A water changing reminding method and device for a pet water feeding apparatus, an apparatus, and a medium

Abstract

The application discloses a pet water feeding equipment water changing reminding method and device, equipment and medium, and relates to the technical field of pet feeding equipment, which comprises the following steps: a server acquires an initial environmental temperature and an initial ammonia nitrogen concentration in water uploaded by a pet water feeding equipment; a target water changing time prediction model trained in advance is used to determine a water changing time based on an oxygen concentration in a user area, the initial ammonia nitrogen concentration and the initial environmental temperature; a timing reminding task is set according to the water changing time, and water changing reminding information is sent to the user based on the timing reminding task.

Description

Technical Field

[0001] This invention relates to the field of pet feeding equipment technology, and in particular to a method, device, equipment, and medium for reminding pets to change water. Background Technology

[0002] Pet feeders are now commonplace on the market. They provide pets with food and water at set times and offer alerts when food or water is low, ensuring better care for your pet. However, pet feeders lack intelligent water change reminders. This is because the nitrite content in water increases over time, and excessive nitrite can be harmful to pets. Summary of the Invention

[0003] In view of this, the present invention provides a method, device, equipment, and medium for reminding pets to change water, which can send water change reminders to users so that users can change the water in a timely manner according to the reminders, thereby further ensuring the safety of pets' drinking water. The specific solution is as follows:

[0004] In the first aspect, this application discloses a method for reminding users to change water in a pet watering device, applied to a server, including:

[0005] Obtain the initial ambient temperature and initial ammonia nitrogen concentration in the water uploaded by the pet water feeding device;

[0006] The water exchange time is determined by a pre-trained target water exchange time prediction model based on the oxygen concentration in the user area, the initial ammonia nitrogen concentration, and the initial ambient temperature.

[0007] Set a timed reminder task based on the water change time, and send water change reminder information to the user based on the timed reminder task.

[0008] Optionally, before obtaining the initial ambient temperature and initial ammonia nitrogen concentration in the water uploaded by the pet water feeding device, the method further includes:

[0009] The drinking water nitrite standard is determined based on the user's selection. The maximum threshold of nitrite in the water is determined based on the drinking water nitrite standard. The water exchange time is then determined by a pre-trained target water exchange time prediction model based on the maximum threshold, the oxygen concentration in the user's area, the initial ammonia nitrogen concentration, and the initial ambient temperature.

[0010] Optionally, before determining the water exchange time based on the oxygen concentration in the user area, the initial ammonia nitrogen concentration, and the initial ambient temperature using a pre-trained target water exchange time prediction model, the method further includes:

[0011] The initial water exchange time prediction model is determined based on the random forest regression model, and a training dataset is determined. The initial water exchange time prediction model is trained using the training dataset, and the target water exchange time prediction model is determined based on the corresponding training results and mean square error.

[0012] Optionally, determining the training dataset includes:

[0013] The training dataset is determined based on each usage time and the corresponding ammonia nitrogen concentration, oxygen concentration, and ambient temperature. Each usage time is the time when the ammonia nitrogen concentration meets the first preset threshold condition under different ammonia nitrogen concentrations, different oxygen concentrations, and different ambient temperatures collected by the pet water feeding device.

[0014] Optionally, the process of collecting each usage time includes:

[0015] A usage time collection command is sent to the pet water feeding device so that, upon receiving the usage time collection command, the pet water feeding device periodically collects various monitoring data. When the current ammonia nitrogen concentration in the monitoring data meets the first preset threshold condition, the current usage time is determined based on the difference between the current time and the initial time. The monitoring data includes ammonia nitrogen concentration, oxygen concentration, and ambient temperature. Furthermore, if any of the collected monitoring data does not meet the corresponding second preset threshold condition, the pet water feeding device adjusts the corresponding ammonia nitrogen concentration, oxygen concentration, or ambient temperature according to a preset change gradient value, and then triggers the next data collection.

[0016] Obtain the usage time returned by the pet water feeding device.

[0017] Optionally, the first preset threshold condition is that the difference between the current ammonia nitrogen concentration and the previous ammonia nitrogen concentration is less than or equal to the target value.

[0018] Optionally, the method further includes: obtaining the current ammonia nitrogen concentration and current ambient temperature monitored by the sensor and re-uploaded by the pet water feeding device according to a preset sampling interval, and determining a new water change time based on the oxygen concentration, current ammonia nitrogen concentration and current ambient temperature of the user area through a pre-trained target water change time prediction model;

[0019] A new timed reminder task is set according to the new water change time, and a water change reminder message is sent to the user based on the new timed reminder task.

[0020] Secondly, this application discloses a pet water feeding device with a water change reminder, applied to a server, comprising:

[0021] The data acquisition module is used to acquire the initial ambient temperature and the initial ammonia nitrogen concentration in the water uploaded by the pet water feeding device;

[0022] The water exchange time determination module is used to determine the water exchange time based on the oxygen concentration in the user area, the initial ammonia nitrogen concentration, and the initial ambient temperature using a pre-trained target water exchange time prediction model.

[0023] The water change reminder sending module is used to set a timed reminder task based on the water change time, and send water change reminder information to the user based on the timed reminder task.

[0024] Thirdly, this application discloses an electronic device, including:

[0025] Memory, used to store computer programs;

[0026] A processor is used to execute the computer program to implement the pet water feeding device water change reminder method as described above.

[0027] Fourthly, this application discloses a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the aforementioned method for reminding users to change water in a pet watering device.

[0028] In this application, the server first obtains the initial ambient temperature and initial ammonia nitrogen concentration in the water uploaded by the pet water feeding device. Then, it determines the water change time based on the oxygen concentration in the user's area, the initial ammonia nitrogen concentration, and the initial ambient temperature using a pre-trained target water change time prediction model. Finally, it sets a timed reminder task based on the water change time and sends a water change reminder message to the user based on the timed reminder task. Therefore, this application determines the water change time using a target water change time prediction model based on ammonia nitrogen concentration and ambient temperature, and sends a water change reminder to the user based on the timed water change, so that the user can change the water in a timely manner. In this way, it can accurately predict changes in the water quality of the pet water feeding device and remind the user to change the water in a timely manner, preventing the pet from drinking poor-quality water and further ensuring the pet's drinking water safety. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0030] Figure 1 This application discloses a flowchart of a method for reminding users to change the water in a pet water feeding device;

[0031] Figure 2 This application discloses a timing diagram of a specific pet water feeding device water change reminder method;

[0032] Figure 3 This application discloses a flowchart of a model training method;

[0033] Figure 4 This application discloses a timing diagram of a specific pet water feeding device water change reminder method;

[0034] Figure 5 This application discloses a flowchart of a data acquisition method;

[0035] Figure 6 This application discloses a schematic diagram of a pet water feeding device with a water change reminder.

[0036] Figure 7 This application discloses a structural diagram of an electronic device. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Currently, pet feeders lack intelligent water change reminders. This is because the nitrite content in water increases over time, and excessive nitrite can harm pets. Furthermore, users are often unaware of the need to change the water or change it randomly, lacking any clear reference standard. To address these technical problems, this application discloses a method, device, equipment, and medium for reminding users to change water in a pet water feeding device. This method sends water change reminders to users, enabling them to change the water promptly and further ensuring pet drinking water safety.

[0039] See Figure 1 As shown in the figure, an embodiment of the present invention discloses a method for reminding users to change water in a pet water feeding device, applied to a server, including:

[0040] Step S11: Obtain the initial ambient temperature and initial ammonia nitrogen concentration in the water uploaded by the pet water feeding device.

[0041] In this embodiment, as Figure 2As shown, before the server obtains the initial ambient temperature and initial ammonia nitrogen concentration in the water uploaded by the pet water dispenser, the user adds the device. After adding the pet water dispenser, the user selects the drinking water nitrite standard, currently including the World Health Organization standard, the European Union standard, and the Safe Drinking Water Act. Based on the user's selected drinking water nitrite standard, the server simultaneously obtains the user's regional information during water change detection to determine the oxygen concentration in that area (which can be queried using latitude and longitude). The server then determines the maximum nitrite threshold in the water based on the drinking water nitrite standard, and subsequently uses a pre-trained target water change time prediction model to determine the water change time based on the maximum threshold, the oxygen concentration in the user's region, the current ammonia nitrogen concentration, and the current ambient temperature. This reduces the use of sensors and lowers hardware costs.

[0042] Afterwards, the user removes the water tank from the pet water dispenser, and simultaneously, the water change countdown timer is reset to zero. Once the user has finished adding water, the water tank is placed back into the pet water dispenser. In one specific embodiment, one minute after the water tank is returned, the sensor begins monitoring the ammonia nitrogen concentration and ambient temperature, simultaneously sending the current ammonia nitrogen concentration and ambient temperature to the pet water dispenser. The pet water dispenser then uploads these data to the server.

[0043] Step S12: Determine the water exchange time based on the oxygen concentration in the user area, the initial ammonia nitrogen concentration, and the initial ambient temperature using a pre-trained target water exchange time prediction model.

[0044] In this embodiment, after the server obtains the initial ambient temperature and the initial ammonia nitrogen concentration in the water uploaded by the pet water feeding device, the server can determine the water change time based on the information uploaded by the pet water feeding device. It should be noted that oxygen participates in the ammonia nitrogen reaction, temperature can affect the nitrate formation rate (the higher the temperature, the faster the formation), and the initial ammonia nitrogen in the water is a precursor to nitrate formation. Therefore, these three data points are all necessary factors affecting the water change time.

[0045] In this embodiment, before determining the water change time based on the oxygen concentration, current ammonia nitrogen concentration, and current ambient temperature in the user area, the server first trains the target water change time prediction model using a pre-trained model. In this process, predicting the water change time of the pet water feeding device is a regression task, and this application uses a random forest regression model for modeling and prediction. Furthermore, a training dataset needs to be determined. During data collection, the training dataset is determined based on each usage time and the corresponding ammonia nitrogen concentration, oxygen concentration, and ambient temperature. Each usage time is the time corresponding to when the ammonia nitrogen concentration meets a first preset threshold condition under different ammonia nitrogen concentrations, different oxygen concentrations, and different ambient temperatures collected by the pet water feeding device. Regarding the collection of usage time data, in this application, the server first sends a usage time collection command to the pet water feeding device. Upon receiving the command, the device periodically collects various monitoring data. When the current ammonia nitrogen concentration in the monitoring data meets a first preset threshold condition, the current usage time is determined based on the difference between the current time and the initial time. The monitoring data includes ammonia nitrogen concentration, oxygen concentration, and ambient temperature. Furthermore, if any collected monitoring data does not meet the corresponding second preset threshold condition, the pet water feeding device adjusts the corresponding ammonia nitrogen concentration, oxygen concentration, or ambient temperature according to a preset change gradient value, and then triggers the next data collection. Finally, the usage time returned by the pet water feeding device is obtained. The first preset threshold condition is that the change in the difference between the current ammonia nitrogen concentration and the previous ammonia nitrogen concentration is less than or equal to a target value.

[0046] In other words, the pet water feeding device in this application sets initial ammonia nitrogen concentration, initial oxygen concentration, initial ambient temperature, and their corresponding gradient values, and collects sensor monitoring data based on target time intervals. It then uses the ammonia nitrogen concentration data to determine whether the current ammonia nitrogen concentration in the water meets a preset threshold condition. If the preset threshold condition is met, the current time is recorded, and the usage time is determined based on the difference between the current time and the initial time. The device then sequentially checks whether the initial ammonia nitrogen concentration, initial oxygen concentration, and initial ambient temperature meet their respective target threshold conditions. If the target threshold condition is met, the data acquisition process ends. If the target threshold condition is not met, the initial ammonia nitrogen concentration, initial oxygen concentration, and initial ambient temperature are modified based on their respective gradient values, and data acquisition is performed based on the modified data until the modified data meets the target threshold condition. If the preset threshold condition is not met, the process returns to the step of collecting sensor monitoring data based on the target time interval. When determining whether the ammonia nitrogen concentration in the water meets the preset threshold condition by using the ammonia nitrogen concentration data in the monitoring data, if the difference between the ammonia nitrogen concentration in the current monitoring data and the ammonia nitrogen concentration in the monitoring data corresponding to the previous time interval is less than or equal to the target value, then the ammonia nitrogen concentration in the water is determined to meet the preset threshold condition; if the difference between the ammonia nitrogen concentration in the current monitoring data and the ammonia nitrogen concentration in the monitoring data corresponding to the previous time interval is greater than the target value, then the ammonia nitrogen concentration in the water is determined not to meet the preset threshold condition.

[0047] In this embodiment, during the model training process, the random forest uses information entropy as the evaluation criterion for features when performing subtree partitioning. Information entropy is the mathematical expectation of the amount of information, and its calculation formula is:

[0048] ;

[0049] in, Information entropy; Represents random events The probability of occurrence.

[0050] The model is evaluated using MSE (Mean Squared Error). MSE measures the deviation between the true and predicted values, accurately reflecting the magnitude of the actual prediction error. The calculation formula is as follows:

[0051] ;

[0052] in, Indicates the predicted value; Represents the actual value.

[0053] As we know, the training data is collected offline, so it does not involve data transmission between the firmware and the cloud. The entire training process takes place on the cloud server. The specific training process is as follows: Figure 3 As shown, the collected sample dataset is first loaded; then, 80% of the samples in the dataset are randomly selected as the training set and 20% as the validation set; next, a random forest model is defined using the machine learning library sklearn; then, the parameter set for grid search is defined, including n_estimators (number of decision trees), max_depth (maximum tree depth), min_samples_split (minimum number of samples per split node), and min_samples_leaf (minimum number of samples per leaf node). The model parameters are evaluated using grid search, with MAE (Mean Absolute Error) as the evaluation metric. The model parameters corresponding to the minimum MAE during the grid search process are taken as the optimal parameters; finally, the random forest model is trained with the optimal parameters, and the model file is saved after training. Finally, the server calculates the water exchange time based on the oxygen concentration, current ammonia nitrogen concentration, and current ambient temperature in the user area using a pre-trained target water exchange time prediction model.

[0054] Step S13: Set a timed reminder task according to the water change time, and send water change reminder information to the user based on the timed reminder task.

[0055] In this embodiment, after calculating the water change time, the server sets a timed reminder task based on the water change time. Simultaneously, the server first returns the water change time to the user, providing the user with a preliminary understanding of the approximate water change time. Finally, the server sends a water change reminder to the user according to the timed reminder task.

[0056] Additionally, since pets' use of water can cause pollution or other changes that alter their parameters, therefore, such as Figure 4 As shown, in this application, the server obtains the current ammonia nitrogen concentration and current ambient temperature monitored by the sensor, which are re-uploaded by the pet water feeding device according to a pre-set sampling interval. Then, it determines a new water change time based on the oxygen concentration, current ammonia nitrogen concentration, and current ambient temperature of the user's area using a pre-trained target water change time prediction model. The server then resets a new timed reminder task based on the new water change time, returns the new water change time to the user, and sends a water change reminder message to the user based on the new timed reminder task. In one specific embodiment, a sampling rate of 24 hours is used to periodically re-monitor; then, based on the server's prediction results, the timed task is reset and the user is notified of the latest time via push notification.

[0057] In summary, this application's server first obtains the initial ambient temperature and initial ammonia nitrogen concentration in the water uploaded by the pet water supply device; then, it determines the water change time based on the oxygen concentration in the user's area, the initial ammonia nitrogen concentration, and the initial ambient temperature using a pre-trained target water change time prediction model; finally, it sets a timed reminder task based on the water change time and sends a water change reminder message to the user based on the timed reminder task. Therefore, this application determines the water change time using a target water change time prediction model based on ammonia nitrogen concentration and ambient temperature, and sends a water change reminder to the user based on the water change time, so that the user can change the water in a timely manner. In this way, it can accurately predict changes in the water quality of the pet water supply device and remind users to change the water in a timely manner, preventing pets from drinking poor-quality water and further ensuring pet drinking water safety.

[0058] Before training the model, this application will first collect data, including the required usage time in the training dataset and the corresponding ammonia nitrogen concentration, oxygen concentration, and ambient temperature for each usage time. The specific data collection process will be described below.

[0059] In this application, the model predicts water change time by setting an upper limit for nitrate, while the initial time only considers ammonia nitrogen concentration. Pet water feeding devices generally use a live water dispensing method, where oxygen in the air has sufficient contact with the water and participates in the reaction of substances; oxygen is an important factor to consider. Therefore, calculating the initial ammonia nitrogen concentration and the change in ammonia nitrogen can estimate the approximate water change time.

[0060] In one specific embodiment, water with an ammonia nitrogen concentration ranging from 0.2 mg / L to 0.8 mg / L was added to the pet water feeding device, varying by 0.05 mg / L each time. The feeding device was placed in a room with adjustable oxygen concentration and temperature. During data collection, the ambient temperature was adjusted from 5°C to 60°C in 5°C intervals, and the oxygen concentration was adjusted from 19.5% to 23.5% in 0.5% intervals. See [link to relevant documentation]. Figure 5As shown, the following settings were first established: oxygen concentration o=19%, ammonia nitrogen concentration c=0.2mg / L, ambient temperature t=0, and gradients for temperature and oxygen concentration changes. A fixed ammonia nitrogen concentration c was added to the water in the pet water feeding device, and the start time was recorded as T0. Then, data on ammonia nitrogen concentration, ambient temperature, and oxygen concentration were collected from the sensors every 3 hours. The system then checked whether the ammonia nitrogen concentration in the water had been depleted. If not, the sensor data was collected again after another 3 hours, and the system checked again to determine if the ammonia nitrogen concentration had been depleted. This cycle continued until the ammonia nitrogen concentration was determined to be depleted, and the time T1 when depletion was confirmed was recorded. This determined the usage time T1-T0, and the usage time along with the corresponding ammonia nitrogen concentration, ambient temperature, and oxygen concentration were stored as sample data. It should be noted that the criterion for determining whether the ammonia nitrogen concentration in the pet water feeding device had been depleted was: the change in ammonia nitrogen concentration between two consecutive sampling times did not exceed 5%.

[0061] After storage, the system checks if the current oxygen concentration exceeds 23.5%. If not, it increases the current oxygen concentration by 0.5% and returns to the step of adding a fixed ammonia nitrogen concentration (c) to the water in the feeding device until the current oxygen concentration exceeds 23.5%. Next, it checks if the current ambient temperature exceeds 60 degrees Celsius. If not, it increases the current ambient temperature by 5 degrees Celsius and returns to the step of adding a fixed ammonia nitrogen concentration (c) to the water in the feeding device until the current ambient temperature exceeds 60 degrees Celsius. Finally, it checks if the current ammonia nitrogen concentration in the water exceeds 0.8 mg / L. If not, it increases the current ammonia nitrogen concentration by 0.05 mg / L and returns to the step of adding a fixed ammonia nitrogen concentration (c) to the water in the feeding device until the current ammonia nitrogen concentration in the water exceeds 0.8 mg / L. The usage time, ammonia nitrogen concentration, ambient temperature, and oxygen concentration corresponding to each usage time when the ammonia nitrogen concentration in the water is depleted are all stored as sample data. This completes the entire data collection process.

[0062] In this way, the data collected by this application can dynamically calculate the water change time based on the initial ammonia nitrogen concentration in the water and the safe concentration standard of nitrate in drinking water. Thus, when changes in the water quality of the pet water feeding equipment are predicted, the user can be reminded to change the water in a timely manner to prevent the pet from drinking poor water and further ensure the safety of the pet's drinking water.

[0063] See Figure 6 As shown, this embodiment of the invention discloses a pet water feeding device with a water change reminder, applied to a server, comprising:

[0064] Data acquisition module 11 is used to acquire the initial ambient temperature and initial ammonia nitrogen concentration in the water uploaded by the pet water feeding device;

[0065] The water exchange time determination module 12 is used to determine the water exchange time based on the oxygen concentration of the user area, the initial ammonia nitrogen concentration, and the initial ambient temperature using a pre-trained target water exchange time prediction model.

[0066] The water change reminder sending module 13 is used to set a timed reminder task according to the water change time, and send water change reminder information to the user based on the timed reminder task.

[0067] In summary, this application's server first obtains the initial ambient temperature and initial ammonia nitrogen concentration in the water uploaded by the pet water supply device; then, it determines the water change time based on the oxygen concentration in the user's area, the initial ammonia nitrogen concentration, and the initial ambient temperature using a pre-trained target water change time prediction model; finally, it sets a timed reminder task based on the water change time and sends a water change reminder message to the user based on the timed reminder task. Therefore, this application determines the water change time using a target water change time prediction model based on ammonia nitrogen concentration and ambient temperature, and sends a water change reminder to the user based on the water change time, so that the user can change the water in a timely manner. In this way, it can accurately predict changes in the water quality of the pet water supply device and remind users to change the water in a timely manner, preventing pets from drinking poor-quality water and further ensuring pet drinking water safety.

[0068] In some specific embodiments, the apparatus may further include:

[0069] The water exchange time determination module is used to determine the drinking water nitrite implementation standard based on the user's selection, and to determine the maximum threshold of nitrite in the water based on the drinking water nitrite implementation standard, so as to determine the water exchange time according to the maximum threshold, the oxygen concentration of the user area, the initial ammonia nitrogen concentration, and the initial ambient temperature through a pre-trained target water exchange time prediction model.

[0070] In some specific embodiments, the apparatus may further include:

[0071] The model training module is used to determine the initial water exchange time prediction model based on the random forest regression model, determine the training dataset, train the initial water exchange time prediction model using the training dataset, and determine the target water exchange time prediction model based on the corresponding training results and mean square error.

[0072] In some specific embodiments, the model training module may specifically include:

[0073] The training dataset determination submodule is used to determine the training dataset based on each usage time and the ammonia nitrogen concentration, oxygen concentration and ambient temperature corresponding to each usage time; each usage time is the time when the ammonia nitrogen concentration meets the first preset threshold condition under different ammonia nitrogen concentrations, different oxygen concentrations and different ambient temperatures collected by the pet water feeding device.

[0074] In some specific embodiments, the training dataset determines the sub-module, which may specifically include:

[0075] The instruction sending unit is used to send a usage time collection instruction to the pet water feeding device, so that after receiving the usage time collection instruction, the pet water feeding device periodically collects various monitoring data. When the current ammonia nitrogen concentration in the monitoring data meets the first preset threshold condition, the current usage time is determined based on the difference between the current time and the initial time. The monitoring data includes ammonia nitrogen concentration, oxygen concentration, and ambient temperature. Furthermore, when any of the collected monitoring data does not meet the corresponding second preset threshold condition, the pet water feeding device adjusts the corresponding ammonia nitrogen concentration, oxygen concentration, or ambient temperature according to a preset change gradient value, and then triggers the next data collection.

[0076] The usage time return unit is used to obtain the usage time returned by the pet water feeding device.

[0077] In some specific embodiments, the apparatus may further include:

[0078] The new water change time determination unit is used to obtain the current ammonia nitrogen concentration and current ambient temperature monitored by the sensor and re-uploaded by the pet water feeding device according to the preset sampling interval time, and to determine the new water change time based on the oxygen concentration, current ammonia nitrogen concentration and current ambient temperature of the user area through a pre-trained target water change time prediction model.

[0079] The water change reminder sending unit is used to reset a new timed reminder task according to the new water change time, and send water change reminder information to the user based on the new timed reminder task.

[0080] Furthermore, embodiments of this application also disclose an electronic device, Figure 7 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.

[0081] Figure 7This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the pet water feeding device water change reminder method disclosed in any of the foregoing embodiments. Alternatively, the electronic device 20 in this embodiment may specifically be a computer.

[0082] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0083] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk, or optical disk, etc. The resources stored thereon can include an operating system 221, computer programs 222, etc., and the storage method can be temporary storage or permanent storage.

[0084] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the pet water feeding device water change reminder method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include computer programs capable of performing other specific tasks.

[0085] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned method for reminding users to change water in a pet watering device. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0086] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0087] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0088] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0089] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0090] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for reminding users to change water in a pet water feeding device, characterized in that, Applied to servers, including: Obtain the initial ambient temperature and initial ammonia nitrogen concentration in the water uploaded by the pet water feeding device; The water exchange time is determined by a pre-trained target water exchange time prediction model based on the oxygen concentration in the user area, the initial ammonia nitrogen concentration, and the initial ambient temperature. Set a timed reminder task based on the water change time, and send water change reminder information to the user based on the timed reminder task.

2. The pet water feeding device water change reminder method according to claim 1, characterized in that, Before obtaining the initial ambient temperature and initial ammonia nitrogen concentration in the water uploaded by the pet watering device, the process also includes: The drinking water nitrite standard is determined based on the user's selection. The maximum threshold of nitrite in the water is determined based on the drinking water nitrite standard. The water exchange time is then determined by a pre-trained target water exchange time prediction model based on the maximum threshold, the oxygen concentration in the user's area, the initial ammonia nitrogen concentration, and the initial ambient temperature.

3. The pet water feeding device water change reminder method according to claim 1, characterized in that, Before determining the water exchange time using a pre-trained target water exchange time prediction model based on the oxygen concentration in the user area, the initial ammonia nitrogen concentration, and the initial ambient temperature, the method further includes: The initial water exchange time prediction model is determined based on the random forest regression model, and a training dataset is determined. The initial water exchange time prediction model is trained using the training dataset, and the target water exchange time prediction model is determined based on the corresponding training results and mean square error.

4. The pet water feeding device water change reminder method according to claim 3, characterized in that, The determination of the training dataset includes: The training dataset is determined based on each usage time and the corresponding ammonia nitrogen concentration, oxygen concentration, and ambient temperature. Each usage time is the time when the ammonia nitrogen concentration meets the first preset threshold condition under different ammonia nitrogen concentrations, different oxygen concentrations, and different ambient temperatures collected by the pet water feeding device.

5. The pet water feeding device water change reminder method according to claim 4, characterized in that, The process of collecting data for each usage time includes: A usage time collection command is sent to the pet water feeding device so that, upon receiving the usage time collection command, the pet water feeding device periodically collects various monitoring data. When the current ammonia nitrogen concentration in the monitoring data meets the first preset threshold condition, the current usage time is determined based on the difference between the current time and the initial time. The monitoring data includes ammonia nitrogen concentration, oxygen concentration, and ambient temperature. Furthermore, if any of the collected monitoring data does not meet the corresponding second preset threshold condition, the pet water feeding device adjusts the corresponding ammonia nitrogen concentration, oxygen concentration, or ambient temperature according to a preset change gradient value, and then triggers the next data collection. Obtain the usage time returned by the pet water feeding device.

6. The pet water feeding device water change reminder method according to claim 5, characterized in that, The first preset threshold condition is that the difference between the current ammonia nitrogen concentration and the previous ammonia nitrogen concentration is less than or equal to the target value.

7. The pet water feeding device water change reminder method according to any one of claims 1 to 6, characterized in that, Also includes: The system obtains the current ammonia nitrogen concentration and current ambient temperature monitored by the sensor and re-uploaded by the pet water feeding device according to the preset sampling interval. Based on the oxygen concentration, current ammonia nitrogen concentration and current ambient temperature in the user area, the system determines the new water change time using a pre-trained target water change time prediction model. A new timed reminder task is set according to the new water change time, and a water change reminder message is sent to the user based on the new timed reminder task.

8. A pet water feeding device with a water change reminder, characterized in that, Applied to servers, including: The data acquisition module is used to acquire the initial ambient temperature and the initial ammonia nitrogen concentration in the water uploaded by the pet water feeding device; The water exchange time determination module is used to determine the water exchange time based on the oxygen concentration in the user area, the initial ammonia nitrogen concentration, and the initial ambient temperature using a pre-trained target water exchange time prediction model. The water change reminder sending module is used to set a timed reminder task based on the water change time, and send water change reminder information to the user based on the timed reminder task.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor is configured to execute the computer program to implement the pet water feeding device water change reminder method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store a computer program, wherein the computer program, when executed by a processor, implements the pet water feeding device water change reminder method as described in any one of claims 1 to 7.

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