Description:FIELD OF DISCLOSURE
[0001] The present disclosure generally relates to a cooking monitoring system, more specifically, relates to a smart cooking monitoring system based on machine learning technology.
BACKGROUND OF THE DISCLOSURE
[0002] In recent years, the advancement of smart home technologies has led to the development of intelligent kitchen systems aimed at enhancing safety, efficiency, and user experience. A system that smartly monitors and alerts is designed to observe various cooking parameters such as temperature, smoke levels, flame intensity, and food spillage in real-time, using a network of integrated sensors and artificial intelligence. These systems play a vital role in preventing common kitchen hazards like overcooking, unattended flames, gas leaks, and excessive smoke, which can lead to health risks or fire accidents.
[0003] The importance of such systems is particularly evident in busy households, homes with elderly residents, or settings where multitasking is common, as they offer a layer of automated supervision and timely alerts through mobile devices, audio signals, or display screens. Beyond safety, these systems also support energy efficiency, help maintain air quality, and enable remote monitoring through cloud connectivity. Additional features such as aroma diffusers, auto-cleaning mechanisms, and learning-based behaviour prediction further contribute to a more intelligent, hygienic, and user-friendly cooking environment. As kitchens evolve into connected spaces, smart monitoring and alert systems are becoming indispensable tools in modern households.
[0004] Traditional systems, particularly those relying on conventional gas stoves and exhaust chimneys, lack the intelligence and automation needed to address modern kitchen safety and efficiency demands. These systems typically operate without real-time monitoring and feedback mechanisms, making them incapable of detecting potentially hazardous conditions such as excessive smoke, gas leaks, overheating, or food spillage. In the absence of automated alerts or preventive responses, users must rely entirely on manual supervision, increasing the risk of fire accidents, overcooked or burnt food, and indoor air pollution. Additionally, conventional chimneys focus solely on smoke suction and do not offer features like air quality analysis, intelligent odour control, or adaptive airflow. They are also inefficient in dynamic cooking environments where human error or distraction is common. The inability to integrate with smart home ecosystems or provide remote monitoring further limits their utility, making them less suitable for today’s connected, fast-paced lifestyles. As a result, traditional systems fall short in delivering the proactive safety, convenience, and environmental control required in modern kitchens.
[0005] The present invention introduces a smart cooking monitoring system that significantly surpasses the capabilities of the prior art. Unlike conventional chimneys and passive cooking setups, the present invention integrates AI-powered analysis and intelligent alert mechanisms to monitor real-time cooking conditions actively. It is capable of detecting smoke, temperature anomalies, gas leakage, and food spillage, thereby enabling early risk identification and timely user notifications through audio, visual, and mobile alerts that aid in preventing overcooking, overflow, and wastage of food. The integrated advanced technology improves the responsiveness and predictive accuracy over time. Also, the system includes an aroma dispensing system to suppress unpleasant odours and improve the overall cooking environment. Incorporating an energy conversion mechanism in the present invention that produces water from the smoke. This recovered water can be repurposed for various non-potable applications such as cleaning, plant irrigation, or other household utility tasks, thereby promoting resource conservation and reducing kitchen waste.
[0006] Further, the present invention is versatile and energy efficient. Additionally, the present invention offers a comprehensive, intelligent, and user-friendly solution for both home and commercial kitchens, ensuring greater safety, efficiency, and environmental consciousness.
[0007] Thus, in light of the above-stated discussion, there exists a need for a smart cooking monitoring system.
SUMMARY OF THE DISCLOSURE
[0008] The following is a summary description of illustrative embodiments of the invention. It is provided as a preface to assist those skilled in the art to more rapidly assimilate the detailed design discussion which ensues and is not intended in any way to limit the scope of the claims which are appended hereto in order to particularly point out the invention.
[0009] According to illustrative embodiments, the present disclosure focuses on a smart cooking monitoring system which overcomes the above-mentioned disadvantages or provide the users with a useful or commercial choice.
[0010] An objective of the present disclosure is to provide a smart cooking monitoring system that enhances kitchen safety, efficiency, and user convenience.
[0011] Another objective of the present disclosure is to integrate advanced techniques in a smart cooking monitoring system to analyse cooking conditions, recognize abnormal events, and predict potential hazards.
[0012] Another objective of the present disclosure is to design a system that is environmentally friendly and sustainable, incorporating an energy conversion mechanism to promote resource conservation.
[0013] Another objective of the present disclosure is to develop a system that generates timely alerts to ensure prompt user response to critical situations.
[0014] Another objective of the present disclosure is to develop a system minimising the release of particulate matter and harmful gases into the environment.
[0015] Another objective of the present disclosure is to assess remote monitoring and control the system from any location through smart devices.
[0016] Another objective of the present disclosure is to offer a system integrated with sensor-driven automation to minimise human error and optimise resource usage.
[0017] Yet another objective of the present disclosure is to create a versatile system suitable for both home and commercial kitchens.
[0018] In light of the above, in one aspect of the present disclosure, a smart cooking monitoring system is disclosed herein. The system comprises a chimney with a pre-defined shape and a hollow interior, positioned above a gas burner to facilitate real-time monitoring of a cooking process, wherein the chimney further comprises a plurality of sensors configured to sense smoke, steam, temperature and food spillage within the cooking zone, an aroma diffuser configured to dispense odour-neutralising agents into the air to neutralise unpleasant odours, a mist harvest unit configured to condense moisture from the smoke into water for utility purposes, a communication model configured to establish a communication link within the chimney, a microcontroller connected to the plurality of sensors, the aroma diffuser, the mist harvest unit, the communication model and configured to identify potential risks associated with cooking metrics and generate timely alerts, wherein the microcontroller further comprises an input module configured to receive sensed data from the plurality of sensors, a pre-processing module configured to filter irrelevant data and remove noise from the received data, a feature extraction module configured to extract relevant features from the data using machine learning models, an evaluation module configured to analyse the extracted features to evaluate cooking metrics, an identification module configured to identify potential risks in real time associated with the evaluated cooking metrics, an alert generation module configured to trigger real-time alerts based on the identified potential risks, an aroma diffuser module configured to activate the aroma diffuser to dispense odour-neutralising agents in response to unpleasant odours, a mist harvest module configured to activate the mist harvest unit to condense the moisture extracted from the smoke into water. The system includes a communication network configured to facilitate the seamless data transmission within the system. The system also includes a user device connected to the chimney via the communication network and configured to monitor the evaluated cooking metrics, identified potential risks and remotely control the operation of the chimney through a user interface.
[0019] In one embodiment, the chimney further comprises a speaker configured to deliver generated alerts and the status of the aroma diffuser and the mist harvest unit.
[0020] In one embodiment, the chimney further comprises a display screen configured to enable users to control operational parameters of the chimney for optimal performance.
[0021] In one embodiment, the chimney further comprises a suction fan configured to expel smoke, steam, and moisture generated during cooking to the external environment.
[0022] In one embodiment, the chimney further comprises an exhaust pipe configured to channel the extracted smoke, steam, and moisture from the suction fan to the external environment.
[0023] In one embodiment, the plurality of sensors further comprises a smoke sensor, a heat sensor and an overflow sensor.
[0024] In one embodiment, the system further comprises a cloud database configured to store and manage real-time data related to the cooking metrics, alert logs and user preferences.
[0025] In one embodiment, the microcontroller further comprises a training and testing module configured to split the data into training and testing datasets and train the machine learning models using training datasets.
[0026] In one embodiment, the alert generation module generates a beep sound, a continuous alarm and intermittent beeps indicating flood overflow, warns of potential fire contact and alerts for overcooking food, respectively.
[0027] In light of the above, in one aspect of the present disclosure, a method for developing a smart cooking monitoring system is disclosed herein, the method comprises sensing smoke, temperature and food spillage within the cooking zone via a plurality of sensors. The method includes receiving sensed data from the plurality of sensors via an input module. The method also includes filtering irrelevant data and removing noise from the received data via a pre-processing module. The method further includes extracting relevant features from the data using machine learning models via a feature extraction module. Furthermore, the method includes analysing the extracted features to evaluate cooking metrics via an evaluation module. Additionally, the method includes identifying potential risks in real time associated with the evaluated cooking metrics via an identification module. Moreover, the method includes triggering real-time alerts based on the identified potential risks via an alert generation module. Also, the method includes activating the aroma diffuser to dispense odour-neutralising agents in response to unpleasant odours via an aroma diffuser module. The method includes activating the mist harvest unit to condense the moisture extracted from the smoke into water via a mist harvest module. In addition to it, the method includes facilitating the seamless data transmission within the system via a communication network. At last, the method includes monitoring the evaluated cooking metrics, identified potential risks, and remotely controlling the operation of the chimney through a user interface via a user device.
[0028] These and other advantages will be apparent from the present application of the embodiments described herein.
[0029] The preceding is a simplified summary to provide an understanding of some embodiments of the present invention. This summary is neither an extensive nor exhaustive overview of the present invention and its various embodiments. The summary presents selected concepts of the embodiments of the present invention in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other embodiments of the present invention are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
[0030] These elements, together with the other aspects of the present disclosure and various features are pointed out with particularity in the claims annexed hereto and form a part of the present disclosure. For a better understanding of the present disclosure, its operating advantages, and the specified object attained by its uses, reference should be made to the accompanying drawings and descriptive matter in which there are illustrated exemplary embodiments of the present disclosure.
BRIEF DESCRIPTION OF THE DRAWINGS
[0031] To describe the technical solutions in the embodiments of the present disclosure or in the prior art more clearly, the following briefly describes the accompanying drawings required for describing the embodiments or the prior art. Apparently, the accompanying drawings in the following description merely show some embodiments of the present disclosure, and a person of ordinary skill in the art can derive other implementations from these accompanying drawings without creative efforts. All of the embodiments or the implementations shall fall within the protection scope of the present disclosure.
[0032] The advantages and features of the present disclosure will become better understood with reference to the following detailed description taken in conjunction with the accompanying drawing, in which:
[0033] FIG. 1 illustrates a block diagram of a smart cooking monitoring system, in accordance with an embodiment of the present disclosure; and
[0034] FIG. 2 illustrates a flow chart of a method, outlining sequential steps for developing a smart cooking monitoring system, in accordance with an embodiment of the present disclosure.
[0035] Like reference, numerals refer to like parts throughout the description of several views of the drawing.
[0036] The smart cooking monitoring system is illustrated in the accompanying drawings, which like reference letters indicate corresponding parts in the various figures. It should be noted that the accompanying figure is intended to present illustrations of exemplary embodiments of the present disclosure. This figure is not intended to limit the scope of the present disclosure. It should also be noted that the accompanying figure is not necessarily drawn to scale.
DETAILED DESCRIPTION OF THE DISCLOSURE
[0037] The following is a detailed description of embodiments of the disclosure depicted in the accompanying drawings. The embodiments are in such detail as to communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure.
[0038] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It may be apparent to one skilled in the art that embodiments of the present disclosure may be practiced without some of these specific details.
[0039] Various terms as used herein are shown below. To the extent a term is used, it should be given the broadest definition persons in the pertinent art have given that term as reflected in printed publications and issued patents at the time of filing.
[0040] The terms “a” and “an” herein do not denote a limitation of quantity, but rather denote the presence of at least one of the referenced items.
[0041] The terms “having”, “comprising”, “including”, and variations thereof signify the presence of a component.
[0042] Referring now to FIG. 1 to FIG. 2 to describe various exemplary embodiments of the present disclosure. FIG. 1 illustrates a block diagram of a smart cooking monitoring system 100, in accordance with an embodiment of the present disclosure.
[0043] The system 100 comprises a chimney 102 which further comprises a plurality of sensors 116, an aroma diffuser 124, a mist harvest unit 126, a communication model 118, a microcontroller 128, an input module 136, a pre-processing module 138, a feature extraction module 142, an evaluation module 144, an identification module 146, an alert generation module 148, an aroma diffuser module 150, a mist harvest module 152. The system 100 includes a communication network 104. The system 100 includes a user device 108.
[0044] The chimney 102 with a pre-defined shape and a hollow interior, positioned above a gas burner to facilitate real-time monitoring of a cooking process. The chimney 102 is designed with a pre-defined geometric shape with a heat-resistant and food-safe stainless-steel material. Further, it represents the main unit of the system 100 and accommodates various components. The base mounting section of the chimney 102 may include but not limited to the wall mounting chimney and the ceiling suspension chimney.
[0045] In one embodiment of the present invention, the pre-defined shape of the chimney 102 may include but not limited to rectangular and trapezoidal shapes.
[0046] The plurality of sensors 116 is configured to sense smoke, steam, temperature and food spillage within the cooking zone. The plurality of sensors 116 constantly gather the data by sensing smoke, steam, temperature and food spillage and send it to the microcontroller 128. The placement of the plurality of sensors 116 ensures timely detection of potential issues.
[0047] In one embodiment of the present invention, the plurality of sensors 116 further comprises a smoke sensor 130, a heat sensor 132 and an overflow sensor 134. The smoke sensor 130 monitors smoke levels to detect possible fire and overcooking incidents. The heat sensors 132 sense a significant increase in temperature inside the chimney 102. The overflow sensor 134 detects when food boils over and spills.
[0048] The aroma diffuser 124 is configured to dispense odour-neutralising agents into the air to neutralise unpleasant odours. The aroma diffuser 124 incorporated into the hollow interior of the chimney 102 contains essential oils with odour-binding properties. They are designed to bond with molecules exhibiting unpleasant odours and neutralise them.
[0049] In one embodiment of the present invention, the aroma diffuser 124 may include timer-based activation and sensor-based activation of the aroma diffuser 124. For instance, after detecting strong odours through the in-built odour sensor activates and dispenses neutralising agents in the air. Also, the aroma diffuser 124 activates after a pre-determined interval of time adjusted by the user, who is an individual, through the display screen 122 and the user device 108.
[0050] The mist harvest unit 126 is configured to condense moisture from the smoke into water for utility purposes. Inside the chimney 102, along the airflow pathway where smoke and steam pass through, the mist harvest unit 126 is placed with a condenser insulated and thermally regulated to maximize smoke and steam capture and subsequently condensation efficiency. The condensed water is further used for kitchen cleaning, watering indoor plants and many other purposes.
[0051] The communication model 118 is configured to establish a communication link within the chimney 102. The communication model 118 enables data transmission from the plurality of sensors 116, the aroma diffuser 124, the mist harvest unit 126 and other components to the microcontroller 128 and vice-versa.
[0052] In one embodiment of the present invention, the communication model 118 may include but not limited to wired and wireless connections.
[0053] In a preferred embodiment of the present invention, the communication model 118 includes wired connections.
[0054] The microcontroller 128 is connected to the plurality of sensors 116, the aroma diffuser 124, the mist harvest unit 126, the communication model 118 and is configured to identify potential risks associated with cooking metrics and generate timely alerts. The microcontroller 128 is responsible for processing data and intercepting valuable information effectively to used it for decision-making. Further, the microcontroller 128 comprises several modules.
[0055] The input module 136 is configured to receive sensed data from the plurality of sensors 116. This module 136 receives smoke, steam, temperature and food spillage readings from the smoke sensor 130, the heat sensor 132 and the overflow sensor 134.
[0056] The pre-processing module 138 is configured to filter irrelevant data and remove noise from the received data. It converts noisy, inconsistent, and uncalibrated input into reliable information. So that accurate and meaningful information is ready for further processing.
[0057] In one embodiment of the present invention, the microcontroller 128 further comprises a training and testing module 140 configured to split the data into training and testing datasets and train the machine learning models using training datasets.
[0058] The feature extraction module 142 is configured to extract relevant features from the data using machine learning models. This module 142 extracts relevant features to recognise patterns and trends to make predictions.
[0059] In one embodiment of the present invention, the machine learning models may include but not limited to decision tree, support vector machines and neural networks.
[0060] The evaluation module 144 is configured to analyse the extracted features to evaluate cooking metrics. This module 144 evaluates cooking metrics, including temperature, smoke and steam, time, liquid levels and so forth to assess measurable aspects of the cooking process in order to understand performance and ensure safety and efficiency.
[0061] In one embodiment of the present invention, it compares the extracted features with pre-saved data in the cloud database 106 to analyse the cooking process.
[0062] In one embodiment of the present invention, the system 100 further comprises a cloud database 106 configured to store and manage real-time data related to the cooking metrics, alert logs and user preferences.
[0063] The identification module 146 is configured to identify potential risks in real time associated with the evaluated cooking metrics. The potential risks associated with the evaluated cooking metrics include overcooking, overflow and food wastage, which may lead to fire hazard, degradation in food quality, short circuit, cooktop contamination and many more.
[0064] In an exemplary embodiment of the present invention, for overcooking detection, the identification module 146 compares against pre-defined thresholds for a specific dish. Further, it monitors temperature and humidity to predict overflow. Furthermore, to minimise food wastage, long idle cooking and energy overuse are examined.
[0065] The alert generation module 148 is configured to trigger real-time alerts based on the identified potential risks. Based on the identified risks, the alert generation module 148 decides which type of alert needs to be triggered on a speaker 120. It features visual, auditory, and notifications.
[0066] In one embodiment of the present invention, the alert generation module 148 generates a beep sound, a continuous alarm and intermittent beeps indicating flood overflow, warns of potential fire contact and alerts for overcooking food, respectively. When the overflow sensor 134 detects food spillage, the module 148 triggers a short beep. When the smoke sensor 130 and heat sensor 132 detect conditions that indicate fire, a continuous alarm is triggered. For overcooking, elevated heat, and mild smoke without overflow, the module 148 triggers intermittent beeping.
[0067] In one embodiment of the present invention, the chimney 102 further comprises the speaker 120 configured to deliver generated alerts and the status of the aroma diffuser 124 and the mist harvest unit 126.
[0068] The aroma diffuser module 150 is configured to activate the aroma diffuser 124 to dispense odour-neutralising agents in response to unpleasant odours.
[0069] The mist harvest module 152 is configured to activate the mist harvest unit 126 to condense the moisture extracted from the smoke into water. This helps to reduce pollution and minimise the release of harmful particles into the environment.
[0070] In one embodiment of the present invention, the chimney 102 further comprises a display screen 122 configured to enable users to control operational parameters of the chimney 102 for optimal performance. It is used to adjust the parameters of the aroma diffuser 124 and the mist harvest unit 126. The display screen 122 comprises a touch interface on the chimney 102 with indicator lights.
[0071] In one embodiment of the present invention, the chimney 102 further comprises a suction fan 114 configured to expel smoke, steam, and moisture generated during cooking to the external environment. The suction fan 114 is placed inside the chimney 102, and near the top to pull smoke and heat.
[0072] In one embodiment of the present invention, the chimney 102 further comprises an exhaust pipe 112 configured to channel the extracted smoke, steam, and moisture from the suction fan 114 to the external environment. The exhaust pipe 112 is positioned inside the chimney 102. It is a vertical pipe extending from the suction fan 114 to expel smoke.
[0073] The communication network 104 is configured to facilitate the seamless data transmission within the system 100.
[0074] In one embodiment of the present invention, the communication network 104 may include but not limited to wired or wireless networks.
[0075] In a preferred embodiment of the present invention, the communication network 104 includes wireless networks.
[0076] The user device 108 is connected to the chimney 102 via the communication network 104 and is configured to monitor the evaluated cooking metrics, identified potential risks and remotely control the operation of the chimney 102 through a user interface 110.
[0077] FIG. 2 illustrates a flow chart of a method 200, outlining sequential steps for developing a smart cooking monitoring system, in accordance with an embodiment of the present disclosure.
[0078] At step 202, smoke, temperature and food spillage are sensed within the cooking zone via the plurality of sensors 116.
[0079] At step 204, sensed data is received from the plurality of sensors 116 via the input module 136.
[0080] At step 206, irrelevant data is filtered, and noise is removed from the received data via the pre-processing module 138.
[0081] At step 208, relevant features are extracted from the data using machine learning models via the feature extraction module 142.
[0082] At step 210, the extracted features are analysed to evaluate cooking metrics via the evaluation module 144.
[0083] At step 212, potential risks in real time are identified associated with the evaluated cooking metrics via the identification module 146.
[0084] At step 214, real-time alerts are triggered based on the identified potential risks via the alert generation module 148.
[0085] At step 216, the aroma diffuser 124 is activated to dispense odour-neutralising agents in response to unpleasant odours via the aroma diffuser module 150.
[0086] At step 218, the mist harvest unit 126 is activated to condense the moisture extracted from the smoke into water via the mist harvest module 152.
[0087] At step 220, the seamless data transmission is facilitated within the system 100 via the communication network 104.
[0088] At step 222, the evaluated cooking metrics, identified potential risks are monitored, and the operation of the chimney 102 is remotely controlled through the user interface 110 via the user device 108.
[0089] The best mode of operation of the present invention, Initially, the plurality of sensors 116 senses critical cooking parameters including smoke, temperature, and food spillage within the cooking zone. The collected sensor data is received by the input module 136 and passed to the pre-processing module 138, where irrelevant information is filtered out to ensure data clarity. The training and testing module 140 trains the machine learning models through training datasets. Further, the machine learning models identify and extract meaningful features from the cleaned data via the feature extraction module 142, which are then analysed by the evaluation module 144 to determine real-time cooking metrics. Based on these metrics, the identification module 146 detects potential risks such as overcooking, spillage, wastage and fire hazards. Upon identification of possible risk, the alert generation module 148 triggers immediate real-time alerts such as a beep sound, a continuous alarm and intermittent beeps indicating flood overflow, warns of potential fire contact and alerts for overcooking food, respectively, to the user on the speaker 120 and the user device 108. Simultaneously, to manage the sensory environment, the aroma diffuser module 150 activates to neutralize unpleasant odours, and the mist harvest module 152 condenses smoke moisture into reusable water, thereby contributing to pollution reduction. Throughout the process, continuous monitoring and remote control of the operation of the chimney 102 is allowed through the user interface 110 of the user device 108 via the communication network 104. This ensures a smart, responsive, and sustainable cooking environment.
[0090] The present invention offers a practical solution for modern cooking environments through its comprehensive multi-parameter monitoring and real-time responsiveness. By simultaneously tracking temperature, pressure, and liquid levels, the system 100 ensures precise oversight of the cooking process. The incorporated smart alert mechanism featuring visual, auditory, and device-based notifications enables timely interventions, effectively preventing risks such as overcooking, spillage, and unnecessary energy consumption. As a result, the system 100 significantly reduces food and minimizes energy usage, contributing to sustainable kitchen practices. With its intuitive, user-friendly interface, the smart cooking monitoring system 100 is ideal for both home users and commercial kitchens, offering a seamless blend of safety, efficiency, and convenience.
[0091] While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it will be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.
[0092] A person of ordinary skill in the art may be aware that, in combination with the examples described in the embodiments disclosed in this specification, units and algorithm steps may be implemented by electronic hardware, computer software, or a combination thereof.
[0093] The foregoing descriptions of specific embodiments of the present disclosure have been presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the present disclosure to the precise forms disclosed, and many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described to best explain the principles of the present disclosure and its practical application, and to thereby enable others skilled in the art to best utilize the present disclosure and various embodiments with various modifications as are suited to the particular use contemplated. It is understood that various omissions and substitutions of equivalents are contemplated as circumstances may suggest or render expedient, but such omissions and substitutions are intended to cover the application or implementation without departing from the scope of the present disclosure.
[0094] Disjunctive language such as the phrase “at least one of X, Y, Z,” unless specifically stated otherwise, is otherwise understood with the context as used in general to present that an item, term, etc., may be either X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain embodiments require at least one of X, at least one of Y, or at least one of Z to each be present.
[0095] In a case that no conflict occurs, the embodiments in the present disclosure and the features in the embodiments may be mutually combined. The foregoing descriptions are merely specific implementations of the present disclosure, but are not intended to limit the protection scope of the present disclosure. Any variation or replacement readily figured out by a person skilled in the art within the technical scope disclosed in the present disclosure shall fall within the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
, Claims:I/We Claim:
1. A smart cooking monitoring system (100), the system (100) comprising:
a chimney (102) with a pre-defined shape and a hollow interior, positioned above a gas burner to facilitate real-time monitoring of a cooking process, wherein the chimney (102) further comprises:
a plurality of sensors (116) configured to sense smoke, steam, temperature and food spillage within the cooking zone;
an aroma diffuser (124) configured to dispense odour-neutralising agents into the air to neutralise unpleasant odours;
a mist harvest unit (126) configured to condense moisture from the smoke into water for utility purposes;
a communication model (118) configured to establish a communication link within the chimney (102);
a microcontroller (128) connected to the plurality of sensors (116), the aroma diffuser (124), the mist harvest unit (126), the communication model (118) and configured to identify potential risks associated with cooking metrics and generate timely alerts, wherein the microcontroller (128) further comprises:
an input module (136) configured to receive sensed data from the plurality of sensors (116);
a pre-processing module (138) configured to filter irrelevant data and remove noise from the received data;
a feature extraction module (142) configured to extract relevant features from the data using machine learning models;
an evaluation module (144) configured to analyse the extracted features to evaluate cooking metrics;
an identification module (146) configured to identify potential risks in real time associated with the evaluated cooking metrics;
an alert generation module (148) configured to trigger real-time alerts based on the identified potential risks;
an aroma diffuser module (150) configured to activate the aroma diffuser (124) to dispense odour-neutralising agents in response to unpleasant odours;
a mist harvest module (152) configured to activate the mist harvest unit (126) to condense the moisture extracted from the smoke into water;
a communication network (104) configured to facilitate the seamless data transmission within the system (100); and
a user device (108) connected to the chimney (102) via the communication network (104) and configured to monitor the evaluated cooking metrics, identified potential risks and remotely control the operation of the chimney (102) through a user interface (110).
2. The system (100) as claimed in claim 1, wherein the chimney (102) further comprises a speaker (120) configured to deliver generated alerts and the status of the aroma diffuser (124) and the mist harvest unit (126).
3. The system (100) as claimed in claim 1, wherein the chimney (102) further comprises a display screen (122) configured to enable users to control operational parameters of the chimney (102) for optimal performance.
4. The system (100) as claimed in claim 1, wherein the chimney (102) further comprises a suction fan (114) configured to expel smoke, steam, and moisture generated during cooking to the external environment.
5. The system (100) as claimed in claim 1, wherein the chimney (102) further comprises an exhaust pipe (112) configured to channel the extracted smoke, steam, and moisture from the suction fan (114) to the external environment.
6. The system (100) as claimed in claim 1, wherein the plurality of sensors (116) further comprises a smoke sensor (130), a heat sensor (132) and an overflow sensor (134).
7. The system (100) as claimed in claim 1, wherein the system (100) further comprises a cloud database (106) configured to store and manage real-time data related to the cooking metrics, alert logs and user preferences.
8. The system (100) as claimed in claim 1, wherein the microcontroller (128) further comprises a training and testing module (140) configured to split the data into training and testing datasets and train the machine learning models using training datasets.
9. The system (100) as claimed in claim 1, wherein the alert generation module (148) generates a beep sound, a continuous alarm and intermittent beeps indicating flood overflow, warns of potential fire contact and alerts for overcooking food, respectively.
10. A method (200) for developing a smart cooking monitoring system (100), the method (200) comprising:
sensing smoke, temperature and food spillage within the cooking zone via a plurality of sensors (116);
receiving sensed data from the plurality of sensors (116) via an input module (136);
filtering irrelevant data and removing noise from the received data via a pre-processing module (138);
extracting relevant features from the data using machine learning models via a feature extraction module (142);
analysing the extracted features to evaluate cooking metrics via an evaluation module (144);
identifying potential risks in real time associated with the evaluated cooking metrics via an identification module (146);
triggering real-time alerts based on the identified potential risks via an alert generation module (148);
activating the aroma diffuser (124) to dispense odour-neutralising agents in response to unpleasant odours via an aroma diffuser module (150);
activating the mist harvest unit (126) to condense the moisture extracted from the smoke into water via a mist harvest module (152);
facilitating the seamless data transmission within the system (100) via a communication network (104); and
monitoring the evaluated cooking metrics, identified potential risks, and remotely controlling the operation of the chimney (102) through a user interface (110) via a user device (108).