Household consumption identification device based on AI algorithm

Abstract

The invention discloses a household consumption identification device based on an AI algorithm, and particularly relates to the xx field, the household consumption identification device comprises a hardware component and an identification system, and the hardware component is connected and matched with the identification system; the hardware assembly comprises a camera, a microphone, a sensor and a touch screen, the camera is used for capturing an image of an article at home, the microphone is used for capturing voice information related to consumption and detecting the moving state change of the article in real time, and the touch screen is used for displaying consumption data, suggestions and analysis results; the recognition system comprises an image recognition module, a natural language processing module, an intelligent learning module and a data storage module, the image recognition module is used for recognizing various consumption items and classifying the consumption items, and the natural language processing module is used for analyzing voice information. According to the invention, family members can more accurately know own consumption habits, make more intelligent consumption decisions and more effectively manage family finance.

Description

Technical Field

[0001] The present invention relates to the field of information processing technology, and more specifically, to a household consumption identification device based on an AI algorithm. Background Art

[0002] In the context of the rapid development of smart homes, household consumer identification devices, as an important part of smart home systems, have a direct impact on the user's life experience due to their functionality and accuracy. With the continuous advancement of artificial intelligence technology, AI algorithms are increasingly being used in household consumer identification devices, greatly improving the performance of the devices and user experience. However, there are still some problems and challenges in the technical implementation and application of existing household consumer identification devices, which to some extent limit the development and application of the devices.

[0003] However, when the existing household consumption identification device is not in use, it can only identify household consumer items and count daily consumption, and cannot predict future consumption trends based on the consumption habits and consumption data of family members, so it cannot provide shopping suggestions and product recommendations to users, and cannot help families set and manage consumption budgets and provide budget overspending warnings. As a result, users cannot get a good consumption experience and are prone to consumption waste. Therefore, a household consumption identification device based on AI algorithm is proposed. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a household consumption identification device based on AI algorithm, which can more accurately understand one's own consumption habits, make more wise consumption decisions, and manage household finances more effectively to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a household consumption identification device based on AI algorithm, comprising a hardware component and an identification system, wherein the hardware component is connected and cooperated with the identification system; The hardware components include a camera, a microphone, a sensor and a touch screen, wherein the camera is used to capture images of items at home, the microphone is used to capture voice information related to consumption, the sensor is used to detect the change of the moving state of items in real time, and the touch screen is used to display consumption data, suggestions and analysis results; The recognition system includes an image recognition module, a natural language processing module, an intelligent learning module and a data storage module. The image recognition module is used to recognize and classify various consumer items. The natural language processing module is used to analyze voice information and recognize items in a shopping list. The intelligent learning module is used to extract historical consumption data, learn the consumption habits of family members, predict future consumption trends, and generate personalized recommendations. The data storage module is used to store the collected data in a database.

[0006] Preferably, a mobile device is also included, and the mobile device can be a mobile phone. The camera, microphone and touch screen are all hardware installed on the mobile phone, and the sensor is installed in furniture or storage container.

[0007] Preferably, the image recognition module includes an image processing unit, an image classification unit and a statistical unit. The image processing unit is used to perform image processing on consumer items photographed by the camera, the image classification unit is used to classify consumer items photographed by the camera, and the statistical unit is used to record information such as the quantity, brand, type, etc. of each item.

[0008] Preferably, the natural speech processing module includes a speech capturing unit, a speech data removal unit and a speech data recording unit, the speech capturing unit is used to capture the speech information of family members, the speech data removal unit is used to exclude the speech data other than the shopping information, and the speech data recording unit is used to record the items in the shopping list and the shopping intentions.

[0009] Preferably, the intelligent learning module includes a calling unit, a learning unit, a prediction unit and a suggestion unit, wherein the calling unit is used to call historical consumption data, the learning unit is used to learn the consumption habits of family members, the prediction unit is used to predict future consumption trends, and the suggestion unit is used to generate personalized shopping suggestions.

[0010] Preferably, the recognition system further includes a consumption habit analysis module, an inventory monitoring and early warning module and a budget management module, wherein the inventory monitoring and early warning module is connected and cooperated with a sensor.

[0011] Preferably, the consumption habit analysis module is connected and cooperated with the learning unit, and the consumption habit analysis module is used to analyze the consumption habits of family members, such as purchase frequency, preferred brand, purchase time, etc.

[0012] Preferably, a threshold adjustment unit is provided in the inventory monitoring and early warning module, and the threshold adjustment unit is connected and cooperated with the statistical unit to detect the inventory of items in real time, and automatically issue an early warning notification when the inventory is lower than a preset threshold.

[0013] Preferably, the budget management module includes a fund recording unit, a fund consumption setting unit and an overspending warning unit, wherein the fund recording unit is used to record total funds, the fund consumption setting unit is used to set a consumption budget, and the overspending warning unit is used to warn of budget overspending.

[0014] A computing program for realizing the household consumption identification device based on AI algorithm.

[0015] Technical effects and advantages of the present invention: The present invention proposes a household consumption identification device based on an AI algorithm. Through the settings of an image recognition module, a natural language processing module, an intelligent learning module, and a data storage module, a family can understand their consumption habits more accurately, make more intelligent consumption decisions, and manage family finances more effectively. At the same time, the settings of sensors, consumption habit analysis modules, inventory monitoring and early warning modules, and budget management modules can timely discover the consumption of household daily necessities, replenish them in time, and during the shopping process, timely issue overspending warnings for family members' consumption to avoid excessive consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the overall structure of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] As attached Figure 1 A household consumption identification device based on an AI algorithm is shown, comprising a hardware component and an identification system, wherein the hardware component is connected and cooperated with the identification system; The hardware components include a camera, a microphone, a sensor and a touch screen, wherein the camera is used to capture images of items at home, the microphone is used to capture voice information related to consumption, the sensor is used to detect the change of the moving state of items in real time, and the touch screen is used to display consumption data, suggestions and analysis results; The recognition system includes an image recognition module, a natural language processing module, an intelligent learning module and a data storage module. The image recognition module is used to recognize and classify various consumer items. The natural language processing module is used to analyze voice information and recognize items in a shopping list. The intelligent learning module is used to extract historical consumption data, learn the consumption habits of family members, predict future consumption trends, and generate personalized recommendations. The data storage module is used to store the collected data in a database.

[0019] During specific implementation, consumer items are photographed through a camera, and the image recognition module recognizes and classifies the photographed images, and records the quantity, brand, type and other information of each classified item. At the same time, the microphone receives the voice of the user, and the natural speech processing module analyzes the voice information of the user, excludes information other than shopping information, organizes the shopping information, and identifies the items that the user needs to purchase. At the same time, it cooperates with the image recognition module to scan the shopping list and determine the shopping list. The intelligent learning module extracts the historical shopping data stored in the data storage module, learns the consumption habits of family members, and predicts future consumption trends, so as to make reasonable shopping suggestions to the user based on the shopping list.

[0020] According to one embodiment of the present invention, a mobile device is also included, and the mobile device can be a mobile phone. The camera, microphone and touch screen are all hardware installed on the mobile phone, and the sensor is installed in furniture or storage container.

[0021] In specific implementation, users can directly identify and record consumer items through their mobile phones, and can directly view the displayed consumption data, suggestions and analysis results on the touch screen. By installing sensors in furniture or consumer item storage containers, the consumption of household items can be detected in real time.

[0022] According to one embodiment of the present invention, the image recognition module includes an image processing unit, an image classification unit and a statistical unit. The image processing unit is used to perform image processing on consumer items photographed by a camera, the image classification unit is used to classify consumer items photographed by the camera, and the statistical unit is used to record information such as the quantity, brand, type, etc. of each item.

[0023] In specific implementation, the image processing unit performs image processing on the consumer items photographed by the camera, and then the image classification unit classifies the consumer items photographed by the camera. Finally, the statistical unit records the quantity, brand, type and other information of each item, so as to determine the consumption of each item in the household.

[0024] According to one embodiment of the present invention, the natural speech processing module includes a speech capturing unit, a speech data removing unit and a speech data recording unit, the speech capturing unit is used to capture the speech information of family members, the speech data removing unit is used to exclude the speech data other than the shopping information, and the speech data recording unit is used to record the items in the shopping list and the shopping intentions.

[0025] In specific implementation, the voice information of family members is captured by the voice capture unit, and then the voice data removal unit is used to eliminate the voice data other than the shopping information, extract the shopping information, and finally the voice data recording unit records the items in the shopping list and the shopping intention.

[0026] According to one embodiment of the present invention, the intelligent learning module includes a calling unit, a learning unit, a prediction unit and a suggestion unit, the calling unit is used to call historical consumption data, the learning unit is used to learn the consumption habits of family members, the prediction unit is used to predict future consumption trends, and the suggestion unit is used to generate personalized shopping suggestions.

[0027] In specific implementation, the historical consumption data is called by the calling unit, and then the learning unit learns the consumption habits of family members, so as to cooperate with the prediction unit to predict future consumption trends. Finally, the suggestion unit is used to generate personalized shopping suggestions based on the consumption habits of family members, so that family members can clearly know the items they need to buy, avoid blind consumption, and shop reasonably.

[0028] According to an embodiment of the present invention, the recognition system further includes a consumption habit analysis module, an inventory monitoring and early warning module and a budget management module, wherein the inventory monitoring and early warning module is connected and cooperated with a sensor.

[0029] According to one embodiment of the present invention, the consumption habit analysis module is connected and cooperated with the learning unit, and the consumption habit analysis module is used to analyze the consumption habits of family members, such as purchase frequency, preferred brands, purchase time, etc.

[0030] In specific implementation, the consumption habits of family members are analyzed through the consumption habit analysis module, and the consumption habits of family members are learned using the learning unit, so as to determine the purchase frequency, preferred brands, purchase time, etc. of family members, so as to make reasonable shopping suggestions and plans for family members, so that users can accurately purchase the required items, avoid overconsumption, and save shopping time.

[0031] According to one embodiment of the present invention, a threshold adjustment unit is provided in the inventory monitoring and warning module, and the threshold adjustment unit is connected and cooperated with the statistical unit to detect the inventory level of the items in real time, and automatically issues a warning notification when the inventory is lower than a preset threshold.

[0032] In specific implementation, sensors are used to detect the usage of household items. When the items are about to be used up and reach the number set by the threshold adjustment unit, family members are promptly warned so that they can purchase and replenish household items in time.

[0033] According to one embodiment of the present invention, the budget management module includes a fund recording unit, a fund consumption setting unit and an overspending warning unit, wherein the fund recording unit is used to record the total funds, the fund consumption setting unit is used to set the consumption budget, and the overspending warning unit is used to warn of budget overspending.

[0034] In specific implementation, when family members shop, the total funds of the user are recorded through the fund recording unit, and the consumption budget is set in conjunction with the fund consumption setting unit. When the consumption during the shopping process exceeds the budget, the overspending warning unit will issue a warning of budget overspending, thereby avoiding overspending by family members and making reasonable planning and utilization of funds.

[0035] An operation program for realizing the household consumption identification device based on AI algorithm is used to run the entire identification system.

[0036] Finally, a few points should be explained: First, in the description of the present invention, it should be noted that, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, which may refer to mechanical connection or electrical connection, or internal communication between two components, or direct connection. "upper", "lower", "left", "right", etc. are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may change; Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other; Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A household consumption identification device based on AI algorithm, characterized by: It includes a hardware component and an identification system, wherein the hardware component is connected and cooperated with the identification system; The hardware components include a camera, a microphone, a sensor and a touch screen, wherein the camera is used to capture images of items at home, the microphone is used to capture voice information related to consumption, the sensor is used to detect the change of the moving state of items in real time, and the touch screen is used to display consumption data, suggestions and analysis results; The recognition system includes an image recognition module, a natural language processing module, an intelligent learning module and a data storage module. The image recognition module is used to recognize and classify various consumer items. The natural language processing module is used to analyze voice information and recognize items in a shopping list. The intelligent learning module is used to extract historical consumption data, learn the consumption habits of family members, predict future consumption trends, and generate personalized recommendations. The data storage module is used to store the collected data in a database.

2. A household consumption identification device based on AI algorithm according to claim 1, characterized in that: It also includes a mobile device, which can be a mobile phone. The camera, microphone and touch screen are all hardware installed on the mobile phone, and the sensor is installed in furniture or storage containers.

3. A household consumption identification device based on AI algorithm according to claim 2, characterized in that: The image recognition module includes an image processing unit, an image classification unit and a statistical unit. The image processing unit is used to perform image processing on consumer items photographed by a camera, the image classification unit is used to classify consumer items photographed by the camera, and the statistical unit is used to record information such as the quantity, brand, type, etc. of each item.

4. The household consumption identification device based on AI algorithm according to claim 3, characterized in that: The natural speech processing module includes a speech capturing unit, a speech data removing unit and a speech data recording unit. The speech capturing unit is used to capture the speech information of family members, the speech data removing unit is used to exclude speech data other than shopping information, and the speech data recording unit is used to record the items in the shopping list and the shopping intention.

5. A household consumption identification device based on AI algorithm according to claim 4, characterized in that: The intelligent learning module includes a calling unit, a learning unit, a prediction unit and a suggestion unit. The calling unit is used to call historical consumption data, the learning unit is used to learn the consumption habits of family members, the prediction unit is used to predict future consumption trends, and the suggestion unit is used to generate personalized shopping suggestions.

6. A household consumption identification device based on AI algorithm according to claim 5, characterized in that: The recognition system also includes a consumption habit analysis module, an inventory monitoring and early warning module and a budget management module, wherein the inventory monitoring and early warning module is connected and coordinated with the sensor.

7. A household consumption identification device based on AI algorithm according to claim 6, characterized in that: The consumption habit analysis module is connected and cooperated with the learning unit, and the consumption habit analysis module is used to analyze the consumption habits of family members, such as purchase frequency, preferred brands, purchase time, etc.

8. The household consumption identification device based on AI algorithm according to claim 7, characterized in that: The inventory monitoring and early warning module is provided with a threshold adjustment unit, which is connected and cooperated with the statistical unit to detect the inventory of items in real time. When the inventory is lower than a preset threshold, an early warning notification is automatically issued.

9. A household consumption identification device based on AI algorithm according to claim 8, characterized in that: The budget management module includes a fund recording unit, a fund consumption setting unit and an overspending warning unit. The fund recording unit is used to record total funds, the fund consumption setting unit is used to set a consumption budget, and the overspending warning unit is used to warn of budget overspending.

10. An operation program for realizing the household consumption identification device based on AI algorithm as described in claim 9.

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