Intelligent heat preservation disc and equipment for measuring mass and weight

Abstract

An apparatus for measuring a weight of a subject object includes: a plurality of load sensor panels arranged in a two-dimensional array and configured to support the subject object placed on the plurality of load sensor panels, in which a weight of the subject object is distributed over the plurality of load sensors; wherein each of the load sensor panels includes a plurality of weight sensors configured to facilitate measurement of a portion of weight borne by the corresponding load sensor panel, and wireless communication circuitry configured to transmit weight signals detected by the plurality of weight sensors to a central server, wherein the central server is configured to determine weight distributions of the object objects at different locations on the plurality of load sensor panels.

Description

Technical Field

[0001] This utility model relates to an intelligent insulated tray and a device for measuring mass and weight, particularly an intelligent insulated tray for use in a nutrition management system for achieving sustainable dietary progress. Background Technology

[0002] While various nutrition management applications based on existing technological solutions are widely used, they have key limitations. Most of these applications require users to manually record food intake and measure serving sizes, introducing inaccuracies in calorie tracking and dietary assessment. Furthermore, self-reporting methods are often unreliable because they rely on user motivation, consistency, and honesty, which vary between individuals. Certain population groups, including children and the elderly, may have difficulty using these technologies effectively or may be unable to self-report their dietary records. Given these limitations, automated dietary monitoring systems capable of accurately identifying foods and estimating serving sizes are crucial for improving the reliability of dietary assessments. Utility Model Content

[0003] According to a first aspect of the present invention, an apparatus for measuring the weight of an object is provided, comprising: a plurality of load sensor panels arranged in a two-dimensional array and configured to support an object placed on the plurality of load sensor panels, wherein the weight of the object is distributed on the plurality of load sensors; wherein each of the load sensor panels includes a plurality of weight sensors configured to facilitate the measurement of a portion of the weight borne by the corresponding load sensor panel; and a wireless communication circuit configured to transmit weight signals detected by the plurality of weight sensors to a central server, wherein the central server is configured to determine the weight distribution of the object at different locations on the plurality of load sensor panels.

[0004] According to the first aspect, the plurality of load sensor panels includes two load sensor panels arranged side by side.

[0005] According to the first aspect, the plurality of weight sensors are located at or near the corners of the corresponding load sensor panel.

[0006] According to the first aspect, each of the load sensor panels further includes a microcontroller configured to be electrically connected to a plurality of weight sensors and wireless communication circuitry.

[0007] According to the first aspect, each of the load sensor panels further includes at least one button configured to be electrically connected to a microcontroller to provide the function of resetting or calibrating the corresponding load sensor panel.

[0008] According to a second aspect of the present invention, an intelligent warming tray is provided, comprising: a device for measuring the weight of an object as described in the first aspect; a warming tray supported by the two side-by-side load sensor panels; and the central server configured to determine the weight distribution of the object at different locations on the plurality of load sensor panels; wherein the object includes food provided by the warming tray.

[0009] According to the second aspect, the heat preservation tray includes a base and two containers placed side by side and supported by the base, wherein the base is physically supported by the plurality of load sensor panels.

[0010] According to the second aspect, the central server is configured to detect the weight of a corresponding portion of food removed from one of the two containers.

[0011] According to the second aspect, the smart warming tray also includes a camera configured to capture images of a corresponding amount of food removed from the warming tray.

[0012] According to the second aspect, the smart insulated tray also includes a facial recognition camera or digital code scanner, which is configured to facilitate the recording of user identity.

[0013] This invention provides an IoT-based nutrition management system equipped with intelligent panels and an artificial intelligence platform to achieve sustainable dietary progress. It also provides solutions for intelligent multi-load sensor panels and intelligent area-weight panels as front-end devices to accurately collect data. The two intelligent panels can operate independently or work together as needed by the monitoring team. For example, the intelligent area-weight panel uses a single image and single measurement method to simultaneously estimate the portion sizes of multiple foods through pixel area-weight relationships. This method improves efficiency and accuracy while reducing user intervention. A residual food subtraction mechanism improves the accuracy of calorie intake estimation by performing a second measurement after consumption. This ensures a more reliable assessment of actual food consumption. Attached Figure Description

[0014] The foregoing and other objects and advantages of this utility model will become more apparent when taken in conjunction with the following detailed description and drawings, wherein like reference numerals denote like components in the various views, and wherein:

[0015] Figure 1A This is a schematic diagram of an intelligent heat preservation plate according to an embodiment of the present utility model.

[0016] Figure 1B This is a schematic diagram illustrating an example of using a smart heat preservation tray.

[0017] Figure 1C yes Figure 1AA block diagram of a device used to measure the weight of an object in a smart insulation tray.

[0018] Figure 2A This is a schematic diagram illustrating an example of the use of a smart warming tray, where the tray is used to hold a type of food.

[0019] Figure 2B yes Figure 2A A diagram illustrating usage examples.

[0020] Figure 3A This is a schematic diagram illustrating an example of the use of a smart warming tray, where the tray is used to hold two types of food.

[0021] Figure 3B yes Figure 3A A diagram illustrating usage examples.

[0022] Figure 4 yes Figure 1C A block diagram of a device used to measure the weight of an object and its components.

[0023] Figure 5A yes Figure 4 A schematic diagram showing the connection between the load sensor and the ADC board in the intelligent panel.

[0024] Figure 5B yes Figure 4 A schematic diagram of the BLE board for the BLE weight sensor in the smart panel.

[0025] Figure 6A The images show photographs of the intelligent heat preservation plate manufactured according to embodiments of the present utility model. Figure 1C A block diagram of a device used to measure the weight of an object and its components.

[0026] Figure 6B yes Figure 6A Photo of the internal circuitry of the intelligent heat preservation plate.

[0027] Figure 7 This is a system architecture of an intelligent area-weight panel and a central server according to an embodiment of the present invention.

[0028] Figure 8 This is a system architecture of an intelligent multi-load sensor panel and a central server according to an embodiment of the present utility model.

[0029] Figure 9A This is a schematic diagram of an intelligent multi-load sensor panel according to an embodiment of the present invention, wherein the intelligent multi-load sensor panel is used to measure the weight change of two types of food.

[0030] Figure 9B yes Figure 9AA schematic diagram of the intelligent multi-load sensor panel.

[0031] Figure 10 The image shows a 3D view of the insulation tray and the intelligent multi-load sensor panel under uniformly distributed load conditions.

[0032] Figure 11A A 2D side view showing the uniformly distributed load across the entire insulation tray is shown.

[0033] Figure 11B A mechanical schematic diagram of a uniformly distributed load is shown.

[0034] Figure 12A A 2D top view showing the uniformly distributed load of two foods is shown.

[0035] Figure 12B It shows Figure 12A Mechanical diagram of a uniformly distributed load in a medium

[0036] Figure 13A This diagram illustrates the mechanics of food 2 (force Δ) being removed from the insulated tray and container.

[0037] Figure 13B This diagram illustrates the mechanics of food 2 (force Δ) being removed without the insulated tray and container.

[0038] Figure 13C It shows Figure 13A and Figure 13B A simplified view. Detailed Implementation

[0039] The inventors believe that the ability to monitor and manage dietary intake on a large scale presents a greater challenge for organizations such as hospitals, nursing homes, medical institutions, sports organizations, and company canteens. Relying solely on manual reporting via user-driven mobile applications is insufficient in this environment. Fixed and automated dietary monitoring systems deployed at designated locations within these institutions will provide a standardized and mandatory approach to dietary monitoring. A fully automated fixed dietary monitoring system must overcome several challenges, particularly in accurately estimating various food portions from images.

[0040] Through their experiments, the inventors learned that since people put different foods on their plates, it would be challenging to monitor the types and quantities of food taken. Therefore, the inventors proposed some methods to monitor and solve this problem.

[0041] Figure 1AA warming tray 100 is shown, which can be used to hold and keep food warm. For example, the warming tray 100 can be used in buffets and banquets to maintain the temperature of food and facilitate self-service by guests. After the food is cooked, it is placed in the inner liner of the warming tray, which can be made of stainless steel to conduct heat evenly. The warming tray can be equipped with heating devices, such as fuel heaters, electric heaters, or hot water baths, which maintain the temperature of the food, keeping it warm throughout the service. Figure 1B The scene also shows a guest taking food and placing it on a plate 101, where the plate 101 used by the guest may have multiple dividers to separate different foods 108.

[0042] Also refer to Figure 1C This illustration shows an embodiment of a device 102 for measuring the weight of an object according to the present invention. The device 102 includes: a plurality of load sensor panels 104 arranged in a two-dimensional array and configured to support an object placed on the plurality of load sensor panels 104, wherein the weight of the object is distributed on the plurality of load sensor panels 104; wherein each of the load sensor panels 104 includes a plurality of weight sensors 106 configured to facilitate the measurement of a portion of the weight borne by the corresponding load sensor panel 104; and a wireless communication circuit configured to transmit the weight signals detected by the plurality of weight sensors 106 to a central server 110, wherein the central server 110 is configured to determine the weight distribution of the object at different locations on the plurality of load sensor panels 104.

[0043] Adding a weighing device 102 below the warming tray 100 is a straightforward method. For example, food placed on a load sensor panel 104 can be supported using a load sensor panel 104. By detecting changes in the weight of the food on the load sensor panel 104, the amount of food a customer takes from the warming tray 102 is recorded, and this data is transmitted to a back-end / central server 110 via a system such as the Internet of Things (IoT). This recording can then be used to provide more relevant information, such as nutritional information or recommendations related to the food portion.

[0044] In a preferred embodiment, the device 102 for measuring the weight of an object has two load sensor panels 104 arranged side-by-side, the panels having a generally rectangular shape, and each load sensor panel 104 has four weight sensors 106 located at or near the corners of the corresponding load sensor panel. Preferably, the sensor panel 104 further includes a microcontroller configured to be electrically connected to the plurality of weight sensors 106 and wireless communication circuitry. Furthermore, the load sensor panel 104 also includes at least one button configured to be electrically connected to the microcontroller to provide a function for resetting or calibrating the corresponding load sensor panel 104, such as reset, zeroing, calibration, etc. The different components and their corresponding functions will be described in more detail below.

[0045] This invention also provides a smart warming tray based on the aforementioned device 102 for measuring the weight of objects. The smart warming tray includes the aforementioned device 102 for measuring the weight of objects; a warming tray 100 supported by the two side-by-side load sensor panels 104; and a central server 110 configured to determine the weight distribution of the object at different locations on the plurality of load sensor panels 104. The central server 110 can accurately calculate or estimate the amount of food actually taken by the guest.

[0046] For example, in a buffet setting, multiple smart warming trays can be used to offer a variety of food choices. Guests can take their trays, walk to them, and use utensils to serve themselves. The tray lids can be opened and closed to maintain the food's temperature and hygiene. However, as... Figure 2A and 2B As shown, each insulated tray can only hold one type of food. If there are many different types of food / drinks, it will take up a lot of space.

[0047] refer to Figure 3A and 3B This illustrates a different application method for a warming tray, wherein the intelligent warming tray includes a base 100A and two containers 100B placed side-by-side and supported by the base, while the base 100A is physically supported by the aforementioned two load sensor panels 104. The two side-by-side load sensor panels 104 can provide sufficient weighing measurement data to a central server 110 to detect the weight of a corresponding portion of food removed from one of the two containers 100B. The calculation method will be further described below.

[0048] The smart warming tray may also include other additional modules, such as a camera 112, which can be used to capture images of a corresponding amount of food removed from the warming tray 100, to provide further assistance to the central server 110 in more accurately estimating the portion size, such as using image analysis combined with artificial intelligence to process images of food on the plates in the customer's hands. The smart warming tray may also include, for example, a facial recognition camera or a digital code scanner 114, for recording the identity of the user / guest.

[0049] Preferably, the heat preservation tray 100 includes a base 100A and two containers 100B placed side by side and supported by the base, wherein the base 100A is physically supported by the plurality of load sensor panels 104, and each load sensor panel 104 includes a plurality of weight sensors 106 for measuring the portion of the weight borne by the corresponding load sensor panel 104.

[0050] In one embodiment of the weighing design, both panels 104 require weight sensors 106, such as load sensor panels that use BLE technology for wireless communication, to detect weight. Figure 4 A block diagram of a single load sensor panel 104 is shown, comprising four load sensors 106, an ADC board 116, and a BLE board 118. The load sensor panel 104 (also referred to herein as a "BLE weight sensor") is implemented using commercial off-the-shelf components (COTS). The main parameters to consider when selecting the load sensor 106 are its sensitivity and resistance. The sensitivity (mV / V) of the load sensor is the output voltage when the input (excitation) voltage is 1mV. In commercial components, the manufacturer provides the sensitivity, resistance, and offset values. Preferably, the plurality of weight sensors 106 are located at or near the corresponding corners of the load sensor panel.

[0051] Preferably, each of the load sensor panels 104 further includes a microcontroller (MCU) 120 configured to be electrically connected to multiple weight sensors and wireless communication circuitry. In the smart panel, load sensors capable of weighing at least 25 kg are considered, as this needs to include the weight of the plate / warmer tray 100. The output of the load sensor 106 is connected to a 24-bit analog-to-digital converter (ADC) 122 designed specifically for weighing applications, controlled by the microcontroller (MCU) shown in Figure 5. The architecture of the 24-bit ADC 122 includes an on-chip programmable gain amplifier (PGA), an analog power regulator, and an internal oscillator. The output of the ADC 122, connected to the MCU 120 for data retrieval, is a serial data output (DOUT) and a serial clock (SCK). Depending on the ADC design for the weighing application, DOUT is held high and SCK is held low until data is ready. When DOUT goes low, it indicates that the digital output is ready. Both the input and overall gain are controlled by the pulse shift of SCK.

[0052] Preferably, the device 102 for measuring the weight of an object provided by the present invention further includes a wireless communication circuit configured to transmit the weight signals detected by the plurality of weight sensors 106 to a central server 110, wherein the central server 110 is configured to determine the weight distribution of the object at different positions on the plurality of load sensor panels 104.

[0053] refer to Figure 6A In addition, 6B, MCU 120, and ADC board 116 transmit data to BLE board 124 via UART. The data can then be transmitted to other BLE-enabled devices for further processing, and ADC board 116 and BLE board 124 can each be equipped with independent MCUs. Furthermore, each load sensor panel 104 further includes at least one button configured to be electrically connected to the microcontroller to provide the function of resetting or calibrating the corresponding load sensor panel. For example, four buttons 126 for different functions can be provided on the BLE board. Figure 6A as well as Figure 6B The manufactured weighing device 102 and its internal circuit connections are shown, where: Button 1 – Reset MCU; Button 2 – Set weighing to zero; Button 3 – First calibration weighing; Button 4 – Second calibration weighing.

[0054] Leveraging the computing power of the central server 110, this system is designed for large-scale institutional use and includes a scalable setup for easy deployment in multiple locations. It can also have a fixed setup, including BLE-enabled circuitry and such... Figure 1CThe tablet shown is used for user identification via facial recognition or QR code scanning. The system also features a central server for food recognition and portion estimation on the intelligent area-weight panel, as well as facial recognition on both panels. All collected data is stored in a database on the central server and can be accessed and analyzed via a web-based interface. This centralized framework supports comprehensive dietary monitoring and management, making it suitable for hospitals, nursing homes, sports facilities, and corporate cafeterias. The ability to record user identity using a facial recognition camera or digital code scanner is described further below.

[0055] Figure 7 as well as Figure 8 As shown Figure 4 The load sensor panel 104 described in section 6 has two independent application scenarios due to user needs.

[0056] Figure 7 The system architecture 700, featuring a smart area-weight panel and a central server, is illustrated. Figure 7 It consists of three main components: a smart area-weight panel, a tablet, and a central server. The smart area-weight panel includes a top-down camera and a BLE weight sensor, while... Figure 7 In this embodiment, only one BLE weight sensor is required. A camera captures a top-view image of the food tray to identify and segment various food items. The BLE weight sensor accurately measures the total weight of the food and wirelessly transmits the data to a connected tablet. In this invention, the camera can be used to capture images of a corresponding number of foods removed from the warming tray, and a central server can retrieve the portion size of each food item using multiple food images and total food weight values. The tablet serves as a multi-functional interface, providing user identification via QR code scanning or facial recognition, receiving data from the BLE weight sensor, and transmitting the collected information to the central server. The central server acts as a processing center, hosting deep learning algorithms for food identification and portion estimation, and providing calorie calculations. It also stores user data, food images, weight measurements, and calorie records. A web-based management platform connects to the server, providing administrators with real-time access to monitor data, analyze dietary patterns, and generate reports.

[0057] Preferably, each fixed setup may include a camera, a BLE weight sensor, and a tablet. The number of setups can be scaled according to venue size and user traffic. For example, a larger cafeteria may require multiple setups to ensure smooth operation and avoid bottlenecks during peak hours. The proposed fixed system implements an innovative algorithm to estimate the portion size (in grams) of a single food item from multiple food images and total weight data. Unlike portable systems with dynamic camera setups, fixed setups benefit from a controlled imaging environment with fixed camera angles, distances, and fields of view. Consistent image capture ensures that the proportions of all food images remain unchanged, eliminating the need to calculate the absolute real-world dimensions of food portions. Instead, the method determines the proportional contribution of the area of ​​each food item to the total weight of all food items on the tray. The method first identifies each food item in the captured images and extracts its corresponding polygonal contour coordinates. This process involves object detection and image segmentation tasks, both of which are well-suited to deep learning-based computer vision techniques.

[0058] Additionally, the state-of-the-art deep learning model YOLOv11 offers an instance segmentation variant (YOLOv11-seg) that combines object detection and image segmentation tasks into a single streamline. This model not only detects multiple foods in a single image but also provides a category label and polygon mask coordinates for each identified item. To facilitate portion estimation, the system uses a predefined area-to-weight ratio (AWR) for each food item before operation. This ratio serves as a standard reference, describing the relationship between pixel area and the actual weight of the food in its common form. The AWR is established under the same imaging conditions as the operation settings and is defined as follows:

[0059]

[0060] The pixel area is calculated using the shoelace formula, which is particularly suitable for calculating the area of ​​irregular polygons. Given a polygon with n vertices and coordinates (x...). i ,y i The area of ​​the food is calculated as follows:

[0061]

[0062] The process of predefining the food area-weight ratio (AWRpre) before operation is shown in Algorithm 1 below.

[0063]

[0064]

[0065] Once the YOLO model detects food and its corresponding outline during operation, the system can introduce an area-weight coefficient (AWC) to quantify the proportional contribution of each food item's area to the total weight of all food items on the tray. AWC is calculated dynamically in real time based on the food detected in each captured image. The AWC calculation is as follows:

[0066]

[0067] Where i refers to each food item detected on the tray. This coefficient is crucial for estimating the weight of each food item because it ensures that the total weight of food measured by the BLE weight sensor is properly distributed among the detected items. By applying AWC, the estimated weight of each food item is calculated as follows: Detected

[0068]

[0069] Here, i represents each food item detected on the tray. The food identification and portion estimation process during operation is shown in Algorithm 2. This real-time computation allows for dynamic estimation of the portions of multiple foods in a single image. Therefore, the proposed system improves efficiency in calorie calculation while maintaining the accuracy of portion estimation.

[0070] Preferably, Figure 7 The illustrated system architecture 700 of the intelligent area-weight panel and central server can be applied to build an intelligent weighing platform to estimate the amount of food taken by a diner. In this embodiment, firstly, the diner selects food and proceeds to the intelligent panel. At the intelligent panel, the system first identifies the user, which can be done by scanning a QR code or facial recognition. Next, the diner places the plate containing the food on the intelligent panel. The camera integrated on the panel captures an image of the food on the plate. Then, the intelligent panel sends this data to the central server.

[0071] On the central server, a series of processes are performed. First, facial recognition is used to verify the user's identity. Then, a food recognition algorithm analyzes the captured image to identify the various foods on the plate. Next, the system estimates the portion size of each food item. Finally, all this information, including the user's identity, the identified foods, and the estimated portion sizes, is recorded in a database. Optionally, after the meal, diners can place any remaining food back on the smart panel for measurement, allowing for a more accurate estimate of their actual food intake. This entire process demonstrates how a smart weighing platform can be used to track and estimate a diner's food intake.

[0072] Figure 8 The system architecture 800, featuring an intelligent multi-load sensor panel and a central server, is illustrated. Figure 8It consists of three main components: a smart multi-load sensor panel, a tablet computer, and a central server. The smart multi-load sensor panel uses static equilibrium to determine and differentiate the type and quantity of collected food. Unlike... Figure 7 The application uses only one load sensor panel 104. Figure 8 The application scenario uses two side-by-side BLE weight sensors / the aforementioned load sensor panel 104. Figure 3A , 3B And 9A shows examples of two foods in the insulated tray 100, simply explaining this smart panel. Figure 9B Two BLE weight sensors are shown detecting two different foods on a plate.

[0073] This invention provides a method for accurately measuring the weight of a corresponding amount of food removed from one of two containers 100B in a warming tray 100 using two side-by-side load sensor panels 104, wherein when the load is uneven, the left or right load sensor panel 104 becomes the fulcrum of the device 102 for measuring the weight of the object, and the amount of weight reduction of the food contained in the warming tray 100 can be measured.

[0074] The intelligent multi-load sensor panel uses static equilibrium to determine and differentiate the type and quantity of collected food. (Reference) Figure 10 This shows a 3D view of the insulation tray 100, where F load This indicates the force exerted by the smart panel 102 on the heat preservation plate legs, and the force is F. load / 4. Due to the uniformly distributed load (UDL), the 3D view of the insulation plate can be converted to a 2D view to more easily describe the following mechanical calculations.

[0075] Each insulated tray can hold two types of food. Each type of food... Figure 11A and 11B The diagram shows a uniformly distributed load (UDL) distributed or diffused within container 100B. It can be assumed that food 1 and food 2 are... Figure 12A As shown, with the same force F food The force is applied at the center of the container. Due to UDL, the 3D static equilibrium calculation can be transformed into... Figure 12B The 2D static equilibrium calculation shown is because Figure 12B Uniformly distributed load (UDL) in the system.

[0076] Therefore, the force exerted by the smart panel on the legs of the heat preservation plate 100 is equal to F. load / 2+F foodThe BLE weight sensor can measure the weight on the load sensor. Therefore, BLE weight sensors 1 and 2 will give results of F'+F1 and F'+F2, respectively. In the application, the MCU is designed to calculate the weight reduction on the scale when the user removes food from the insulated tray.

[0077] exist Figure 13A In this context, Δ is a positive number, representing the difference in force (F) applied by the smart panel to the warming plate legs as the user removes food from either side. load +F1 and F load +F2, where F1≠F2). Figure 13B The weight of the warming tray 100 is eliminated, so the force displayed is only due to the food. Figure 13C It is a simplified diagram showing how each food item is on the scale.

[0078] according to Figure 13C Static equilibrium in

[0079] F1+F2=-Δ-----(5)

[0080] When F2 is the fulcrum

[0081] F1×2d=-Δ×0.5d

[0082] 2F1=-0.5Δ-----(6)

[0083] When F1 is the pivot point

[0084] F²×2d=-Δ×1.5d

[0085] 2F²=-1.5Δ-----(7)

[0086] Since F = mg, (5) becomes

[0087] m1+m2=-Δm

[0088] (6) and (7) become

[0089] 2m1=-0.5Δm=>m1=-0.25Δm

[0090] 2m2=-1.5Δm=>m2=-0.75Δm

[0091] m1 and m2 are the weights displayed by BLE weight sensors 1 and 2, respectively.

[0092] m1 + m2 = -Δm is the total weight taken away.

[0093] |m2|>|m1| indicates that the weight was taken from the right side (food item 2).

[0094] Preferably, Figure 8 The illustrated system architecture 800 of the intelligent area-weight panel and central server can be applied to build a process that uses an intelligent weighing platform to estimate the amount of food a diner takes. In this embodiment, firstly, the diner selects food and proceeds to the intelligent panel. At the intelligent panel, the system first identifies the user, which can be done by scanning a QR code or facial recognition. Next, the diner places the plate containing the food on the intelligent panel, at which point the system calculates the food weight. Then, the intelligent panel sends the data to the central server.

[0095] On the central server, a facial recognition process verifies the user's identity and records the relevant data in the database. Finally, after the meal, diners can view their food intake information through a mobile app or web system. This scenario primarily focuses on the direct calculation of food weight and providing feedback to diners after the meal via the mobile app or web system. Compared to previous scenarios, this version emphasizes initial weight measurement and final information viewing, omitting detailed food identification and portion estimation steps.

[0096] Advantageously, this invention provides an automated dietary monitoring system designed to accurately track food intake in institutional environments such as hospitals, nursing homes, sports facilities, and company canteens. It addresses the challenges of manually recording food intake, which is often time-consuming and error-prone, especially when individuals need to obtain nutritional data and estimate portion sizes. The system integrates deep learning and IoT technologies to simplify dietary monitoring and ensure a standardized and efficient approach. This solution improves the accuracy of portion estimation, reduces user intervention, and enables large-scale dietary monitoring in controlled environments.

[0097] Advantageously, this invention provides an automated dietary monitoring system designed to accurately track food intake in institutional environments such as hospitals, nursing homes, sports facilities, and company canteens. Furthermore, this modular design ensures that the system can be customized to the unique needs of various institutional environments while maintaining efficiency and user-friendliness.

[0098] The above are merely specific embodiments of this utility model and are not intended to limit the scope of protection of this utility model. Any modifications or substitutions that are obvious to those skilled in the art should be within the scope of protection of this utility model. Therefore, the scope of protection of this utility model should be determined by the scope of the claims.

Claims

1. An apparatus for measuring the weight of an object, comprising: Comprising: a plurality of load sensor panels arranged in a two-dimensional array and configured to support an object item placed thereon, wherein a weight of the object item is distributed across the plurality of load sensor panels; wherein each of the load sensor panels comprises a plurality of weight sensors configured to facilitate measurement of a partial weight borne by the corresponding load sensor panel, and a wireless communication circuit configured to transmit weight signals detected by the plurality of weight sensors to a central server, wherein the central server is configured to determine a weight distribution of the object item at different locations on the plurality of load sensor panels.

2. The apparatus of claim 1, wherein, wherein the plurality of load sensor panels comprises two load sensor panels arranged side by side.

3. The apparatus of claim 1, wherein, wherein the plurality of weight sensors are located at corners or adjacent locations of the corners of the corresponding load sensor panel.

4. The apparatus of claim 3, wherein, wherein each of the load sensor panels further comprises a microcontroller configured to be electrically connected with the plurality of weight sensors and the wireless communication circuit.

5. The apparatus of claim 4, wherein, wherein each of the load sensor panels further comprises at least one button configured to be electrically connected with the microcontroller to provide a function of resetting or calibrating the corresponding load sensor panel.

6. An intelligent thermal server characterized by, Comprising: the apparatus for measuring a weight of an object item according to claim 2; a thermal insulation tray supported by the two load sensor panels arranged side by side; and the central server configured to determine a weight distribution of the object item at different locations on the plurality of load sensor panels; wherein the object item comprises food provided by the thermal insulation tray. wherein the thermal insulation tray comprises a base and two containers placed side by side and supported by the base, wherein the base is physically supported by the plurality of load sensor panels.

7. The intelligent thermal server of claim 6, wherein, wherein the central server is configured to detect a weight of a respective serving of food removed from one of the two containers.

8. The intelligent thermal server of claim 7, wherein, further comprising a camera configured to capture an image of a respective amount of food removed from the thermal insulation tray.

9. The intelligent thermal server of claim 8, wherein, further comprising a facial recognition camera or a digital code scanner configured to facilitate recording of a user’s identity.

10. The intelligent thermal server of claim 9, wherein, ​

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