A system for controlling a smart cooking device and method of operating the same

Abstract

The present disclosure proposes a system (100) for controlling a smart cooking device (10) that performs both cooking and cleaning operations without any user intervention, thereby enhancing overall convenience and efficiency. The system (100) for controlling the smart cooking device (10) comprises plurality of sensors (102), a user interface (104) and a control unit (106). The proposed system (100) synchronizes multiple motors and gear mechanisms to automate the handling of ingredients, ensuring seamless execution of cutting, transferring, and cooking processes. The proposed system (100) ensures the processing of ingredients is governed intelligently, thereby adhering to the precise specifications of recipes without requiring any manual input, thereby enhancing user convenience. The proposed system (100) coordinates the different stages of cooking, heating, and mixing operations.

Description

A System for Controlling a Smart Cooking Device and Method of Operating the SameDESCRIPTION:Field of the invention:

[0001] The present disclosure generally relates to the technical field of automated cooking appliances, and in specific, relates to a system for controlling a smart cooking device that performs both cooking and cleaning operations without any user intervention, thereby enhancing overall convenience and efficiency.Background of the invention:

[0002] Automatic cooking devices have transformed modern culinary practices by integrating advanced technology to simplify meal preparation. These appliances, ranging from multi-cookers to smart ovens, are designed to perform a variety of cooking tasks autonomously, significantly reducing the need for constant user supervision. By following pre-programmed recipes, these devices aim to make cooking more accessible, particularly for individuals who may lack culinary skills or time to dedicate to meal preparation. The primary allure of automatic cooking devices lies in their ability to automate time-consuming tasks, allowing users to focus on other aspects of their lives while still enjoying homemade meals.

[0003] As technological advancements continue to shape the culinary landscape, many automatic cooking devices now feature enhanced functionalities such as touch screens, WiFi connectivity, and integrated sensors. These innovations enable users to access a wealth of recipes, monitor cooking progress remotely, and customize their cooking preferences according to dietary needs. However, despite these advancements, numerous existing automatic cooking appliances exhibit limitations that hinder their ability to deliver a truly hands-free cooking experience. This raises important questions about the effectiveness of current control systems in achieving their intended purpose.

[0004] One significant issue with contemporary automatic cooking devices is the lack of comprehensive automation in the cooking process. While many devices can follow a preprogrammed sequence that includes recipe selection, ingredient loading, and cooking, theyoften fall short in fully automating ingredient preparation. Users frequently find themselves needing to chop, slice, or dice ingredients manually, which undermines the essence of an automated cooking system. Although some devices attempt to manage ingredient preparation, they often introduce additional steps that increase user interaction rather than decrease it, ultimately detracting from the overall efficiency of the cooking process.

[0005] Moreover, another critical limitation involves the food transfer process that occurs post-cooking. Many automatic cooking devices require users to manually transfer the cooked food from the appliance to serving dishes, adding an unnecessary layer of complexity. Additionally, the absence of integrated self-cleaning mechanisms necessitates manual cleaning of the cooking vessel and its components after the cooking process. These shortcomings significantly diminish the user experience, as they fail to automate all stages of cooking, from preparation to cleaning, which should be the hallmark of modern automatic cooking appliances.

[0006] Several specific limitations characterize the control systems of existing automatic cooking devices. First, there is a notable lack of recipe customization and recommendation features. Most devices do not offer personalized recipe suggestions based on user preferences, past cooking history, or dietary restrictions, limiting convenience and adaptability for users. Furthermore, current systems heavily rely on user accuracy for ingredient measurement, often resulting in inconsistent cooking outcomes due to manual errors. Many devices also require manual input at various cooking stages, such as ingredient preparation and timing adjustments, which interrupts the automation process and demands constant user oversight.

[0007] Additionally, the complexity of managing multi-step cooking processes poses challenges for existing devices. Many cooking appliances struggle to handle intricate recipes involving various cooking techniques, like boiling, frying, and mixing. Their control systems often lack the capability to transition seamlessly between these processes without user intervention. Moreover, there is often inadequate precision in timing and temperature control, particularly for complex cooking tasks. Many devices fail to adjust cooking temperatures based on real-time data, leading to undercooked or overcooked food that does not meet users' expectations.

[0008] Finally, most automatic cooking devices lack an integrated feedback loop for recipe improvement, preventing continuous enhancement of cooking outcomes and user satisfaction. Additionally, ingredient transfer mechanisms often lead to inconsistent cutting precision and uneven cooking results. The poor integration of cloud connectivity limits realtime recipe updates and interaction with online databases, further restricting the potential for dynamic cooking adjustments.

[0009] Therefore, there is a need for a system that aims to address these critical challenges by providing a fully automated sequence that enhances convenience and efficiency throughout the cooking process. There is also a need for a system that improves the overall user experience by reducing the need for constant monitoring and manual input, allowing users to focus on other tasks while the cooking process is fully automated. Further, there is also a need for a system that coordinates the different stages of cooking, heating, and mixing operations.Objectives of the invention:

[0010] The primary objective of the invention is to provide a system for controlling a smart cooking device that performs both cooking and cleaning operations without any user intervention, thereby enhancing overall convenience and efficiency.

[0011] Another objective of the invention is to provide a system for controlling a smart cooking device that synchronizes multiple motors and gear mechanisms to automate the handling of ingredients, ensuring seamless execution of cutting, transferring, and cooking processes.

[0012] The other objective of the invention is to provide a system for controlling a smart cooking device that ensures the processing of ingredients is governed intelligently, thereby adhering to the precise specifications of recipes without requiring any manual input, thereby enhancing user convenience.

[0013] The other objective of the invention is to provide a system for controlling a smart cooking device that facilitates the automated transfer of ingredients between various cooking units, such as from cutting sections to boiling or frying units, optimizing the workflow and minimizing user intervention.

[0014] The other objective of the invention is to provide a system for controlling a smart cooking device that implements an integrated self-cleaning mechanism activated postcooking, utilizing a pump and nozzle setup to ensure the thorough cleaning of the cooking vessel and internal components without user involvement.

[0015] The other objective of the invention is to provide a system for controlling a smart cooking device that coordinates the different stages of cooking, heating, and mixing operations.

[0016] Yet another objective of the invention is to provide a system for controlling a smart cooking device that improves the overall user experience by reducing the need for constant monitoring and manual input, allowing users to focus on other tasks while the cooking process is fully automated.

[0017] Further objective of the invention is to provide a system for controlling a smart cooking device that maintains a hygienic environment by ensuring automated cleaning of the smart cooking device, thereby eliminating the need for manual cleaning and enhancing food safety.Summary of the invention:

[0018] The present disclosure proposes a system for controlling a smart cooking device and method of operating the same. The following presents a simplified summary in order to provide a basic understanding of some aspects of the claimed subject matter. This summary is not an extensive overview. It is not intended to identify key / critical elements or to delineate the scope of the claimed subject matter. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.

[0019] In order to overcome the above deficiencies of the prior art, the present disclosure is to solve the technical problem to provide a system for controlling a smart cooking device that performs both cooking and cleaning operations without any user intervention, thereby enhancing overall convenience and efficiency.

[0020] According to an aspect, the invention provides a system for controlling a smart cooking device. In one embodiment herein, the system for controlling the smart cooking device comprises plurality of sensors, a user interface, and a control unit.

[0021] In one embodiment herein, the plurality of sensors is configured to determine one or more cooking parameters for maintaining precise control over a cooking process. The plurality of sensors includes a weight sensor, a temperature sensor, a water level sensor, a time sensor and a moisture sensor. In one embodiment herein, the user interface is configured to facilitate a user to provide cooking inputs for selecting and customizing recipes, thereby enhancing cooking experience. The cooking inputs include user health status, user diet data and user spice levels.

[0022] In one embodiment herein, the control unit having a processor and a memory for storing one or more instruction executable by the processor. The control unit is in communication with a server and a database via a network. The control unit is in communication with the plurality of sensors. The control unit is configured to receive data related to one or more cooking parameters from the plurality of sensors and the cooking inputs provided by the user from the user interface.

[0023] The control unit is configured to analyze the data related to one or more cooking parameters and the cooking inputs using at least one intelligent computational system. In particular, the at least one intelligent computational system includes a recommendation model, a decision model, machine learning (ML) and artificial intelligence (Al) models, a fuzzy logic model, and a rule-based model. The control unit is configured to actuate a loading unit by automatically controlling a driving unit, thereby facilitating the user to place ingredients for a selected recipe into respective containers of the loading unit.

[0024] The control unit is configured to control the loading unit to transfer the ingredients into a feeding unit from the containers, thereby performing cutting and mixing of the ingredients. The control unit is configured to actuate a multi-grid cutting unit automatically to slice the ingredients into user-preferred sizes and according to the selected recipe using plurality of slicers and plurality of cutting blades, thereby enabling uniform cutting and mixing operations upon actuation of the multi-grid cutting unit.

[0025] The control unit is configured to operate a simmering unit to receive the sliced ingredients from the multi-grid cutting unit for performing a boiling operation based on the selected recipe. The control unit is configured to activate a boiling and frying unit for receiving the sliced ingredients from the loading unit and the simmering unit for both selectively boiling and frying the sliced ingredients, thereby ensuring optimal cooking performance while maintaining precise control over the cooking process. The control unit is configured to operate a filtering unit to transfer the boiled ingredient from the simmering unit upon performing the simmering operation.

[0026] In one embodiment herein, the control unit is configured to actuate a cleaning unit for automatically performing a cleaning operation of the boiling and frying unit and the simmering unit upon completion of the cooking process. In one embodiment herein, the weight sensor is configured to measure the weight of the ingredients for the selected recipe. The temperature sensor is configured to measure the temperature of a heating unit using plurality of parameters, which includes at least one of cold junction compensation (CJC), voltage-to-temperature conversion, signal filtering, error detection and correction and temperature smoothing.

[0027] In one embodiment herein, the control unit is configured to actuate an oil container to selectively dispense oil onto the boiling and frying unit while preparing the selected recipe. The control unit is configured to actuate a water container to selectively dispense water onto the boiling and frying unit and the simmering unit upon completion of the cooking process. The control unit is configured to receive a signal from a capturing unit upon dispensing an excess amount of the oil and water. The capturing unit utilizes one or more directives for monitoring and analyzing the cooking operation. In particular, the one or more directives include at least one of computer vision, food recognition, cooking process monitoring, and smoke and overheating detection.

[0028] In one embodiment herein, the control unit is configured to receive user feedback from the user through an alerting unit, thereby analyzing the user feedback using multiple feedback instructions and updating the user feedback to the database via the network. The multiple feedback instructions include at least one of Rating feedback, Text-Based feedback, behavioral feedback, preference surveys, real-time feedback and sensor feedback.

[0029] According to another aspect, the invention provides a method for operating the system for controlling the smart cooking device. At one step, the control unit receives the data related to the one or more cooking parameters from the plurality of sensors and the cooking inputs provided by the user from the user interface. At one step, the control unit analyzes the data related to the one or more cooking parameters and the cooking inputs using the at least one intelligent computational system.

[0030] At one step, the control unit actuates the loading unit by automatically controlling the driving unit, thereby facilitating the user to place ingredients for a selected recipe into the respective containers of the loading unit. At one step, the control unit controls the loading unit to transfer the ingredients into the feeding unit from the containers, thereby performing the cutting and mixing of the ingredients. At one step, the control unit actuates the multi-grid cutting unit to slice the ingredients automatically into user-preferred sizes and according to the selected recipe using the plurality of slicers and the plurality of cutting blades, thereby enabling uniform cutting and mixing operations upon actuation of the multigrid cutting unit.

[0031] At one step, the control unit operates the simmering unit to receive the sliced ingredients from the multi-grid cutting unit for performing the boiling operation based on the selected recipe. At one step, the control unit activates the boiling and frying unit for receiving the sliced ingredients from the loading unit and the simmering unit for both selectively boiling and frying the sliced ingredients, thereby ensuring optimal cooking performance while maintaining the precise control over the cooking process.

[0032] Further, objects and advantages of the present invention will be apparent from a study of the following portion of the specification, the claims, and the attached drawings.Detailed description of drawings:

[0033] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate an embodiment of the invention, and, together with the description, explain the principles of the invention.

[0034] FIG. 1 illustrates a block diagram of a system for controlling a smart cooking device, in accordance to an exemplary embodiment of the invention.

[0035] FIG. 2 illustrates a pictorial representation of a display unit of the system for controlling the smart cooking device, in accordance to an exemplary embodiment of the invention.

[0036] FIG. 3 illustrates a block diagram of a system for controlling a smart cooking device while selecting a recipe, in accordance to an exemplary embodiment of the invention.

[0037] FIG. 4 illustrates a block diagram of a system for controlling a smart cooking device while loading ingredients, in accordance to an exemplary embodiment of the invention.

[0038] FIG. 5 illustrates a block diagram of a system for controlling a smart cooking device while performing a cooking operation, in accordance to an exemplary embodiment of the invention.

[0039] FIG. 6 illustrates a block diagram of a system for controlling a smart cooking device while collecting feedback, in accordance to an exemplary embodiment of the invention.

[0040] FIG. 7 illustrates a flowchart of a process for the system of controlling the smart cooking device, in accordance to an exemplary embodiment of the invention.

[0041] FIG. 8 illustrates a flowchart of a method for operating the system for controlling the smart cooking device, in accordance to an exemplary embodiment of the invention.Detailed invention disclosure:

[0042] Various embodiments of the present invention will be described in reference to the accompanying drawings. Wherever possible, same or similar reference numerals are used in the drawings and the description to refer to the same or like parts or steps.

[0043] The present disclosure has been made with a view towards solving the problem with the prior art described above, and it is an object of the present invention to provide a system for controlling a smart cooking device that performs both cooking and cleaning operations without any user intervention, thereby enhancing overall convenience and efficiency.

[0044] According to an exemplary embodiment of the invention, FIG. 1 refers to a block diagram of a system 100 for controlling a smart cooking device 10. In one embodimentherein, the system 100 is configured to automatically control the smart cooking device 10 for enhancing the cooking experience for a user. The system 100 is adapted to enable the smart cooking device 10 to perform various cooking steps seamlessly while performing a cooking process for preparing a selected recipe for the user. The system 100 is configured to send one or more notifications to the user while performing the cooking process, thereby ensuring that the user remains informed and engaged without needing to manually intervene for achieving optimal cooking results. The system 100 implements a fully automated operational sequence, significantly improving the efficiency and convenience of the cooking process.

[0045] In one embodiment herein, the system 100 for controlling the smart cooking device 10 comprises plurality of sensors 102, a user interface 104 and a control unit 106. In one embodiment herein, the plurality of sensors 102 is configured to determine one or more cooking parameters for maintaining precise control over a cooking process. The plurality of sensors 102 includes a weight sensor, a temperature sensor, a water level sensor, a time sensor and a moisture sensor. In one embodiment herein, the user interface 104 is configured to facilitate a user to provide cooking inputs for selecting and customizing recipes, thereby enhancing the cooking experience. The cooking inputs include user health status, user diet data and user spice levels.

[0046] In one embodiment herein, the control unit 106 having a processor 108 and a memory 110 for storing one or more instruction executable by the processor 108. The control unit 106 is in communication with a server 132 and a database 130 via a network 134. The control unit 106 is in communication with the plurality of sensors 102. The control unit 106 is configured to receive data related to one or more cooking parameters from the plurality of sensors 102 and the cooking inputs provided by the user from the user interface 104.

[0047] The control unit 106 is configured to analyze the data related to one or more cooking parameters and the cooking inputs using at least one intelligent computational system. In particular, the at least one intelligent computational system includes a recommendation model, a decision model, machine learning (ML) and artificial intelligence (Al) models, a fuzzy logic model, and a rule-based model. The control unit 106 is configured to actuate aloading unit 112 by automatically controlling a driving unit 114, thereby facilitating the user to place ingredients for a selected recipe into respective containers of the loading unit 112.

[0048] The control unit 106 is configured to control the loading unit 112 to transfer the ingredients into a feeding unit 116 from the containers, thereby performing cutting and mixing of the ingredients. The control unit 106 is configured to actuate a multi-grid cutting unit 118 automatically to slice the ingredients into user-preferred sizes and according to the selected recipe using plurality of slicers and plurality of cutting blades, thereby enabling uniform cutting and mixing operations upon actuation of the multi-grid cutting unit 118.

[0049] The control unit 106 is configured to operate a simmering unit 120 to receive the sliced ingredients from the multi-grid cutting unit 118 for performing a boiling operation based on the selected recipe. The control unit 106 is configured to activate a boiling and frying unit 122 for receiving the sliced ingredients from the loading unit 112 and the simmering unit 120 for both selectively boiling and frying the sliced ingredients, thereby ensuring optimal cooking performance while maintaining precise control over the cooking process. The control unit 106 is configured to operate a filtering unit 128 to transfer the boiled ingredient from the simmering unit 120 upon performing the simmering operation.

[0050] In one embodiment herein, the control unit 106 is configured to actuate a cleaning unit 124 for automatically performing a cleaning operation of the boiling and frying unit 122 and the simmering unit 120 upon completion of the cooking process. In one embodiment herein, the weight sensor is configured to measure the weight of the ingredients for the selected recipe. The temperature sensor is configured to measure the temperature of a heating unit using plurality of parameters, which includes at least one of cold junction compensation (CJC), voltage-to-temperature conversion, signal filtering, error detection and correction and temperature smoothing.

[0051] In one embodiment herein, the control unit 106 is configured to actuate an oil container to selectively dispense oil onto the boiling and frying unit while preparing the selected recipe. The control unit 106 is configured to actuate a water container to selectively dispense water onto the boiling and frying unit 122 and the simmering unit 120 upon completion of the cooking process. The control unit 106 is configured to receive a signal from a capturing unit upon dispensing an excess amount of the oil and water. Thecapturing unit utilizes one or more directives for monitoring and analyzing the cooking operation. In particular, the one or more directives include at least one of computer vision, food recognition, cooking process monitoring, and smoke and overheating detection.

[0052] In one embodiment herein, the control unit 106 is configured to receive user feedback from the user through an alerting unit 126, thereby analyzing the user feedback using multiple feedback instructions and updating the user feedback to the database 130 via the network 134. The multiple feedback instructions include at least one of Rating feedback, Text-Based feedback, Behavioral feedback, Preference Surveys, Real-Time feedback, and Sensor feedback.

[0053] In one embodiment herein, the loading unit 112 is configured to enable the user to place a plurality of ingredients in a plurality of containers, thereby dispensing at least one of the plurality of ingredients selectively. The weight sensor is configured to measure the weight of each ingredient and transmit weight data using multiple measurements. In one embodiment herein, the feeding unit 116 is configured to selectively receive at least one of the plurality of ingredients from the loading unit 102 based on the selected recipe.

[0054] In one embodiment herein, the multi-grid cutting unit 118 is configured to slice the selected ingredient automatically in a desired manner based on the selected recipe using at least one of the plurality of cutting blades and the plurality of slicers, thereby transferring the sliced ingredient. In one embodiment herein, the boiling and frying unit 122 is configured to receive the sliced ingredients from the loading unit 112 and the simmering unit 120 for performing the cooking operation to prepare the selected recipe. The boiling and frying unit 122 is in communication with the control unit 106, which alerts the user upon preparation of the selected recipe using the alerting unit 126.

[0055] In one embodiment herein, the simmering unit 120 is configured to receive the sliced ingredients from the multi-grid cutting unit 118 for performing the boiling operation based on the user selection. The filtering unit 116 is configured to transfer the boiled ingredients from the simmering unit 120 to the boiling and frying unit 122 upon performing the simmering operation. In one embodiment herein, the cleaning unit 118 is configured to clean the boiling and frying unit 122 by spraying a liquid upon performing the cooking operation.

[0056] In one embodiment herein, the smart cooking device 10 is provided with the heating unit, which is operated by electrical power supplied by an electrical power source to perform cooking operations such as boiling, frying, simmering, or baking by generating and regulating heat. In one embodiment herein, the electrical power source could be at least one of an external power supply and batteries. The smart cooking device 10 is connected to an external electrical supply via a power cord. The smart cooking device 10 eliminates concerns about power depletion, thereby making it ideal for energy-intensive operations like baking or prolonged simmering while ensuring seamless and uninterrupted operation.

[0057] The user interface 104 is configured to enable the user to provide the cooking inputs, user suggestions, and select at least one recipe. The user data includes user health status, user diet data, and user spice levels. In one embodiment herein, the system 100 for controlling the smart cooking device 10 comprises the oil chamber, the water chamber, and the capturing unit. In one embodiment herein, the system 100 for controlling the smart cooking device 10 comprises a spices unit that is connected with the feeding unit 116 for dispensing a selective amount of spices based on the selected recipe.

[0058] In one example embodiment herein, the system 100 is designed to control the smart cooking device 10 using a computing device connected via a cellular network. This arrangement enables seamless communication between the user and the smart cooking device 10, allowing for remote operation and control. Specifically, the system 100 functions by processing information provided by the user through the computing device, ensuring precise adjustments and personalized cooking experiences.

[0059] The information provided by the user may include various forms of input, such as media files (for example, images of recipes), textual instructions (for example, cooking steps or ingredient preferences), and audio commands (for example, voice instructions for starting or stopping the smart cooking device 10). This flexibility in input types ensures that users can interact with the system 100 in a manner that best suits their convenience and technological preferences.

[0060] The computing device facilitating this interaction can be any one of a range of common devices, including a smartphone, computer, laptop, or personal digital assistant (PDA). These devices act as an interface, allowing users to transmit their instructions to thesystem 100, which in turn executes the corresponding commands on the smart cooking device 10. The integration of such versatile computing devices ensures that the system 100 remains accessible and easy to use for a broad spectrum of users. This embodiment highlights the adaptability of the system 100, leveraging the capabilities of modern computing devices and cellular networks to provide users with enhanced control and convenience in managing their cooking tasks remotely.

[0061] According to another embodiment of the invention, FIG. 2 refers to a pictorial representation 200 of the user interface 104 of the system 100 for controlling the smart cooking device 10. In one example embodiment, the pictorial representation 200 initially displays a screenshot 136 that allows the user to select at least one of a plurality of recipes for preparing the desired dish. The screenshot 136 shows the plurality of recipes based on previously cooked meals or top-rated options. The user interface 104 presents several options, including create, favorite, search, try new, categories, recipe selection, recipe removal, interconnectivity, microphone, and signal indicators.

[0062] The "create" option allows the user to input data for preparing a customized recipe. The "favorite" option enables the user to select one or more preferred recipes based on taste. The "search" option assists the user in finding specific recipes. The "try new" option introduces new recipes that are updated in the database 130. The "categories" option helps the user to select recipes from different categories. The "recipe selection" and "recipe removal" options enable users to choose and remove one or more recipes from the plurality of available recipes based on their requirements.

[0063] The "interconnectivity" option lets the user to connect with a user device for accessing the system 100 for controlling the smart cooking device 10. The microphone facilitates the use of voice commands to input recipe details or instructions. The signal indicators display the smart cooking device's connection status, including Wi-Fi, Bluetooth, or cloud synchronization, ensuring smooth data transfer and the proper functioning of connected peripherals.

[0064] According to another embodiment of the invention, FIG. 3 refers to a block diagram 300 of the system 100 for controlling the smart cooking device 10 while selecting the recipe. At step 302, the user needs to provide the cooking input, where the user provide theirpreferences or requests for the recipe selection. The cooking input includes multiple factors such as desired cuisine, available ingredients, or dietary restrictions. At step 304, the user activates the smart cooking device 10, thereby allowing subsequent process to initiate. At step 306, the network 134 includes a cloud network that serves as the hub for connecting the smart cooking device 10, frameworks, and the recipe database 130, thereby facilitating seamless communication between them.

[0065] At step 308, the plurality of models are used to filter, select, and recommend recipes based on the user data and preferences. In particular, the plurality of models includes at least one of recommendation model, a decision model, machine learning (ML) and artificial intelligence (Al) models, a fuzzy logic model, and a rule-based model. The recommendation model comprises collaborative filtering and content-based filtering. The collaborative filtering leverages user behavior data, such as previous recipe choices, ratings, and interactions, to recommend similar recipes. It identifies patterns among different users with similar preferences and suggests recipes that align with the user's historical choices.

[0066] For instance, if a user consistently selects Italian dishes, the system 100 will prioritize Italian recipes. The content-based filtering recommends recipes based on the inherent attributes of the recipe itself, such as ingredients, cooking style, cuisine type, and preparation methods. The system 100 compares the user's previous selections with recipes that share similar attributes. For example, if the user shows a preference for dishes with tomatoes and basil, then the content-based filtering will suggest recipes containing these ingredients.

[0067] The decision tree model narrows down the recipe selection process by presenting the user with a series of questions or prompts, such as the type of cuisine they prefer, available ingredients, dietary restrictions, cooking time, or level of complexity. Based on the user's responses, the system 100 follows a decision path to present the most appropriate recipe. For example, if the user selects "low-carb," the decision tree filters out recipes with high carbohydrate content and presents suitable options like salads or protein-rich dishes.

[0068] The machine learning (ML) and artificial intelligence (Al) models comprise neural networks and reinforcement learning. The neural networks are trained using large datasets of user preferences, ingredient combinations, and recipe data. The neural networks identifypatterns in user behavior, such as frequently used ingredients or favored cuisines, and predicts future preferences. Over time, the system 100 becomes more accurate at anticipating the types of recipes a user might enjoy, offering personalized recommendations based on ingredient combinations and cooking techniques.

[0069] The reinforcement learning model allows the system 100 to learn from user feedback by analyzing how satisfied a user is with a recommended recipe. Based on positive or negative feedback (for example, ratings or reviews), the system 100 adjusts its future recommendations, gradually improving its ability to match the user's taste and preferences. If the user consistently rates recipes containing chicken highly, the system 100 will prioritize similar options in future recommendations.

[0070] The fuzzy logic model is useful in situations where the user's input is vague or uncertain. For example, when a user says, "I want something spicy, but not too spicy," fuzzy logic can interpret and quantify this input based on a range of spiciness levels. The system 100 then suggests recipes that balance the user's preference for moderate spiciness. By adjusting variables according to the level of ambiguity in the input, fuzzy logic ensures that recipes selected meet the user's criteria without requiring precise answers.

[0071] The rule-based model governs the recipe selection process based on specific criteria. These rules can be tailored according to the user's dietary preferences, available ingredients, nutritional requirements, or time constraints. For example, a rule might state: 'If the user selects a vegetarian recipe and has carrots and potatoes available, suggest recipes that include these ingredients. The system 100 follows these rules to filter and present only the recipes that match the defined criteria, ensuring that the options provided are relevant to the user's current needs.

[0072] At step 310, the analysis is typically performed after generating the plurality of models to refine or evaluate the selected recipes before presenting them to the user. At step 312, the control unit 106 displays the recipes through the user interface 104 upon analysis. At step 314, the user needs to select at least one recipe from the displayed options. At step 316, the control unit 106 displays the necessary ingredients to the user for preparing the desired recipe. At step 318, the recipe database connects to the cloud and stores all therecipes. The database 130 is queried based on the input, and the cloud retrieves relevant recipes using the plurality of models.

[0073] According to another embodiment of the invention, FIG. 4 refers to a block diagram 400 of the system 100 for controlling a smart cooking device 10 while loading ingredients. At step 402, the user needs to select the recipe from the available options in the recipe database. At step 404, the cloud network 134 is responsible for communication between the various system components, transmitting the selected recipe data, ingredient information, and calibration instructions to ensure accurate handling of the recipe. At step 406, the control unit 106 retrieves data from the loading database, which includes ingredient quantities, instructions, and any pre-set adjustments or user preferences upon choosing the recipe.

[0074] At step 408, the control unit 106 uses the multiple measurements related to ingredient management. The multiple measurements comprise data calibration and conversion, filtering, real-time adjustment and recipe scaling. In data calibration and conversion measurement, the control unit 106 uses the weight sensor to measure the weight of ingredients. The electrical signals from the weight sensor are converted into digital weight values using an analog-to-digital converter (ADC). Calibration is critical to ensure that the control unit 106 provides accurate weight values for precise ingredient measurements during cooking.

[0075] The control unit 106 applies filtering measurements, such as low-pass filters or moving average filters, to the raw sensor data. These filters help eliminate noise and provide consistent, stable weight readings. During real-time adjustment, as ingredients are added, the control unit 106 continuously monitors their weight. If the control unit 106 detects an incorrect quantity for example either too much or too little then the control unit 106 provides immediate feedback to the user through visual or audio signals. This ensures that ingredient measurements are corrected on the spot, preventing errors.

[0076] When the user adjusts the recipe for a different serving size, the control unit 106 uses a scaling framework to recalibrate the weight of each ingredient. For example, if the user changes the recipe designed for four servings to two servings, the system 100 will automatically adjust the target weight of all ingredients accordingly, ensuring accurateproportions. At step 410, once the recipe is selected and ingredient data are processed, the control unit 106 performs an analysis of the customized recipe to ensure that all ingredient measurements and adjustments meet the desired criteria. This analysis also verifies the real-time adjustments made by the system 100 during ingredient handling.

[0077] At step 412, the control unit 106 displays the final list of required ingredients, along with their adjusted quantities, to the user after calibration and real-time adjustment. This allows the user to review the customized recipe before proceeding with the cooking process. At step 414, the control unit 106 assists in weighing the ingredients using the calibrated weight sensor. Based on the real-time feedback and the filtering frameworks, the control unit 106 ensures that the correct amounts are used for each ingredient.

[0078] At step 416, the user needs to load the ingredients into the cooking device 10 for preparation upon completion of the weighing process. The control unit 106 ensures that only the correctly measured and calibrated quantities are used. At step 418, the ingredients may be further customized based on specific user preferences or dietary requirements. This step allows the control unit 106 to adjust ingredients according to nutritional guidelines or user-defined customizations before finalizing the recipe.

[0079] According to another embodiment of the invention, FIG. 5 refers to a block diagram 500 of a system 100 for controlling a smart cooking device 10 while performing the cooking operation. At step 502, the user needs to load ingredients into the cooking device 10. At step 504, the cloud network 134 is responsible for communicating the loaded data and previous cooked data. At step 506, the cooking database is in communication with the cloud network 134. The cooking database includes various cooking recipes, cooking times, and temperature settings facilitates efficient recipe retrieval and execution.

[0080] The temperature sensor is positioned in the boiling and frying unit 122 and the simmering unit 120 to closely monitor the boiling and frying unit 122 and the simmering unit 120. Several frameworks are utilized to ensure accurate measurements, compensate for environmental factors, filter noise, and manage the system 100 using the plurality of parameters includes at least one of cold junction compensation (CJC), voltage-to- temperature conversion, signal filtering, and error detection. The cold junctioncompensation (CJC) parameter corrects temperature measurements by compensating for temperature variations at the cold junction using additional sensors.

[0081] The voltage-to-temperature conversion parameter converts the millivolt output of the temperature sensor into temperature readings using lookup tables or polynomial equations for precision. The signal filtering parameter remove noise and ensure the accuracy of temperature readings. The signal filtering parameter comprises low-pass filters, moving average filter and Kalman filter. The low-pass filters remove high-frequency noise while preserving the true temperature signal. The moving average filter smooths data by averaging consecutive readings, reducing random noise.

[0082] The Kalman filter predicts the next temperature value based on previous measurements, correcting it with new data. The error detection and correction parameter identifies faults like open or short circuits through open circuit detection, short circuit detection and outlier detection. The open circuit detection monitors for abnormally high voltage readings. The short circuit detection detects sudden signal fluctuations. The outlier detection identifies readings significantly different from expected values. The temperature smoothing frameworks handle fluctuations in readings using techniques like the exponential moving average (EMA) for real-time smoothing without excessive lag.

[0083] The capturing unit is placed under the feed cover towards the water and oil chambers facing towards the bottom side covering both the boiling and frying unit 122 and the simmering unit 120. The capturing unit in the automatic cooking device 10 provides valuable functionalities like monitoring the cooking process, recognizing ingredients, and ensuring food is cooked correctly. Several types of modules are involved to make this work efficiently. Here are the main categories of modules used in the capturing unit of the automatic cooking device 10.

[0084] The several types of modules include a computer vision module, a food recognition module, a cooking process monitoring module, and a smoke detection module and an optical flow module. The computer vision module enables the capturing unit 516 i.e., Al camera to analyze visual information from the cooking environment, providing critical functionalities such as object detection, image classification, and segmentation. The object detection identifies ingredients, cookware, and utensils using frameworks, for example, aYOLO (You Only Look Once) model, which is a real-time object detection module. Image classification uses convolutional neural networks (CNNs) to recognize specific food types. Segmentation utilizes models such as U-Net or Mask R-CNN to separate food from the background, allowing the system 100 to focus on cooking areas.

[0085] In one example embodiment, the food recognition module utilizes a Food-101 dataset combined with convolutional neural networks (CNNs), to identify and classify food items accurately. This information aids in personalized recipe recommendations by mapping the identified food items to suitable recipes. The cooking process monitoring module continuously tracks the cooking state by analyzing visual cues from the food. The cooking process monitoring module communicates with the image processing and machine learning models, such as Temporal Convolutional Networks (TCNs), to detect state changes (for example, color shifts or bubbling patterns) with high precision.

[0086] Texture variations in the food are captured using edge detection techniques, such as the canny edge detector, thereby enabling precise detection of subtle transformations in food surfaces. Additionally, a heat map generation module creates thermal maps to identify hot spots or areas of uneven cooking, ensuring consistent heat distribution. To enhance safety and cooking efficiency, the smoke and overheating detection module integrates advanced smoke and optical flow analysis. The smoke and overheating detection module monitors visual feeds to identify the presence of smoke or steam, serving as an early indicator of overcooking or burning.

[0087] The optical flow module tracks particle movement (steam or smoke) to identify boiling or overheating. At step 514, the control unit 106 is in communication with the several types of modules while performing the cooking operation. At step 520, the control unit 106 alerts the user upon preparing the selected recipe. At step 522, the user needs to respond and select at least one option to either hold or serve the prepared recipe. If the user selects "hold the food" then the control unit 106 holds the prepared recipe for a predetermined time as step 524. If the user selects "serve" then the control unit 106 serves the food to the user as step 526.

[0088] According to another embodiment of the invention, FIG. 6 refers to a block diagram 600 of the system 100 for controlling the smart cooking device 10 while collecting feedback.At step 602, the prepared food is ready to be served once the cooking process is completed. At step 604, the cloud network 134 is responsible for communicating the data to the cooking and feedback process, ensuring efficient communication between all connected components. At step 605, after the cooking process is completed, the data from the cooking experience is sent and stored in the feedback database. This database holds previous feedback records and helps generate insights for future cooking sessions.

[0089] At step 606, the feedback is collected from the user and analysed in multiple feedback instructions that include at least one of rating feedback, text-based feedback, behavioral feedback, preference surveys, real-time feedback, and sensor feedback. In one example embodiment herein, the multiple feedback instructions include star ratings, binary feedback, text-based input, behavioral observations, surveys, real-time feedback, and sensor data. Each instruction is supported by various frameworks to process the feedback and improve user experience.

[0090] The user needs to rate the prepared recipes on a scale of one to five stars based on their satisfaction, providing a quick and user-friendly way to gather feedback. The control unit 106 can use averages or weighted averages of these ratings to refine future recipe suggestions. For example, instructions like collaborative filtering can be applied to adjust recipe recommendations based on similar users' preferences. In addition, this binary feedback option simplifies the user input, allowing the user to either approve or disapprove of the recipe. The control unit 106 uses reinforcement learning to strengthen the likelihood of recommending recipes with positive feedback, while recipes with negative feedback become less likely to appear in future recommendations.

[0091] In one example embodiment herein, the user needs to provide detailed comments about the recipe through open-ended text feedback. This allows for more specific input on factors such as taste, texture, or cooking time. Natural language processing (NLP) instructions analyze user sentiment in these comments, categorizing feedback as positive, negative, or neutral. Additionally, predefined tags or reasons such as "Too Spicy" or "Undercooked" provide users with quick options to describe their experience. These inputs are analysed using rule-based systems or decision trees to identify recurring issues, thereby enabling recipe refinement by adjusting parameters like cooking time or temperature.

[0092] In one embodiment herein, the control unit 106 monitor's usage patterns, including how frequency of specific recipes being cooked, how often the user adjusts cooking parameters and abandoning the recipe in midway. Machine learning models analyze these behavior patterns to adapt future recipe recommendations and improve timing or cooking settings. Furthermore, if the user manually adjusts cooking time or settings during the cooking process, the smart cooking device 10 records these changes. Reinforcement learning can then use this data to automatically optimize the recipe for future cooking sessions.

[0093] After cooking, the user is prompted with short surveys asking about specific aspects of the meal, such as taste, doneness, or ingredient quality. Decision trees or weighted scoring systems process the survey results, allowing the control unit 106 to fine-tune future recipe suggestions or adjust cooking settings accordingly. Through voice assistants, the user provides real-time feedback, such as saying, "Make it less crispy next time." Voice recognition systems, coupled with Al models, can immediately adjust future recommendations or cooking settings based on this input.

[0094] The cooking device 10 also employs sensors to monitor food for temperature, moisture, or texture. By comparing expected outcomes with actual results, the control unit 106 gathers implicit feedback. Predictive instructions adjust future recipes to better match user preferences, leveraging machine learning to learn from these discrepancies. Each of these feedback instructions contributes to refining the cooking device's ability to offer personalized and optimized cooking experiences tailored to individual user preferences.

[0095] At step 610, the control unit 106 provides feedback types to collect the user response based on the prepared recipe or food. At step 612, the user needs to provide the feedback based on the prepared recipe, thereby storing the feedback in the multiple feedback instructions for further cooking sessions.

[0096] According to another embodiment of the invention, FIG. 7 refers to a flowchart 700 of a process for the system 100 of controlling the smart cooking device 10. At step 1, the user begins the smart cooking device 10 by turning ON the external electrical supply and selecting the desired recipe from the user interface 104. At step 2, the user interface 104 displays recommended recipes that are stored in the database 130 via the cloud network134 based on the user's previous cooking history or popular choices. At step 3, the control unit 106 lists the necessary ingredients for that recipe, upon selecting the desired recipe by the user.

[0097] At step 4, the user prepares the ingredients by weighing, washing, peeling, and placing the vegetables and spices into the loading unit 102. The water and oil chambers are also filled as specified by the selected recipe. Once these preparations are complete, the user presses the start button on the control unit 106. This action triggers the control unit 106 to initiate the cooking process. Following the recipe instructions, the control unit 106 actuates the driving unit 114, which rotates the loading unit 102 in at least one direction to transfer the ingredients efficiently.

[0098] When the at least one of the plurality of chambers aligns with the trapezoidal pocket of the feeding unit 116, the control unit 106 commands the chamber to rotate and dispense the required ingredients into the feeding unit 116. At step 5, the control unit 106 activates the feeding unit, ensuring that the ingredients are pushed into the multi-grid cutting unit 118. Simultaneously, the control unit 106 activates the multi-grid cutting unit 118 to process the ingredients, cutting them into the desired size and shape. The prepared ingredients are then directed to either the boiling and frying unit 122 or the simmering unit 120, depending on the recipe's requirements.

[0099] At step 6, the control unit 106 activates the boiling and frying unit 122 to initiate either boiling or frying operations as specified by the recipe. The control unit 106 also controls the oil and water chambers to dispense their contents into the simmering unit 120. The liquid in the simmering unit 120 is preheated to the required temperature. Once the temperature is reached, the sliced ingredients are transferred from the boiling and frying unit 122 to the simmering unit 120. The ingredients are then cooked for the duration specified by the recipe, ensuring they are prepared precisely as intended.

[0100] At step 7, after the simmering process is complete, the control unit 106 activates the boiling and frying unit 122 for receiving the sliced ingredients from the multi-grid cutting unit 118 and boiled ingredients from the simmering unit 120. This movement allows the filtering unit 116 to transfer the simmered ingredients back to the boiling and frying unit122. Upon completing the transfer, the filtering unit 116 and the boiling and frying unit 122 return to their original positions, ensuring the cooking process transitions smoothly.

[0101] At step 8, once the food is fully prepared, the control unit 106 notifies the user through the user interface 104 via the alerting unit 126. If the user opts to serve the food, the control unit 106 actuates the boiling and frying unit 122 to dispense the prepared dish into a serving bowl positioned at the designated area. The boiling and frying unit 122 ensures all food is transferred completely. If the user chooses not to serve immediately, the food remains securely stored within the boiling and frying unit 122 until the user is ready to serve.

[0102] At step 9, after serving, the boiling and frying unit 122 is actuated by the control unit 106 for the cleaning process. The control unit 106 activates the cleaning unit 118, spraying water into the boiling and frying unit 122. So, the boiling and frying unit 122 ensures thorough cleaning. At step 10, the control unit 106 prompts the user to provide feedback on the recipe through various feedback options. At step 11, the user's feedback is stored in the cloud network 134 to aid in future recipe recommendations during the recipe selection process.

[0103] According to another embodiment of the invention, FIG. 8 refers to a flowchart 800 of a method for operating the system 100 for controlling the smart cooking device 10. At step 802, the control unit 106 receives the data related to the one or more cooking parameters from the plurality of sensors 102 and the cooking inputs provided by the user from the user interface 104. At step 804, the control unit 106 analyzes the data related to the one or more cooking parameters and the cooking inputs using the at least one intelligent computational system.

[0104] At step 806, the control unit 106 actuates the loading unit 112 by automatically controlling the driving unit 114, thereby facilitating the user to place ingredients for a selected recipe into the respective containers of the loading unit 112. At step 808, the control unit 106 controls the loading unit 112 to transfer the ingredients into the feeding unit 116 from the containers, thereby performing the cutting and mixing of the ingredients. At step 810, the control unit 106 actuates the multi-grid cutting unit 118 to slice the ingredients automatically into user-preferred sizes and according to the selected recipeusing the plurality of slicers and the plurality of cutting blades, thereby enabling uniform cutting and mixing operations upon actuation of the multi-grid cutting unit 118.

[0105] At step 812, the control unit 106 operates the simmering unit 120 to receive the sliced ingredients from the multi-grid cutting unit 118 for performing the boiling operation based on the selected recipe. At step 814, the control unit 106 activates the boiling and frying unit 122 for receiving the sliced ingredients from the loading unit 112 and the simmering unit 120 for both selectively boiling and frying the sliced ingredients, thereby ensuring optimal cooking performance while maintaining the precise control over the cooking process.

[0106] Numerous advantages of the present disclosure may be apparent from the discussion above. In accordance with the present disclosure, a system 100 for controlling a smart cooking device 10 is disclosed. The proposed system 100 performs both cooking and cleaning operations without any user intervention, thereby enhancing overall convenience and efficiency. The proposed system 100 synchronizes multiple motors and gear mechanisms to automate the handling of ingredients, ensuring seamless execution of cutting, transferring, and cooking processes.

[0107] The proposed system 100 ensures the processing of ingredients is governed intelligently, thereby adhering to the precise specifications of recipes without requiring any manual input, thereby enhancing user convenience. The proposed system 100 facilitates the automated transfer of ingredients between various cooking units, such as from cutting sections to boiling and frying unit 122, optimizing the workflow and minimizing user intervention. The proposed system 100 implements an integrated self-cleaning mechanism activated post-cooking, utilizing a pump and nozzle setup to ensure the thorough cleaning of the cooking vessel and internal components without user involvement.

[0108] The proposed system 100 coordinates the different stages of cooking, heating, and mixing operations. The proposed system 100 improves the overall user experience by reducing the need for constant monitoring and manual input, allowing users to focus on other tasks while the cooking process is fully automated. The proposed system 100 maintains a hygienic environment by ensuring automated cleaning of the smart cooking device 10, thereby eliminating the need for manual cleaning and enhancing food safety.

[0109] It will readily be apparent that numerous modifications and alterations can be made to the processes described in the foregoing examples without departing from the principles underlying the invention, and all such modifications and alterations are intended to be embraced by this application.

Claims

CLAIMS:I / We Claim:

1. A system (100) for controlling a smart cooking device (10), comprising: plurality of sensors (102) configured to determine one or more cooking parameters for maintaining precise control over a cooking process; a user interface (104) configured to facilitate a user to provide cooking inputs for selecting and customizing recipes, thereby enhancing cooking experience; a control unit (106) having a processor (108) and a memory (110) for storing one or more instructions executable by the processor (108), wherein the control unit (106) is communicated with a server (132) and a database (130) via a network (134), wherein the control unit (120) is configured to: receive data related to one or more cooking parameters from the plurality of sensors (102) and the cooking inputs provided by the user from the user interface (104); analyze the data related to one or more cooking parameters and the cooking inputs using at least one intelligent computational system; actuate a loading unit (112) by automatically controlling a first driving unit (114), thereby facilitating the user to place ingredients for a selected recipe into respective containers of the loading unit (112); control the loading unit (112) to transfer the ingredients into a feeding unit (116) from the containers, thereby performing cutting and mixing of the ingredients; actuate a multi-grid cutting unit (118) automatically to slice the ingredients into userpreferred sizes and according to the selected recipe using plurality of slicers and plurality of cutting blades, thereby enabling uniform cutting and mixing operations upon actuation of the multi-grid cutting unit (118); operate a simmering unit (120) to receive the sliced ingredients from the multi-grid cutting unit (118) for performing a boiling operation based on the selected recipe; andactivate a boiling and frying unit (122) for receiving the sliced ingredients from the loading unit (112) and the simmering unit (120) for both selectively boiling and frying the sliced ingredients, thereby ensuring optimal cooking performance while maintaining the precise control over the cooking process.

2. The system (100) for controlling the smart cooking device (10) as claimed in claim 1, wherein the control unit (106) is configured to: actuate a cleaning unit (124) for automatically performing a cleaning operation of the boiling and frying unit (122) and the simmering unit (120) upon completion of the cooking process.

3. The system (100) for controlling the smart cooking device (10) as claimed in claim 1, wherein the plurality of sensors (102) is in communication with the control unit (106), wherein the plurality of sensors (102) includes a weight sensor, a temperature sensor, a water level sensor, a time sensor and a moisture sensor.

4. The system (100) for controlling the smart cooking device (10) as claimed in claim 3, wherein the weight sensor is configured to measure weight of the ingredients for the selected recipe, wherein the temperature sensor is configured to measure temperature of a heating unit using plurality of parameters, wherein the plurality of parameters includes at least one of Cold Junction Compensation (CJC), Voltage-to-Temperature Conversion, Signal Filtering, Error Detection and Correction and Temperature Smoothing.

5. The system (100) for controlling the smart cooking device (10) as claimed in claim 1, wherein the control unit (106) is configured to: actuate an oil container to selectively dispense oil onto the boiling and frying unit (122) while preparing the selected recipe; actuate a water container to selectively dispense water onto the boiling and frying unit (122) and the simmering unit (120) upon completion of the cooking process; andreceive a signal from a capturing unit upon dispensing excess amount of the oil and water, wherein the capturing unit utilizes one or more directives for monitoring and analyzing the cooking operation, wherein the one or more directives include at least one of computer vision, food recognition, cooking process monitoring, and smoke and overheating detection.

6. The system (100) for controlling the smart cooking device (10) as claimed in claim 1, wherein the cooking inputs include user health status, user diet data and user spice levels, wherein the at least one intelligent computational system includes a recommendation model, a decision model, machine learning (ML) and artificial intelligence (Al) models, a fuzzy logic model, and a rule-based model.

7. The system (100) for controlling the smart cooking device (10) as claimed in claim 1, wherein the control unit (106) is configured to receive user feedback from the user through an alerting unit (126), thereby analyzing the user feedback using multiple feedback instructions and updating the user feedback to the database (130) via the network (134).

8. The system (100) for controlling the smart cooking device (10) as claimed in claim 1, wherein the multiple feedback instructions include at least one of rating feedback, textbased feedback, behavioral feedback, preference surveys, real-time feedback and sensor feedback.

9. The system (100) for controlling the smart cooking device (10) as claimed in claim 1, wherein the control unit (106) is configured to operate a filtering unit (128) to transfer the boiled ingredient from the simmering unit (114) upon performing the simmering operation.

10. A method for operating a system (100) for controlling a smart cooking device (10), comprising: receiving, by a control unit (106), data related to one or more cooking parameters from plurality of sensors (102) and cooking inputs provided by a user from a user interface (104);analyzing, by the control unit (106), the data related to one or more cooking parameters and the cooking inputs using at least one intelligent computational system; actuating, by the control unit (106), a loading unit (112) by automatically controlling a first driving unit (114), thereby facilitating the user to place ingredients for a selected recipe into respective containers of the loading unit (112); controlling, by the control unit (106), the loading unit (112) to transfer the ingredients into a feeding unit (116) from the containers, thereby performing cutting and mixing of the ingredients; actuating, by the control unit (106), a multi-grid cutting unit (118) to slice the ingredients automatically into user-preferred sizes and according to the selected recipe using plurality of slicers and plurality of cutting blades, thereby enabling uniform cutting and mixing operations upon actuation of the multi-grid cutting unit (118); operating, by the control unit (106), a simmering unit (120) to receive the sliced ingredients from the multi-grid cutting unit (118) for performing a boiling operation based on the selected recipe; and activating, by the control unit (106), a boiling and frying unit (122) for receiving the sliced ingredients from the loading unit (112) and the simmering unit (120) for both selectively boiling and frying the sliced ingredients, thereby ensuring optimal cooking performance while maintaining the precise control over the cooking process.DATE AND SIGNATURE:Dated this 9thday of December, 2024Patent Agent Name: Hima Bindu AttiI NPA - 3925

Images