A pre-prepared food preservation device and method

Abstract

This invention discloses a pre-prepared food preservation device and method. The device includes a housing, a multi-dimensional sensing module and a control module disposed within the housing, as well as an interaction module, a communication module, and a central control module. The multi-dimensional sensing module and the control module are connected to the central control module via the communication module, used to detect parameters of the pre-prepared food inside the housing and to regulate the temperature. The interaction module communicates with the central control module for parameter setting and information display. The central control module performs logical analysis based on the real-time parameters collected by the multi-dimensional sensing module, determines the preservation status, and generates a preservation strategy. The preservation status is pushed to the interaction module, and the preservation strategy controls the control module to adjust the temperature, humidity, and ventilation rate inside the housing. This invention uses the multi-dimensional sensing module to monitor temperature, humidity, and various characteristic gases in real time, and the central control module performs multi-dimensional spoilage risk quantification calculations, dynamically synthesizing a freshness index, thereby executing targeted preservation strategies.

Description

Technical Field

[0001] This invention relates to the field of food preservation technology, specifically to a pre-prepared food preservation device and method. Background Technology

[0002] In recent years, with changes in residents' consumption habits and advancements in food processing technology, the pre-prepared food (pre-cooked meals) industry has experienced explosive growth, becoming a crucial industry connecting farms and dining tables. Currently, existing pre-prepared food preservation technologies fall into two main categories. One focuses on sterilization and packaging during processing, such as non-thermal sterilization technologies like ultra-high pressure treatment and irradiation, as well as modified atmosphere packaging (MAP) technology that inhibits microbial growth by replacing the gas composition within the packaging. The other focuses on temperature control during distribution, such as achieving "rapid freshness locking" through liquid nitrogen flash freezing, or using multi-temperature zone independently controlled refrigeration equipment to adapt to the storage needs of different product categories. These technologies have played a positive role in extending the shelf life of pre-prepared foods in specific dimensions. However, existing preservation technologies and equipment still have the following shortcomings in practical applications: 1. Limited Perception Dimensions and Lack of Comprehensive Assessment: Most existing food preservation devices rely primarily on monitoring single or a few environmental parameters such as temperature and humidity. However, the spoilage of pre-prepared food is a complex biochemical process involving microbial metabolism, lipid oxidation, and protein decomposition, which is accompanied by the production of specific volatile organic compounds (VOCs) and characteristic gases such as ammonia (NH3). Traditional single-parameter monitoring struggles to capture the microscopic changes in the early stages of food spoilage in a timely and accurate manner; often, by the time parameters exceed acceptable limits, irreversible deterioration in food quality has already occurred.

[0003] 2. Passive control logic and lack of intelligent decision-making: The control logic of existing equipment is usually based on a passive response of fixed thresholds, such as activating cooling when the temperature exceeds a set value. This simple feedback control cannot dynamically and precisely intervene according to the specific type of food, storage stage, and the evolution trend of spoilage risk. For example, for some pre-catchable fruits and vegetables, their physiological metabolic activities are completely different from the protein spoilage of meat products, requiring differentiated environmental control strategies, which existing equipment cannot adaptively adjust.

[0004] 3. Vague status feedback and lack of quantitative early warning mechanisms: Current technologies mostly only provide binary status prompts of "normal / abnormal," making it impossible for users or managers to intuitively understand the remaining "freshness" of food and the source of spoilage risk (whether it's a microbial outbreak, oxidation due to packaging leaks, or excessive temperature fluctuations). This vague feedback mechanism is not conducive to refined inventory management and reducing food spoilage. Summary of the Invention

[0005] Therefore, to address the aforementioned shortcomings, this invention provides a pre-prepared food preservation device and method. By introducing a multi-dimensional sensing module, it achieves real-time monitoring of temperature, humidity, and various characteristic gases. A central control module performs multi-dimensional quantitative calculations of spoilage risk, dynamically synthesizes a freshness index, and then executes targeted preservation strategies. This invention achieves a shift from single-environment control to multi-dimensional intelligent quality assessment and precise intervention, solving the problems of single-dimensional sensing, passive control logic, and lack of quantitative early warning in existing technologies. This significantly improves the preservation effect and quality stability of pre-prepared foods during storage.

[0006] On the one hand, the present invention provides a pre-prepared food preservation device, including a housing, a multi-dimensional sensing module, a control module, an interaction module, a communication module, and a central control module; The multi-dimensional sensing module and the control module are located inside the box and are connected to the main control module through the communication module to perform parameter detection and temperature control on the pre-prepared food inside the box. The interactive module is communicatively connected to the central control module and is used for setting parameters and / or displaying information; The central control module performs logical analysis based on the real-time parameters collected by the multi-dimensional sensing module to determine the preservation status and formulate a preservation strategy. The preservation status is pushed to the interaction module, and the preservation strategy is used to control the control module. The control module controls the temperature, humidity and air exchange rate inside the chamber according to the preservation strategy.

[0007] Optionally, the multidimensional sensing module includes: Temperature sensor, used to collect the temperature inside the chamber; A humidity sensor is used to collect humidity data inside the enclosure. A multi-gas sensor array is used to collect data inside the chamber. VOCs / NH 3 or / and O 2 or / and CO 2 Parameter information.

[0008] Optionally, the control module includes: The fresh air unit is used to regulate the air environment inside the enclosure; The humidity control unit is used to regulate the humidity inside the cabinet; The temperature control unit is used to regulate the temperature inside the chamber.

[0009] On the other hand, the present invention also provides a method for preserving prepared food, the method comprising: Step S1: Acquisition of basic information and parameter initialization; The system receives basic food information input by the user, including at least the food category and expected shelf life; it then calls a preset ideal environment parameter package based on the food category and collects data. t The initial environmental parameters at time =0 are used as the baseline values; Step S2: Real-time multidimensional data acquisition; The real-time environmental parameters inside the enclosure are periodically collected by a multi-dimensional sensing module, including real-time temperature. T ( t Real-time humidity RH ( t And a real-time gas concentration group, wherein the real-time gas concentration group includes at least the real-time oxygen concentration. C O2 ( t Real-time carbon dioxide concentration C CO2 ( t Real-time volatile organic compound concentration C VOCs ( t and real-time ammonia concentration C NH3 ( t ); Step S3: Quantitative calculation of multi-dimensional corruption risk; Based on the aforementioned real-time environmental parameters, respiratory metabolic abnormality scores, specific putrefactive gas scores, and cumulative environmental stress scores are calculated respectively, resulting in a putrefactive risk score across these three dimensions: (1) Respiratory metabolic abnormality score ( R meta ):based on C O2 ( t )and C CO2 ( t The absolute concentration deviation and its rate of change over time are calculated using respiratory quotient verification logic. (2) Specific putrefactive gas score ( R chem ):based on C VOCs ( t )and C NH3 ( t The weighted calculation is performed based on the characteristic gas weights corresponding to the food category. (3) Cumulative score of environmental stress ( R env ):based on T ( t )and RH (t The storage time is calculated by equivalent integral of the temperature acceleration factor model relative to the deviation from the ideal environmental parameter package. Step S4: Dynamic synthesis of freshness index; Based on the food category and current storage stage, the weight coefficients of the above three dimensions of spoilage risk scores are dynamically allocated, and the current freshness index is synthesized through a linear or non-linear weighted formula. Step S5: Status Output and Trend Correction. Output the final freshness assessment result and the corresponding preservation status level.

[0010] The pre-prepared food preservation method further includes: implementing a preservation strategy according to the preservation status level, which includes: vitality maintenance mode, metabolic inhibition mode, purification and repair mode and hot food rapid cooling adaptive mode. When the freshness index is greater than or equal to the first set value, the vitality maintenance mode is executed. When the freshness index is less than the first set value and greater than the second set value, the metabolic inhibition mode is executed. When the freshness index is less than or equal to the second set value, the purification and repair mode is executed; When the food is hot, the hot food rapid cooling adaptive mode is executed.

[0011] The present invention has the following advantages: This invention represents a leap from single-parameter monitoring to multi-dimensional comprehensive quality assessment, significantly improving the accuracy and timeliness of corruption risk identification.

[0012] This invention overcomes the limitations of traditional preservation equipment that relies solely on temperature and humidity for monitoring, by introducing a combination of temperature sensors, humidity sensors, and a multi-gas sensor array. VOCs / NH 3 / O 2 / CO 2 The multi-dimensional sensing module not only focuses on external environmental factors leading to food spoilage, but also directly captures characteristic metabolic products released during spoilage (such as volatile organic compounds and ammonia) and gaseous changes caused by respiration (such as oxygen consumption and carbon dioxide accumulation). By collecting this data in real time, the central control module can delve into the microscopic biochemical level of food spoilage, keenly detecting anomalies in the early stages of spoilage. This avoids irreversible quality deterioration caused by the delayed perception of traditional methods, thus achieving true "proactive early warning" of pre-preserved food quality without the addition of preservatives.

[0013] Furthermore, it has achieved an upgrade from "passive response to fixed thresholds" to "multi-dimensional risk quantification and intelligent control", thereby improving the scientific nature and accuracy of preservation strategies.

[0014] This invention transforms abstract sensor data into specific, quantifiable spoilage risk indicators through the built-in algorithm logic of the central control module. Specifically, this method uses quantitative calculations across three dimensions—abnormal respiratory metabolism score, specific spoilage gas score, and cumulative environmental stress score—to reflect whether food is spoiling and further analyzes the main causes of spoilage (whether it is due to uncontrolled physiological metabolism, microbial outbreak, or cumulative environmental fluctuations). Based on this, the central control module can dynamically synthesize a freshness index and execute highly matched preservation strategies (such as maintaining viability, inhibiting metabolism, and purifying and repairing). This intelligent decision-making mechanism based on risk assessment changes the simple control logic of traditional equipment, achieving precise and coordinated control of temperature, humidity, and ventilation within the enclosure, maximizing the golden shelf life of food while reducing energy consumption.

[0015] It also enables the transition from binary status prompts to quantitative feedback and trend prediction, providing the ability for refined management and decision-making.

[0016] This invention, through its interactive module, not only displays the current operating status of the equipment to the user, but more importantly, through the logical analysis of the central control module, it intuitively pushes to the user the "freshness status" and "freshness index" calculated from multiple dimensions. Users will no longer see merely vague prompts like "normal" or "abnormal," but rather quantitative and visualized information such as "Current freshness 85%, the main risk stems from slightly faster respiratory metabolism, and suppression mode has been activated." This transparent feedback mechanism provides catering enterprises and supermarket managers with scientific inventory rotation basis (such as the precise execution of "first-in, first-out") and loss analysis data, helping to optimize supply chain management and effectively reduce food waste and economic losses caused by information asymmetry.

[0017] This invention also possesses high adaptability and versatility, capable of meeting the complex preservation needs of various types of pre-prepared foods. The method receives user-inputted food category information during the initialization phase and invokes the corresponding ideal environment parameter package. All subsequent risk quantification calculations and weight allocations are dynamically adjusted based on the food category and current storage stage (e.g., leafy vegetables focus on respiratory metabolic inhibition, while meat focuses on spoilage gas monitoring). Furthermore, the method's specially designed "hot food rapid cooling adaptive mode" precisely addresses the industry pain point of rapidly passing hot food through dangerous temperature zones. This "tailored" adaptive capability allows the invention to be widely applied to the preservation of various pre-prepared foods, including vegetables, fruits, meats, seafood, and cooked foods. Attached Figure Description

[0018] Figure 1This is a system block diagram of the pre-prepared food preservation device described in this invention; Figure 2 This is a flow field diagram of a pre-prepared food preservation method. Detailed Implementation

[0019] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0020] In this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, without necessarily requiring or implying any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0021] As described in the background section, however, existing preservation technologies and equipment still have the following drawbacks in practical applications: 1. Limited Perception Dimensions and Lack of Comprehensive Assessment: Most existing food preservation devices rely primarily on monitoring single or a few environmental parameters such as temperature and humidity. However, the spoilage of pre-prepared foods is a complex biochemical process involving microbial metabolism, lipid oxidation, and protein decomposition, which is accompanied by the production of specific volatile organic compounds (VOCs). VOCs ) and ammonia ( NH 3 Characteristic gases such as ) are present. Traditional single-parameter monitoring is difficult to capture the microscopic changes in the early stages of food spoilage in a timely and accurate manner. Often, when the parameter exceeds the standard, the food quality has already undergone irreversible deterioration.

[0022] 2. Passive control logic and lack of intelligent decision-making: The control logic of existing equipment is usually based on a passive response of fixed thresholds, such as activating cooling when the temperature exceeds a set value. This simple feedback control cannot dynamically and precisely intervene according to the specific type of food, storage stage, and the evolution trend of spoilage risk. For example, for some pre-catchable fruits and vegetables, their physiological metabolic activities are completely different from the protein spoilage of meat products, requiring differentiated environmental control strategies, which existing equipment cannot adaptively adjust.

[0023] 3. Vague status feedback and lack of quantitative early warning mechanisms: Current technologies mostly only provide binary status prompts of "normal / abnormal," making it impossible for users or managers to intuitively understand the remaining "freshness" of food and the source of spoilage risk (whether it's a microbial outbreak, oxidation due to packaging leaks, or excessive temperature fluctuations). This vague feedback mechanism is not conducive to refined inventory management and reducing food spoilage.

[0024] For the reasons mentioned above, this embodiment provides a pre-prepared food preservation device, including a housing, a multi-dimensional sensing module, a control module, an interaction module, a communication module, and a central control module. The multi-dimensional sensing module and the control module are located inside the box and are connected to the main control module through the communication module to perform parameter detection and temperature control on the pre-prepared food inside the box. The interactive module is communicatively connected to the central control module and is used for setting parameters and / or displaying information; The central control module performs logical analysis based on the real-time parameters collected by the multi-dimensional sensing module to determine the preservation status and formulate a preservation strategy. The preservation status is pushed to the interaction module, and the preservation strategy is used to control the control module. The control module controls the temperature, humidity and air exchange rate inside the chamber according to the preservation strategy.

[0025] Optionally, the multidimensional sensing module includes: Temperature sensor, used to collect the temperature inside the chamber; A humidity sensor is used to collect humidity data inside the enclosure. A multi-gas sensor array is used to collect data inside the chamber. VOCs / NH 3 or / and O 2 or / and CO 2 Parameter information.

[0026] Optionally, the control module includes: The fresh air unit is used to regulate the air environment inside the enclosure; The humidity control unit is used to regulate the humidity inside the cabinet; The temperature control unit is used to regulate the temperature inside the chamber.

[0027] In another embodiment, a method for preserving prepared food is also provided, the method comprising: Step S1: Acquisition of basic information and parameter initialization; The system receives basic food information input by the user, including at least the food category and expected shelf life; it then calls a preset ideal environment parameter package based on the food category and collects data. tThe initial environmental parameters at time =0 are used as the baseline values; Step S2: Real-time multidimensional data acquisition; The real-time environmental parameters inside the enclosure are periodically collected by a multi-dimensional sensing module, including real-time temperature. T ( t Real-time humidity RH ( t And a real-time gas concentration group, wherein the real-time gas concentration group includes at least the real-time oxygen concentration. C O2 ( t Real-time carbon dioxide concentration C CO2 ( t Real-time volatile organic compound concentration C VOCs ( t and real-time ammonia concentration C NH3 ( t ); Step S3: Quantitative calculation of multi-dimensional corruption risk; Based on the aforementioned real-time environmental parameters, respiratory metabolic abnormality scores, specific putrefactive gas scores, and cumulative environmental stress scores are calculated respectively, resulting in a putrefactive risk score across these three dimensions: The respiratory metabolic abnormality score R meta Based on C O2 ( t )and C CO2 ( t The absolute concentration deviation and its rate of change over time are calculated using respiratory quotient verification logic. For example, the respiratory metabolic abnormality score R meta The calculations specifically include: Calculate the increase in carbon dioxide concentration per unit time ΔC CO2 / Δt And the reduction in oxygen concentration | ΔC O2 / Δt |; Calculate the real-time respiratory quotient RQ(t) =( ΔC CO2 / Δt ) / | ΔC O2 / Δt |; like RQ(t) Exceeding the normal respiratory quotient threshold range for this food category [RQ min , RQ max ],or ΔC CO2 / Δt Exceeding the threshold for explosive growth K burst This will significantly improve R meta The value; in, , f (·)and g (·) is the normalization function.

[0028] The specific putrefactive gas score R chem Based on C VO2 ( t )and C NH3 ( t The weighted calculation is performed based on the characteristic gas weights corresponding to the food category. The specific putrefactive gas score R chem The calculations specifically include: Based on the food category determined in step S1, the corresponding sensitive gas fingerprint database is loaded. The fingerprint database defines the spoilage contribution weight coefficients of different gas components for that food category. α i ; For meat or seafood, improve C NH3 ( t Weighting coefficients α NH3 For fruits, vegetables, or pasta products, improve C VOCs ( t Weighting coefficients of specific fermentation product components in ) α VOCs ; calculate ,in C i ( t ) is the first i gas concentration, Th i This refers to the safety threshold for the gas; If any gas concentration C i ( t Exceeding the critical threshold for irreversible decay Th critical Then set directly Rchem This is the maximum value.

[0029] The cumulative score of environmental stress R env Based on T ( t )and RH ( t The storage time is calculated by equivalent integral of the temperature acceleration factor model relative to the deviation from the ideal environmental parameter package. The cumulative score of environmental stress R env The calculation uses a time-temperature equivalent model: Calculate the current temperature T ( t The reaction rate acceleration factor under ) ,in T opt The optimal storage temperature for this food category. Q 10 Temperature coefficient; Calculate humidity stress penalty P rh When the real-time humidity RH ( t ) Exceeding the optimal humidity range RH min , RH max ]hour, P rh Greater than zero, otherwise zero; Calculate the cumulative effect using a discrete accumulation method: ; in, λ This is the humidity weighting coefficient.

[0030] Step S4: Dynamic synthesis of freshness index; Based on the food category and current storage stage, the weight coefficients of the above three dimensions of spoilage risk scores are dynamically allocated, and the current freshness index is synthesized through a linear or non-linear weighted formula. The specific logic for dynamically allocating weight coefficients is as follows: Define weight vector W ( t )=[ W A ( t ), W B ( t ), W C ( t )], respectively corresponding to Rmeta , R chem and R env ; In the initial stage of storage, when t < t threshold At the same time, increase the weight of environmental stress. W C ( t Reduce the weight of specific putrefactive gases. W B ( t ); In the later stages of storage, when t≥t threshold Or, when a significant increase in gas concentration is detected, the weight of specific putrefactive gases is gradually increased. W B ( t ); The weighting coefficients satisfy the normalization condition: W A ( t )+ W B ( t )+ W C ( t =1.

[0031] The synthetic freshness index FI ( t The formula for calculating ) is: ; in, R meta ( t ), R chem ( t ), R env ( t All scores are risk scores that have been normalized to the [0,1] interval. If the calculation result FI ( t If ) < 0, then force it to be set to 0; if FI ( t If ) > 100, then it will be forcibly set to 100.

[0032] Step S5: State output and trend correction, based on the calculated... FI ( t Perform smoothing filtering and combine it with FI ( tThe rate of change of the freshness value predicts the future trend of freshness and outputs the final freshness assessment result and the corresponding preservation status level.

[0033] The smoothing filtering process employs a first-order inertial filtering algorithm: ; in, β For filter coefficients, 0 < β <1, FI final ( t -1) represents the output value at the previous time step.

[0034] The prediction of freshness trends in future moments specifically includes: Calculate the instantaneous rate of change of the freshness index ; like v ( t Less than the negative slope threshold - K drop Even now FI final ( t If the level is high, the food is also determined to be in a rapid spoilage stage, and a "warning" status is marked in the output results to trigger a high-intensity preservation strategy in advance.

[0035] The pre-prepared food preservation method further includes: implementing a preservation strategy based on the preservation status level, the preservation strategy including: Strategy 1: Vitality Maintenance Mode (Corresponding to Freshness Level) when FI final ( t ≥85, and corruption risk score R meta , R chem When all levels are low, the food is considered to be in a "fresh / high-quality" state.

[0036] The core logic is that the primary task at this stage is to "delay aging," not to "rescue from emergency." The system should maintain a stable environment optimal for this type of food, avoiding temperature fluctuations caused by frequent power adjustments.

[0037] Temperature and humidity control: Precise temperature control. Strictly maintain the optimal storage temperature for this product category. T opt (e.g. leafy greens 4) ℃ For tropical fruits, the temperature should be kept at 12℃, with an allowable fluctuation range of ±0.5℃. Maintain high humidity (90%-95%) to prevent moisture loss, but fine-tune the air duct if condensation risk is detected.

[0038] Gas regulation: Micro-circulation ventilation. Controlling oxygen and carbon dioxide concentrations within the ideal controlled atmosphere parameter range (e.g., 3% for apples). O 2+5% CO 2) Maintain low-intensity breathing without the need for strong exhaust ventilation, thereby reducing energy consumption.

[0039] Early warning mechanism: Only basic data is recorded, no alarms are triggered, and the user terminal displays a "fresh as ever" status.

[0040] Strategy 2: Metabolic Inhibition Mode (Corresponding to: Sub-fresh / Mild Spoilage Risk Level) When 0≤ FI ( t <85, or any risk score (e.g. R meta When a significant upward trend is observed, the food is determined to have entered a state of "sub-fresh / initial risk".

[0041] The core logic is that microorganisms become active or the food's respiration intensifies at this point. The core strategy is to "slow down and cool down," forcibly interrupting the initial reactions of the spoilage chain.

[0042] Temperature and humidity control: Active cooling. If physical conditions permit, appropriately lower the temperature by 1-2 degrees Celsius within a safe range. ℃ (But not below freezing point), significantly reducing the rate of biochemical reactions using the Arrhenius equation. Lowering the humidity setpoint to around 80% inhibits the growth of humid microorganisms.

[0043] Gas conditioning: Enhanced controlled atmosphere. Activate the powerful ventilation module to accelerate the removal of accumulated gases. CO 2 and VOCs For fruits and vegetables, appropriately reduce... O 2 Concentration is used to induce dormancy; for meat, the flow rate of chilled air is increased to form a protective film.

[0044] Early warning mechanism: Push a "Keep Fresh" reminder to users, recommending that they consume the food as soon as possible, and record this "metabolic surge" event for subsequent analysis.

[0045] Strategy 3: Purification and Repair Mode (Corresponding to Corruption / Medium Risk Level) When 50≤ FI(t) <70, and specific putrefactive gas score R chem Exceeding the standard (e.g.) NH 3 or specific VOCs When there is a sudden increase, the food is determined to be in the "early stage of spoilage / on the verge of reversibility".

[0046] The core logic is that simple temperature control is insufficient to solve the problem; it is necessary to intervene and eliminate the "chemical environment." The goal at this stage is to remove the factors that induce putrefaction and attempt to reverse the microenvironment.

[0047] Temperature and humidity control: Maintain a low temperature. Keep the minimum safe temperature to prevent accelerated spoilage.

[0048] Gas conditioning: Initiate the purification program. Activate the active sterilization and deodorization modules inside the chamber (such as photocatalysis, plasma, or activated carbon adsorption) to specifically decompose... NH 3 sulfides and macromolecules VOCs Perform deep ventilation to dilute the concentration of harmful gases inside the chamber.

[0049] Early warning mechanism: Issue a "high risk" alert, forcefully push a notification to the user, clearly informing them that "the food is spoiling rapidly" and providing the expected countdown to spoilage.

[0050] Strategy 4: Emergency Freshness Preservation and Intervention Mode (Corresponding to: Severe Spoilage / Irreversible Level) when FI ( t If the concentration is less than 50, or the gas concentration exceeds the irreversible critical threshold, then... Th critical At that time, the food was determined to be "severely spoiled / inedible".

[0051] The core logic is that food itself has become a huge source of pollution. The core strategy has shifted from "protecting food" to "protecting the environment," preventing "one bad apple from spoiling the whole bunch."

[0052] Temperature and humidity control: Deep freezing / ultra-low temperature locking. If it is a freezer or has a quick-freeze function, it will activate rapid cooling to lower the food temperature to -18°C or lower, forcibly freezing the moisture and completely locking in microbial activity (although it cannot kill all microorganisms, it can stop their reproduction).

[0053] Environmental isolation: Activate independent air ducts or negative pressure mode. For equipment with multiple compartments, close the dampers leading to other compartments to prevent putrid odors and bacteria from spreading through the air ducts.

[0054] Mandatory Warning: A red "Do Not Consume" warning pops up on the user's device, forcibly requiring the user to clean up. The system automatically records this serious spoilage incident and recommends that the user thoroughly clean and disinfect the storage room.

[0055] Strategy 5: Adaptive Strategy for Rapid Cooling of Hot Food For special conditions identified as "hot food" (such as freshly cooked dishes), in t =0 until the temperature stabilizes: Powerful heat dissipation: The fan runs at full speed and the compressor operates at high frequency, quickly reducing the center temperature to [a lower value].T safe The following points outline how to avoid the "dangerous temperature zone" (40℃~60℃) which is a window for microbial outbreaks.

[0056] Delayed monitoring: During this stage, false alarms from gas sensors caused by high temperatures are actively shielded, and only temperature feedback is relied upon.

[0057] Mode switching: Once the temperature stabilizes, immediately switch modes according to the current... FI The initial value is switched to the corresponding mode mentioned above (usually, at this point, it should directly enter the "vitality maintenance mode").

[0058] This invention uses quantitative calculations across three dimensions—abnormal respiratory metabolism score, specific putrefactive gas score, and cumulative environmental stress score—to determine whether food is spoiling and further analyzes the main causes of spoilage (whether it's due to uncontrolled physiological metabolism, microbial outbreaks, or accumulated environmental fluctuations). Based on this, the central control module can dynamically synthesize a freshness index and execute highly matched preservation strategies (such as maintaining vitality, inhibiting metabolism, and purifying and repairing). This intelligent decision-making mechanism based on risk assessment changes the simple control logic of traditional equipment, achieving precise and coordinated control of temperature, humidity, and ventilation within the enclosure, maximizing the golden shelf life of food while reducing energy consumption.

[0059] It also enables the transition from binary status prompts to quantitative feedback and trend prediction, providing the ability for refined management and decision-making.

[0060] This invention, through its interactive module, not only displays the current operating status of the equipment to the user, but more importantly, through the logical analysis of the central control module, it intuitively pushes to the user the "freshness status" and "freshness index" calculated from multiple dimensions. Users will no longer see merely vague prompts like "normal" or "abnormal," but rather quantitative and visualized information such as "Current freshness 85%, the main risk stems from slightly faster respiratory metabolism, and suppression mode has been activated." This transparent feedback mechanism provides catering enterprises and supermarket managers with scientific inventory rotation basis (such as the precise execution of "first-in, first-out") and loss analysis data, helping to optimize supply chain management and effectively reduce food waste and economic losses caused by information asymmetry.

[0061] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A pre-prepared food preservation device, characterized in that: It includes a housing, a multi-dimensional sensing module, a control module, an interaction module, a communication module, and a central control module; The multi-dimensional sensing module and the control module are located inside the box and are connected to the main control module through the communication module to perform parameter detection and temperature control on the pre-prepared food inside the box. The interactive module is communicatively connected to the central control module and is used for setting parameters and / or displaying information; The central control module performs logical analysis based on the real-time parameters collected by the multi-dimensional sensing module to determine the preservation status and formulate a preservation strategy. The preservation status is pushed to the interaction module, and the preservation strategy is used to control the control module. The control module controls the temperature, humidity and air exchange rate inside the chamber according to the preservation strategy.

2. The pre-prepared food preservation device according to claim 1, characterized in that: The multi-dimensional sensing module includes: Temperature sensor, used to collect the temperature inside the chamber; A humidity sensor is used to collect humidity data inside the enclosure. A multi-gas sensor array is used to collect data inside the chamber. VOCs / NH 3 or / and O 2 or / and CO 2 Parameter information.

3. The pre-prepared food preservation device according to claim 1, characterized in that: The control module includes: The fresh air unit is used to regulate the air environment inside the enclosure; The humidity control unit is used to regulate the humidity inside the cabinet; The temperature control unit is used to regulate the temperature inside the chamber.

4. A method for preserving prepared food, characterized in that, This is achieved by controlling the pre-prepared food preservation device as described in any one of claims 1-3, the method comprising: Step S1: Acquisition of basic information and parameter initialization; The system receives basic food information input by the user, including at least the food category and expected shelf life; it then calls a preset ideal environment parameter package based on the food category and collects data. t=0 The initial environmental parameters at each moment are used as the baseline values; Step S2: Real-time multidimensional data acquisition; The real-time environmental parameters inside the enclosure are periodically collected by a multi-dimensional sensing module, including real-time temperature. T ( t Real-time humidity RH ( t And a real-time gas concentration group, wherein the real-time gas concentration group includes at least the real-time oxygen concentration. C O2 ( t Real-time carbon dioxide concentration C CO2 ( t Real-time volatile organic compound concentration C VOCs ( t and real-time ammonia concentration C NH3 ( t ); Step S3: Quantitative calculation of multi-dimensional corruption risk; Based on the real-time environmental parameters, respiratory metabolism abnormality score, specific putrefactive gas score, and environmental stress cumulative score are calculated respectively, and putrefactive risk score is calculated from these three dimensions. Step S4: Dynamic synthesis of freshness index; Based on the food category and current storage stage, the weight coefficients of the above three dimensions of spoilage risk scores are dynamically allocated, and the current freshness index is synthesized through a linear or non-linear weighted formula. Step S5: Status Output and Trend Correction. Output the final freshness assessment result and the corresponding preservation status level.

5. The method for preserving prepared food according to claim 4, characterized in that, Also includes: Preservation strategies are implemented based on the preservation status level. These strategies include: vitality maintenance mode, metabolism inhibition mode, purification and repair mode, and hot food rapid cooling adaptive mode. When the freshness index is greater than or equal to the first set value, the vitality maintenance mode is executed. When the freshness index is less than the first set value and greater than the second set value, the metabolic inhibition mode is executed. When the freshness index is less than or equal to the second set value, the purification and repair mode is executed; When the food is hot, the hot food rapid cooling adaptive mode is executed.

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