An abnormal monitoring method, device, monitoring equipment and storage medium

Abstract

This application is applicable to the field of monitoring technologies, and provides an abnormal monitoring method, device, monitoring device, and storage medium. Among them, the above abnormal monitoring method is applied to a monitoring device, and the monitoring device is used to monitor a target object. The abnormal monitoring method includes: obtaining monitoring data of the monitoring device, where the monitoring data includes at least one of the working data of each working module of the monitoring device and the object data of the target object; if the monitoring data meets the abnormal determination condition, it is determined that the monitoring device or the target object is in an abnormal state. The embodiments of this application can perform abnormal monitoring on both the monitoring device and the target object, can not only complete the monitoring work of the target object, but also avoid the situation of erroneously judging that the monitored object is abnormal or performing ineffective monitoring on the monitored object due to the abnormality of the monitoring device itself, and improve the reliability of abnormal monitoring.

Description

Technical Field

[0001] This application belongs to the field of monitoring technology, and particularly relates to an abnormal monitoring method, device, monitoring device, and storage medium. Background Art

[0002] Monitoring devices are often used to monitor objects such as the elderly, children, and pets, and send notifications in a timely manner when it is found that the monitored object is in an abnormal state. Traditional monitoring devices have a single function. Their abnormal monitoring methods can basically only monitor data such as the body temperature, heart rate, and weight of the object, and use these data to determine whether the object is in an abnormal state. It is found in practical applications that this abnormal monitoring method lacks reliability, and there are often situations where it wrongly judges that the monitored object is abnormal or ineffective monitoring of the monitored object, thus causing a problem of waste of resources. Summary of the Invention

[0003] Embodiments of this application provide an abnormal monitoring method, device, monitoring device, and storage medium, which can perform abnormal monitoring on both the monitoring device and the target object, can not only complete the monitoring work of the target object, but also avoid the situation of wrongly judging that the monitored object is abnormal or ineffective monitoring of the monitored object due to the abnormality of the monitoring device itself, and solve the problem of insufficient reliability of the abnormal monitoring method in the prior art.

[0004] In a first aspect of the embodiments of this application, an abnormal monitoring method is provided, which is applied to a monitoring device for monitoring a target object. The abnormal monitoring method includes:

[0005] Obtain the monitoring data of the monitoring device, where the monitoring data includes at least one of the working data of each working module of the monitoring device and the object data of the target object;

[0006] If the monitoring data meets the abnormal determination condition, it is determined that the monitoring device or the target object is in an abnormal state.

[0007] In some embodiments of this application, the monitoring data includes the object data of the target object. If the monitoring data meets the abnormal determination condition, it is determined that the monitoring device or the target object is in an abnormal state, including: obtaining the target growth stage of the target object; obtaining the reference data range corresponding to the target growth stage; if the object data is outside the reference data range corresponding to the target growth stage, it is determined that the monitoring data meets the abnormal determination condition, and it is determined that the target object is in the abnormal state.

[0008] In some embodiments of the present application, the object data includes the weight value of the target object, the weight difference of the target object within a preset time period, and the age value of the target object; obtaining the target growth stage of the target object includes: determining the basic growth stage value of the target object according to the weight value; using the weight difference and the age value to correct the basic growth stage value, calculating the target growth stage value of the target object, and obtaining the target growth stage of the target object.

[0009] In some embodiments of the present application, using the weight difference and the age value to correct the basic growth stage value and calculate the target growth stage value of the target object includes: using a correction formula to correct the basic growth stage value and calculate the target growth stage value of the target object, where P′ is the target growth stage value, P is the basic growth stage value, W is the stage weight corresponding to the age value, and D n is the weight difference of the target object within a preset time period, and D p is the expected weight difference value corresponding to the preset time period.

[0010] In some embodiments of the present application, the monitoring data includes the working data of each working module of the monitoring device, and the working data includes the rotation value of the motor of each working module and the current value of each working module. If the monitoring data meets the abnormal determination condition, determining that the monitoring device or the target object is in an abnormal state includes: if the rotation value does not reach the preset reference rotation value, or the current value is outside the preset normal current range, determining that the monitoring data meets the abnormal determination condition and determining that the monitoring device is in the abnormal state.

[0011] In some embodiments of the present application, the working data includes the device image when the monitoring device is working, and the object data includes the object image of the target object. If the monitoring data meets the abnormal determination condition, determining that the monitoring device or the target object is in an abnormal state includes: performing abnormal recognition on the device image, and when any one of the working modules is identified as abnormal, determining that the monitoring data meets the abnormal determination condition and determining that the monitoring device is in the abnormal state; and / or performing abnormal recognition on the object image, and when the behavior of the target object is identified as abnormal, determining that the monitoring data meets the abnormal determination condition and determining that the target object is in the abnormal state.

[0012] In some embodiments of the present application, after determining that the monitoring device or the target object is in an abnormal state, it includes: sending a prompt message corresponding to the abnormal state to the user terminal to prompt the user to perform abnormal processing; and / or, if it is determined that the target object is in the abnormal state, determining a guardianship strategy for the target object according to the abnormal state in which the target object is located, and sending the guardianship strategy to the user terminal.

[0013] An abnormal monitoring device provided in the second aspect of the embodiments of the present application is configured in a monitoring device, and the monitoring device is used to monitor a target object. The abnormal monitoring device includes:

[0014] A data acquisition unit, configured to acquire monitoring data of the monitoring device, where the monitoring data includes at least one of working data of each working module of the monitoring device and object data of the target object.

[0015] An abnormal monitoring unit, configured to determine that the monitoring device or the target object is in an abnormal state if the monitoring data meets an abnormal determination condition.

[0016] A monitoring device provided in the third aspect of the embodiments of the present application includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above abnormal monitoring method are implemented.

[0017] A computer-readable storage medium provided in the fourth aspect of the embodiments of the present application stores a computer program. When the computer program is executed by a processor, the steps of the above abnormal monitoring method are implemented.

[0018] A computer program product provided in the fifth aspect of the embodiments of the present application, when the computer program product runs on a monitoring device, enables the monitoring device to execute the abnormal monitoring method described in any one of the above first aspects.

[0019] In the embodiments of the present application, by acquiring the monitoring data of the monitoring device, if the monitoring data meets the abnormal determination condition, it is determined that the monitoring device or the target object is in an abnormal state. Since the monitoring data includes at least one of the working data of each working module of the monitoring device and the object data of the target object monitored by the monitoring device, the monitoring device can perform abnormal monitoring on both the monitoring device and the target object, can not only complete the monitoring work of the target object, but also avoid the situation of misjudging that the monitored object is abnormal or performing ineffective monitoring on the monitored object due to the abnormality of the monitoring device itself, improves the reliability of abnormal monitoring, and reduces the waste of resources. Description of the Drawings

[0020] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the accompanying drawings required for use in the embodiments or the description of the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0021] Figure 1 is a schematic flowchart of the implementation of an abnormal monitoring method provided by an embodiment of the present application;

[0022] Figure 2 is a schematic structural diagram of a monitoring system provided by an embodiment of the present application;

[0023] Figure 3 is a schematic flowchart of the specific implementation of abnormal monitoring of a target object provided by an embodiment of the present application;

[0024] Figure 4 is a schematic structural diagram of an abnormal monitoring device provided by an embodiment of the present application;

[0025] Figure 5 is a schematic structural diagram of a monitoring device provided by an embodiment of the present application. Detailed implementation manners

[0026] In order to make the purpose, technical solutions and advantages of the present application more clear and understandable, the following further details the present application in combination with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present application.

[0027] Monitoring devices are often used to monitor objects such as the elderly, children, and pets, and send notifications in a timely manner when it is found that the monitored object is in an abnormal state. Traditional monitoring devices have a single function. Their abnormal monitoring methods can basically only monitor data such as the body temperature, heart rate, and weight of the object, and use these data to determine whether the object is in an abnormal state. In practical applications, it is found that this abnormal monitoring method has insufficient reliability, and there are often situations where it wrongly judges that the monitored object is abnormal or ineffective monitoring of the monitored object, thus causing a problem of waste of resources.

[0028] For example, when a monitoring device monitors a pet, due to an abnormality in the feeding module of the pet device, it cannot effectively monitor the pet; for another example, when a monitoring device monitors a child, the image acquisition module wrongly judges that the child is in an abnormal state due to the occlusion of foreign objects.

[0029] The present application is precisely proposed to solve the above problems.

[0030] To illustrate the technical solution of the present application, specific embodiments are used for illustration below.

[0031] Figure 1 The figure shows a schematic implementation flowchart of an abnormal monitoring method provided by an embodiment of the present application. This method can be applied to a monitoring device and is applicable to situations where the reliability of the abnormal monitoring method needs to be improved.

[0032] Among them, the above-mentioned monitoring device is used to monitor a target object, and the target object can refer to objects such as the elderly, children, and pets that need to be monitored.

[0033] Specifically, as Figure 2 shown, the above-mentioned monitoring device can be a monitoring device in a monitoring system. The monitoring system includes a cloud server, a monitoring device, and a user terminal. The monitoring device can perform abnormal monitoring and report abnormal status information to the cloud server in real time. The cloud server can send the abnormal status information to the user terminal. The user terminal can be used by the guardian of the target object so that the guardian can perform abnormal handling in a timely manner after receiving the abnormal status information.

[0034] Among them, the above-mentioned monitoring device can be a simple monitoring device only used to detect whether the target object has an abnormality, or a multifunctional device that can also provide places for feeding, defecation, playing, etc. and can complete tasks such as feeding, cleaning feces, and monitoring. The present application does not limit this.

[0035] Specifically, the above-mentioned abnormal monitoring method can include the following steps S101 to step S102.

[0036] Step S101, obtain the monitoring data of the monitoring device.

[0037] Among them, the above-mentioned monitoring data includes at least one of the working data of each working module of the monitoring device and the object data of the target object.

[0038] In the embodiment of the present application, each working module of the above-mentioned monitoring device is respectively used to perform different monitoring functions.

[0039] Specifically, please refer to Figure 2, the above-mentioned working modules may include, but are not limited to, a weighing module for measuring the weight of the target object, a feeding module for feeding the target object, a feces cleaning module for cleaning the feces of the target object, a sensing module for obtaining the physical sign data of the target object, an image acquisition module for collecting real-time images of the target object and the monitoring device, a communication module for interacting with the cloud server, etc. The monitoring device can obtain the device images of each working module during operation captured by the image acquisition module, and can also obtain the rotation values of the motors of each working module, or the current values of each working module as the above-mentioned working data.

[0040] Correspondingly, the above-mentioned object data refers to the data of the target object collected by the above-mentioned working modules. For example, the physical sign data of the target object collected by the sensing module, the weight value of the target object collected by the weighing module, the object image of the target object collected by the image acquisition module, etc.

[0041] Step S102, if the monitoring data meets the abnormal determination condition, it is determined that the monitoring device or the target object is in an abnormal state.

[0042] In the embodiment of the present application, after the monitoring device obtains the monitoring data, it can determine whether each item of monitoring data meets the corresponding abnormal determination condition. If the working data of any one working module meets the abnormal determination condition, it can be confirmed that the monitoring device is in an abnormal state. If the object data of the target object meets the abnormal determination condition, it can be determined that the target object is in an abnormal state. Otherwise, it can be confirmed that neither the monitoring device nor the target object is in an abnormal state.

[0043] In some embodiments of the present application, after determining that the monitoring device or the target object is in an abnormal state, the monitoring device can send a prompt message corresponding to the abnormal state to the user terminal to prompt the user to perform abnormal processing.

[0044] Moreover, if it is determined that the target object is in an abnormal state, the monitoring device can also determine the monitoring strategy for the target object according to the abnormal state of the target object, and send the monitoring strategy to the user terminal. The monitoring strategy may include information such as the recipe, feeding amount, feeding frequency, etc. used for feeding the target object.

[0045] It should be noted that the monitoring device can execute the above-mentioned steps S101 and S102 at a preset frequency to achieve real-time abnormal monitoring.

[0046] In an embodiment of the present application, by obtaining the monitoring data of the monitoring device, if the monitoring data meets the abnormal determination condition, it is determined that the monitoring device or the target object is in an abnormal state. Since the monitoring data includes at least one of the working data of each working module of the monitoring device and the object data of the target object monitored by the monitoring device, the monitoring device can perform abnormal monitoring on both the monitoring device and the target object, can not only complete the monitoring work of the target object, but also avoid misjudging that the monitored object is abnormal or performing ineffective monitoring on the monitored object due to the abnormality of the monitoring device itself, improving the reliability of abnormal monitoring and reducing the waste of resources.

[0047] In order to further improve the reliability of abnormal monitoring, in some embodiments of the present application, when the above-mentioned monitoring device performs abnormal monitoring on the target object, the following steps S301 to S303 may also be executed.

[0048] Step S301, obtain the target growth stage where the target object is located.

[0049] In an embodiment of the present application, the target object has different growth stages. Taking a pet as an example, a pet has different growth stages such as infancy, estrus, adulthood, and old age. The maintenance methods of pets in different growth stages are different, and the normal ranges of corresponding weight values and physical sign data are also different.

[0050] The monitoring device can obtain the target growth stage where the target object is located to perform targeted abnormal monitoring on the target object in different growth stages.

[0051] Specifically, in order to obtain a more accurate growth stage, the monitoring device can determine the basic growth stage value of the target object according to the weight value of the target object, and use the weight difference of the target object within a preset time period and the age value of the target object to correct the basic growth stage value, calculate the target growth stage value of the target object, and obtain the target growth stage where the target object is located.

[0052] Among them, the weight value can be the weight value calculated by the aforementioned weighing module.

[0053] Considering that the target object is a living body and its behavior is uncontrollable, the monitoring device can judge whether the target object enters or leaves the inside of the monitoring device through visual recognition, obtain the total weight weighed by the weighing module when the target object is stationary inside the monitoring device, and the total weight weighed by the weighing module when the target object leaves the inside of the monitoring device, and then use the weight difference before and after the target object enters the monitoring device to obtain the weight of the target object: T 目标对象 =T 目标对象静止于监护设备内 -T 宠物离开监护设备 .

[0054] Using the weights of the target object collected at the start time and end time corresponding to the preset time period respectively, the monitoring device can calculate the weight difference of the target object within the preset time period.

[0055] Among them, the preset time period can be one day, one week, one month, etc., and can be set by the staff according to the actual situation. The start time can refer to 0:00 of a day, Monday, the first day of a month, and correspondingly, the end time can refer to 24:00 of a day, Sunday, the last day of a month.

[0056] The above age value can be obtained by the monitoring device from the information sent by the user through the user terminal.

[0057] After obtaining the weight value of the target object, the weight difference of the target object within the preset time period, and the age value of the target object, the monitoring device can determine the basic growth stage value of the target object according to the weight value, and use the weight difference and age value to correct the basic growth stage value, calculate the target growth stage value of the target object, and obtain the target growth stage where the target object is located.

[0058] Specifically, the monitoring device can obtain multiple reference weight ranges set by the staff according to experience values, and multiple basic growth stage values corresponding to each reference weight range. Each basic growth stage value corresponds to a weight value respectively. If the weight value of the target object belongs to a certain reference weight range, the monitoring device can use the basic growth stage value closest to the weight value of the target object within the reference weight range as the basic growth stage value P of the target object.

[0059] Next, the monitoring device can use the correction formula to correct the basic growth stage value P and calculate the target growth stage value of the target object.

[0060] Among them, P′ is the target growth stage value, P is the basic growth stage value. W is the stage weight corresponding to the age value, which can be determined according to the age value and can be used to characterize the growth rate of the target object. Since the younger the age, the faster the growth rate, correspondingly, the stage weight corresponding to the age value is larger. D n is the weight difference of the target object within the preset time period, D p is the expected weight difference corresponding to the preset time period, which can be set by the staff according to historical experience values.

[0061] In the implementation manner of the present application, since the weight changes in each growth stage of the target object are different, generally, the lower the age, the faster the weight increases. Therefore, on the basis of the basic growth stage value, using the weight difference and age value for correction can obtain the target growth stage value, and then accurately confirm the target growth stage where the target object is located.

[0062] Step S302: Obtain the reference data range corresponding to the target growth stage.

[0063] Specifically, the monitoring device may store the reference data range of each type of data corresponding to each growth stage preset by the staff. According to the target growth stage, the monitoring device can query the reference data range of each type of data corresponding to the target growth stage.

[0064] Step S303: If the object data is outside the reference data range corresponding to the target growth stage, determine that the monitoring data meets the abnormal determination condition and determine that the target object is in an abnormal state.

[0065] In some embodiments of the present application, if the object data is outside the reference data range corresponding to the target growth stage, the monitoring device may determine that the monitoring data meets the abnormal determination condition and determine that the target object is in an abnormal state.

[0066] Among them, each type of data has a corresponding reference data range for the target growth stage.

[0067] In some embodiments of the present application, the monitoring device may perform abnormal determination on the following types of data:

[0068] Whether the weight is abnormal: T 目标对象 ∈[T min , T max , if it exceeds the range, it is abnormal;

[0069] Whether the weight difference is abnormal: D n ∈[D min , D max , if it exceeds the range, it is abnormal;

[0070] Whether the body temperature is abnormal: t ∈ [t min , t max , if it exceeds the range, it is abnormal;

[0071] Whether the heart rate is abnormal: h ∈ p[h min , h max , where p is the weight value corresponding to the target growth stage, if it exceeds the range, it is abnormal;

[0072] Whether the respiratory rate is abnormal: b ∈ [b min , b max , if it exceeds the range, it is abnormal.

[0073] Among them, the body temperature, heart rate, and respiratory rate are the physical sign data of the target object collected by the aforementioned sensing module.

[0074] In an implementation manner of the present application, by obtaining the target growth stage of the target object, and then obtaining the reference data range corresponding to the target growth stage, if the object data is outside the reference data range corresponding to the target growth stage, it is determined that the monitoring data meets the abnormal judgment conditions, and it is determined that the target object is in an abnormal state. The target object can be monitored for abnormalities according to the growth stage, which solves the problem that traditional monitoring equipment cannot perform abnormal monitoring of the target object at different growth stages.

[0075] In addition, the monitoring device can also use the target object image acquired by the image acquisition module to identify abnormal behavior of the object image. The abnormality identification step can use a pre-trained abnormality identification model or other abnormality identification algorithms.

[0076] When it is identified that the behavior of the target object is abnormal, for example, when it is identified that the target object is vomiting or sneezing, the monitoring device can determine that the monitoring data meets the abnormality determination conditions and determine that the target object is in an abnormal state.

[0077] In other embodiments of the present application, the monitoring device may perform abnormality detection on each of its own working modules.

[0078] Specifically, the monitoring device can determine that the monitoring data meets the abnormal judgment conditions and determine that the monitoring device is in an abnormal state when the rotation value of the motor of each working module does not reach the preset reference rotation value, or the current value of each working module is outside the preset normal current range.

[0079] For example, if the rotation value of the motor of the feeding module does not reach the preset reference rotation value, it means that the motor of the feeding module has not rotated into place, that is, the actual feeding amount does not reach the feeding amount required by the target object, then the monitoring device can determine that the monitoring data meets the abnormal judgment condition and determines that the monitoring device is in an abnormal state. If the rotation value of the motor of the defecation module does not reach the preset reference rotation value, it means that the motor of the defecation module has not rotated into place, that is, the defecation module has not completed the defecation work, then the monitoring device can determine that the monitoring data meets the abnormal judgment condition and determines that the monitoring device is in an abnormal state.

[0080] For another example, when the current value of the lighting module is outside the preset normal current range, it means that the lighting module has not completed the lighting work normally. The monitoring device can determine that the monitoring data meets the abnormal judgment conditions and determine that the monitoring device is in an abnormal state.

[0081] In addition, the monitoring device may also perform abnormality recognition using the device image of the monitoring device acquired by the image acquisition module. Similarly, the abnormality recognition step may use a pre-trained abnormality recognition model or other abnormality recognition algorithms.

[0082] When any one of the working modules is identified as abnormal, for example, the brightness of the light projected by the lighting module is lower than the brightness threshold, or there is foreign matter in any one of the working modules, the monitoring device can determine that the monitoring data meets the abnormal determination condition and determine that the monitoring device is in the abnormal state.

[0083] In the embodiments of the present application, by monitoring each working module to determine whether the monitoring device is abnormal, it is possible to avoid ineffective monitoring caused by the working module not working properly and the problem of misjudging that the object being monitored is abnormal due to the influence of foreign matter on the working module, thereby improving the reliability of the abnormal monitoring method.

[0084] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other sequences.

[0085] As Figure 4 shown in the structural schematic diagram of an abnormal monitoring device 400 provided by an embodiment of the present application. The abnormal monitoring device 400 is configured on a monitoring device, and the monitoring device is used to monitor a target object.

[0086] Specifically, the abnormal monitoring device 400 may include:

[0087] A data acquisition unit 401, configured to acquire the monitoring data of the monitoring device, where the monitoring data includes at least one of the working data of each working module of the monitoring device and the object data of the target object;

[0088] An abnormal monitoring unit 402, configured to determine that the monitoring device or the target object is in an abnormal state if the monitoring data meets the abnormal determination condition.

[0089] In some embodiments of the present application, the above monitoring data includes the object data of the target object. Specifically, the abnormal monitoring unit 402 may be configured to: acquire the target growth stage of the target object; acquire the reference data range corresponding to the target growth stage; if the object data is outside the reference data range corresponding to the target growth stage, determine that the monitoring data meets the abnormal determination condition and determine that the target object is in the abnormal state.

[0090] In some embodiments of the present application, the above object data includes the weight value of the target object, the weight difference of the target object within a preset time period, and the age value of the target object. The above abnormal monitoring unit 402 may specifically be configured to: determine the basic growth stage value of the target object according to the weight value; correct the basic growth stage value by using the weight difference and the age value, calculate the target growth stage value of the target object, and obtain the target growth stage in which the target object is located.

[0091] In some embodiments of the present application, the above abnormal monitoring unit 402 may specifically be configured to: use a correction formula to correct the basic growth stage value, and calculate the target growth stage value of the target object, where P′ is the target growth stage value, P is the basic growth stage value, W is the stage weight corresponding to the age value, and D n is the weight difference of the target object within a preset time period, and D p is the expected value of the weight difference corresponding to the preset time period.

[0092] In some embodiments of the present application, the above monitoring data includes the working data of each working module of the monitoring device. The working data includes the rotation value of the motor of each working module and the current value of each working module. The above abnormal monitoring unit 402 may specifically be configured to: if the rotation value does not reach a preset reference rotation value, or the current value is outside a preset normal current range, determine that the monitoring data meets the abnormal determination condition, and determine that the monitoring device is in the abnormal state.

[0093] In some embodiments of the present application, the above working data includes the device image when the monitoring device is working, and the above object data includes the object image of the target object. The above abnormal monitoring unit 402 may specifically be configured to: perform abnormal recognition on the device image, and when any one of the working modules is recognized as abnormal, determine that the monitoring data meets the abnormal determination condition, and determine that the monitoring device is in the abnormal state; and / or, perform abnormal recognition on the object image, and when the behavior of the target object is recognized as abnormal, determine that the monitoring data meets the abnormal determination condition, and determine that the target object is in the abnormal state.

[0094] In some embodiments of the present application, the above abnormal monitoring device 400 further includes an abnormal processing unit, configured to send a prompt message corresponding to the abnormal state to the user terminal after determining that the monitoring device or the target object is in the abnormal state, so as to prompt the user to perform abnormal processing; and / or, if it is determined that the target object is in the abnormal state, determine the guardianship strategy of the target object according to the abnormal state in which the target object is located, and send the guardianship strategy to the user terminal.

[0095] It should be noted that, for the convenience and conciseness of description, the specific working process of the above abnormal monitoring device 400 can be referred to Figures 1 to 3 the corresponding process of the method described above, which will not be elaborated here.

[0096] As Figure 5 shown, it is a schematic diagram of a monitoring device provided by an embodiment of the present application. The monitoring device 5 may include: a processor 50, a memory 51, and a computer program 52 stored in the memory 51 and executable on the processor 50, such as an abnormal monitoring program. When the processor 50 executes the computer program 52, the steps in the above various embodiments of the abnormal monitoring method are implemented, such as Figure 1 the steps S101 to S102 shown. Alternatively, when the processor 50 executes the computer program 52, the functions of each module / unit in the above device embodiments are implemented, such as Figure 4 the data acquisition unit 401 and the abnormal monitoring unit 402 shown.

[0097] The computer program may be divided into one or more modules / units. The one or more modules / units are stored in the memory 51 and executed by the processor 50 to complete the present application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the monitoring device.

[0098] For example, the computer program may be divided into: a data acquisition unit 401 and an abnormal monitoring unit 402.

[0099] The specific functions of each unit are as follows: The data acquisition unit is used to acquire the monitoring data of the monitoring device, and the monitoring data includes at least one of the working data of each working module of the monitoring device and the object data of the target object; the abnormal monitoring unit is used to determine that the monitoring device or the target object is in an abnormal state if the monitoring data meets the abnormal determination condition.

[0100] The monitoring device may include, but is not limited to, a processor 50 and a memory 51. Those skilled in the art can understand that Figure 5 it is only an example of the monitoring device and does not constitute a limitation on the monitoring device. It may include more or fewer components than shown in the figure, or combine some components, or different components. For example, the monitoring device may further include an input / output device, a network access device, a bus, etc.

[0101] The so-called processor 50 may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, or the processor may also be any conventional processor, etc.

[0102] The memory 51 may be an internal storage unit of the monitoring device, such as the hard disk or memory of the monitoring device. The memory 51 may also be an external storage device of the monitoring device, such as a plug-in hard disk equipped on the monitoring device, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Further, the memory 51 may also include both the internal storage unit and the external storage device of the monitoring device. The memory 51 is used to store the computer program and other programs and data required by the monitoring device. The memory 51 may also be used to temporarily store the data that has been output or will be output.

[0103] It should be noted that for the convenience and brevity of description, the structure of the above-mentioned monitoring device may also refer to the specific description of the structure in the method embodiment, which will not be elaborated here.

[0104] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above division of each functional unit and module is used as an example. In practical applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of the present application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiment, which will not be elaborated here.

[0105] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For parts not detailed or recorded in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0106] Those of ordinary skill in the art will realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0107] In the embodiments provided in this application, it should be understood that the disclosed device / monitoring device and method can be implemented in other ways. For example, the device / monitoring device embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical or other forms.

[0108] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0109] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0110] When the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of this application, it can also be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0111] The above-described embodiments are only used to illustrate the technical solutions of this application, rather than to limit them; although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of this application, and should all be included in the protection scope of this application.

Claims

1. An abnormal monitoring method, characterized in that, it is applied to a monitoring device for monitoring a target object, and the abnormal monitoring method includes: obtaining monitoring data of the monitoring device, where the monitoring data includes at least one of the working data of each working module of the monitoring device and the object data of the target object; if the monitoring data meets the abnormal determination condition, it is determined that the monitoring device or the target object is in an abnormal state; wherein, the monitoring data includes the object data of the target object, the object data includes the weight value of the target object, the weight difference of the target object within a preset time period, and the age value of the target object; the abnormal state is determined based on the target growth stage of the target object; the target growth stage is obtained by correcting a basic growth stage value using the weight difference and the age value to calculate the target growth stage value of the target object; the basic growth stage value is determined according to the weight value.

2. The abnormal monitoring method according to claim 1, characterized in that, the monitoring data includes the object data of the target object; the step of, if the monitoring data meets the abnormal determination condition, determining that the monitoring device or the target object is in an abnormal state, includes: obtaining the target growth stage of the target object; obtaining the reference data range corresponding to the target growth stage; if the object data is outside the reference data range corresponding to the target growth stage, it is determined that the monitoring data meets the abnormal determination condition, and it is determined that the target object is in the abnormal state.

3. The abnormal monitoring method according to claim 1, characterized in that, the process of correcting the basic growth stage value using the weight difference and the age value to calculate the target growth stage value of the target object includes: Using a correction formula correct the basic growth stage value to calculate the target growth stage value of the target object, where P ′ is the target growth stage value, P is the basic growth stage value, W is the stage weight corresponding to the age value, D n is the weight difference of the target object within a preset time period, D p is the expected value of the weight difference corresponding to the preset time period.

4. The abnormal monitoring method according to any one of claims 1 to 3, characterized in that, the monitoring data includes the working data of each working module of the monitoring device, and the working data includes the rotation value of the motor of each working module and the current value of each working module; the step of, if the monitoring data meets the abnormal determination condition, determining that the monitoring device or the target object is in an abnormal state, includes: if the rotation value does not reach the preset reference rotation value, or the current value is outside the preset normal current range, it is determined that the monitoring data meets the abnormal determination condition, and it is determined that the monitoring device is in the abnormal state.

5. The abnormal monitoring method according to any one of claims 1 to 3, characterized in that, the working data includes the device image when the monitoring device is working, and the object data includes the object image of the target object; the step of, if the monitoring data meets the abnormal determination condition, determining that the monitoring device or the target object is in an abnormal state, includes: performing abnormal identification on the device image, and when any one of the working modules is identified as abnormal, it is determined that the monitoring data meets the abnormal determination condition, and it is determined that the monitoring device is in the abnormal state. And / or, perform anomaly recognition on the object image, and when it is recognized that the behavior of the target object is abnormal, determine that the monitoring data meets the anomaly determination condition and determine that the target object is in the abnormal state.

6. The anomaly monitoring method according to any one of claims 1 to 3, characterized in that after determining that the monitoring device or the target object is in an abnormal state, it includes: sending a prompt message corresponding to the abnormal state to the user terminal to prompt the user to perform anomaly handling; and / or, if it is determined that the target object is in the abnormal state, determine the guardianship strategy of the target object according to the abnormal state in which the target object is located, and send the guardianship strategy to the user terminal.

7. An anomaly monitoring device, characterized in that configured in a monitoring device, the monitoring device is used to monitor a target object, and the anomaly monitoring device includes: a data acquisition unit for acquiring monitoring data of the monitoring device, the monitoring data including at least one of the working data of each working module of the monitoring device and the object data of the target object; an anomaly monitoring unit for determining that the monitoring device or the target object is in an abnormal state if the monitoring data meets the anomaly determination condition; wherein, the monitoring data includes the object data of the target object, the object data includes the weight value of the target object, the weight difference of the target object within a preset time period, and the age value of the target object; the abnormal state is determined based on the target growth stage of the target object; the target growth stage is obtained by correcting the basic growth stage value using the weight difference and the age value to calculate the target growth stage value of the target object; the basic growth stage value is determined according to the weight value.

8. A monitoring device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that when the processor executes the computer program, the steps of the anomaly monitoring method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that when the computer program is executed by a processor, the steps of the anomaly monitoring method according to any one of claims 1 to 6 are implemented.

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