Intelligent water cup use state monitoring and feedback method

Abstract

The invention discloses an intelligent water cup use state monitoring and feedback method, and relates to the technical field of intelligent water cup monitoring and feedback, and the method comprises the following steps: collecting temperature data and water level data of an intelligent water cup, employing the temperature data of the intelligent water cup, obtaining a heat preservation effect value of the intelligent water cup through calculation, and setting a water level threshold value of the intelligent water cup; the method comprises the following steps: acquiring an intelligent water cup water level comparison curve graph, constructing an intelligent water cup heat preservation degree monitoring model by using an LASSO regression algorithm, analyzing intelligent water cup water level data and intelligent water cup temperature data, acquiring an evaluation result, feeding back the evaluation result to a client, and taking corresponding measures by the client to intervene and cope with the evaluation result. The sensor technology, the PTC technology and the modern information technology are closely combined, temperature data and water level data of the intelligent water cup are accurately captured, the use state of the intelligent water cup is comprehensively monitored in real time, and the intelligent degree in the use state monitoring and feedback process of the intelligent water cup is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent water cup monitoring and feedback, and specifically to a method for monitoring and feedback on the usage status of an intelligent water cup. Background Technique

[0002] In the context of the rapid development of modern technology, intelligent water cups, as part of Internet of Things (IoT) devices, have gradually integrated into people's daily lives. Traditional water cups only provide basic drinking functions, while intelligent water cups integrate advanced sensor technologies and wireless communication capabilities, enabling real-time monitoring and feedback of usage status. The built-in liquid level sensor can accurately sense changes in water volume, reminding users to replenish water or record water intake, which helps to achieve personalized health management. Secondly, the temperature sensor is used to detect the temperature of the drink to ensure safe drinking and can provide heating or cooling suggestions for users through a supporting application. Through wireless communication protocols such as Bluetooth or Wi-Fi, the intelligent water cup can connect to the user's smartphone or other intelligent devices and upload the collected data to the cloud for analysis and processing. In addition, by using big data analysis and artificial intelligence algorithms, the intelligent water cup can learn the user's drinking habits, provide customized health guidance, and even predict the user's drinking needs;

[0003] Although there have been significant advancements in existing methods for monitoring and feedback on the usage status of intelligent water cups, there are still some issues that need to be optimized. It is difficult for intelligent water cups to adjust the insulation level according to changes in the external temperature and the user's insulation requirements. Secondly, during the process of the user receiving water, the intelligent water cup cannot monitor the real-time water level situation and send a feedback signal, resulting in water overflow and affecting the user experience. Summary of the Invention

[0004] To achieve the above objectives, the present invention is realized through the following technical solutions: A method for monitoring and feedback on the usage status of an intelligent water cup, including the following steps:

[0005] Step 1: Collect the temperature data and water level data of the intelligent water cup. Among them, the temperature data is the internal temperature and external temperature of the intelligent water cup at the same time interval, and the water level data is the real-time water level data of the intelligent water cup;

[0006] Step 2: Use the temperature data of the intelligent water cup to calculate and obtain the insulation effect value of the intelligent water cup;

[0007] Step 3: Set the water level threshold of the intelligent water cup and obtain the water level comparison curve graph of the intelligent water cup;

[0008] Step 4: Use the LASSO regression algorithm to construct a monitoring model for the insulation level of the intelligent water cup;

[0009] Step 5: Analyze the water level data of the smart water cup and evaluate the monitoring results of the water level change in real time; analyze the temperature data of the smart water cup and evaluate the influence of the external temperature on the heat preservation degree of the smart water cup.

[0010] Step 6: Receive the monitoring results of the water level change and the influence of the external temperature on the heat preservation degree of the smart water cup, and feedback the evaluation results to the client, and the client takes corresponding measures to intervene and respond.

[0011] Preferably, in the above Step 1, the process of collecting the temperature data of the smart water cup includes:

[0012] Equip a thermistor sensor on the side of the inner liner of the smart water cup, and equip a digital sensor on the outer shell of the smart water cup. Through the RTC chip, equip the thermistor sensor and the digital temperature sensor with the same clock source, set the time interval to 1 minute, and collect the internal temperature and external temperature of the smart water cup simultaneously.

[0013] Preferably, in the above Step 1, the process of collecting the water level data of the smart water cup includes:

[0014] Embed the pressure sensor in the bottom of the smart water cup, and use the relationship between liquid pressure and depth P = ρgh to record the pressure value P when the smart water cup is full of water max , and collect the real-time water level data of the smart water cup.

[0015] Preferably, in the above Step 2, the process of obtaining the heat preservation effect value of the smart water cup by calculation using the temperature data of the smart water cup includes:

[0016] Perform a moving average filtering process on the collected temperature data of the smart water cup:

[0017]

[0018] where, T n is the internal temperature of the smart water cup after the moving average filtering process, T W is the external temperature of the smart water cup after the moving average filtering process, x is the number of temperature data of the smart water cup collected, T 1 , T 2 ,..., T x are the internal temperature values of the smart water cup collected, t 1 , t 2 ,..., t x are the external temperature values of the smart water cup collected;

[0019] Calculate the heat preservation effect value of the smart water cup:

[0020] ΔT = T n - T w

[0021]

[0022] Among them, ΔT is the temperature difference between the inside and outside of the intelligent water cup, ΔT(0) is the initial temperature difference, ΔT(t) is the temperature difference after time t, and k is the heat preservation effect value of the intelligent water cup.

[0023] Preferably, in the third step, the process of setting the water level threshold of the intelligent water cup includes:

[0024] Based on the relationship between liquid pressure and depth P = ρgh, using the maximum pressure value P when the intelligent water cup is full of water max , reserving 10% space for the intelligent water cup, and calculating the water level value corresponding to the 10% reserved space of the intelligent water cup according to the fact that ρg is a constant:

[0025]

[0026] Among them, h t is the water level value corresponding to the reserved 10% space, ρ is the density of water, specifically 1×10 3 kg / m 3 , g is the acceleration due to gravity, specifically 9.8m / s 2 , obtaining the water level value h corresponding to the 10% reserved space of the intelligent water cup t , setting h t as the water level threshold of the intelligent water cup.

[0027] Preferably, in the third step, the process of obtaining the water level comparison curve graph of the intelligent water cup includes:

[0028] Establish a two-dimensional plane coordinate system, with the time of collecting the water level data of the intelligent water cup as the abscissa and the water level data of the intelligent water cup as the ordinate. Map the water level threshold Q of the intelligent water cup in the form parallel to the horizontal axis into the two-dimensional plane coordinate system and mark it with a red line. Map the collected real-time water level data of the intelligent water cup into the two-dimensional plane coordinate system and mark it with a black line to obtain the water level comparison curve graph of the intelligent water cup.

[0029] Preferably, in the fourth step, the process of constructing the intelligent water cup heat preservation degree monitoring model by using the LASSO regression algorithm includes:

[0030] A1. Take the internal temperature, external temperature and their corresponding heat preservation degrees of the intelligent water cup as the data set. Among them, 70% of the data set is divided into the training set, and 30% of the data set is divided into the test set;

[0031] A2. Take the internal temperature and external temperature of the smart water cup as the feature vectors, and the corresponding heat preservation effect value of the smart water cup as the target vector. Organize the internal temperature and external temperature of the smart water cups in the training set into a feature matrix X, and organize the corresponding heat preservation effect values of the smart water cups into a target matrix Y. Import the feature matrix X and the target matrix Y into the LASSO regression algorithm library. Through the cross-validation method, set the regularization parameter alpha to create a LASSO regression model object;

[0032] A3. Use the feature matrix X and the target vector Y of the training set to train the LASSO model. According to the characteristics of the internal temperature and external temperature of the smart water cup and their corresponding heat preservation effect values, combined with the regularization parameter alpha, train the linear relationship between the internal temperature and external temperature of the smart water cup and the corresponding heat preservation effect value of the smart water cup, so that the heat preservation effect value k of the smart water cup > 0.8, output a high heat preservation level; when the heat preservation effect value 0.6 < k < 0.8 of the smart water cup, output a good heat preservation level; when the heat preservation effect value k of the smart water cup < 0.6, output a low heat preservation level;

[0033] A4. Input the internal temperature and external temperature of the smart water cup in the test set into the trained LASSO model, output the corresponding heat preservation level, evaluate the consistency between the heat preservation level corresponding to the actual heat preservation effect value k and the heat preservation level output by the test set, and optimize the LASSO model by adjusting the model parameters to obtain a smart water cup heat preservation level monitoring model.

[0034] Preferably, in step five, the process of analyzing the water level data of the smart water cup and evaluating the water level change monitoring result includes:

[0035] Analyze the real-time water level data of the smart water cup, combined with the water level comparison curve graph of the smart water cup. When the water level of the smart water cup reaches below 70% of the water level threshold ht, the water level of the smart water cup is normal and the overflow risk is 0%;

[0036] When the water level of the smart water cup reaches between 70% and 90% of the water level threshold ht, the water level of the smart water cup is on the high side and the overflow risk is 50%;

[0037] When the water level of the smart water cup reaches above 90% of the water level threshold ht, the water level of the smart water cup is on the high side and the overflow risk is 80%;

[0038] Preferably, in step five, the process of analyzing the temperature data of the smart water cup and evaluating the influence result of the external temperature on the heat preservation level of the smart water cup includes:

[0039] Analyze the temperature data inside and outside the intelligent water cup. Combining with the monitoring model of the heat preservation degree of the intelligent water cup, when the heat preservation effect value k of the intelligent water cup is greater than 0.8, the heat preservation degree of the intelligent water cup is high; when the heat preservation effect value of the intelligent water cup satisfies 0.6 < k < 0.8, the heat preservation degree of the intelligent water cup is good; when the heat preservation effect value k of the intelligent water cup is less than 0.6, the heat preservation degree of the intelligent water cup is low.

[0040] Preferably, in the sixth step, the process of receiving the monitoring result of the water level change and the influence result of the external temperature on the heat preservation degree of the intelligent water cup, and feeding back the evaluation result to the client for the client to take corresponding measures to intervene and respond includes:

[0041] Receive the monitoring result of the water level change. When the overflow risk is 0%, the intelligent water cup continuously monitors the water level change and sends a voice feedback signal of "Normal water addition, no overflow risk" to the client; when the overflow risk is 50%, the intelligent water cup sends a voice feedback signal of "Medium water overflow risk, please add water carefully" to the client, and the client takes measures to reduce the water receiving flow rate to respond; when the overflow risk is 80%, the intelligent device sends a voice feedback signal of "High overflow risk, please stop adding water" to the client, and the client takes measures to terminate the water addition process to respond;

[0042] Receive the influence result of the external temperature on the heat preservation degree of the intelligent water cup. When the heat preservation degree of the intelligent water cup is high, continuously monitor the heat preservation degree, send a voice feedback signal of "The current heat preservation degree is high, and the water temperature is kept good" to the client, and provide a heat preservation performance table for the user to intuitively feel the change of the heat preservation degree; when the heat preservation degree of the intelligent water cup is good, the intelligent water cup increases the power to compensate for the change of the external temperature, reduces the heat loss, improves the heat preservation performance, and sends a voice feedback signal of "Good heat preservation condition, optimizing" to the client; when the heat preservation degree of the intelligent water cup is low, the intelligent water cup starts the heat preservation strengthening function, distributes power to the heat preservation element, and sends a voice feedback signal of "Low heat preservation degree, please drink as soon as possible" to the client.

[0043] The beneficial effects of the present invention are as follows: For the method for monitoring and feedback of the usage status of the intelligent water cup, compared with the traditional method for monitoring and feedback of the usage status of the intelligent water cup, in the method of the present invention, sensor technology, PTC technology and modern information technology are closely combined to accurately capture the temperature data and water level data of the intelligent water cup, obtain the internal temperature and external temperature of the intelligent water cup at the same time interval and the real-time water level data of the intelligent water cup, achieving real-time and comprehensive monitoring of the usage status of the intelligent water cup. Through calculation, the heat preservation effect value of the intelligent water cup is obtained, the water level threshold of the intelligent water cup is set, the water level comparison curve graph of the intelligent water cup is obtained, and the LASSO regression algorithm is used to construct a monitoring model for the heat preservation degree of the intelligent water cup, solving the problem that it is difficult for the intelligent water cup to adjust the heat preservation degree according to the external temperature change and the heat preservation requirements of the user, and during the process of the user receiving water, the intelligent water cup cannot monitor the real-time water level situation and send out a feedback signal, resulting in water overflow and affecting the customer experience. It ensures that the method in the present invention can refine the dynamic monitoring standard for the method of monitoring and feedback of the usage status of the intelligent water cup within a more accurate range, making the monitored data more accurate indicators under the same conditions. The research and application of this method significantly enhance the degree of intelligence in the process of monitoring and feedback of the usage status of the intelligent water cup. Brief Description of the Drawings

[0044] Figure 1 It is a flowchart of a method for monitoring and feedback of the usage status of an intelligent water cup according to the present invention. Detailed Embodiment

[0045] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0046] As Figure 1 shown, the present invention provides a technical solution: a method for monitoring and feedback of the usage status of an intelligent water cup

[0047] Step 1: Collect the temperature data and water level data of the intelligent water cup. Among them, the temperature data is the internal temperature and external temperature of the intelligent water cup at the same time interval, and the water level data is the real-time water level data of the intelligent water cup;

[0048] Step 2: Use the temperature data of the intelligent water cup to obtain the heat preservation effect value of the intelligent water cup through calculation;

[0049] Step 3: Set the water level threshold of the intelligent water cup and obtain the water level comparison curve graph of the intelligent water cup;

[0050] Step 4: Use the LASSO regression algorithm to construct a monitoring model for the heat preservation degree of the intelligent water cup;

[0051] Step 5: Analyze the water level data of the intelligent water cup and evaluate the monitoring results of the water level change in real time; analyze the temperature data of the intelligent water cup and evaluate the influence of the external temperature on the heat preservation degree of the intelligent water cup;

[0052] Step 6: Receive the monitoring results of the water level change and the influence of the external temperature on the heat preservation degree of the intelligent water cup, and feedback the evaluation results to the client, and the client takes corresponding measures to intervene and respond.

[0053] In Step 1, the process of collecting the temperature data of the intelligent water cup includes:

[0054] Equip a thermistor sensor on the side of the inner liner of the intelligent water cup, and equip a digital sensor on the outer shell of the intelligent water cup. Through the RTC chip, equip the thermistor sensor and the digital temperature sensor with the same clock source, set the time interval to 1 minute, and collect the internal temperature and external temperature of the intelligent water cup at the same time.

[0055] In Step 1, the process of collecting the water level data of the intelligent water cup includes:

[0056] Embed the pressure sensor at the bottom of the intelligent water cup, and use the relationship between liquid pressure and depth P = ρgh to record the pressure value P when the intelligent water cup is full of water max and collect the real-time water level data of the intelligent water cup.

[0057] In Step 2, the process of obtaining the heat preservation effect value of the intelligent water cup by calculation using the temperature data of the intelligent water cup includes:

[0058] Perform moving average filtering on the collected temperature data of the intelligent water cup:

[0059]

[0060] where T n is the internal temperature of the intelligent water cup after moving average filtering, T W is the external temperature of the intelligent water cup after moving average filtering, x is the number of temperature data of the intelligent water cup collected, T 1 , T 2 ,..., T x is the internal temperature value of the intelligent water cup collected, t 1 , t 2 ,..., t x is the external temperature value of the intelligent water cup collected;

[0061] Calculate the heat preservation effect value of the intelligent water cup:

[0062] ΔT = Tn -T w

[0063]

[0064] Among them, ΔT is the temperature difference between the inside and outside of the intelligent water cup, ΔT(0) is the initial temperature difference, ΔT(t) is the temperature difference after time t, and k is the heat preservation effect value of the intelligent water cup.

[0065] In step three, the process of setting the water level threshold of the intelligent water cup includes:

[0066] Based on the relationship between liquid pressure and depth P = ρgh, using the maximum pressure value P when the intelligent water cup is full of water max , reserving 10% space for the intelligent water cup, and according to ρg being a constant, calculating the water level value corresponding to the 10% reserved space of the intelligent water cup:

[0067]

[0068] Among them, h t is the water level value corresponding to the reserved 10% space, ρ is the density of water, specifically 1×10 3 kg / m 3 , g is the acceleration due to gravity, specifically 9.8m / s 2 , obtaining the water level value h corresponding to the 10% reserved space of the intelligent water cup t , setting h t as the water level threshold of the intelligent water cup.

[0069] In step three, the process of obtaining the water level comparison curve graph of the intelligent water cup includes:

[0070] Establish a two-dimensional plane coordinate system, with the time of collecting the water level data of the intelligent water cup as the abscissa and the water level data of the intelligent water cup as the ordinate. Map the water level threshold Q of the intelligent water cup onto the two-dimensional plane coordinate system in the form parallel to the horizontal axis and mark it with a red line. Map the collected real-time water level data of the intelligent water cup onto the two-dimensional plane coordinate system and mark it with a black line to obtain the water level comparison curve graph of the intelligent water cup.

[0071] In step four, the process of constructing the intelligent water cup heat preservation degree monitoring model using the LASSO regression algorithm includes:

[0072] A1. Take the internal temperature, external temperature and their corresponding heat preservation degrees of the intelligent water cup as the data set. Among them, 70% of the data set is divided into the training set, and 30% of the data set is divided into the test set;

[0073] A2. Take the internal temperature and external temperature of the intelligent water cup as feature vectors, and the corresponding heat preservation effect value of the intelligent water cup as the target vector. Organize the internal temperature and external temperature of the intelligent water cups in the training set into a feature matrix X, and organize the corresponding heat preservation effect values of the intelligent water cups into a target matrix Y. Import the feature matrix X and the target matrix Y into the LASSO regression algorithm library, and through the cross-validation method, set the regularization parameter alpha to create a LASSO regression model object;

[0074] A3. Use the feature matrix X and the target vector Y of the training set to train the LASSO model. According to the characteristics of the internal temperature and external temperature of the intelligent water cup and their corresponding heat preservation effect values, combined with the regularization parameter alpha, train the linear relationship between the internal temperature and external temperature of the intelligent water cup and the corresponding heat preservation effect value of the intelligent water cup, so that the heat preservation effect value k of the intelligent water cup > 0.8, output a high heat preservation level; when the heat preservation effect value of the intelligent water cup is 0.6 < k < 0.8, output a good heat preservation level; when the heat preservation effect value of the intelligent water cup k < 0.6, output a low heat preservation level;

[0075] A4. Input the internal temperature and external temperature of the intelligent water cup in the test set into the trained LASSO model, output the corresponding heat preservation level, evaluate the consistency between the heat preservation level corresponding to the actual heat preservation effect value k and the heat preservation level output by the test set, and optimize the LASSO model by adjusting the model parameters to obtain an intelligent water cup heat preservation level monitoring model.

[0076] Step Five. The process of analyzing the water level data of the intelligent water cup and evaluating the water level change monitoring results in real time includes:

[0077] Analyze the real-time water level data of the intelligent water cup, and combine it with the water level comparison curve graph of the intelligent water cup. When the water level of the intelligent water cup reaches below 70% of the water level threshold ht, the water level of the intelligent water cup is normal and the overflow risk is 0%;

[0078] When the water level of the intelligent water cup reaches between 70% and 90% of the water level threshold ht, the water level of the intelligent water cup is on the high side and the overflow risk is 50%;

[0079] When the water level of the intelligent water cup reaches above 90% of the water level threshold ht, the water level of the intelligent water cup is on the high side and the overflow risk is 80%;

[0080] Step Five. The process of analyzing the temperature data of the intelligent water cup and evaluating the influence result of the external temperature on the heat preservation level of the intelligent water cup includes:

[0081] Analyze the temperature data inside and outside the smart water cup. Combining with the monitoring model of the heat preservation degree of the smart water cup, when the heat preservation effect value k of the smart water cup is greater than 0.8, the heat preservation degree of the smart water cup is high; when the heat preservation effect value of the smart water cup satisfies 0.6 < k < 0.8, the heat preservation degree of the smart water cup is good; when the heat preservation effect value k of the smart water cup is less than 0.6, the heat preservation degree of the smart water cup is low.

[0082] In step six, the process of receiving the monitoring result of the water level change and the influence result of the external temperature on the heat preservation degree of the smart water cup, and feeding back the evaluation result to the client for the client to take corresponding measures to intervene and respond includes:

[0083] Receive the monitoring result of the water level change. When the overflow risk is 0%, the smart water cup continuously monitors the water level change and sends a voice feedback signal of "Normal water addition, no overflow risk" to the client; when the overflow risk is 50%, the smart water cup sends a voice feedback signal of "Medium water overflow risk, please add water carefully" to the client, and the client takes measures to reduce the water receiving flow rate to respond; when the overflow risk is 80%, the smart device sends a voice feedback signal of "High overflow risk, please stop adding water" to the client, and the client takes measures to terminate the water addition process to respond;

[0084] Receive the influence result of the external temperature on the heat preservation degree of the smart water cup. When the heat preservation degree of the smart water cup is high, continuously monitor the heat preservation degree, send a voice feedback signal of "The current heat preservation degree is high, and the water temperature remains good" to the client, and provide a heat preservation performance table for the user to intuitively feel the change of the heat preservation degree; when the heat preservation degree of the smart water cup is good, the smart water cup increases the power compensation for the external temperature change, reduces heat dissipation, and improves the heat preservation performance, and sends a voice feedback signal of "Good heat preservation condition, optimizing" to the client; when the heat preservation degree of the smart water cup is low, the smart water cup activates the heat preservation strengthening function, distributes power to the heat preservation element, and sends a voice feedback signal of "Low heat preservation degree, please drink as soon as possible" to the client.

[0085] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation. An element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0086] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for monitoring and providing feedback on the use status of a smart water cup, characterized in that: The following steps are involved: Step 1: Collect temperature data and water level data of the smart water cup, wherein the temperature data is the internal temperature and external temperature of the smart water cup at the same time interval, and the water level data is the real-time water level data of the smart water cup; Step 2: Using the temperature data of the smart water cup, obtain the thermal insulation effect value of the smart water cup through calculation; Step 3: Set the water level threshold of the smart water cup and obtain the water level comparison curve of the smart water cup; Step 4: Use the LASSO regression algorithm to build a smart water cup insulation degree monitoring model; Step 5: Analyze the water level data of the smart water cup and evaluate the water level change monitoring results in real time; analyze the temperature data of the smart water cup and evaluate the impact of the external temperature on the heat preservation degree of the smart water cup; Step 6: Receive the monitoring results of water level changes and the impact of external temperature on the thermal insulation level of the smart water cup, and feed back the evaluation results to the client, which will take corresponding measures to intervene.

2. The method for monitoring and providing feedback on the use status of a smart water cup according to claim 1, characterized in that: In step 1, the process of collecting temperature data of the smart water cup includes: Equip the side of the smart water cup with a thermistor sensor and the outer shell of the smart water cup with a digital sensor; The RTC chip is used to equip the thermistor sensor and the digital temperature sensor with the same clock source, and the time interval is set to 1 minute. The internal and external temperatures of the smart water cup are collected at the same time.

3. The method for monitoring and providing feedback on the use status of a smart water cup according to claim 2, characterized in that: In step 1, the process of collecting water level data of the smart water cup includes: The pressure sensor is embedded in the bottom of the smart water cup. The relationship between liquid pressure and depth P = ρgh is used to record the pressure value P when the smart water cup is full of water. max , and collect real-time water level data of the smart water cup.

4. The method for monitoring and providing feedback on the use status of a smart water cup according to claim 3, characterized in that: In step 2, the process of obtaining the heat preservation effect value of the smart water cup by calculation using the temperature data of the smart water cup includes: Perform sliding average filtering on the collected smart water cup temperature data: Among them, T n is the internal temperature of the smart water cup after sliding smoothing filtering, T W is the external temperature of the smart water cup after sliding smoothing filtering, x is the number of smart water cup temperature data collected, T1, T2, ..., T x is the collected temperature value inside the smart water cup, t1, t2, ..., t x The collected external temperature value of the smart water cup; Calculate the insulation effect value of the smart water cup: ΔT=T n -T w Among them, ΔT is the temperature difference between the inside and outside of the smart water cup, ΔT(0) is the initial temperature difference, ΔT(t) is the temperature difference after t time, and k is the insulation effect value of the smart water cup.

5. The method for monitoring and providing feedback on the use status of a smart water cup according to claim 4, characterized in that: In step 3, the process of setting the water level threshold of the smart water cup includes: Based on the relationship between liquid pressure and depth P = ρgh, the maximum pressure value P when the smart water cup is full of water is used. max , reserve 10% of the space for the smart water cup, and calculate the water level value corresponding to the 10% space reserved for the smart water cup in combination with the constant setting of ρg: Among them, h t is the water level corresponding to the reserved 10% space, ρ is the density of water, specifically 1×10 3 kg / m 3 , g is the acceleration due to gravity, specifically 9.8m / s 2 , get the water level value h corresponding to the 10% space reserved by the smart water cup t , set h t It is the water level threshold of the smart water cup.

6. The method for monitoring and providing feedback on the use status of a smart water cup according to claim 5, characterized in that: In step 3, the process of obtaining the water level comparison curve of the smart water cup includes: A two-dimensional coordinate system is established, with the time of collecting the water level data of the smart water cup as the horizontal coordinate and the water level data of the smart water cup as the vertical coordinate. The water level threshold Q of the smart water cup is mapped to the two-dimensional coordinate system in a form parallel to the horizontal axis and marked with a red line. The collected real-time water level data of the smart water cup is mapped to the two-dimensional coordinate system and marked with a black line to obtain the water level comparison curve of the smart water cup.

7. The method for monitoring and providing feedback on the use status of a smart water cup according to claim 6, characterized in that: In step 4, the process of constructing a smart water cup heat preservation degree monitoring model using the LASSO regression algorithm includes: A1. The internal temperature and external temperature of the smart water cup and their corresponding insulation levels are used as a data set, of which 70% of the data set is divided into a training set and 30% of the data set is divided into a test set; A2. The internal temperature and external temperature of the smart water cup are used as feature vectors, and the corresponding insulation effect value of the smart water cup is used as the target vector. The internal temperature and external temperature of the smart water cup in the training set are sorted into a feature matrix X, and the corresponding insulation effect value of the smart water cup is sorted into a target matrix Y. The feature matrix X and the target matrix Y are imported into the LASSO regression algorithm library. Through the cross-validation method, the regularization parameter alpha is set to create a LASSO regression model object. A3. Use the feature matrix X and target vector Y of the training set to train the LASSO model. According to the characteristics of the internal temperature, external temperature of the smart water cup and their corresponding heat preservation effect values, combined with the regularization parameter alpha, train the linear relationship between the internal temperature, external temperature of the smart water cup and the corresponding heat preservation effect value of the smart water cup, so as to achieve a heat preservation effect value k>0.8 of the smart water cup, output a high heat preservation level, a heat preservation effect value of 0.6<k<0.8 of the smart water cup, output a good heat preservation level, and a heat preservation effect value k<0.6 of the smart water cup, output a low heat preservation level; A4. Input the internal temperature and external temperature of the smart water cup in the test set into the trained LASSO model, output the corresponding heat preservation level, evaluate the consistency between the heat preservation level corresponding to the actual heat preservation effect value k and the heat preservation level output by the test set, and optimize the LASSO model by adjusting the model parameters to obtain a smart water cup heat preservation level monitoring model.

8. The method for monitoring and providing feedback on the use status of a smart water cup according to claim 7, characterized in that: In step five, the process of analyzing the water level data of the smart water cup and evaluating the water level change monitoring result in real time includes: Analyze the real-time water level data of the smart water cup, and combine it with the water level comparison curve of the smart water cup. When the water level of the smart water cup reaches below 70% of the water level threshold ht, the water level of the smart water cup is normal and the overflow risk is 0%; When the water level of the smart water cup reaches between 70% and 90% of the water level threshold ht, the water level of the smart water cup is on the high side and the overflow risk is 50%; When the water level of the smart water cup reaches above 90% of the water level threshold ht, the water level of the smart water cup is on the high side and the overflow risk is 80%.

9. The method for monitoring and providing feedback on the use status of a smart water cup according to claim 8, characterized in that: In step five, the process of analyzing the temperature data of the smart water cup and evaluating the influence result of the external temperature on the heat preservation level of the smart water cup includes: Analyze the internal and external temperature data of the smart water cup, and combine it with the smart water cup heat preservation level monitoring model. When the heat preservation effect value k of the smart water cup is greater than 0.8, the heat preservation level of the smart water cup is high; when the heat preservation effect value of the smart water cup satisfies 0.6<k<0.8, the heat preservation level of the smart water cup is good; when the heat preservation effect value k of the smart water cup is less than 0.6, the heat preservation level of the smart water cup is low.

10. The method for monitoring and providing feedback on the use status of a smart water cup according to claim 9, characterized in that: In step six, the process of receiving the water level change monitoring result and the influence result of the external temperature on the heat preservation level of the smart water cup, and feeding back the evaluation result to the client, and the client taking corresponding measures to intervene and respond includes: Receive the water level change monitoring result. When the overflow risk is 0%, the smart water cup continuously monitors the water level change and sends a voice feedback signal of "Normal water addition, no overflow risk" to the client; when the overflow risk is 50%, the smart water cup sends a voice feedback signal of "Medium water overflow risk, please add water carefully" to the client, and the client takes measures to reduce the water receiving flow to respond; when the overflow risk is 80%, the smart device sends a voice feedback signal of "High overflow risk, please stop adding water" to the client, and the client takes measures to terminate the water addition process to respond; Receive the results of the effect of the outside temperature on the insulation level of the smart water cup. When the insulation level of the smart water cup is high, the insulation level is continuously monitored, and a voice feedback signal of "the current insulation level is high and the water temperature is maintained well" is sent to the client, and an insulation performance table is provided so that the user can intuitively feel the changes in the insulation level; when the insulation level of the smart water cup is good, the smart water cup increases power to compensate for changes in the outside temperature, reduces heat loss, improves insulation performance, and sends a voice feedback signal of "the insulation status is good and is being optimized" to the client; when the insulation level of the smart water cup is low, the smart water cup starts the insulation enhancement function, allocates power to the insulation element, and sends a voice feedback signal of "the insulation level is low, please drink as soon as possible" to the client.

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