Accurate drinking water management system and data sharing platform

Abstract

The invention provides a precise drinking water management system and a data sharing platform. The accurate drinking water management system comprises a data acquisition module used for collecting physiological parameters, activity data and environment information of a user; and the intelligent processing module is used for processing the data from the data acquisition module, generating a water drinking target based on the data and providing personalized water drinking suggestions. The accurate drinking water management system provided by the invention can provide personalized drinking water suggestions according to the physiological characteristics, daily activities and environmental conditions of the user, help the user to better meet the body requirements, can help the user to establish a good drinking water habit by using the system for a long time, and is beneficial to the overall health; collected health information can be used for long-term health data analysis, and deeper health insight is provided for related research.

Description

Technical Field

[0001] The present invention relates to the technical field of health monitoring, and in particular to a precise drinking water management system and a data sharing platform. Background Art

[0002] Water is an important component of the human body and plays a variety of important physiological roles, which is crucial for human health. However, despite the widespread recognition of the impact of water intake on health, the research data on the relationship between water and health is still insufficient. Existing research often focuses on the population level and lacks in-depth understanding of individual water needs. For example, people of different ages, genders, weights, and activity levels have different water requirements and intake methods, and these individual differences are often ignored in existing research. In addition, environmental factors such as climate, temperature, and humidity also affect individual water needs.

[0003] The intake and excretion of water in the human body are in a dynamic balance. Insufficient water intake will affect the hydration status of the human body, and further affect cognition and health. Therefore, maintaining an appropriate hydration status is of great significance for maintaining and promoting the health of the body. It is of great significance to judge one's own hydration status and timely replenish water to make the body in an appropriate hydration status; in addition, the drinking actions caused by timely water replenishment also help to reduce the impact of sedentary behavior on health. Sedentary behavior can lead to weakening of the myocardium, slow blood circulation, and cause diseases such as hypertension and coronary artery embolism, while actions such as standing, walking, and water conservation during drinking can effectively alleviate the health risks brought by long-term sitting.

[0004] In addition, in order to provide more accurate drinking water advice, it is necessary to collect a large amount of individual drinking water volume data and conduct scientific research analysis in combination with these data to better understand the water needs of each person. However, there is currently no data sharing platform for the field of drinking water.

[0005] Currently, there are some drinking water management systems. For example, CN108461121A discloses a method and system for recommending drinking water volume, which integrates the influencing factors of individual drinking water volume. However, this system does not propose specific parameters for the recommended drinking water volume corresponding to each factor. CN107550189A discloses a drinking water volume reminder system and method, which reminds of the drinking water volume by detecting the drinking water volume, preset personal drinking water volume, and drinking time, but cannot achieve the function of providing precise drinking water management according to the body's hydration status and sedentary status. Summary of the Invention

[0006] In view of the above current situations and problems existing in the prior art, the purpose of the present invention is to provide a precise drinking water management system and a data sharing platform. This system can provide clear recommended drinking water amounts based on user information and the surrounding environment, and has the function of managing drinking water according to the user's hydration status and sedentary time. At the same time, the present invention also provides a drinking water health data sharing platform.

[0007] Specifically, the present invention first provides a precise drinking water management system, which mainly consists of two parts: a data acquisition module for collecting users' physiological parameters, activity data, and environmental information; and an intelligent processing module for processing the data from the data acquisition module, generating a drinking water target based on the data, and providing personalized drinking water suggestions. The data acquisition module and the intelligent processing module are electrically connected. The data acquisition module includes multiple sensors and an input interface for collecting users' physiological parameters, activity data, and environmental information and transmitting them to the intelligent processing module.

[0008] Among them, the data acquisition module further includes:

[0009] A user input interface for receiving personal information input by the user, such as age, gender, weight, height, and drinking water information, etc.;

[0010] A physiological sensor for real-time monitoring of users' physiological parameters, such as hydration status, heart rate, blood pressure, etc.;

[0011] An activity sensor for recording users' activity data, such as physical activity level and sedentary time;

[0012] An environmental sensor for detecting environmental information of the user's surrounding environment, such as temperature, humidity, altitude, longitude and latitude, etc. information; and

[0013] A drinking water data collector for collecting users' drinking water amount information.

[0014] Furthermore, the drinking water information further includes the type and brand of drinking water, whether a water treatment device is used and the brand used.

[0015] Among them, the intelligent processing module further includes:

[0016] A data receiving module for receiving the data from the data acquisition module;

[0017] A data processing module for calculating and generating a drinking water target value according to physiological parameters, activity data, and environmental information; and calculating and generating water quality data according to the longitude and latitude information and drinking water information of the user; and

[0018] The intelligent reminder module is used to provide drinking water reminders, including reminding the user of the time, frequency, and quantity of drinking water based on the user's hydration status, sedentary time, and drinking water target value.

[0019] Furthermore, the drinking water target value is calculated based on the physical activity level, body weight, humidity, altitude, temperature, and whether the user is an athlete.

[0020] Furthermore, the drinking water target value is further calculated according to the following formula:

[0021] RWI (ml / d) = {[1076 × PAL] + [14.34 × W (kg)] + [374.9 × S] + [5.823 × H (%)] + [1070 × AS] + [0.4726 × A (m)] – [0.3529 × Y (years) 2 + [24.78 × Y (years)] + [1.865 × T (°C) 2 – [19.66 × T (°C)] – 713.1} × 55%

[0022] Where, RWI is the drinking water target value, with the unit of ml / d; PAL is the physical activity level; W is the body weight, with the unit of kg; S is the gender, 1 for male and 0 for female; H is the local air humidity, with the unit of %; AS is the athlete status, 1 for athlete and 0 for non-athlete; A is the altitude, with the unit of m; Y is the age, with the unit of years; T is the local temperature, with the unit of °C. Through this algorithm, the system dynamically adjusts the drinking water advice according to the user's activity data and environmental changes; and can predict the user's predicted drinking water data in the future period through the historical drinking water data.

[0023] Furthermore, the drinking water reminder plan is as follows: When it is detected that the user has not been active or has a low activity level within 45 minutes, or the hydration status is insufficient, remind the user to get up and drink water to ensure the user's physical health. Reminding the user to replenish water and get up and move according to the hydration status and sedentary status can avoid the decline of physiological functions caused by chronic dehydration in the user, and avoid health problems caused by sedentary behavior.

[0024] Among them, the hydration status is one of the important factors to consider in individual drinking water management. The hydration status refers to the body's water reaching an appropriate level, which is crucial for physical health and is determined by the water intake and output. If the water intake is roughly equal to the water output, the water in the body is in a state of water balance, that is, the normal hydration status; when the body intakes too little water or loses too much water, the body is in a state of dehydration; when the body intakes too much water, the body is in a state of overhydration, and in severe cases, it may cause water intoxication. The hydration status can usually be judged by total water intake, body weight, plasma osmotic pressure, urine-related indicators (urine osmotic pressure, urine specific gravity, urine output, urination frequency, urine color), saliva osmotic pressure, tear osmotic pressure, etc. In the present invention, the individual skin hydration status obtained by transdermal measurement using a physiological sensor is one of the important factors for providing dynamic drinking water suggestions by real-time monitoring of the user's physiological parameters.

[0025] Furthermore, when it is detected that the user is below the drinking water target value at 17:00 on the same day, an alarm is issued and a water replenishment plan is provided. When the user's water intake is below the drinking water target, the user can be reminded to replenish water in time to avoid health problems caused by acute water shortage.

[0026] Among them, the method for generating the water quality data is as follows:

[0027] The water quality conditions of domestic drinking water in each county-level city (district), the water quality data of each brand of bottled drinking water, and the filtration functions of each brand and model of water treatment equipment are pre-stored in the system;

[0028] According to the user's longitude and latitude information, judge the county-level city (district) where the user is located;

[0029] According to the drinking water information input by the user, judge the type of drinking water;

[0030] If the type of drinking water is bottled drinking water, generate the water quality data of the corresponding brand;

[0031] If the type of drinking water is tap water, further judge whether a water treatment equipment is used;

[0032] If the type of drinking water is tap water and no water treatment equipment is used, generate the water quality data of the domestic drinking water in the county-level city (district) where the user is located;

[0033] If the type of drinking water is tap water and a water treatment equipment is used, generate the water quality data according to the water quality conditions of the domestic drinking water in the county-level city (district) where the user is located and the filtration function of the water treatment equipment.

[0034] In addition, the system may further include an intelligent device interface for connecting to devices such as intelligent water cups or intelligent bracelets, and disposing all or part of the components of the data acquisition module and the intelligent reminder module in the intelligent device to monitor the user's water intake (drinking water information) and physiological parameters in real time, provide drinking water reminders, and achieve personalized drinking water health management.

[0035] Meanwhile, the present invention also provides a data sharing platform, which includes:

[0036] A data upload module for uploading the user's drinking water data to a cloud server for storage to build a big data platform for drinking water health;

[0037] A platform docking module for docking with other open health platforms through the user's unique identification code to enrich the data types; and

[0038] A data download module for downloading the drinking water data obtained from the cloud server for data mining, data visualization, data modeling, data prediction, etc., to achieve precise long-term health analysis of the user and provide data support for scientific research in the field of drinking water.

[0039] The precise drinking water management system provided by the present invention can provide personalized drinking water suggestions according to the user's physiological characteristics, daily activities and environmental conditions, helping the user better meet the body's needs. Long-term use of this system can help the user establish good drinking water habits, which is beneficial to overall health; the collected health information can be used for long-term health data analysis to provide deeper health insights for relevant research. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic diagram of the composition framework of a precise drinking water management system provided by the present invention.

[0041] Figure 2 It is a schematic diagram of the core algorithm of the drinking water target of a precise drinking water management system provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] To clearly illustrate the technical features of this solution, the present invention will be elaborated in detail below through specific embodiments and in combination with its drawings. The following disclosure provides many different embodiments or examples for implementing different structures of the present invention. To simplify the disclosure of the present invention, the components and settings of specific examples are described below. In addition, the present invention may repeat reference numerals and / or letters in different examples. This repetition is for the purpose of simplification and clarity, and does not itself indicate the relationship between the various embodiments and / or settings discussed. It should be noted that the components illustrated in the drawings are not necessarily drawn to scale. The present invention omits the description of well-known components and processing technologies and processes to avoid unnecessarily limiting the present invention.

[0043] As Figure 1 shown in the framework of a precise drinking water management system, the system is divided into a data acquisition module and an intelligent processing module. Each component of the data acquisition module, such as the user input interface, physiological sensor, activity sensor, environmental sensor, and drinking water data collector, transmits the data measured / collected by itself to the intelligent processing module. The intelligent processing module includes a data receiving module, a data processing module, and an intelligent reminder module.

[0044] The data acquisition module specifically may include:

[0045] The user input interface is used to receive personal information input by the user, such as age, gender, weight, height, and drinking water information, etc.

[0046] The physiological sensor is used to continuously monitor the physiological state of the user, such as the hydration state, heart rate, blood pressure, etc.

[0047] The activity sensor is used to record the user's physical activity level and sedentary time.

[0048] The environmental sensor is used to detect information such as the temperature, humidity, altitude, etc. of the environment where the user is located.

[0049] The drinking water amount calculation engine (drinking water data collector) is used to calculate the user's daily drinking water amount according to the collected data and user information.

[0050] The data acquisition module is electrically connected to the intelligent processing module. The way of electrical connection includes the data line connection of physical hardware and also includes wireless signal connection. Among them, the data acquisition module is used to collect the user's drinking water information, physiological data, activity data, and environmental data where the user is located and send them to the intelligent processing module.

[0051] The intelligent processing module includes a data receiving module, which is used to receive the data of the data acquisition module.

[0052] The intelligent processing module further includes a data processing module, which is used to calculate and generate a drinking water target value according to the physiological, activity, and environmental information. The drinking water target value is calculated according to data such as the physical activity level, weight, relative humidity, altitude, temperature, whether the user is an athlete, etc., according to the core algorithm (such as Figure 2 ).

[0053] The core algorithm is:

[0054] RWI (ml / d) = {[1076 × PAL] + [14.34 × W (kg)] + [374.9 × S] + [5.823 × H (%)] + [1070 × AS] + [0.4726 × A (m)] – [0.3529 × Y (years) 2+[24.78 × Y (years)] + [1.865 × T (°C) 2 – [19.66 × T (°C)] – 713.1} × 55%

[0055] Where RWI is the drinking water target, in ml / d; PAL is the physical activity level, 0.5 for inactive, 1.5 for moderately active, and 2.5 for very active; W is the body weight, in kg; S is the gender, 1 for male and 0 for female; H is the local air humidity, in %; AS is the athlete status, 1 for athlete and 0 for non-athlete; A is the altitude, in m; Y is the age, in years; T is the local temperature, in °C.

[0056] The data processing module is also used to calculate and generate water quality data based on the longitude and latitude information and drinking water information of the user. The method for generating the water quality data is as follows:

[0057] The system pre-stores the domestic drinking water quality conditions of each county-level city (district), the water quality data of each brand of bottled drinking water, and the filtration functions of each brand and model of water treatment equipment.

[0058] Based on the longitude and latitude information of the user, determine the county-level city (district) where the user is located;

[0059] Based on the drinking water information input by the user, determine the type of drinking water;

[0060] If the type of drinking water is bottled drinking water, generate the water quality data of the corresponding brand.

[0061] If the type of drinking water is tap water, further determine whether a water treatment equipment is used;

[0062] If the type of drinking water is tap water and no water treatment equipment is used, generate the domestic drinking water quality data of the county-level city (district) where the user is located;

[0063] If the type of drinking water is tap water and a water treatment equipment is used, generate the water quality data based on the domestic drinking water quality conditions of the county-level city (district) where the user is located and the filtration function of the water treatment equipment.

[0064] The intelligent processing module also includes an intelligent reminder module, which is used to provide drinking water reminders according to the user's hydration status, sedentary status, and drinking water target value, including the time, frequency, and quantity of the user's drinking water. The specific optional implementation scheme of the drinking water reminder is as follows: when it is detected that the user has no activity or low activity within 45 minutes, or the hydration status is insufficient, remind the user to get up and drink water to ensure the user's physical health; in addition, when it is detected that the user's drinking water is lower than the drinking water target at 17:00 on the same day, an alarm is issued and a water replenishment plan is provided.

[0065] The present invention also provides a data sharing platform, which includes:

[0066] A data upload module, which is used to upload the user's drinking water data to the cloud server for storage, and build a big data platform for drinking water health.

[0067] A platform docking module: This data sharing platform can be docked with other open health platforms through the user's unique identification code to enrich the data types.

[0068] A data download module, which is used to download the drinking water data obtained from the cloud server, perform data mining, data visualization, data modeling, data prediction, etc., realize accurate long-term health analysis of users, and provide data support for scientific research in the field of drinking water.

[0069] Specifically and exemplarily, in the embodiment of the present invention, in a precise drinking water management system, the smart bracelet can obtain the user's physiological parameters, activity level, or drinking water information, etc. through Bluetooth or wireless network. The smart water cup obtains the drinking water volume information through the built-in weighing device, and obtains the environmental data through the built-in environmental sensor. After the data acquisition module obtains the information, it sends the data to the intelligent processing module.

[0070] The intelligent processing module first receives the data. The data processing module generates a drinking water target value according to the above core algorithm. The following takes two examples to introduce the specific application of a precise drinking water management system provided by the present invention.

[0071] Embodiment 1

[0072] The smart water cup obtains the user's drinking water volume data, and sets a display control panel (as the user input interface) on the water cup. The user inputs information such as age, gender, weight, and physical activity level on the panel, and obtains the environmental data through the built-in environmental sensor. After the data acquisition module obtains the information, it sends the data to the intelligent processing module.

[0073] The data processing unit of the intelligent processing module generates a drinking water target according to the core algorithm. Specifically, a 20-year-old male with a generally active physical activity level (PAL = 1.5), a weight of 70 kg, living in an area with an altitude of 75 m, an average temperature of 10 °C, and a relative humidity of 50% in the location, the drinking water target for that day is obtained as 1.6 L.

[0074] And according to the user's longitude and latitude information, 116°20′30″ east longitude and 39°52′56″ north latitude, it is judged that the location is Xicheng District, Beijing, the drinking water information shows tap water and no water treatment equipment is used, and the drinking water quality data of the user is generated according to the drinking water quality situation in Beijing.

[0075] When the system detects that the user has no activity or low activity within 45 minutes, or the hydration status is insufficient, it reminds the user to get up and drink water to ensure the user's physical health; when it detects that the user's water intake is below the daily water intake target at 17:00 on the same day, it issues an alarm and provides a hydration plan.

[0076] In addition, the present invention also provides a data sharing platform. The data upload module uploads the user's physiological information, activity information, environmental information, water intake and water quality information (such as the data and solutions obtained in Embodiment 1 and Embodiment 2) to the cloud server for storage, to build a big data platform for drinking water health. This platform can be docked with other open health platforms through the user's unique identification code, such as a mobile phone number, to access more data types. Researchers can log in to the platform to obtain the drinking water data, perform data mining, data visualization, data modeling, data prediction, etc., to achieve accurate long-term health analysis of users, and provide data support for scientific research in the field of drinking water.

[0077] Embodiment 2

[0078] A display control panel (serving as the user input interface) is set on the smart bracelet. The user inputs information such as age, gender, and weight on the panel. The body activity level is obtained through the built-in activity sensor, the environmental data is obtained through the environmental sensor, and the user's physiological parameters are obtained through the built-in physiological sensor. After the data acquisition module obtains the information, it sends the data to the intelligent processing module.

[0079] The data processing unit of the intelligent processing module generates a drinking water target according to the core algorithm. Specifically, for a 30-year-old woman with a very active body activity level (PAL = 2.5), a weight of 50 kg, living in an area with an altitude of 125 m, an average temperature of 10°C, and a relative humidity of 30% at the location, the drinking water target for the day is 1.8 L.

[0080] Similarly, according to the user's latitude and longitude information, the location is determined, and the drinking water quality data of the user is generated according to the drinking water quality or brand of the living area. When the system detects that the user has no activity or low activity within 45 minutes, or the hydration status is insufficient, it reminds the user to get up and drink water to ensure the user's physical health; when it detects that the user's water intake is below the daily drinking water target of 1.8 L at 17:00 on the same day, it issues an alarm and provides a hydration plan.

[0081] At the same time, the drinking water data of the user is uploaded to the cloud server for storage through the data upload module, and is docked with other open health platforms through the user's unique identification code, so as to achieve accurate long-term health analysis of the user.

[0082] Furthermore, the data sharing platform is open to relevant researchers, and the obtained data provides data support for scientific research and feeds back to optimize the system.

Claims

1. A precise drinking water management system, characterized in that, The system includes: A data collection module for collecting users' physiological parameters, activity data, and environmental information; and An intelligent processing module for processing data from the data collection module, generating a drinking water goal based on the data, and providing personalized drinking water suggestions.

2. The precise drinking water management system according to claim 1, characterized in that The data collection module further includes: A user input interface for receiving personal information input by the user, such as age, gender, weight, height, and drinking water information, etc.; A physiological sensor for real-time monitoring of users' physiological parameters, such as hydration status, heart rate, blood pressure, etc.; An activity sensor for recording users' activity data, such as physical activity level and sedentary time; An environmental sensor for detecting environmental information of the environment where the user is located, such as temperature, humidity, altitude, longitude and latitude, etc.; and A drinking water data collector for collecting users' drinking water volume information.

3. The precise drinking water management system according to claim 1 or 2, characterized in that, The drinking water information further includes the type and brand of drinking water, whether a water treatment device is used and the brand used.

4. The precise drinking water management system according to any one of claims 1 to 3, characterized in that, The intelligent processing module further includes: A data receiving module for receiving data from the data collection module; A data processing module for calculating and generating a drinking water goal value according to physiological parameters, activity data, and environmental information; and calculating and generating water quality data according to the longitude and latitude information and drinking water information of the user; and An intelligent reminder module for providing drinking water reminders, including reminding the user of the time, frequency, and quantity of drinking water according to the user's hydration status, sedentary time, and drinking water goal value.

5. The precise drinking water management system according to claim 4, characterized in that The drinking water goal value is calculated according to the physical activity level, weight, humidity, altitude, temperature, and whether the user is an athlete.

6. The precise drinking water management system according to claim 5, characterized in that, The drinking water goal value is further calculated according to the following formula: RWI (ml / d) = {[1076 × PAL] + [14.34 × W (kg)] + [374.9 × S] + [5.823 × H (%)] + [1070 × AS] + [0.4726 × A (m)] – [0.3529 × Y (years) 2 + [24.78 × Y (years)] + [1.865 × T (°C) 2 – [19.66 × T (°C)] – 713.1} × 55% where, RWI is the drinking water goal value, unit ml / d; PAL is the physical activity level; W is the weight, unit kg; S is the gender, 1 for male and 0 for female; H is the local air humidity, unit %; AS is the athlete status, 1 for athlete and 0 for non-athlete; A is the altitude, unit: m; Y is the age, unit: year; T is the local temperature, unit: °C.

7. The precise drinking water management system according to claims 1 to 6, characterized in that, The method for generating the water quality data is as follows: The water quality conditions of domestic drinking water in each county-level city (district), the water quality data of each brand of packaged drinking water, and the filtration functions of each brand and model of water treatment device are pre-stored in the system; According to the longitude and latitude information of the user, judge the county-level city (district) where the user is located; According to the drinking water information input by the user, judge the type of drinking water; If the type of drinking water is packaged drinking water, generate the water quality data of the corresponding brand; If the type of drinking water is tap water, further judge whether a water treatment device is used; If the type of drinking water is tap water and no water treatment device is used, generate the water quality data of the domestic drinking water in the county-level city (district) where the user is located; If the type of drinking water is tap water and a water treatment device is used, generate water quality data according to the water quality conditions of domestic drinking water in the county-level city (district) where the user is located and the filtration function of the water treatment device.

8. The precise drinking water management system according to any one of claims 4-7, characterized in that, The drinking water reminder scheme is as follows: When it is detected that the user has no activity or low activity within 45 minutes, or the hydration status is insufficient, remind the user to get up and drink water to ensure the user's physical health; When it is detected that the user is below the drinking water goal value at 17:00 on the same day, issue an alarm and provide a water replenishment plan.

9. The precise drinking water management system according to any one of claims 1 to 8, characterized in that, It also includes a smart device interface for connecting to devices such as smart water cups or smart bracelets.

10. A data sharing platform, characterized in that, The data sharing platform includes: A data upload module for uploading the user's drinking water data to a cloud server for storage to build a big data platform for drinking water health; A platform docking module that docks with other open health platforms through the user's unique identification code to enrich the data types; and A data download module for downloading the drinking water data obtained from the cloud server for data mining, data visualization, data modeling, data prediction, etc., to achieve precise long-term health analysis of users and provide data support for scientific research in the field of drinking water.

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