Food material management method, device and system
By acquiring historical information about the food in the refrigerator, the system identifies target ingredients and generates purchasing recommendations, solving the problem of traditional refrigerators' inability to intelligently manage food and achieving more accurate food procurement and higher user satisfaction.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NINGBO FOTILE KITCHEN WARE CO LTD
- Filing Date
- 2026-01-07
- Publication Date
- 2026-06-05
AI Technical Summary
Traditional refrigerators struggle to intelligently control the addition, reduction, and variety of food based on user preferences and healthy eating guidelines, leading to food expiration or shortages and failing to meet diverse user needs.
By acquiring historical procurement and consumption information of food storage equipment, target ingredients are identified, and demand is updated based on target adjustment coefficients to generate procurement recommendations, thereby improving the intelligence of food management.
It improved the accuracy of procurement recommendations and enhanced the intelligence and user experience of food ingredient management.
Smart Images
Figure CN122155140A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of intelligent kitchen appliance technology, and in particular to a method, device and system for food management. Background Technology
[0002] With the rapid development of technology and the improvement of people's living standards, the demand for smart home appliances is also growing. Traditional refrigerators are prone to food expiration and shortages during use, but they are difficult to intelligently control the increase, decrease, and variety of food in the refrigerator according to user preferences and healthy eating guidelines, making it difficult to meet various user needs. Summary of the Invention
[0003] To address the aforementioned problems in the prior art, this invention discloses a method, apparatus, and system for food ingredient management, which can improve the accuracy of procurement recommendations and thus enhance the intelligence of food ingredient management. The technical solution disclosed in this invention is as follows: According to one aspect of the disclosed embodiments of the present invention, a method for managing food ingredients is provided, the method comprising: Acquire historical purchase information, historical consumption information, and current inventory of various ingredients in food storage equipment; the historical purchase information includes historical purchase quantity and historical purchase frequency, and the historical consumption information includes historical consumption quantity and historical consumption rate. Based on the historical procurement frequency and historical consumption rate of each ingredient, the target ingredient is determined from the multiple ingredients; The target adjustment coefficient for the target ingredient is determined based on its historical purchase volume. The historical consumption of the target ingredient is updated based on the target adjustment coefficient to obtain the demand for the target ingredient; Based on the difference between the demand for the target ingredient and the current inventory, the target purchase quantity of the target ingredient is determined; Purchase recommendations are generated based on the target purchase quantity of the target ingredient, so that users can purchase the target ingredient based on the target purchase quantity.
[0004] Optionally, determining the target adjustment coefficient for the target ingredient based on its historical purchase volume includes: In multiple historical periods, if the change in the historical purchase volume of the target ingredient is greater than zero, the preset adjustment coefficient is positively adjusted to obtain the target adjustment coefficient. In the multiple historical periods, if the historical purchase volume of the target ingredient is less than the first preset purchase threshold, or if the current inventory of the target ingredient is greater than or equal to the first preset inventory threshold, the preset adjustment coefficient is negatively adjusted to obtain the target adjustment coefficient.
[0005] Optionally, determining the target ingredient from the multiple ingredients based on the historical purchase frequency and the historical consumption rate includes: Based on the historical purchase frequency and historical consumption rate of each ingredient, the preferred ingredients are determined from the multiple ingredients; Based on the historical purchasing frequency of the preferred ingredients and preset seasonal parameters, the seasonal matching information of the preferred ingredients is determined; the seasonal matching information is used to characterize the degree of seasonal matching of the preferred ingredients. The preferred ingredients whose seasonal matching information is greater than or equal to a preset matching threshold and whose current inventory is less than a second preset inventory threshold are determined as the target ingredients.
[0006] Optionally, determining the target ingredient from the multiple ingredients based on the historical purchase frequency and the historical consumption rate includes: Based on the historical purchase frequency and historical consumption rate of each ingredient, the preferred ingredients are determined from the multiple ingredients; Based on the historical consumption sequence of the preferred ingredients in multiple historical periods and the current inventory, the initial predicted consumption of the preferred ingredients is calculated. Based on the festival and seasonal factors corresponding to the preferred ingredients, the initial predicted consumption is corrected to obtain the target predicted consumption of the preferred ingredients. Based on the target predicted consumption and current inventory of the preferred ingredients, the supply duration of the preferred ingredients is determined; The preferred ingredients whose supply time is less than or equal to a preset time threshold are identified as the target ingredients.
[0007] Optionally, determining preferred ingredients from the multiple ingredients based on the historical purchase frequency and historical consumption rate of each ingredient includes: Among the various ingredients, those whose historical purchase frequency is greater than or equal to a second preset purchase threshold and whose historical consumption rate is greater than or equal to a preset consumption threshold are identified as the preferred ingredients.
[0008] Optionally, determining preferred ingredients from the multiple ingredients based on the historical purchase frequency and historical consumption rate of each ingredient includes: Based on the degree of correlation between the various ingredients, multiple related ingredient combinations are identified from the various ingredients; Based on the historical purchase frequency and historical consumption rate of each associated food combination, a target associated food combination is determined from the plurality of associated food combinations; The ingredients in the target associated ingredient combination are identified as the preferred ingredients.
[0009] Optionally, after determining the target purchase quantity of the target ingredient based on the difference between the demand and current inventory of the target ingredient, the method further includes: Obtain the historical number of times the user ignored the purchase suggestion for the target ingredient; If the number of times the target ingredient has been ignored in the past exceeds a preset threshold, the procurement attenuation information corresponding to the number of times the ingredient has been ignored is determined. The target purchase quantity of the target ingredient is updated based on the purchase attenuation information to obtain the updated purchase quantity of the target ingredient. Accordingly, the process of generating procurement recommendations based on the target purchase quantity of the target ingredient includes: Purchase recommendations are generated based on the updated purchase volume of the target ingredient, so that the user can purchase the target ingredient based on the updated purchase volume.
[0010] According to another aspect of the disclosed embodiments of the present invention, a food ingredient management device is provided, the device comprising: The first acquisition module is used to acquire historical purchase information, historical consumption information and current inventory of various ingredients in the food storage equipment; the historical purchase information includes historical purchase quantity and historical purchase frequency, and the historical consumption information includes historical consumption quantity and historical consumption rate. The target ingredient determination module is used to determine the target ingredient from the multiple ingredients based on the historical purchase frequency and historical consumption rate of each ingredient; The adjustment coefficient determination module is used to determine the target adjustment coefficient of the target ingredient based on the historical purchase volume of the target ingredient; The demand determination module is used to update the historical consumption of the target ingredient based on the target adjustment coefficient to obtain the demand of the target ingredient. The target purchase quantity determination module is used to determine the target purchase quantity of the target ingredient based on the difference between the demand for the target ingredient and the current inventory. The procurement suggestion generation module is used to generate procurement suggestions based on the target procurement quantity of the target ingredient, so that the user can purchase the target ingredient based on the target procurement quantity.
[0011] According to another aspect of the disclosed embodiments of the present invention, a food management system is provided. The system includes a sensing module, a control unit, a cloud platform, and a client. The sensing module is disposed in the food storage device, and the sensing module, the cloud platform, and the client are respectively communicatively connected to the control unit. The sensing module is used to identify each type of ingredient and sense the weight of each type of ingredient; the client is used to receive the purchasing suggestions; and the control unit is used to execute the ingredient management method as described above.
[0012] Optionally, the system also includes a cloud, which is communicatively connected to the control unit, and is used to store the correspondence between each ingredient and preset seasonal parameters.
[0013] According to another aspect of the disclosed embodiments of the present invention, an electronic device for food ingredient management is provided, including a processor and a memory, wherein the memory stores at least one instruction, which is loaded and executed by the processor to implement the food ingredient management method described above.
[0014] According to another aspect of the embodiments disclosed in this invention, a computer-readable storage medium is provided, wherein at least one instruction is stored in the computer storage medium, the at least one instruction being loaded and executed by a processor to implement the food ingredient management method described in any of the preceding claims.
[0015] According to another aspect of the disclosed embodiments of the present invention, a computer program product containing instructions is provided, which, when run on a computer, causes the computer to perform the food ingredient management method described in any of the above-described embodiments of the present invention.
[0016] The food ingredient management method, apparatus, and system provided by this invention have the following technical effects: The food ingredient management method provided by this invention includes acquiring historical procurement information, historical consumption information, and current inventory of various food ingredients stored in food storage equipment; the historical procurement information includes historical procurement quantity and historical procurement frequency, and the historical consumption information includes historical consumption quantity and historical consumption rate; based on the historical procurement frequency and historical consumption rate of each food ingredient, a target food ingredient is determined from the various food ingredients; based on the historical procurement quantity of the target food ingredient, a target adjustment coefficient is determined; based on the target adjustment coefficient, the historical consumption quantity of the target food ingredient is updated to obtain the demand quantity of the target food ingredient; based on the difference between the demand quantity of the target food ingredient and the current inventory, a target procurement quantity of the target food ingredient is determined; and based on the target procurement quantity of the target food ingredient, procurement suggestions are generated. This improves the accuracy of procurement suggestions, thereby enhancing the intelligence of food ingredient management and improving the user experience.
[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description
[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1 This is a flowchart illustrating a food ingredient management method according to an exemplary embodiment; Figure 2 This is a schematic diagram illustrating a process for determining target ingredients according to an exemplary embodiment; Figure 3 This is a schematic diagram illustrating another process for determining target ingredients according to an exemplary embodiment; Figure 4 This is a block diagram illustrating a food ingredient management device according to an exemplary embodiment; Figure 5 This is a schematic diagram illustrating a food ingredient management system according to an exemplary embodiment; Figure 6 This is a schematic diagram of the structure of a control unit according to an exemplary embodiment; Figure 7 This is a block diagram illustrating a terminal electronic device for food ingredient management according to an exemplary embodiment; Figure 8 This is a block diagram illustrating a server electronic device for food ingredient management according to an exemplary embodiment. Detailed Implementation
[0020] To enable those skilled in the art to better understand the technical solutions disclosed in this invention, the technical solutions in the disclosed embodiments will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.
[0021] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention disclosed herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.
[0022] To make the objectives, technical solutions, and advantages disclosed in the embodiments of this application clearer, the embodiments of this application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the embodiments of this application and are not intended to limit the embodiments of this application.
[0023] Please see Figure 1 , Figure 1 This is a flowchart illustrating a method for managing food ingredients according to an exemplary embodiment. This specification provides the operational steps of the method as described in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operational steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual system or server product execution, the methods shown in the embodiments or drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment). Specifically, as... Figure 1 As shown, the above method may include: S101: Obtain historical purchase information, historical consumption information, and current inventory of various ingredients in the food storage equipment.
[0024] In one specific embodiment, the food storage device can be an appliance such as a refrigerator. Historical procurement information may include historical procurement quantity and frequency, while historical consumption information may include historical consumption quantity and rate. Specifically, consumption and procurement information for each type of food can be determined using weight sensors, and food types can be identified by capturing images of the food using a camera.
[0025] S103: Based on the historical purchase frequency and historical consumption rate of each ingredient, determine the target ingredient from a variety of ingredients.
[0026] In an optional embodiment, such as Figure 2 As shown, the above method of determining target ingredients from a variety of ingredients based on historical purchasing frequency and historical consumption rate can include: S201: Based on the historical purchase frequency and historical consumption rate of each ingredient, determine the preferred ingredient from a variety of ingredients.
[0027] In one specific embodiment, the preferred ingredients can be those that are purchased frequently and consumed at a high rate.
[0028] Optionally, the method of determining preferred ingredients from a variety of ingredients based on the historical purchase frequency and historical consumption rate of each ingredient may include: Among a variety of ingredients, those with a historical purchase frequency greater than or equal to a second preset purchase threshold and a historical consumption rate greater than or equal to a preset consumption threshold are identified as preferred ingredients.
[0029] Specifically, the second preset procurement threshold and the preset consumption threshold can be set according to actual application needs.
[0030] Optionally, the method of determining preferred ingredients from a variety of ingredients based on the historical purchase frequency and historical consumption rate of each ingredient may also include: Based on the degree of correlation between various ingredients, multiple related ingredient combinations are identified from a variety of ingredients; Based on the historical procurement frequency and historical consumption rate of each associated food combination, the target associated food combination is determined from multiple associated food combinations; The ingredients in the target-related ingredient combination are identified as preferred ingredients.
[0031] In one specific embodiment, association rule mining algorithms (such as Apriori) can be used to identify frequently co-occurring food combinations. Frequency thresholds (such as more than or equal to 3 times per week) can also be set to filter out invalid food combinations. Target associated food combinations can be those with high purchase frequency and high consumption rate. Food combinations with a historical purchase frequency greater than or equal to a second preset purchase threshold and a historical consumption rate greater than or equal to a preset consumption threshold can be identified as target associated food combinations.
[0032] S203: Based on the historical purchase frequency of preferred ingredients and preset seasonal parameters, determine the seasonal matching information of preferred ingredients.
[0033] In one specific embodiment, seasonal matching information can be used to characterize the degree of seasonal matching of preferred ingredients. Optionally, the seasonal matching information corresponding to historical purchasing frequency and preset seasonal parameters can be determined based on the correspondence between historical purchasing frequency, preset seasonal parameters and seasonal matching information; alternatively, seasonal matching information can be obtained by performing corresponding calculations on historical purchasing frequency and preset seasonal parameters. Specifically, the seasonal matching information can be obtained by multiplying historical purchasing frequency and preset seasonal parameters.
[0034] S205: Select preferred ingredients whose seasonal matching information is greater than or equal to a preset matching threshold and whose current inventory is less than a second preset inventory threshold as target ingredients.
[0035] In one specific embodiment, the target ingredients can be ingredients that need to be purchased. High-frequency ingredients favored by users that have a high degree of seasonality and low current inventory levels can be identified as target ingredients and recommended to the user. Specifically, the preset matching threshold and the second preset inventory threshold are set according to actual application needs.
[0036] In an optional embodiment, such as Figure 3 As shown, the above method of determining target ingredients from a variety of ingredients based on historical procurement frequency and historical consumption rate may also include: S301: Based on the historical purchase frequency and historical consumption rate of each ingredient, determine the preferred ingredient from a variety of ingredients.
[0037] S303: Based on the historical consumption sequence of preferred ingredients in multiple historical periods and the current inventory, calculate the initial predicted consumption of preferred ingredients.
[0038] In one specific embodiment, based on time series analysis (ARIMA or exponential smoothing), a historical consumption curve is fitted based on the historical consumption sequence to predict the cyclical consumption of ingredients. Specifically, each cycle can be daily, weekly, monthly, etc.
[0039] S305: Based on the festival and seasonal influencing factors corresponding to the preferred ingredients, the initial predicted consumption is corrected to obtain the target predicted consumption of the preferred ingredients.
[0040] Specifically, holiday and seasonal influencing factors (e.g., 0.9 for summer cucumbers and 0.2 for mutton) can be introduced to dynamically adjust the predicted consumption. Optionally, the holiday and seasonal influencing factors can be multiplied by the initial predicted consumption to obtain the target predicted consumption; alternatively, the holiday and seasonal influencing factors can be fused first, and then the fused factor can be multiplied by the initial predicted consumption to obtain the target predicted consumption. Specifically, fusing the holiday and seasonal influencing factors can involve directly summing or weighted summing, etc.
[0041] S307: Determine the supply duration of preferred ingredients based on the target predicted consumption and current inventory levels.
[0042] Specifically, based on the preset consumption amount of preferred ingredients within a cycle and the current inventory level, it can be determined how long the ingredients will last before being consumed. Specifically, the supply duration can be obtained by dividing the current inventory level by the target predicted consumption amount.
[0043] S309: Select preferred ingredients whose supply duration is less than or equal to a preset duration threshold as target ingredients.
[0044] Specifically, preferred ingredients with short supply durations can be identified as target ingredients, meaning those that are expected to be consumed quickly and in short supply within a short period. The preset duration threshold can be set according to actual application needs.
[0045] In practical applications, user historical data can be analyzed to extract high-frequency food combinations (such as "eggs and tomatoes" accessed 3 times a week) and generate a preferred dish library; access timestamps can be recorded, and the seasonal database (containing seasonal and regional recommended ingredients) can be matched with the preferred dish library to filter recommended dishes for the current season (such as prioritizing "cold cucumber salad" over "braised mutton" in summer); the supply duration can be calculated and determined based on the current inventory and cycle consumption (such as an average daily consumption of 0.5 eggs).
[0046] S105: Determine the target adjustment coefficient for the target ingredient based on its historical purchase volume.
[0047] In one specific embodiment, the target adjustment coefficient is used to adjust the target purchase quantity of ingredients.
[0048] Optionally, determining the adjustment coefficient for the target ingredient based on its historical purchase volume may include: In multiple historical periods, when the changes in the historical procurement volume of the target ingredient are all greater than zero, the preset adjustment coefficient is positively adjusted to obtain the target adjustment coefficient. In multiple historical cycles, when the historical purchase volume of the target ingredient is less than the first preset purchase threshold, or when the current inventory of the target ingredient is greater than or equal to the first preset inventory threshold, the preset adjustment coefficient is negatively adjusted to obtain the target adjustment coefficient.
[0049] In one specific embodiment, if the historical purchase volume of the target ingredient changes more than zero across multiple historical periods (i.e., the historical purchase volume increases continuously), then the adjustment coefficient needs to be increased. For example, the preset adjustment coefficient can be increased by a first preset fixed increment, or it can be obtained by multiplying the preset adjustment coefficient by a second preset fixed increment. Conversely, if the historical purchase volume of the target ingredient is less than a first preset purchase threshold across multiple historical periods, or the current inventory of the target ingredient is greater than or equal to a first preset inventory threshold (i.e., the historical purchase volume is low or there has been no continuous purchase), or the current inventory has not been short for a long time, then the adjustment coefficient needs to be decreased. For example, the preset adjustment coefficient can be decreased by a third preset fixed increment, or it can be obtained by multiplying the preset adjustment coefficient by a fourth preset fixed increment. Specifically, the preset adjustment coefficient, the first preset fixed increment, the second preset fixed increment, the third preset fixed increment, and the fourth preset fixed increment can be set according to actual application requirements. The preset adjustment coefficient can be set to 1.2, the first and second preset fixed increments are positive values, and the third and fourth preset fixed increments are negative values.
[0050] In practical applications, the preset adjustment coefficient can be set to 1.2 (additionally covering 20% of daily needs), the first preset fixed increment can be set to 0.1, and the third preset fixed increment can be set to -0.05. Based on 1.2, each increment can increase by 0.1 or decrease by 0.05. Optionally, the preset adjustment coefficient can be increased during major holidays (such as the Spring Festival). Specifically, the adjustment increment for holidays can be set according to actual application needs, for example, it can be set to 0.3. Furthermore, an upper and lower limit can be set for the adjustment coefficient according to actual application needs; for example, the upper limit can be set to 2.0, and the lower limit can be set to 1.
[0051] S107: Update the historical consumption of the target ingredient based on the target adjustment coefficient to obtain the demand for the target ingredient.
[0052] In one specific embodiment, the target adjustment coefficient and the historical consumption can be multiplied to obtain the aforementioned demand.
[0053] S109: Determine the target purchase quantity of the target ingredient based on the difference between the demand for the target ingredient and the current inventory.
[0054] In one specific embodiment, the target purchase quantity can be determined by the difference between the demand for the target ingredient and the current inventory. Alternatively, the difference between the demand for the target ingredient and the current inventory can be rounded up, and the larger of the difference between the rounded difference and zero can be used as the target purchase quantity.
[0055] Specifically, the target purchase quantity can be determined using the following formula: R = max(0,ceil(B×k) S)) Where R represents the target purchase quantity, B represents the historical consumption quantity, k represents the target adjustment coefficient, S represents the current inventory quantity, and ceil() represents rounding up.
[0056] S111: Generate procurement suggestions based on the target procurement quantity of the target ingredients, so that users can purchase the target ingredients based on the target procurement quantity.
[0057] In one specific embodiment, the procurement suggestion may include the target ingredients and the corresponding target procurement quantity, and may also include the current inventory of the target ingredients, so that users can choose whether to make the purchase according to their own needs.
[0058] Optionally, after determining the target purchase quantity of the target ingredient based on the difference between the demand and current inventory of the target ingredient, the above method may further include: Obtain the historical number of times users ignored purchase suggestions for the target ingredients; If the number of times the target ingredient has been ignored in the past exceeds a preset threshold, determine the procurement attenuation information corresponding to the number of times the ingredient has been ignored in the past. The target purchase quantity of the target ingredient is updated based on the purchase attenuation information to obtain the updated purchase quantity of the target ingredient.
[0059] In practical applications, procurement suggestions can be displayed on the client side. Target ingredients can be sorted and recommended to users (e.g., by sorting ingredients according to their target purchase quantity from largest to smallest). A user selection mechanism can be provided, allowing users to choose to accept or ignore any ingredient's procurement suggestion based on their needs, and perform corresponding actions on the client side. The number of times a user ignores a procurement suggestion for each ingredient is recorded. If the number of times a procurement suggestion for an ingredient is ignored exceeds a preset threshold, the recommendation level of that target ingredient can be reduced. For example, the target purchase quantity of the target ingredient can be reduced, or the position weight of the target ingredient in the procurement recommendation list displayed to the user can be lowered. Specifically, procurement attenuation information can be used to represent the degree of reduction in the target purchase quantity of an ingredient, or the degree of reduction in the position weight of an ingredient. Procurement attenuation information can also be used to represent the decrease in the position of an ingredient in the procurement recommendation list. The preset threshold can be set according to actual application needs, for example, it can be set to 3.
[0060] In one specific embodiment, the procurement attenuation information of the target ingredient can be multiplied by the target procurement quantity to obtain the procurement quantity that needs to be reduced. The updated procurement quantity is then determined based on the difference between the target procurement quantity and the procurement quantity that needs to be reduced. Optionally, when the procurement attenuation information represents a decrease in the position of the ingredient in the procurement recommendation list, if the historical ignore count corresponding to the target ingredient exceeds a preset threshold, the procurement attenuation information can be reduced to decrease the position of the target ingredient in the procurement recommendation list, thus obtaining the updated position of the ingredient in the procurement recommendation list.
[0061] Optionally, if the number of times a purchase recommendation for any ingredient is ignored exceeds a preset threshold, and the ingredient is depleted and has not been replenished recently, then the purchase request for that ingredient will be invalidated. If any ingredient is ranked low in the purchase recommendation list, below a preset position threshold, and the inventory of that ingredient remains zero for multiple periods, then the recommendation for that ingredient will be stopped. A confirmation mechanism can be provided to allow users to make a choice, such as "We detected that you have not purchased eggs recently, do you want to stop the reminder?" The options could include pausing for 1 month, permanently disabling, or continuing to remind.
[0062] Accordingly, the above-mentioned procurement recommendations based on the target purchase quantity of the target ingredient may include: Purchase recommendations are generated based on the updated purchase volume of the target ingredients, enabling users to purchase the target ingredients based on the updated purchase volume.
[0063] As can be seen from the technical solutions provided in the embodiments of this specification above, the food management method provided in this specification first obtains historical procurement information, historical consumption information, and current inventory of various food ingredients in the food storage equipment; the historical procurement information includes historical procurement quantity and historical procurement frequency, and the historical consumption information includes historical consumption quantity and historical consumption rate; based on the historical procurement frequency and historical consumption rate of each food ingredient, a target food ingredient is determined from the various food ingredients; based on the historical procurement quantity of the target food ingredient, a target adjustment coefficient for the target food ingredient is determined; based on the target adjustment coefficient, the historical consumption quantity of the target food ingredient is updated to obtain the demand quantity of the target food ingredient; based on the difference information between the demand quantity of the target food ingredient and the current inventory, the target procurement quantity of the target food ingredient is determined; and based on the target procurement quantity of the target food ingredient, a procurement suggestion is generated. This improves the accuracy of the procurement suggestion and thus enhances the intelligence of food management.
[0064] This invention also provides a food ingredient management device, such as... Figure 4 As shown, the device, deployed in a food storage facility, includes: The first acquisition module 410 is used to acquire historical purchase information, historical consumption information and current inventory of various ingredients in the food storage device; the historical purchase information includes historical purchase quantity and historical purchase frequency, and the historical consumption information includes historical consumption quantity and historical consumption rate. The target ingredient determination module 420 is used to determine the target ingredient from the multiple ingredients based on the historical purchase frequency and historical consumption rate of each ingredient; The adjustment coefficient determination module 430 is used to determine the target adjustment coefficient of the target ingredient based on the historical purchase volume of the target ingredient; The demand determination module 440 is used to update the historical consumption of the target ingredient based on the target adjustment coefficient to obtain the demand of the target ingredient; The target purchase quantity determination module 450 is used to determine the target purchase quantity of the target ingredient based on the difference information between the demand for the target ingredient and the current inventory. The procurement suggestion generation module 460 is used to generate procurement suggestions based on the target procurement quantity of the target ingredient, so that the user can purchase the target ingredient based on the target procurement quantity.
[0065] Optionally, the adjustment coefficient determination module 430 includes: A positive adjustment unit is used to positively adjust a preset adjustment coefficient when the change in the historical purchase volume of the target ingredient is greater than zero in multiple historical periods, so as to obtain the target adjustment coefficient. A negative adjustment unit is used to negatively adjust the preset adjustment coefficient in the multiple historical periods when the historical purchase volume of the target ingredient is less than a first preset purchase threshold, or the current inventory of the target ingredient is greater than or equal to a first preset inventory threshold, so as to obtain the target adjustment coefficient.
[0066] Optionally, the target ingredient determination module 420 includes: A preferred ingredient determination unit is used to determine preferred ingredients from the multiple ingredients based on the historical purchase frequency and historical consumption rate of each ingredient. The seasonal matching information determination unit is used to determine the seasonal matching information of the preferred ingredients based on the historical purchase frequency of the preferred ingredients and preset seasonal parameters; the seasonal matching information is used to characterize the degree of seasonal matching of the preferred ingredients. The first target ingredient determination unit is used to determine the preferred ingredients whose seasonal matching information is greater than or equal to a preset matching threshold and whose current inventory is less than a second preset inventory threshold as the target ingredients.
[0067] Optionally, the target ingredient determination module 420 includes: A preferred ingredient determination unit is used to determine preferred ingredients from the multiple ingredients based on the historical purchase frequency and historical consumption rate of each ingredient. The initial predicted consumption unit is used to calculate the initial predicted consumption of the preferred food based on the historical consumption sequence of the preferred food in multiple historical periods and the current inventory. The target predicted consumption unit is used to correct the initial predicted consumption based on the festival influence factor and seasonal influence factor corresponding to the preferred food ingredients, so as to obtain the target predicted consumption of the preferred food ingredients. The supply duration determination unit is used to determine the supply duration of the preferred ingredients based on the target predicted consumption and current inventory of the preferred ingredients. The second target ingredient determination unit is used to determine the preferred ingredients whose supply time is less than or equal to a preset time threshold as the target ingredients.
[0068] Optionally, the preferred ingredient determination unit includes: The first preferred ingredient determination unit is used to determine the preferred ingredients among the various ingredients whose historical purchase frequency is greater than or equal to a second preset purchase threshold and whose historical consumption rate is greater than or equal to a preset consumption threshold.
[0069] Optionally, the preferred ingredient determination unit includes: The associated ingredient combination identification unit is used to identify multiple associated ingredient combinations from the multiple ingredients based on the degree of association between the multiple ingredients; The target associated food ingredient combination determination unit is used to determine the target associated food ingredient combination from the plurality of associated food ingredient combinations based on the historical purchase frequency and historical consumption rate of each associated food ingredient combination; The second preferred ingredient determination unit is used to determine the ingredients in the target associated ingredient combination as the preferred ingredients.
[0070] Optionally, the device further includes: The second acquisition module is used to acquire the historical number of times the user ignored the purchase suggestion for the target ingredient. The procurement attenuation information determination module is used to determine the procurement attenuation information corresponding to the historical number of times the target ingredient is ignored is greater than a preset number threshold. The update module is used to update the target purchase quantity of the target ingredient based on the purchase attenuation information, so as to obtain the updated purchase quantity of the target ingredient. Accordingly, the procurement suggestion generation module 460 includes: The procurement suggestion generation unit is used to generate procurement suggestions based on the updated procurement quantity of the target ingredient, so that the user can purchase the target ingredient based on the updated procurement quantity.
[0071] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.
[0072] This invention also provides a food ingredient management system, such as... Figure 5 As shown, the system includes a sensing module 510, a control unit 520, and a client 530. The sensing module 510 is installed in the food storage device. The sensing module 510 and the client 530 are respectively connected to the control unit 520. The sensing module 510 is used to identify each type of food and sense the weight of each type of food. The client 530 is used to receive purchasing suggestions. The control unit 520 is used to execute the above-mentioned food management method.
[0073] Specifically, the sensing module 510 may include a weight sensing module and an image acquisition module. The image acquisition module is used to identify each type of food in the food storage device, and the weight sensing module is used to sense the weight of each type of food, thereby determining the current inventory, consumption and purchase quantity of each type of food.
[0074] Specifically, the client 530 may include, but is not limited to, electronic devices such as smartphones, desktop computers, tablets, laptops, smart speakers, digital assistants, augmented reality (AR) / virtual reality (VR) devices, smart wearable devices, in-vehicle terminals, and smart TVs; it may also be software running on the aforementioned electronic devices, such as applications or mini-programs. The operating system running on the electronic device in this embodiment may include, but is not limited to, Android, iOS, Linux, and Windows systems.
[0075] In this embodiment of the specification, the sensing module 510 connects to the system wirelessly (Wi-Fi / BLE) and transmits the collected food images and food weight information to the control unit 520 (MCU) via a serial communication link. The control unit 520 identifies each type of food based on the food images and determines the current inventory based on the food weight information. At the same time, it can obtain the historical consumption information and historical purchase information of each type of food stored in the system. Based on the above-mentioned food management method, it generates a food purchase suggestion and sends it to the client 530 so that the user can purchase food based on the purchase quantity in the purchase suggestion.
[0076] In addition, it should be noted that, Figure 5 The diagram shown is merely a schematic representation of a food ingredient management system, and the embodiments described in this specification are not limited to the above.
[0077] Optionally, the system also includes a cloud 540, which is connected to the control unit 520. The cloud 540 is used to store the correspondence between each ingredient and preset seasonal parameters.
[0078] Specifically, Cloud 540 can be a cloud server providing cloud computing services. Cloud 540 can store information on seasonal ingredients, such as the correspondence between each ingredient and preset seasonal parameters. Based on this correspondence, the control unit can determine the degree of seasonal matching between the user's preferred ingredients among various ingredients in the ingredient storage device, thereby filtering out ingredients that both meet the user's dietary preferences and are suitable for the current season. Then, based on the inventory and consumption of these ingredients, it can generate purchasing suggestions and send them to the client.
[0079] Regarding the food management system in the above embodiments, the specific methods by which each module performs its operations have been described in detail in the embodiments of the food management method, and will not be elaborated here.
[0080] This application embodiment can divide the control unit into functional units based on the above examples. For example, each function can be divided into its own functional unit, or two or more functions can be integrated into one processing unit. The integrated modules can be implemented in hardware or as software functional modules. Optionally, the module division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.
[0081] like Figure 6 As shown in the diagram, this application embodiment also provides a schematic diagram of a control unit 520. The control unit 520 includes a processor 610, and optionally, also includes a memory 620 and a communication interface 630 connected to the processor 610. The processor 610, memory 620, and communication interface 630 are connected via a bus 640.
[0082] Processor 610 may be a central processing unit (CPU), a general-purpose processor, a network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller unit, a programmable logic device (PLD), or any combination thereof. Processor 610 may also be any other device with processing capabilities, such as a circuit, device, or software module. Processor 610 may also include multiple CPUs, and processor 610 may be a single-core processor. CPU) processor, or multi-core (multi) CPU (Processor). Here, "processor" can refer to one or more devices, circuits, or processing cores used to process data (such as computer program instructions).
[0083] Memory 620 may be read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, random access memory (RAM) or other types of dynamic storage devices capable of storing information and instructions, or electrically erasable programmable read-only memory. EEPROM (Electronic EPROM) and CD-ROM (Compact Disc Read-Only Memory, CD) The memory 620 can be a ROM or other optical disc storage, optical disk storage (including compressed optical disks, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer. This application embodiment does not impose any limitations on this. The memory 620 can exist independently or be integrated with the processor 610. The memory 620 may contain computer program code. The processor 610 executes the computer program code stored in the memory 620 to implement the control flow provided in this application embodiment.
[0084] The communication interface 630 can be used to communicate with other devices or communication networks (such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.). The communication interface 630 can be a module, circuit, transceiver, or any device capable of enabling communication.
[0085] Bus 640 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. Bus 640 can be divided into address bus, data bus, control bus, etc.
[0086] Figure 7 This is a block diagram illustrating a terminal electronic device for food ingredient management according to an exemplary embodiment. The electronic device can be a terminal, and its internal structure diagram can be as follows: Figure 7 As shown, the electronic device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a food management method. The display screen can be a liquid crystal display (LCD) or an e-ink display. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the device's casing, or an external keyboard, touchpad, or mouse.
[0087] Figure 8This is a block diagram illustrating a server electronic device for food ingredient management according to an exemplary embodiment. The electronic device may be a server, and its internal structure diagram may be as follows: Figure 8 As shown, the electronic device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a food ingredient management method.
[0088] Those skilled in the art will understand that Figure 7 or Figure 8 The structures shown are merely block diagrams of some structures related to the disclosed solutions of this invention, and do not constitute a limitation on the electronic devices to which the disclosed solutions of this invention are applied. Specific electronic devices may include more or fewer components than those shown in the figures, or combine certain components, or have different component arrangements.
[0089] In an exemplary embodiment, an electronic device for food ingredient management is also provided. The electronic device includes a processor and a memory, the memory storing at least one instruction, which is loaded and executed by the processor to implement the food ingredient management method as disclosed in the embodiments of the present invention.
[0090] In an exemplary embodiment, a computer-readable storage medium is also provided, which stores at least one instruction, which is loaded and executed by a processor to implement the food ingredient management method in the disclosed embodiments of the present invention.
[0091] In an exemplary embodiment, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute the food ingredient management method in the disclosed embodiments of the present invention.
[0092] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.
[0093] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles disclosed herein and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.
[0094] It should be understood that the present invention is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is limited only by the appended claims.
Claims
1. A method for managing food ingredients, characterized in that, The method includes: Acquire historical purchase information, historical consumption information, and current inventory of various ingredients in food storage equipment; the historical purchase information includes historical purchase quantity and historical purchase frequency, and the historical consumption information includes historical consumption quantity and historical consumption rate. Based on the historical procurement frequency and historical consumption rate of each ingredient, the target ingredient is determined from the multiple ingredients; The target adjustment coefficient for the target ingredient is determined based on its historical purchase volume. The historical consumption of the target ingredient is updated based on the target adjustment coefficient to obtain the demand for the target ingredient; Based on the difference between the demand for the target ingredient and the current inventory, the target purchase quantity of the target ingredient is determined; Purchase recommendations are generated based on the target purchase quantity of the target ingredient, so that users can purchase the target ingredient based on the target purchase quantity.
2. The method according to claim 1, characterized in that, The step of determining the target adjustment coefficient for the target ingredient based on its historical purchase volume includes: In multiple historical periods, if the change in the historical purchase volume of the target ingredient is greater than zero, the preset adjustment coefficient is positively adjusted to obtain the target adjustment coefficient. In the multiple historical periods, if the historical purchase volume of the target ingredient is less than the first preset purchase threshold, or if the current inventory of the target ingredient is greater than or equal to the first preset inventory threshold, the preset adjustment coefficient is negatively adjusted to obtain the target adjustment coefficient.
3. The method according to claim 1, characterized in that, The process of determining the target ingredient from the multiple ingredients based on the historical purchase frequency and the historical consumption rate includes: Based on the historical purchase frequency and historical consumption rate of each ingredient, the preferred ingredients are determined from the multiple ingredients; Based on the historical purchasing frequency of the preferred ingredients and preset seasonal parameters, the seasonal matching information of the preferred ingredients is determined; the seasonal matching information is used to characterize the degree of seasonal matching of the preferred ingredients. The preferred ingredients whose seasonal matching information is greater than or equal to a preset matching threshold and whose current inventory is less than a second preset inventory threshold are determined as the target ingredients.
4. The method according to claim 1, characterized in that, The process of determining the target ingredient from the multiple ingredients based on the historical purchase frequency and the historical consumption rate includes: Based on the historical purchase frequency and historical consumption rate of each ingredient, the preferred ingredients are determined from the multiple ingredients; Based on the historical consumption sequence of the preferred ingredients in multiple historical periods and the current inventory, the initial predicted consumption of the preferred ingredients is calculated. Based on the festival and seasonal factors corresponding to the preferred ingredients, the initial predicted consumption is corrected to obtain the target predicted consumption of the preferred ingredients. Based on the target predicted consumption and current inventory of the preferred ingredients, the supply duration of the preferred ingredients is determined; The preferred ingredients whose supply time is less than or equal to a preset time threshold are identified as the target ingredients.
5. The method according to claim 3 or 4, characterized in that, The process of determining preferred ingredients from among the various ingredients based on the historical purchase frequency and historical consumption rate of each ingredient includes: Among the various ingredients, those whose historical purchase frequency is greater than or equal to a second preset purchase threshold and whose historical consumption rate is greater than or equal to a preset consumption threshold are identified as the preferred ingredients.
6. The method according to claim 3 or 4, characterized in that, The process of determining preferred ingredients from among the various ingredients based on the historical purchase frequency and historical consumption rate of each ingredient includes: Based on the degree of correlation between the various ingredients, multiple related ingredient combinations are identified from the various ingredients; Based on the historical purchase frequency and historical consumption rate of each associated food combination, a target associated food combination is determined from the plurality of associated food combinations; The ingredients in the target associated ingredient combination are identified as the preferred ingredients.
7. The method according to claim 1, characterized in that, After determining the target purchase quantity of the target ingredient based on the difference between the demand and current inventory of the target ingredient, the method further includes: Obtain the historical number of times the user ignored the purchase suggestion for the target ingredient; If the number of times the target ingredient has been ignored in the past exceeds a preset threshold, the procurement attenuation information corresponding to the number of times the ingredient has been ignored is determined. The target purchase quantity of the target ingredient is updated based on the purchase attenuation information to obtain the updated purchase quantity of the target ingredient. Accordingly, the process of generating procurement recommendations based on the target purchase quantity of the target ingredient includes: Purchase recommendations are generated based on the updated purchase volume of the target ingredient, so that the user can purchase the target ingredient based on the updated purchase volume.
8. A food ingredient management device, characterized in that, The device includes: The first acquisition module is used to acquire historical purchase information, historical consumption information and current inventory of various ingredients in the food storage equipment; the historical purchase information includes historical purchase quantity and historical purchase frequency, and the historical consumption information includes historical consumption quantity and historical consumption rate. The target ingredient determination module is used to determine the target ingredient from the multiple ingredients based on the historical purchase frequency and historical consumption rate of each ingredient; The adjustment coefficient determination module is used to determine the target adjustment coefficient of the target ingredient based on the historical purchase volume of the target ingredient; The demand determination module is used to update the historical consumption of the target ingredient based on the target adjustment coefficient to obtain the demand of the target ingredient. The target purchase quantity determination module is used to determine the target purchase quantity of the target ingredient based on the difference between the demand for the target ingredient and the current inventory. The procurement suggestion generation module is used to generate procurement suggestions based on the target procurement quantity of the target ingredient, so that the user can purchase the target ingredient based on the target procurement quantity.
9. A food ingredient management system, characterized in that, The system includes a sensing module, a control unit, a cloud platform, and a client. The sensing module is installed in the food storage device, and the sensing module, the cloud platform, and the client are all communicatively connected to the control unit. The sensing module is used to identify each type of ingredient and sense the weight of each type of ingredient; the client is used to receive the purchasing suggestions; and the control unit is used to execute the ingredient management method as described in any one of claims 1 to 7.
10. The system according to claim 9, characterized in that, The system also includes a cloud platform, which is communicatively connected to the control unit. The cloud platform is used to store the correspondence between each ingredient and preset seasonal parameters.