CN114090091A

CN114090091A - Automatic equipment starting method and device, electronic equipment and storage medium

Info

Publication number: CN114090091A
Application number: CN202111425347.7A
Authority: CN
Inventors: 张一戈; 王益锋
Original assignee: Lian Ying Changzhou Medical Technology Co ltd
Current assignee: Lian Ying Changzhou Medical Technology Co ltd
Priority date: 2021-11-26
Filing date: 2021-11-26
Publication date: 2022-02-25

Abstract

The invention provides an automatic equipment starting method, an automatic equipment starting device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring historical use data of equipment; establishing a starting condition model of the equipment through a machine learning algorithm based on the historical use data; the starting condition model comprises a starting condition and a starting parameter of the equipment; and when the equipment meets the starting-up condition, controlling the equipment to start up according to the starting-up parameters. The invention establishes the starting condition model of the equipment through a machine learning algorithm based on the historical use data of the equipment, and controls the equipment to start by the starting parameters when the equipment meets the starting condition, thereby realizing the automatic starting of the equipment.

Description

Automatic equipment starting method and device, electronic equipment and storage medium

Technical Field

The invention relates to the technical field of equipment starting, in particular to an automatic equipment starting method and device, electronic equipment and a storage medium.

Background

Devices such as medical linear accelerators, medical imaging devices, are widely used in the medical field. However, the conventional device generally realizes power-on control through a key, a knob, a touch screen and the like. Namely: the equipment user needs to manually start the machine when using the equipment.

The starting mode of the existing equipment has the following problems: the degree of automation is not high, and there is a risk of misoperation.

Disclosure of Invention

In view of the above, it is desirable to provide an apparatus auto-boot method, an apparatus, an electronic apparatus, and a storage medium, which are used to solve the technical problems of the prior art that the degree of automation of booting the apparatus is not high and there is a risk of misoperation.

In one aspect, the present invention provides an automatic boot method for a device, including:

acquiring historical use data of equipment;

establishing a starting condition model of the equipment through a machine learning algorithm based on the historical use data; the starting condition model comprises a starting condition and a starting parameter of the equipment;

and when the equipment meets the starting-up condition, controlling the equipment to start up according to the starting-up parameters.

In some possible implementations, the device includes a plurality of components, the boot condition model includes a plurality of boot condition submodels in one-to-one correspondence with the plurality of components, the boot condition includes a plurality of boot sub-conditions in one-to-one correspondence with the plurality of components, and the boot parameter includes a plurality of boot sub-parameters in one-to-one correspondence with the plurality of components; when the equipment meets the starting-up condition, controlling the equipment to start up according to the starting-up parameters comprises the following steps:

and when the at least one component meets the corresponding startup sub-condition, controlling the at least one component to start up according to the corresponding startup sub-parameter.

In some possible implementations, the boot condition includes an environmental condition and/or a temporal condition; when the equipment meets the starting-up condition, controlling the equipment to start up according to the starting-up parameters comprises the following steps:

monitoring environmental information of the environment where the equipment is located in real time;

judging whether the environmental information meets the environmental conditions;

when the environmental information meets the environmental conditions, controlling the equipment to start up according to the starting-up parameters; and/or

Monitoring time information of the equipment in real time;

judging whether the time information meets the time condition or not;

and when the time information meets the time condition, controlling the equipment to start up according to the starting-up parameters.

In some possible implementations, the method for automatically booting a device further includes:

establishing a pre-operation model of the equipment through a machine learning algorithm based on the historical usage data;

and pre-operating the equipment through the pre-operation model.

In some possible implementations, before the pre-running the device by the pre-running model, the method further includes:

judging whether a target object exists in the space where the equipment is located;

and determining that the target object does not exist in the space where the equipment is located, and pre-operating the equipment through the pre-operation model.

In some possible implementations, the pre-run model includes a pre-heat sub-model and/or a self-test sub-model; the pre-running of the equipment through the pre-running model comprises:

preheating the equipment through the preheating sub-model;

and/or the presence of a gas in the gas,

and self-checking the equipment through the self-checking sub-model.

establishing a sleep condition model of the device through a machine learning algorithm based on the historical usage data, the sleep condition model including sleep conditions of the device;

judging whether the equipment meets a dormancy condition;

judging whether the equipment is in an idle state or not;

judging whether a worker exists in the space where the equipment is located;

and when the equipment meets the sleep condition and is in an idle state, controlling the equipment to enter the sleep state.

On the other hand, the invention also provides an automatic starting device of the equipment, which comprises:

a historical usage data acquisition unit for acquiring historical usage data of the device;

the starting condition model establishing unit is used for establishing a starting condition model of the equipment through a machine learning algorithm based on the historical use data; the starting condition model comprises a starting condition and a starting parameter of the equipment;

and the automatic starting unit is used for controlling the equipment to start according to the starting parameters when the equipment meets the starting conditions.

In another aspect, the present invention also provides an electronic device comprising a memory and a processor, wherein,

a memory for storing a program;

and the processor is coupled with the memory and used for executing the program stored in the memory so as to realize the steps in the automatic starting method of the equipment in any one of the implementation modes.

The invention further provides a computer-readable storage medium for storing a computer-readable program or instruction, which, when executed by a processor, is capable of implementing the steps in the method for automatically booting a device in any one of the above-mentioned implementation manners.

The beneficial effects of adopting the above embodiment are: the automatic starting method of the equipment provided by the invention establishes the starting condition model of the equipment through the machine learning algorithm based on the historical use data of the equipment, controls the equipment to start according to the starting parameters when the equipment meets the starting condition, realizes the automatic starting of the equipment, improves the automation degree of the starting of the equipment, and avoids the false triggering of the equipment because the equipment is not required to be started by using personnel.

Furthermore, a starting condition model of the equipment is established based on the historical use data and the machine learning algorithm, the historical starting data of the equipment is fully considered, the starting condition and the starting parameter of the equipment can be accurately obtained, and the accuracy of automatic starting of the equipment is improved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a schematic flow chart illustrating an embodiment of an automatic booting method for a device according to the present invention;

FIG. 2 is a schematic flow chart of one embodiment of S103 of FIG. 1;

FIG. 3 is a schematic flow chart of another embodiment of S103 of FIG. 1 according to the present invention;

FIG. 4 is a schematic flow chart illustrating one embodiment of pre-operation of the apparatus provided by the present invention;

FIG. 5 is a flowchart illustrating an embodiment of ensuring that no target object exists in the space where the device is located according to the present invention;

FIG. 6 is a flowchart illustrating an embodiment of auto-hibernating of a device provided by the present invention;

FIG. 7 is a schematic structural diagram of an apparatus auto-boot apparatus according to an embodiment of the present invention;

fig. 8 is a schematic structural diagram of an embodiment of an electronic device provided in the present invention.

Detailed Description

The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

In the description of the embodiments of the present invention, "a plurality" means one or more than one unless otherwise specified. "plurality" means two or more. "and/or" describes the association relationship of the associated objects, meaning that three relationships may exist, for example: a and/or B, may represent: a exists alone, A and B exist simultaneously, and B exists alone.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

The invention provides an automatic equipment starting method, an automatic equipment starting device, electronic equipment and a storage medium, which are respectively explained below.

Before the examples are presented, the device is defined. In embodiments of the invention, the device may be a general purpose device or a special purpose device, such as: the device may be an electrical device, a computer device, a medical device, or the like.

In some embodiments of the present invention, the apparatus is a medical apparatus, and specifically, the apparatus may be a medical accelerator, an X-ray diagnostic apparatus, an ultrasonic diagnostic apparatus, a functional examination apparatus, a sterilization apparatus, or the like.

Fig. 1 is a schematic flowchart of an embodiment of an automatic boot method of a device according to the present invention, as shown in fig. 1, the automatic boot method of the device includes:

s101, acquiring historical use data of equipment;

s102, establishing a starting condition model of the equipment through a machine learning algorithm based on historical use data; the starting condition model comprises starting conditions and starting parameters of the equipment;

and S103, when the equipment meets the starting-up condition, controlling the equipment to start up according to the starting-up parameter.

Compared with the prior art, the automatic starting method of the equipment provided by the embodiment of the invention establishes the starting condition model of the equipment through the machine learning algorithm based on the historical use data of the equipment, controls the equipment to start according to the starting parameters when the equipment meets the starting condition, realizes the automatic starting of the equipment, improves the automation degree of the starting of the equipment, and avoids the false triggering of the equipment because the equipment is not required to be started by equipment users.

The historical usage data in step S101 includes time data and environment data of the device in historical usage. Of course, the historical usage data may also include other related data besides the time data and the environmental data, and is not limited herein.

In an embodiment of the present invention, when the apparatus is a medical accelerator apparatus, the historical usage data in step S101 includes: the medical accelerator device comprises a medical accelerator device, a treatment beam component, an imaging component and other mechanical components, wherein the medical accelerator device comprises a power supply, a power supply and a power supply.

It should be understood that: the machine learning algorithm in step S102 may be capable of learning certain knowledge and capabilities from existing data (historical usage data) for processing new data, and may be designed to perform various tasks, in embodiments of the present invention, for determining whether a device is powered on.

In some embodiments of the present invention, examples of Machine learning algorithms include, but are not limited to, Deep Neural Networks (DNNs), Support Vector Machines (SVMs), decision trees, random forest algorithms, and the like.

In some embodiments of the present invention, the specific process of establishing the boot condition model of the device is as follows: firstly, an initial model is established according to any one of the machine learning algorithms mentioned above, then the initial model is trained based on historical use data, a starting condition model can be obtained after the training is completed, and the equipment can be controlled to be automatically started according to the starting condition model by starting parameters when the equipment meets the starting condition.

In some embodiments of the present invention, the power-on parameters in step S102 may include a motor speed of the device, a temperature of the device, a posture of the device, and a position of the device at the time of power-on. Of course, the startup parameters may also include other related startup parameters besides the motor speed, the device temperature, the device attitude, and the device position of the device at startup, which are not limited herein.

As the integration of the device becomes higher, in some embodiments of the present invention, the device includes a plurality of components, the boot condition model includes a plurality of boot condition sub-models corresponding to the plurality of components one to one, the boot condition includes a plurality of boot sub-conditions corresponding to the plurality of components one to one, and the boot parameter includes a plurality of boot sub-parameters corresponding to the plurality of components one to one;

step S103 is: and when at least one component meets the corresponding boot sub-condition, controlling at least one component to boot with the corresponding boot sub-parameter.

The embodiment of the invention can realize the independent startup of different parts in the equipment by setting the plurality of startup condition submodels which are in one-to-one correspondence with the plurality of parts, avoids the need of starting up the whole equipment when one or two parts in the equipment are needed to be started up, reduces the startup coupling degree among the plurality of different parts of the equipment, further improves the automation degree of the startup of the equipment and can improve the startup efficiency of the equipment.

It should be noted that: the multiple power-on condition submodels may run in parallel, in series, or in a mixture of series and parallel. The specific operation mode may be determined according to the power-on sequence relationship among the components, which is not described herein.

In some embodiments of the present invention, the boot conditions include environmental conditions and/or temporal conditions.

By setting the starting-up conditions to include the environmental conditions, the technical problem that the equipment is damaged when the equipment is started in a severe environment can be avoided, and the use safety of the equipment is improved. Moreover, the starting-up conditions including the time conditions are set, so that the time accuracy of starting up the equipment can be improved, the problem that the use cost of the equipment is improved due to the fact that the equipment is started up in advance is solved, the technical problems that the use of the equipment is delayed and the experience of equipment using personnel is reduced due to the fact that the equipment is started up in advance are solved, and the use cost of the equipment is reduced while the equipment is used in time is guaranteed.

In some embodiments of the invention, the environmental conditions include the temperature and humidity of the environment, and the like.

In some embodiments of the present invention, as shown in fig. 2, when the boot condition is an environmental condition, step S103 includes:

s201, monitoring environmental information of an environment where equipment is located in real time;

s202, judging whether the environmental information meets the environmental conditions;

and S203, when the environmental information meets the environmental conditions, the control equipment is started up according to the starting-up parameters.

In some embodiments of the invention, the environmental information comprises a first environmental threshold and a second environmental threshold, and the first environmental threshold is less than the second environmental threshold; the environment information in step S203 meeting the environment condition is specifically: when the environmental information is greater than or equal to the first environmental threshold and less than or equal to the second environmental threshold, the environmental information satisfies the environmental condition.

To further improve the time accuracy of the device powering on, in some other embodiments of the invention, the environmental condition comprises a first accurate environmental threshold, the environmental condition being satisfied only if the environmental information is equal to the first accurate environmental threshold.

It should be understood that: when the specific conditions are satisfied, the environmental information satisfies the environmental conditions, and can be adjusted according to the actual requirements of the equipment, which is not specifically limited herein.

In some embodiments of the present invention, as shown in fig. 3, when the boot condition is a time condition, step S103 includes:

s301, monitoring time information of the equipment in real time;

s302, judging whether the time information meets a time condition;

and S303, when the time information meets the time condition, controlling the equipment to start up according to the starting-up parameters.

In some embodiments of the invention, the time condition comprises a first threshold point in time and a second threshold point in time, and the first threshold point in time is earlier than the second threshold point in time; the time information in step S203 meeting the time condition is specifically: the time information satisfies a time condition when the time information is later than or equal to a first threshold time point and earlier than or equal to a second threshold time point.

To further improve the time accuracy of the device powering on, in some other embodiments of the invention, the time condition comprises a first accurate point in time, the time condition being fulfilled only if the time information equals the first accurate point in time.

It should be understood that: when the specific condition is satisfied, the time information satisfies the time condition, and can be adjusted according to the actual requirement of the equipment, which is not specifically limited herein.

In some embodiments of the present invention, in order to reduce the booting cost while ensuring the security of booting the device, it may be configured to control the device to boot with the booting parameters only when the device satisfies the time condition and the environmental condition at the same time.

Since some devices, including medical devices, are used, it is often necessary to perform at least one pre-operational action to ensure subsequent proper operation of the device. For example: for the medical accelerator equipment, before the medical accelerator equipment is used formally, at least one pre-operation program needs to be operated, so that the reliability of the medical accelerator equipment is ensured when the medical accelerator equipment is used formally. In the prior art, a user who needs to use the device manually controls the device to execute at least one pre-running program, which results in a low degree of automation of the pre-running of the device, and also may cause a technical problem of running the at least one pre-running program in a missing manner, in order to solve the above technical problem, in some embodiments of the present invention, as shown in fig. 4, the method for automatically booting the device further includes:

s401, establishing a pre-operation model of the equipment through a machine learning algorithm based on historical use data;

s402, pre-running the equipment through the pre-running model.

According to the embodiment of the invention, based on the historical use data of the equipment, the pre-operation model of the equipment is established through the machine learning algorithm, and the pre-operation of the equipment is carried out through the pre-operation model, so that the automatic pre-operation of the equipment is realized, and the automation degree of the pre-operation of the equipment is improved.

Furthermore, a pre-operation model of the equipment is established based on historical use data and a machine learning algorithm, all pre-operation programs of the equipment are fully fused, operation leakage is avoided, and reliability of pre-operation of the equipment is improved.

It should be understood that: the machine learning algorithm in step S401 may be capable of learning certain knowledge and capabilities from existing data (historical usage data) for processing new data, and may be designed to perform various tasks, in embodiments of the present invention, for determining whether a device is pre-operational.

The specific process of establishing the pre-operation model of the device is the same as the specific process of establishing the startup condition model of the device, and is not described herein again.

It should be noted that: the pre-operation model comprises a plurality of pre-operation sub-models which correspond to the components one by one, and the plurality of pre-operation sub-models can be the same or different. For example: when the pre-running programs of the two components are different, the two pre-running submodels corresponding to the two components are also different.

It should also be noted that: multiple pre-run sub-models of different components can be run simultaneously, i.e.: and the parallel operation is carried out so as to improve the operation efficiency of the pre-operation of the equipment.

Further, since in some devices pre-run, for example: when the medical accelerator apparatus is operated in advance, it will emit a therapeutic beam, and some parts of the medical accelerator apparatus will also move, and the therapeutic beam has radiation influence on the human body, and when the parts move, it may collide and bump against the personnel using the apparatus, and when there are other obstacles in the space where the medical accelerator apparatus is located, during the movement of the parts of the medical accelerator apparatus, the obstacles may damage the medical accelerator apparatus, so as to avoid causing harm to the personnel in the space where the apparatus is located and/or damage to the apparatus when the apparatus is operated in advance, in some embodiments of the present invention, as shown in fig. 5, before step S402, it further includes:

s501, judging whether a target object exists in a space where the equipment is located;

s502, determining that no target object exists in the space where the equipment is located, and pre-operating the equipment through a pre-operation model.

It should be understood that: the target object may be a human body, an animal body and/or other obstacles in the space in which the device is located.

In some embodiments of the present invention, it is determined that a target object exists in a space where a device is located, and no pre-operation is performed. Further, determining that a target object exists in the space where the equipment is located, and generating first warning information to prompt the target object to leave the space where the equipment is located while not performing pre-operation; and pre-operating the equipment through the pre-operation model when the target object does not exist in the space where the equipment is to be determined.

It should be understood that: the first warning information may be an acoustic and/or optical warning information.

According to the embodiment of the invention, the pre-operation of the equipment is carried out through the pre-operation model only when the target object does not exist in the space where the equipment is located, so that the damage to a human body and/or the damage to the equipment caused by the pre-operation of the equipment can be avoided, and the safety of the operation of the equipment is improved.

It should be understood that: in step S501, it can be determined whether a target object exists in the space where the device is located by using a camera or an infrared detection device.

Further, in order to avoid the damage to the equipment caused by the staff or other personnel using the equipment entering the space where the equipment is located when the equipment is pre-run, in some embodiments of the present invention, while the equipment is pre-run through the pre-run model, the method further includes:

generating second warning information to prompt staff and other personnel to prohibit entering the space where the equipment is located,

according to the embodiment of the invention, the second warning information is generated to prompt the staff and other personnel to forbid entering the room where the equipment is located, so that the situation that the personnel mistakenly enters the space where the equipment which is in the pre-operation process is located and damages to the body of the personnel can be avoided, and the safety of the equipment in the pre-operation process can be further improved.

It should be understood that: the second warning information may be an acoustic and/or optical warning information.

In some embodiments of the invention, the pre-run model comprises a pre-heat sub-model and/or a self-test sub-model; step S402 includes:

preheating the equipment through a preheating sub-model;

and/or the presence of a gas in the gas,

and carrying out self-inspection on the equipment through the self-inspection model.

Whether the equipment is preheated or self-checked or the equipment is preheated and self-checked at the same time can be determined according to the actual use requirement of the equipment, and detailed description is omitted here.

In an embodiment of the present invention, the preheating of the apparatus may be preheating of an electron gun and a magnetron of the medical accelerator to ensure that the medical accelerator can enter a normal beam-exiting state.

In an embodiment of the present invention, the self-checking of the device may be checking whether a normally-closed power connection point of the medical accelerator is in a normally-closed state, whether a power voltage of the medical accelerator satisfies a voltage threshold range, whether a temperature of a cooling medium of a constant temperature water cooling system inside the medical accelerator satisfies a temperature threshold range, and the like. The medical accelerator can be ensured to be normally used by carrying out self-checking on the equipment.

According to the embodiment of the invention, the equipment is preheated through the preheating sub-model, so that the equipment can be in a usable state before the equipment is in formal operation, the equipment is prevented from being preheated first when the equipment is in formal operation, and the use efficiency of the equipment is further improved.

The embodiment of the invention carries out self-checking on the equipment through the self-checking submodel, and can determine whether the equipment is in a normal working state or not and whether the equipment needs to be maintained or not through the self-checking result before the equipment is formally operated, thereby ensuring the use safety of the equipment.

In a specific embodiment of the present invention, the specific manner of determining whether the device is in a normal operating state and whether the device needs to be maintained according to the self-test result is as follows: the self-checking submodel can judge whether the equipment is in a normal working state or not according to the parameters of the equipment in the pre-operation process and whether the equipment needs to be maintained or not, and specifically comprises the following steps: when the operation parameters exceed the theoretical working parameter range when the equipment is in the normal working state, the equipment is in the abnormal state and needs to be maintained, otherwise, the equipment is not used.

Furthermore, after the equipment is formally operated and used, the equipment is usually required to be manually operated by a worker using the equipment to enter a sleep mode, the automation degree is low, and the condition that the equipment is forgotten to be adjusted to the sleep mode after the equipment is used is often caused, so that the technical problems of low service life of the equipment and increase of the use cost of the equipment are caused.

In order to solve the above technical problem, in some embodiments of the present invention, as shown in fig. 6, the method for automatically booting a device further includes:

s601, establishing a sleep condition model of the equipment through a machine learning algorithm based on historical use data, wherein the sleep condition model comprises sleep conditions of the equipment;

s602, judging whether the equipment meets a sleep condition;

s603, judging whether the equipment is in an idle state;

and S604, when the equipment meets the sleep condition and is in an idle state, controlling the equipment to enter the sleep state.

According to the embodiment of the invention, when the equipment meets the sleep condition and is in the idle state, the equipment is controlled to enter the sleep state, so that the automatic sleep of the equipment is realized, the use cost of the equipment is reduced, and the service life of the equipment is prolonged.

The specific process of establishing the sleep condition model of the device is the same as the specific process of establishing the start condition model of the device, and is not described herein again.

It should be understood that: the sleep condition in step S601 is a sleep time condition, that is: at which point the control device automatically sleeps.

It should be noted that: in order to avoid collision damage to people in the space where the device is located or damage to the device when the device enters the sleep state, in some embodiments of the present invention, before step S604, at least one component in the device may move:

if it is determined whether the target object exists in the space where the device is located, step S604 is: and when the equipment meets the dormancy condition, the equipment is in an idle state, and no target object exists in the space where the equipment is located, the equipment is controlled to enter the dormancy state.

By judging whether the target object exists in the space where the control equipment is positioned before the control equipment is in dormancy, the reliability and the safety of the equipment in automatic dormancy can be further improved.

It should also be noted that: in order to further reduce the use cost of the device and prolong the service life of the device, in some embodiments of the invention, the device is controlled to automatically shut down when the duration of the sleep state of the device exceeds a preset time.

It should be understood that: the preset time can be adjusted according to actual conditions, for example: 5 minutes, 10 minutes, etc., and is not particularly limited herein.

Likewise, the machine learning algorithm in step S601 may be capable of learning certain knowledge and capabilities from existing data (historical usage data) for processing new data, and may be designed to perform various tasks, in embodiments of the present invention, for determining whether a device is dormant.

In order to enable a designated person to obtain information of automatic power-on, self-test, automatic sleep and automatic power-off of the device in time, in some embodiments of the present invention, the method for automatic power-on of the device further includes:

when the equipment is started up according to the starting-up parameters, generating starting-up prompt information and sending the starting-up prompt information to appointed personnel;

after the equipment is operated in advance, generating pre-operation result information and sending the pre-operation result information to a formulation personnel;

when the equipment automatically sleeps, generating dormancy prompt information and sending the dormancy prompt information to a designated person;

when the equipment is automatically powered off, the power-off prompt information is generated and sent to the appointed personnel.

The embodiment of the invention can enable the appointed personnel to know the state of the equipment in real time by generating the information and sending the information to the appointed personnel, thereby being convenient for carrying out manual adjustment and control on the equipment and improving the redundancy of automatic startup, pre-operation, automatic dormancy and automatic shutdown of the equipment.

In the specific embodiment of the present invention, the power-on prompt message, the pre-operation result message, the hibernation prompt message, and the power-off prompt message may notify the designated person through a mobile phone message or a mail.

In order to better implement the automatic boot method of the device in the embodiment of the present invention, on the basis of the automatic boot method of the device, as shown in fig. 7, correspondingly, an embodiment of the present invention further provides an automatic boot apparatus 700 of the device, including:

a historical usage data acquisition unit 701 for acquiring historical usage data of the device;

a starting-up condition model establishing unit 702, configured to establish a starting-up condition model of the device through a machine learning algorithm based on historical usage data; the starting condition model comprises starting conditions and starting parameters of the equipment;

the auto-boot unit 703 is configured to control the device to boot up according to the boot parameters when the device meets the boot conditions.

The device auto-boot apparatus 600 provided in the foregoing embodiment may implement the technical solutions described in the foregoing embodiment of the device auto-boot method, and the specific implementation principles of the modules or units may refer to the corresponding contents in the foregoing embodiment of the device auto-boot method, which is not described herein again.

As shown in fig. 8, the present invention also provides an electronic device 800. The electronic device 800 includes a processor 801, a memory 802, and a display 803. Fig. 8 shows only some of the components of the electronic device 800, but it is to be understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead.

The memory 802 may be an internal storage unit of the electronic device 800 in some embodiments, such as a hard disk or memory of the electronic device 800. The memory 802 may also be an external storage device of the electronic device 800 in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc., provided on the electronic device 800.

Further, the memory 802 may also include both internal storage units and external storage devices of the electronic device 800. The memory 802 is used for storing application software and various data installed in the electronic device 800.

The processor 801 may be, in some embodiments, a Central Processing Unit (CPU), microprocessor or other data Processing chip for executing program codes stored in the memory 802 or Processing data, such as the device auto-on method of the present invention.

The display 803 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch panel, or the like in some embodiments. The display 803 is used to display information at the electronic device 800 as well as to display a visual user interface. The

components

801 and 803 of the electronic device 800 communicate with each other via a system bus.

In one embodiment, when the processor 801 executes the device auto-on program in the memory 802, the following steps may be implemented:

acquiring historical use data of equipment;

establishing a starting condition model of the equipment through a machine learning algorithm based on historical use data; the starting condition model comprises starting conditions and starting parameters of the equipment;

It should be understood that: in addition to the above functions, the processor 801 may also implement other functions when executing the device auto-boot program in the memory 802, which may be referred to in the foregoing description of the corresponding method embodiments.

Further, the type of the electronic device 800 is not particularly limited in the embodiment of the present invention, and the electronic device 800 may be a portable electronic device such as a mobile phone, a tablet computer, a Personal Digital Assistant (PDA), a wearable device, and a laptop computer (laptop). Exemplary embodiments of portable electronic devices include, but are not limited to, portable electronic devices that carry an IOS, android, microsoft, or other operating system. The portable electronic device may also be other portable electronic devices such as laptop computers (laptop) with touch sensitive surfaces (e.g., touch panels), etc. It should also be understood that in other embodiments of the present invention, the electronic device 800 may not be a portable electronic device, but may be a desktop computer having a touch-sensitive surface (e.g., a touch panel).

Accordingly, an embodiment of the present application further provides a computer-readable storage medium, where the computer-readable storage medium is used to store a computer-readable program or instruction, and when the program or instruction is executed by a processor, the steps in the method for automatically starting up a device or the functions in the apparatus for automatically starting up a device provided in the foregoing method embodiments can be implemented.

Those skilled in the art will appreciate that all or part of the flow of the method implementing the above embodiments may be implemented by instructing relevant hardware (such as a processor, a controller, etc.) by a computer program, and the computer program may be stored in a computer readable storage medium. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory.

The above method, apparatus, electronic device and storage medium for automatically booting the device provided by the present invention are described in detail, and a specific example is applied in the description to explain the principle and the implementation of the present invention, and the description of the above embodiment is only used to help understanding the method and the core idea of the present invention; meanwhile, for those skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims

1. An automatic boot method for a device, comprising:

acquiring historical use data of equipment;

2. The device auto-on method of claim 1, wherein the device comprises a plurality of components, the boot condition model comprises a plurality of boot condition sub-models in one-to-one correspondence with the plurality of components, the boot condition comprises a plurality of boot sub-conditions in one-to-one correspondence with the plurality of components, and the boot parameter comprises a plurality of boot sub-parameters in one-to-one correspondence with the plurality of components; when the equipment meets the starting-up condition, controlling the equipment to start up according to the starting-up parameters comprises the following steps:

3. The device auto-on method according to claim 1 or 2, wherein the boot condition includes an environmental condition and/or a time condition; when the equipment meets the starting-up condition, controlling the equipment to start up according to the starting-up parameters comprises the following steps:

Monitoring time information of the equipment in real time;

judging whether the time information meets the time condition or not;

4. The device auto-on method of claim 1, further comprising:

and pre-operating the equipment through the pre-operation model.

5. The auto-on method of claim 4, further comprising, prior to pre-running the device via the pre-run model:

6. The device auto-on method of claim 4, wherein the pre-run model comprises a pre-heat sub-model and/or a self-test sub-model; the pre-running of the equipment through the pre-running model comprises:

preheating the equipment through the preheating sub-model;

and/or the presence of a gas in the gas,

and self-checking the equipment through the self-checking sub-model.

7. The device auto-on method of claim 1, further comprising:

judging whether the equipment meets a dormancy condition;

judging whether the equipment is in an idle state or not;

8. An apparatus auto-on device, comprising:

9. An electronic device comprising a memory and a processor, wherein,

the memory is used for storing programs;

the processor, coupled to the memory, is configured to execute the program stored in the memory to implement the steps in the device auto-on method of any one of the preceding claims 1 to 7.

10. A computer-readable storage medium storing a computer-readable program or instructions, which when executed by a processor, is capable of implementing the steps in the method for automatically booting a device according to any one of claims 1 to 7.