A SMART KITCHEN TRAY SYSTEM FOR REAL-TIME INGREDIENT MONITORING AND AUTOMATED REPLENISHMENT

Abstract

The present invention discloses a smart kitchen tray system (100) designed for real-time monitoring of ingredient levels and automated replenishment through e-commerce integration. The system includes a kitchen tray (102) with multiple compartments (104A-N), each equipped with a load cell (106A-N) positioned beneath the compartments to measure the weight of ingredients. Each load cell (106A-N) converts the weight exerted by the ingredients into electrical signals. A Node MCU (108) processes these signals, determining the remaining quantities based on predefined thresholds. The system interfaces with external devices and e-commerce platforms, allowing for automatic ordering when ingredient levels fall below set thresholds. A user interface (116), accessible via a touch screen or mobile app, provides real-time ingredient data, alerts users when quantities are low, and allows customization of inventory settings. The system offers a streamlined, automated approach to kitchen inventory management, optimizing efficiency and convenience in ingredient monitoring and restocking. FIG. 1

Specification

Description:BACKGROUND
Technical Field
[0001] The present invention pertains to the field of smart home appliances and inventory management systems. Specifically, it relates to a smart kitchen tray system designed for real-time monitoring of ingredient levels and integrated with an e-commerce interface for automatic inventory management and online ordering.
Description of the Related Art
[0002] Effective kitchen inventory management is essential in both households and commercial kitchens to ensure the continuous availability of essential ingredients. Traditionally, tracking ingredient levels has relied on manual checks and frequent grocery store visits, which can be time-consuming and inefficient. Recent advancements in smart home technology have introduced various IoT-based solutions for kitchen inventory monitoring, aimed at simplifying this process. However, many of these solutions are limited in scope and functionality. For instance, some focus specifically on appliances like refrigerators, while others offer IoT connectivity for tracking inventory but lack integrated e-commerce capabilities for automated ordering. Existing systems often address either inventory tracking or e-commerce integration independently, but rarely both in a single device. Many prior solutions, such as smart refrigerators and IoT-enabled kitchen scales, lack the versatility and adaptability needed to monitor a wide variety of ingredients.
[0003] Therefore, there arises a need to address the aforementioned technical drawbacks in existing technologies by providing a smart kitchen tray system that combines real-time inventory monitoring with seamless e-commerce integration.
SUMMARY OF THE INVENTION
[0004] The first aspect of the present invention provides a smart kitchen tray system for real-time ingredient monitoring and automated replenishment. The system includes a kitchen tray with a plurality of compartments designed to hold a plurality of containers filled with ingredients. A plurality of load cells are integrated into the kitchen tray and positioned under the plurality of compartments. Each load cell is configured to measure the weight of ingredients. The load cells convert the weight exerted by the ingredients into electrical signals. An amplifier is coupled to the plurality of load cells that amplifies the electrical signals generated by the load cells to ensure accurate weight measurements. A node MCU is configured to receive amplified weight data from the amplifier and processing the data to (i) determine the remaining quantity of the ingredients in the plurality of containers based on predefined thresholds, and (ii) connect with external devices and e-commerce platforms for automated ordering of ingredients when the ingredients level fall below the set thresholds. A user interface is connected to the node MCU. The user interface displays real-time ingredient levels, triggers alerts when ingredient levels fall below set thresholds, and enables users to manage inventory settings.
[0005] In some embodiments, the node MCU is configured to automatically generate a shopping list and place the order through the e-commerce platform when the ingredient levels fall below the predefined thresholds.
[0006] In some embodiments, the node MCU is configured to track the ingredient usage patterns over time and provide insights and recommendations for optimizing inventory management.
[0007] In some embodiments, the plurality of load cells are calibrated periodically against a reference scale to ensure accuracy of measurements.
[0008] In some embodiments, each load cell is configured to measure the weight of ingredients based on strain gauge principle.
[0009] In some embodiments, the system includes a power source configured to provide a stable power supply to the kitchen tray system.
[0010] The second aspect of the present invention provides a method for real-time ingredient monitoring and automated replenishment in a smart kitchen tray system. The method includes (i) placing a plurality of containers filled with ingredients into a plurality of compartments on a kitchen tray, the plurality of compartments are positioned over a plurality of load cells, (ii) measuring weight of the ingredients in the plurality of containers by using the plurality of load cells that converts the weight of the ingredients into an electrical signal, (iii) amplifying the electrical signals from the plurality of load cells using an amplifier to ensure accuracy in weight measurements, (iv) receiving the amplified weight data from the amplifier and processing the weight data using a node MCU to determine the remaining quantity of the ingredients in each container based on predefined threshold levels, (v) displaying real-time ingredient levels on a user interface connected to the node MCU triggering alerts when ingredient levels fall below the predefined thresholds, and enabling the user to manage inventory settings via the user interface, and (vi) connecting the node MCU with external devices and e-commerce platforms for automated ordering of the ingredients when the ingredient levels fall below the set thresholds.
[0011] In some embodiments, the method includes automatically generating a shopping list and place the order through the e-commerce platform when the ingredient levels fall below the predefined thresholds.
[0012] In some embodiments, the method includes tracking the ingredient usage patterns over time and provide insights and recommendations for optimizing inventory management.
[0013] In some embodiments, the plurality of load cells are calibrated periodically against a reference scale to ensure accuracy of measurements.
[0014] The advantage of the present invention lies in its ability to streamline kitchen management through an integrated, versatile solution that combines real-time ingredient monitoring, automated ordering, and smart home compatibility. The system's advanced sensing technology and load cells provide accurate, real-time data on ingredient levels, ensuring users to monitor their stock effectively and avoid shortages. Seamless integration with e-commerce platforms enables automatic shopping list generation and direct ordering, reducing manual intervention and ensuring timely replenishment. Additionally, the user-friendly interface allows for easy access to inventory levels, alert settings, and consumption insights, which can help reduce waste and optimize inventory management. The tray's multiple compartments support a wide variety of ingredients, enhancing its flexibility and adaptability in diverse kitchen environments. With energy-efficient operation and options for rechargeable batteries, the smart tray offers a reliable and sustainable approach to automated kitchen inventory management.
[0015] These and other aspects of the embodiments herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood, however, that the following descriptions, while indicating preferred embodiments and numerous specific details thereof, are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the embodiments herein without departing from the spirit thereof, and the embodiments herein include all such modifications.
BRIEF DESCRIPTION OF THE DRAWINGS
[0016] The embodiments herein will be better understood from the following detailed description with reference to the drawings, in which:
[0017] FIG.1 is a smart kitchen tray system for real-time ingredient monitoring and automated replenishment according to some embodiments herein;
[0018] FIG.2 illustrates the exploded view of the kitchen tray of FIG.1 according to some embodiments herein;
[0019] FIGS.3A-C illustrate various views of the kitchen tray of FIG.1 according to some embodiments herein;
[0020] FIG.4 illustrates the load cell of FIG.1 according to some embodiments herein;
[0021] FIG.5 illustrates a method for real-time ingredient monitoring and automated replenishment in a smart kitchen tray system according to some embodiments herein;
[0022] FIG. 6 is a schematic diagram of a computer architecture in accordance with the embodiments herein.
DETAILED DESCRIPTION OF THE DRAWINGS
[0023] The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
[0024] As mentioned, there remains a need to address the aforementioned technical drawbacks in existing technologies by providing a smart kitchen tray system that combines real-time inventory monitoring with seamless e-commerce integration. The system provides a solution that enhances kitchen management by offering a versatile, user-friendly device capable of streamlining inventory control, reducing manual checks, and ensuring that essential ingredients are readily available without the need for frequent store visits. Referring now to the drawings, and more particularly to FIGS. 1 through 6, where similar reference characters denote corresponding features consistently throughout the figures, preferred embodiments are shown.
[0025] FIG.1 is a smart kitchen tray system for real-time ingredient monitoring and automated replenishment according to some embodiments herein. The system 100 include a kitchen tray 102 with a plurality of compartments 104A-N, a plurality of load cells 106A-N, a node MCU 108, an amplifier 110, a power source 112, a plurality of containers 114A-N, a user interface 116 and a communication network 118. The plurality of load cells 106A-N are integrated into the kitchen tray 102 and are placed strategically under the plurality of compartments 104A-N where ingredients are stored.
[0026] The plurality of containers 114A-N filled with the food ingredients are placed on the plurality of compartments 104A-N. The plurality of compartments 104A-N includes varying sizes designed to accommodate different types of ingredients, such as grains, pulses, spices, and other kitchen items. Each compartment is equipped with its own load cell to measure and monitor the quantity of the ingredients placed inside. The plurality of load cells 106A-N are sensors that measure weight based on the strain gauge principle. As the ingredients are placed in the plurality of compartments 104A-N, the plurality of load cells 106A-N detects the weight and convert this force into an electrical signal. The plurality of load cells 106A-N measures the weight of each ingredient in the plurality of containers 114A-N and transmit the weight data to the node MCU 108 through the amplifier 110. The amplifier 110 may be a HX711 24-bit amplifier used to amplify the weak electrical signals produced by the plurality of load cells 106A-N when the weight is applied. The node MCU 108 processes the weight data and updates the user interface 116 in real-time. The node MCU 108 interprets the electrical signals from the plurality of load cells 106A-N to determine the precise weight of the ingredients. The weight data is then used to calculate the remaining quantity of each ingredient based on predefined thresholds. The node MCU 108 continuously monitors the weight measurements, keep track of the available quantity in each of the containers 114A-N and update in real-time. The plurality of load cells 106A-N are calibrated to ensure accuracy across various ingredient types and quantities. The node MCU 108 acts as the central processing unit and communication hub, collecting data from the plurality of load cells 106A-N and interfaces with the user interface 116. The user interface 116 may include a touch screen and a mobile application. The user interface 116 displays the weight and levels of the ingredients, and triggers alerts when thresholds are reached. The user interface 116 enables the users to set threshold alerts for when ingredient levels fall below a specified amount, view real-time ingredient levels, and manage settings with ease. The user interface 116 provides real-time updates and notifications to the user. In some embodiments, the user interface 116 is an intuitive user interface integrated into the kitchen tray 102. The communication network 118 may include a Bluetooth or Wi-Fi module integrated into the node MCU 108, enabling seamless communication with external devices and e-commerce platforms for automatic ordering. The node MCU 108 is configured to communicate with external e-commerce platforms, through the communication network 118 enabling automatic ordering of ingredients when the ingredient levels fall below set thresholds. When ingredient levels fall below the predefined thresholds, the node MCU 108 automatically generates a shopping list or places an order directly through the e-commerce portal. This ensures that the necessary ingredients are reordered without manual intervention. The node MCU 108 tracks usage patterns and consumption trends of ingredients over time providing insights and recommendations for optimizing inventory management, helping users understand their usage patterns and adjust thresholds accordingly. To ensure accuracy, reference scales are periodically used to compare and validate the measurements from the digital scales (i.e.) plurality of load cells 106A-N. The power source 112 provides a stable power supply ensuring that all components of the smart kitchen tray 102 remain powered for continuous and reliable operation. The power source 112 may be a rechargeable battery or a direct AC power source. The rechargeable battery provides continuous operation for up to 48 hours on a single charge. The integrated workflow of the system 100 guarantees accurate measurements, seamless user interaction, and efficient e-commerce integration for a fully automated kitchen management experience. The power source 112 maintains connectivity with smart devices and home networks, enabling seamless communication and synchronization with the e-commerce platform and other smart home systems. The smart kitchen tray 102 functions accurately, integrates smoothly with the user interface 116 and e-commerce platforms, and operates reliably in a typical kitchen environment.
[0027] Table 1 displays the accuracy of weight measurement for various ingredients measured by the smart kitchen tray system 100.
[0028] Table 1:
Ingredient Measured Weight Reference Scale Accuracy
Rice 500g 499.8g ±0.2g
Lentils 250g 249.9g ±0.1g
Flour 1kg 999.5g ±0.5g
Sugar 750g 749.7g ±0.3g
Salt 100g 99.8g ±0.2g

[0029] The table 1 compares the recorded weights with values obtained from a more accurate reference scale. Each ingredient such as rice, lentils, flour, sugar, and salt is measured by the system, with the recorded weight listed under "Measured Weight" and the true weight from the reference scale listed under "Reference Scale." The "Accuracy" column indicates the margin of error, expressed as a tolerance (e.g., ±0.2g for rice), showing how close each measured weight is to the reference scale value. For instance, rice measured at 500g by the tray has a reference weight of 499.8g, resulting in a tolerance of ±0.2g. Lentils, measured at 250g, show a reference value of 249.9g with a tolerance of ±0.1g. Similarly, flour was recorded at 1kg, with the reference showing 999.5g and an accuracy of ±0.5g. Sugar and salt also display close readings to the reference, with tolerances of ±0.3g and ±0.2g, respectively. This data suggests that the smart kitchen tray system provides reliable and accurate measurements, with minimal deviation from the reference, ensuring precise ingredient tracking suitable for kitchen applications.
[0030] FIG.2 illustrates the exploded view of the kitchen tray 102 of FIG.1 according to some embodiments herein. The kitchen tray 102 includes the plurality of containers 114A-N, the plurality of compartments 104A-N, a base tray 202, a closing tray 204, the plurality of load cells 106A-N. The functioning of the components is described in FIG.2.
[0031] FIG.3A-C illustrate various views of the kitchen tray 102 of FIG.1 according to some embodiments herein. FIG.3A illustrates the isometric view of the kitchen tray 102. FIG.3B illustrates the top view of the kitchen tray 102. FIG.3C illustrates the bottom view of the kitchen tray 102.
[0032] FIG.4 illustrates the load cell 106A of FIG.1 according to some embodiments herein. FIG.4 includes the load cell 106A and the container 114A. The load cell 106A is a beam type load cell.
[0033] FIG.5 illustrates a method for real-time ingredient monitoring and automated replenishment in a smart kitchen tray system according to some embodiments herein.
[0034] At step 502, the method includes placing a plurality of containers filled with ingredients into a plurality of compartments on a kitchen tray, the plurality of compartments are positioned over a plurality of load cells.
[0035] At step 504, the method includes measuring weight of the ingredients in the plurality of containers by using the plurality of load cells (106A-N) that converts the weight of the ingredients into an electrical signal.
[0036] At step 506, the method includes amplifying the electrical signals from the plurality of load cells using an amplifier.
[0037] At step 508, the method includes receiving the amplified weight data from the amplifier and processing the data using a node MCU to determine the remaining quantity of the ingredients in each container based on predefined threshold levels.
[0038] At step 510, the method includes displaying real-time ingredient levels on a user interface connected to the node MCU triggering alerts when ingredient levels fall below the predefined thresholds, and enabling the user to manage inventory settings via the user interface.
[0039] At step 512, the method includes connecting the node MCU with external devices and e-commerce platforms for automated ordering of ingredients when the ingredients levels fall below the set thresholds.
[0040] A representative hardware environment for practicing the embodiments herein
is depicted in FIG. 6 with reference to FIGS. 1 through 5. This schematic drawing illustrates a hardware configuration of a central server / MCU 108 / computer system in accordance with the embodiments herein. The central server / MCU 108 / computer includes at least one processing device 10 and a cryptographic processor 11. The special-purpose CPU 10 and the cryptographic processor (CP) 11 may be interconnected via system bus 14 to various devices such as a random access memory (RAM) 15, read-only memory (ROM) 16, and an input/output (I/O) adapter 17. The I/O adapter 17 can connect to peripheral devices, such as disk units 12 and tape drives 13, or other program storage devices that are readable by the system. The central server / MCU 108 / computer can read the inventive instructions on the program storage devices and follow these instructions to execute the methodology of the embodiments herein. The central server / MCU 108 / computer system further includes a user interface adapter 20 that connects a keyboard 18, mouse 19, speaker 25, microphone 23, and/or other user interface devices such as a touch screen device (not shown) to the bus 14 to gather user input. Additionally, a communication adapter 21 connects the bus 14 to a data processing network 26, and a display adapter 22 connects the bus 14 to a display device 24, which provides a graphical user interface (GUI) 30 of the output data in accordance with the embodiments herein, or which may be embodied as an output device such as a monitor, printer, or transmitter, for example. Further, a transceiver 27, a signal comparator 28, and a signal converter 29 may be connected with the bus 14 for processing, transmission, receipt, comparison, and conversion of electric or electronic signals.
[0041] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the appended claims.


, Claims:I/We claim:

1. A smart kitchen tray system (100) for real-time ingredient monitoring and automated replenishment, wherein the system comprises,
a kitchen tray (102) with a plurality of compartments (104A-N) designed to hold a plurality of containers (114A-N) filled with the ingredients;
a plurality of load cells (106A-N) integrated into the kitchen tray (102) and positioned under the plurality of compartments (104A-N), wherein the plurality of load cells (106A-N) convert weight exerted by the ingredients into electrical signals;
an amplifier (110) coupled to the plurality of load cells (106A-N), wherein the amplifier (110) amplifies the electrical signals generated by the plurality of load cells (106A-N);
a node MCU (108) configured to receive amplified weight data from the amplifier (110) and processing the weight data to
(i) determine remaining quantity of the ingredients in the plurality of containers (114A-N) based on predefined thresholds; and
(ii) connect with external devices and e-commerce platforms for automated ordering of the ingredients when the ingredient levels fall below the set thresholds; and
a user interface (116) connected to the node MCU (108), wherein the user interface (116) displays real-time ingredient levels, triggers alerts when ingredient levels fall below set thresholds, and enables users to manage inventory settings.

2. The system (100) as claimed in claim 1, wherein the node MCU (108) is configured to automatically generate a shopping list and place the order through the e-commerce platform when the ingredient levels fall below the predefined thresholds.

3. The system (100) as claimed in claim 1, wherein the node MCU (108) is configured to track the ingredient usage patterns over time and provide insights and recommendations for optimizing inventory management.
4. The system (100) as claimed in claim 1, wherein the plurality of load cells (106A-N) are calibrated periodically against a reference scale to ensure accuracy of measurements.

5. The system (100) as claimed in claim 1, wherein the plurality of load cells (106A-N) are configured to measure the weight of the ingredients based on strain gauge principle.

6. The system (100) as claimed in claim 1, wherein the system (100) comprises a power source (112) configured to provide a stable power supply to the kitchen tray system (100).

7. A method for real-time ingredient monitoring and automated replenishment in a smart kitchen tray system (100), the method comprises,
placing a plurality of containers (114A-N) filled with the ingredients into a plurality of compartments (104A-N) on a kitchen tray (102), wherein the plurality of compartments (104A-N) are positioned over a plurality of load cells (106A-N);
measuring weight of the ingredients in the plurality of containers (114A-N) by using the plurality of load cells (106A-N) that converts the weight of the ingredients into an electrical signal;
amplifying the electrical signals from the plurality of load cells (106A-N) using an amplifier (110);
receiving the amplified weight data from the amplifier (110) and processing the data using a node MCU (108) to determine the remaining quantity of the ingredients in the plurality of containers (114A-N) based on predefined threshold levels;
displaying real-time ingredient levels on a user interface (116) connected to the node MCU (108), triggering alerts when the ingredient levels fall below the predefined thresholds, and enabling the user to manage inventory settings via the user interface (116); and
connecting the node MCU (108) with external devices and e-commerce platforms for automated ordering of ingredients when levels fall below the set thresholds.

8. The method as claimed in claim 7, wherein the method comprises automatically generating a shopping list and place the order through the e-commerce platform when the ingredient levels fall below the predefined thresholds.

9. The method as claimed in claim 7, wherein the method comprises tracking ingredient usage patterns over time and provide insights and recommendations for optimizing inventory management.

10. The method as claimed in claim 7, wherein the plurality of load cells (106A-N) are calibrated periodically against a reference scale to ensure accuracy of measurements.

Dated this November 13, 2024

Arjun Karthik Bala
(IN/PA 1021)
Agent for Applicant

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