., a microbiology prediction-based model) applied to at least one step of a processing process or a shared kitchen process is characterized in that it can predict the number of microorganisms in a food ingredient or fresh food product as a function of at least one environmental factor.

[0152]

[0153] FIG. 6 is a diagram illustrating an exemplary computing device that may implement devices and / or systems according to various embodiments of the present invention.

[0154] An exemplary computing device (600) capable of implementing devices according to some embodiments of the present disclosure will now be described in more detail with reference to FIG. 6.

[0155] A computing device (600) may include one or more processors (610), a bus (650), a communication interface (670), a memory (630) for loading a computer program (691) executed by the processor (610), and a storage (690) for storing the computer program (691). However, only components related to the embodiment of the present disclosure are illustrated in FIG. 6.

[0156] Accordingly, a person skilled in the art will appreciate that other general components may be included in addition to the components illustrated in FIG. 6.

[0157] The processor (610) controls the overall operation of each component of the computing device (600). The processor (610) may include a central processing unit (CPU), a microprocessor unit (MPU), a microcontroller unit (MCU), a graphics processing unit (GPU), or any other form of processor (610) well known in the art of the present disclosure. In addition, the processor (610) may perform operations for at least one application or program for executing a method according to embodiments of the present disclosure. The computing device (600) may include one or more processors (610). The computing device (600) may refer to artificial intelligence (AI).

[0158] The memory (630) stores various data, commands, and / or information. The memory (630) can load one or more programs (691) from the storage (690) to execute methods according to embodiments of the present disclosure. The memory (630) may be implemented as a volatile memory such as RAM, but the technical scope of the present disclosure is not limited thereto.

[0159] The bus (650) provides communication between components of the computing device (600). The bus (650) may be implemented as various types of buses, such as an address bus, a data bus, and a control bus.

[0160] The communication interface (670) supports wired and wireless Internet communication of the computing device (600). Furthermore, the communication interface (670) may support various communication methods other than Internet communication. To this end, the communication interface (670) may be configured to include a communication module well known in the technical field of the present disclosure.

[0161] According to some embodiments, the communication interface (670) may be omitted.

[0162] Storage (690) can non-temporarily store one or more programs (691) and various data.

[0163] Storage (690) may be configured to include non-volatile memory such as Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), flash memory, a hard disk, a removable disk, or any form of computer-readable recording medium well known in the art to which the present disclosure pertains.

[0164] The computer program (691) may include one or more instructions that, when loaded into the memory (630), cause the processor (610) to perform methods / operations according to various embodiments of the present disclosure. That is, the processor (610) may perform the methods / operations according to various embodiments of the present disclosure by executing the one or more instructions.

[0165]

[0166] Although the preferred embodiments of the present invention have been illustrated and described above, the present invention is not limited to the specific embodiments described above, and various modifications may be made by a person skilled in the art without departing from the gist of the present invention as claimed in the claims. Furthermore, such modifications should not be understood individually from the technical idea or prospect of the present invention.

Claims

1. A quality prediction model determination unit for determining at least one quality prediction model among a plurality of quality prediction models to estimate quality indicators of at least one food ingredient and fresh food to be cooked and sold with the food ingredient; A quality prediction unit that predicts the quality indicators of the food material and the fresh food based on the passage of time or temperature change by considering at least one of the types of the food material and environmental factors according to the processing process in the space where the food material is processed using the quality prediction model; and A quality prediction device based on fresh food environment information, comprising a display unit that displays quality indicators of the predicted food materials and fresh food based on the passage of time or temperature change so as to enable monitoring.

2. In claim 1, A quality prediction device based on fresh food environment information, characterized in that the above quality indicator is expressed as the number of microorganisms in the food material or the fresh food.

3. In claim 2, The above processing process includes a storage step after receiving the food material, a preparation step of the food material, a storage step after preparation of the food material, a cooking step of the food material, and a sales waiting step of the fresh food. A quality prediction device based on fresh food environment information, characterized in that the quality prediction model predicts quality indicators of the food material or the fresh food at each stage of the processing process.

4. In claim 3, A quality prediction device based on fresh food environment information, characterized in that the quality prediction model applied to at least one step of the processing process can predict the number of microorganisms in the food material or the fresh food that changes by using at least one environmental factor as a medium.

5. In claim 4, A quality prediction device based on fresh food environment information, wherein the environmental factors include at least one of the temperature of the space, a cooking tool for cooking the food material, a storage container for storing the food material or the fresh food, and a packaging container for packaging the food material or the fresh food.

6. In claim 3, The quality prediction model is a quality prediction device based on fresh food environment information, which receives at least one of the type of the food ingredient, the time of receipt of the food ingredient, the storage time and storage temperature of the food ingredient, and the mixing ratio of the food ingredient as a prediction parameter, and outputs the quality index according to the passage of time or change in temperature.

7. A quality prediction method based on fresh food environment information executed on at least one processor, A quality prediction model determination step of determining at least one quality prediction model among a plurality of quality prediction models to estimate quality indicators of at least one food ingredient and fresh food to be cooked and sold with the food ingredient; An input receiving step of receiving at least one of the type of the food ingredient, the time of receipt of the food ingredient, the storage time and storage temperature of the food ingredient, and the mixing ratio of the food ingredient as a prediction parameter into the determined quality prediction model; A quality prediction step for predicting the quality indicators of the food material and the fresh food according to the passage of time or change in temperature by considering at least one of the types of the food material and environmental factors according to the processing process in the space where the food material is processed using the quality prediction model; and A quality prediction method based on fresh food environment information, comprising: a display step for displaying the predicted quality indicators of the food material and the fresh food based on the passage of time or change in temperature using a display unit so that the quality indicators can be monitored.

8. In claim 7, A quality prediction method based on fresh food environment information, characterized in that the above quality indicator is expressed as the number of microorganisms in the food material or the fresh food.

9. In claim 7, The above processing process includes a storage step after receiving the food material, a preparation step of the food material, a storage step after preparation of the food material, a cooking step of the food material, and a sales waiting step of the fresh food. A quality prediction method based on fresh food environment information, wherein the quality prediction step includes a step of predicting a quality index of the food material or the fresh food at each step of the processing process using the quality prediction model.

10. In claim 9, A quality prediction method based on fresh food environmental information, characterized in that the quality prediction model applied to at least one step of the above processing process can predict the number of microorganisms in the food material or the fresh food that changes by means of at least one environmental factor.

11. In claim 10, A quality prediction method based on fresh food environment information, wherein the environmental factors include at least one of the temperature of the space, a cooking tool for cooking the food material, a storage container for storing the food material or the fresh food, and a packaging container for packaging the food material or the fresh food.

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