A smart formula preparation control system based on infant physiological parameters

Abstract

This invention discloses an intelligent formula preparation control system based on infant physiological parameters, belonging to the technical field of infant feeding equipment. To address the problems of existing formula preparation equipment failing to dynamically generate feeding plans based on individual infant differences, lacking sufficient mixing accuracy, and exhibiting poor temperature control stability, this invention includes an application input unit, a feeding plan generation unit, a wireless communication unit, as well as a formula powder compartment, a water compartment, a mixing compartment, a heating unit, and a temperature control unit. The input unit acquires the infant's physiological parameters and feeding needs. Based on this, the feeding plan generation unit calculates the amount of formula powder, water, and target temperature. These parameters are transmitted to the formula preparation equipment via the communication unit for execution. During the formula preparation process, the system adjusts key parameters and feeds back the operational data to the application for recording and optimization. This invention achieves intelligent generation of feeding parameters and coordinated control of the formula preparation process, improving the accuracy and stability of the process.

Description

Technical Field

[0001] This invention relates to the field of infant feeding equipment technology, and in particular to an intelligent formula preparation control device and control method based on infant physiological parameters, specifically involving multi-parameter detection and adjustment, automatic proportioning control and safe output control technology. Background Technology

[0002] Feeding infants is a crucial aspect of their growth and development. The precision of the formula's proportions, the uniformity of mixing, and the temperature control directly affect an infant's nutrient absorption, digestive efficiency, and overall health. Infants of different ages, weights, and growth stages require different feeding amounts, formula concentrations, and drinking temperatures. Therefore, in addition to meeting basic proportion requirements, it is essential to scientifically adapt the formula to individual infant differences to ensure the safety and effectiveness of feeding.

[0003] In daily feeding practices, the amount of food fed to infants and the ratio of formula to liquid are usually determined with reference to their physiological parameters, such as weight, age in months, daily intake, and growth status. These parameters have formed relatively stable guidelines through long-term childcare practice and infant nutrition research, used to determine the amount of food fed and the concentration of formula to infants at different stages to ensure nutritional balance and growth needs. Therefore, developing feeding plans based on infant physiological parameters has an objective basis and scientific foundation, providing accurate calculations for formula preparation, rather than simply relying on experience or fixed presets.

[0004] Currently, traditional formula preparation methods largely rely on manual operation. Operators must rely on experience to manually measure the amount of water and formula powder, and adjust the water temperature. This process is easily affected by factors such as differences in operator experience, changes in ambient temperature, tool precision, and operator fatigue, leading to inconsistencies in the concentration, temperature, and mixing state of each batch of formula. This instability is further reduced during nighttime feedings or frequent feedings, posing potential safety risks.

[0005] To improve the convenience and safety of formula preparation, various automatic or semi-automatic formula preparation devices have emerged on the market. These devices typically feature metered water supply, heating, and preliminary mixing functions, which can replace manual operation to some extent. However, existing devices generally operate based on fixed parameters or manual user input, lacking the ability to dynamically generate personalized feeding plans based on infant physiological parameters. Furthermore, most devices have a simple control process, usually adjusting only the water volume, formula powder volume, or temperature independently, lacking closed-loop control capabilities for coordinated adjustment of multiple parameters. This makes it difficult to promptly correct deviations between actual output and target parameters.

[0006] Furthermore, existing milk preparation equipment typically lacks comprehensive real-time monitoring of key parameters during the milk preparation process, such as milk volume, actual temperature, and mixing uniformity. Even with single-sensor feedback, it can only achieve simple open-loop or weak feedback control, failing to form a continuous closed-loop adjustment mechanism. This results in the inability to guarantee the proportioning accuracy and temperature stability during the milk preparation process under changes in equipment status or environmental disturbances.

[0007] Furthermore, existing equipment has limited data interaction capabilities with terminals, with most only supporting parameter presets or result display. It lacks the ability to record, analyze, and utilize actual operational data, and cannot optimize control strategies based on historical data. For infants of different ages, physical conditions, and physiological states, existing equipment struggles to provide personalized, scientific formula preparation plans and dynamic adjustment capabilities.

[0008] Therefore, it is necessary to provide an intelligent formula preparation control method and system based on infant physiological parameters. This method can scientifically calculate the amount of formula powder, water, and target temperature according to parameters such as the infant's weight, age, and growth status, and achieve closed-loop collaborative control through real-time detection of multiple parameters during the formula preparation process. This solution can dynamically adjust the formula preparation parameters in actual operation to ensure accurate formula ratio, uniform mixing, and stable temperature, thereby improving the scientific nature, safety, and controllability of the formula preparation process and meeting the personalized feeding needs of modern families. Summary of the Invention

[0009] This invention relates to infant feeding equipment control technology, and more particularly to an intelligent formula preparation control system and method based on infant physiological parameters. Addressing the limitations of existing formula preparation equipment in terms of proportioning accuracy, temperature control, and dynamic adjustment capabilities, this invention provides an intelligent control technology that can automatically generate personalized formula preparation plans based on physiological parameters such as infant weight, age, daily feeding amount, and growth status, and achieve closed-loop coordinated adjustment through real-time multi-parameter detection during the formula preparation process.

[0010] This invention tightly integrates infant physiological parameters with formula preparation control parameters, forming a closed-loop control mechanism that dynamically generates, adjusts in real time, and adaptively optimizes. This enables precise control over the amount of formula powder, water, mixing ratio, and formula temperature. This method not only ensures the scientific accuracy and uniformity of the formula ratio but also allows for timely parameter adjustments based on the actual formula preparation status, significantly improving the stability and safety of the preparation process while meeting the individualized feeding needs of different infants.

[0011] The core innovation of this system and method lies in its pioneering use of infant physiological parameters as input. Target formula preparation parameters are calculated using mathematical models or algorithms, and closed-loop adjustment is achieved through real-time feedback from multiple parameters. This overcomes the technical bottleneck of existing equipment that relies solely on fixed presets or single-parameter control. By continuously monitoring key parameters such as milk volume, temperature, and mixing state, and making coordinated adjustments based on deviations, this invention achieves dynamic optimization control of the formula preparation process from initial output to final output.

[0012] This invention features both historical data accumulation and adaptive optimization capabilities, enabling the analysis of deviation data from multiple milk preparations and adjustments to subsequent control strategies, thus continuously improving control accuracy over long-term use. Furthermore, this method can be extended to scenarios involving collaborative control of multiple devices or centralized cloud management, providing families or childcare institutions with a scientific, reliable, and controllable intelligent feeding solution.

[0013] Through the above technical solutions, this invention not only realizes the automatic generation of personalized feeding plans based on infant physiological parameters, but also upgrades the open-loop control of the milk preparation process to multi-parameter closed-loop collaborative control, which greatly improves the accuracy of milk powder ratio, mixing uniformity and temperature stability, providing infants with a safer, more scientific and controllable feeding method. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the overall structure of the intelligent milk preparation control device of the present invention;

[0016] Figure 2 This is a flowchart illustrating the intelligent formula preparation control method of the present invention.

[0017] Figure 3 This is a schematic diagram of the operation mode and safety control structure in this invention. Specific implementation methods

[0018] The intelligent formula preparation control method of the present invention is applied to a system consisting of a formula preparation device and a terminal. The formula preparation device includes a formula powder compartment, a water compartment, a mixing compartment, a heating unit, a temperature control unit, a control unit, and a detection module, and establishes a data connection with the terminal via a wireless communication module. The terminal is used to input infant physiological parameters and feeding requirements data, and transmits the relevant data to the control unit.

[0019] Before preparing formula, the user inputs the infant's weight, age in months, daily feeding amount, formula type, and user-defined parameters via the terminal. Based on this data, the system generates a feeding plan using preset rules, mathematical models, or lookup tables, determining the target formula preparation parameters. These target parameters include the amount of formula powder, the amount of water, the mixing ratio, and the target formula temperature. The formula powder concentration conforms to the formula preparation standards, and the target formula temperature is set within a range suitable for direct consumption by the infant, such as 36–39°C. In some embodiments, for infants weighing approximately 5–7 kg and aged 3–6 months, the amount of water used for a single formula preparation can be 180–240 ml, corresponding to a formula powder amount of approximately 20–25 g / 100 ml, but is not limited to these ranges.

[0020] After receiving the target formula preparation parameters, the control unit controls the water supply unit and the formula dispensing unit to output a quantitative amount of formula. Water output can be achieved through flow control, time control, or other quantitative methods. Formula dispensing can be achieved through screw conveying, vibratory feeding, pneumatic conveying, or weighing feedback, ensuring the initial output closely approximates the target parameters. The equipment is equipped with a container detection unit to detect whether the bottle is placed in a preset position. The control unit only performs formula dispensing or milk release operations when the bottle is detected in a valid position, preventing misoperation or spillage.

[0021] The heating unit heats the water or milk powder according to the target temperature, and the temperature control unit adjusts the heating process to ensure the output temperature meets the target requirements. Heating power and heating time can be dynamically adjusted; for example, the heating rate can be controlled within the range of approximately 1–2°C / second to balance efficiency and stability. The mixing unit mixes the water and milk powder during the milk preparation process. Mixing methods include, but are not limited to, rotary stirring, vibration mixing, or aeration mixing. The mixing intensity and time can be dynamically set according to the milk volume and concentration, for example, a mixing speed of 100–600 rpm and a mixing time of 20–90 seconds, but are not limited to these.

[0022] During the milk preparation process, the detection module acquires real-time milk preparation status parameters, including at least one of milk volume, actual temperature, and mixing state. Volume can be detected by liquid level or flow rate, temperature is acquired by a temperature sensor, and the mixing state can be characterized by turbidity detection, optical detection, or other methods. The control unit compares these status parameters with target milk preparation parameters, calculates the deviation, and dynamically adjusts the water output, milk powder addition, heating process, and mixing process based on the deviation. This adjustment can be performed independently on a single parameter or through a multi-parameter collaborative optimization mechanism to avoid amplifying the overall deviation due to a single adjustment.

[0023] The closed-loop regulation process runs through the entire milk preparation process. Through multiple iterations, the actual output gradually approaches the target range, thus ensuring the accuracy of milk ratio and temperature stability even under conditions of ambient temperature changes, equipment status fluctuations, or continuous use.

[0024] After the formula is prepared, the system sends the actual output data back to the terminal. This data includes the actual water volume, the amount of formula powder, the temperature change process, and deviation records. The terminal can store and analyze this data and use it for parameter optimization or strategy adjustment in subsequent formula preparation processes. For example, if the temperature is detected to be too low during multiple formula preparations, pre-compensation adjustments can be made to the subsequent heating parameters.

[0025] In addition, the equipment can be equipped with an operation input unit to select different working modes, including powder quantity adjustment, water quantity adjustment and temperature adjustment modes. Users can set them individually or in combination as needed, and the system will perform parameter fusion and control execution based on these settings.

[0026] The method described in this invention is not limited to specific sensor types, control algorithms, or actuator forms. It can be implemented using PID control, fuzzy control, model predictive control, or other control methods, and can be extended to multi-device collaborative control or cloud management scenarios. By combining infant physiological parameters, feeding plan generation, real-time detection of multiple parameters, and closed-loop adjustment, dynamic optimization control of the formula preparation process is achieved, thereby improving the accuracy of formula ratio, temperature stability, and overall safety.

Claims

1. A closed-loop control method for intelligent formula preparation based on infant physiological parameters, characterized in that, Includes the following steps: Acquire infant physiological parameters and feeding requirements data, and generate target formula preparation parameters based on the data. The target formula preparation parameters include at least the amount of formula powder, the amount of water, and the target formula temperature. The water supply unit, milk powder dispensing unit, heating unit, and mixing unit are controlled to perform the milk preparation process according to the target milk preparation parameters, so that the initial output is close to the target milk preparation parameters. During the milk preparation process, the milk preparation status parameters are acquired in real time, and the status parameters include at least one or more of the following: milk volume, actual temperature, and mixing state. The state parameters are compared with the target formula preparation parameters to obtain the deviation value, and the water supply, formula powder addition, heating and mixing processes are dynamically adjusted based on the deviation value to form a multi-parameter closed-loop control. After the milk is prepared, the actual output data is recorded or transmitted back for optimization and adjustment of the subsequent milk preparation process.

2. The method according to claim 1, characterized in that, The infant's physiological parameters include at least one of weight, age in months, daily feeding amount, or growth status. The target formula preparation parameters are generated through preset rules, lookup tables, or mathematical models to ensure that the formula concentration meets the preset feeding standards and that the target formula temperature is within the range acceptable to the infant.

3. The method according to claim 1, characterized in that, The dynamic adjustment is a multi-parameter coordinated adjustment process. The control unit adjusts the water output, milk powder dosage, heating power and mixing parameters independently or in combination according to the magnitude and trend of the deviation of each parameter, so that the milk preparation result converges to the target range.

4. The method according to claim 1, characterized in that, The status parameters are obtained through a detection module installed in the milk preparation equipment. The detection module includes one or more of the following: a liquid level detection unit, a flow rate detection unit, a temperature detection unit, and a mixing state detection unit.

5. The method according to claim 1, characterized in that, The milk preparation equipment includes a container detection unit, and the control unit controls the dispensing of milk powder or the output of milk liquid only when the container is detected to be in a preset position.

6. The method according to claim 1, characterized in that, The method further includes receiving a mode selection command input by the user, wherein the mode includes one or more of the following: powder quantity adjustment mode, water quantity adjustment mode, and temperature adjustment mode, and the control unit adjusts the target milk preparation parameters or control process according to the mode.

7. The method according to claim 1, characterized in that, The heating unit heats the water or milk according to the target milk temperature, and the temperature control unit dynamically adjusts the heating process; the mixing unit mixes the milk powder and water by stirring, vibration or bubbling.

8. The method according to claim 1, characterized in that, The actual output data includes state parameters and deviation records of at least one milk preparation process, and the method further includes adaptive optimization of subsequent target milk preparation parameters or control strategies based on the data.

9. An intelligent milk preparation control system, characterized in that, include: The input unit is used to acquire infant physiological parameters and feeding needs data. The feeding program generation unit is used to generate target formula preparation parameters; The control unit is used to control the water supply unit, milk powder dispensing unit, heating unit and mixing unit to perform the milk preparation process according to the target milk preparation parameters, and to perform closed-loop regulation based on the status parameters; The detection module is used to acquire milk preparation status parameters; The communication unit is used to realize data transmission and result feedback. The control unit is used to perform the method according to any one of claims 1 to 8.

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