CN108334974A

CN108334974A - Hazards monitoring method, apparatus, helmet and computer readable storage medium

Info

Publication number: CN108334974A
Application number: CN201711367818.7A
Authority: CN
Inventors: 吴疆
Original assignee: Shanghai Han Li Electronic Technology Co Ltd
Current assignee: Shanghai Han Li Electronic Technology Co Ltd
Priority date: 2017-12-18
Filing date: 2017-12-18
Publication date: 2018-07-27

Abstract

The embodiment of the present disclosure discloses hazards monitoring method, apparatus, helmet and computer readable storage medium.The method is run on helmet, including：It obtains degree of danger and analyzes parameter；The degree of danger analysis parameter includes the human life characteristic of the environmental parameter and the user for dressing the helmet of the helmet region；Existence threat assessment is carried out to degree of danger analysis parameter, an existence threat index is calculated；The existence threat index is used to indicate the user under the present circumstances by actual bodily harm or lethal possibility；Include on the permeability display unit on the helmet by the existence threat index.In this way, the risk data that can be faced in real time according to the variation of environment and the determining fire fighter of the variation of fire fighter's own bodies situation, and then include on the permeability display unit of wearable device by risk data.

Description

Danger monitoring method and device, head-mounted equipment and computer readable storage medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a risk monitoring method and apparatus, a head-mounted device, and a computer-readable storage medium.

Background

In the prior art, fire fighting equipment can provide basic precaution requirements for firefighters from the aspects of materials, oxygen supply and the like, but is limited to a passive method. The present fire fighting equipment can not evaluate the on-site danger from an autonomous angle, timely perform withdrawing work favorable for firemen, and can not allow a rear command system to timely perform safety precaution measures.

Disclosure of Invention

The embodiment of the disclosure provides a danger monitoring method and device, a head-mounted device and a computer-readable storage medium.

In a first aspect, a method for risk monitoring is provided in an embodiment of the present disclosure.

Specifically, the danger monitoring method is executed on a head-mounted device, and includes:

acquiring a risk degree analysis parameter; the risk degree analysis parameters comprise environmental parameters of an area where the head-mounted equipment is located and human body vital sign data of a user wearing the head-mounted equipment;

carrying out survival threat assessment on the risk degree analysis parameters, and calculating to obtain a survival threat index; the survival threat index is used for indicating the possibility that the user is physically injured or killed under the current environment;

displaying the survival threat index on a transparent display unit on the head-mounted device.

Optionally, performing survival threat assessment on the risk degree analysis parameter, and calculating to obtain a survival threat index, including:

inputting the risk degree analysis parameters into a predefined fitting function to obtain a survival threat index; the predefined fitting function is obtained in advance according to historical risk degree analysis parameters and casualty rate of the user under the historical risk degree analysis parameters in a fitting mode.

inputting the risk degree analysis parameters into a threat index identification model to obtain a survival threat index; the threat index recognition model is obtained by training a machine learning model by utilizing a training sample in advance.

and respectively calculating different risk degree analysis parameters by adopting respective corresponding calculation rules to obtain different kinds of survival threat indexes.

Optionally, the heterogeneous survival threat indices include at least one of:

a temperature threat index, a harmful gas threat index, and an explosion threat index.

Optionally, the risk degree analysis parameter further includes navigation data corresponding to the current position of the head-mounted device; wherein, carry out survival threat assessment to the degree of danger analysis parameter, calculate and obtain a survival threat index, still include:

determining a route for a user wearing the head-mounted device to escape from a current location and environmental parameters related to the route according to the navigation data;

and determining an escape route threat index according to the route and the environment parameters related to the route.

Optionally, performing survival threat assessment on the risk degree analysis parameter, and calculating to obtain a survival threat index, further comprising:

determining different escape route threat indexes corresponding to one or more routes;

displaying the survival threat index on a transparent display unit on the head-mounted device, comprising:

correspondingly presenting one or more routes and escape route threat indexes on the permeability display unit; or,

the route determined according to the escape route threat index and the position information of the head-mounted device is presented on the transparent display unit.

determining an oxygen survival threat index according to the oxygen surplus; or,

determining a comprehensive survival threat index according to the oxygen margin and at least one other parameter in the risk degree analysis parameters;

the oxygen allowance is obtained through an oxygen breathing system on the head-mounted equipment.

Optionally, the method further comprises:

predicting a survival threat index within a future preset time range according to the risk degree analysis parameters;

and displaying the predicted survival threat index on the permeability display unit.

Optionally, the method further comprises:

generating an early warning signal in response to a triggering event in which the survival threat index exceeds a predetermined threshold;

transmitting the identification of the head-mounted device, the current location, the survival threat index, and the risk level analysis parameters to a control center and/or other head-mounted devices within a predetermined range.

Optionally, the method further comprises:

executing a preset process of a life sustaining system in response to a triggering event that the survival threat index exceeds a predetermined threshold; the preset processing includes at least one of: starting a cooling module, accelerating oxygen supply, starting a lighting system and starting a navigation system.

Optionally, the method further comprises:

and responding to a triggering event that the survival threat index exceeds a preset threshold value, determining a threat factor corresponding to the survival threat index, and presenting the survival threat index and the threat factor on the permeability display unit.

Optionally, the method further comprises:

acquiring an environment image;

determining a survival threat index of an object in the environment according to the environment image;

and when an object is displayed on the permeability display unit, the survival threat index of the object is displayed on the object in a superposition manner according to the orientation information of the head-mounted equipment.

Optionally, the method further comprises:

monitoring the running condition of a preset module arranged on the head-mounted equipment;

and sending out an early warning signal when the running condition of the preset module is abnormal.

Optionally, obtaining a risk level analysis parameter includes:

and acquiring the analysis parameters of the risk degree detected by other preset head-mounted equipment through a data network.

In a second aspect, an embodiment of the present disclosure further discloses a danger monitoring device, where the device is disposed on a head-mounted device, and includes:

a first obtaining module configured to obtain a risk degree analysis parameter; the risk degree analysis parameters comprise environmental parameters of an area where the head-mounted equipment is located and human body vital sign data of a user wearing the head-mounted equipment;

the calculation module is configured to perform survival threat assessment on the risk degree analysis parameter and calculate to obtain a survival threat index; the survival threat index is used for indicating the possibility that the user is physically injured or killed under the current environment;

a first display module configured to display the survival threat index on a transparent display unit on the head-mounted device.

Optionally, the calculation module includes:

a fitting submodule configured to input the risk degree analysis parameter to a predefined fitting function, resulting in a survival threat index; the predefined fitting function is obtained in advance according to historical risk degree analysis parameters and casualty rate of the user under the historical risk degree analysis parameters in a fitting mode.

Optionally, the calculation module includes:

the identification submodule is configured to input the risk degree analysis parameters into a threat index identification model to obtain a survival threat index; the threat index recognition model is obtained by training a machine learning model by utilizing a training sample in advance.

Optionally, the calculation module includes:

and the calculation submodule is configured to calculate different kinds of survival threat indexes by respectively adopting the different risk degree analysis parameters and the respective corresponding calculation rules.

Optionally, the survival threat index comprises at least one of:

Optionally, the risk degree analysis parameter further includes navigation data corresponding to the current position of the head-mounted device; wherein the computing module further comprises:

a first determination sub-module configured to determine a route for a user wearing the head-mounted device to escape from a current location and the route-related environmental parameter from the navigation data;

a second determination submodule configured to determine an escape route threat index based on the route and the route-related environmental parameter.

Optionally, the computing module further comprises:

a third determining submodule configured to determine different escape route threat indexes corresponding to one or more of the routes;

the first display module includes:

a first display sub-module configured to present one or more of the routes and escape route threat indices in correspondence to the permeability display unit; or

A second display sub-module configured to present the route determined according to the escape route threat index and the position information of the head-mounted device on the transparent display unit.

Optionally, the computing module further includes:

a fourth determination submodule configured to determine an oxygen survival threat index based on the oxygen margin; or

A fifth determining submodule configured to determine a composite survival threat index based on the oxygen margin and at least one other of the risk level analysis parameters; the oxygen allowance is obtained through an oxygen breathing system on the head-mounted equipment.

Optionally, the method further comprises:

a prediction module configured to predict a survival threat index within a predetermined time range in the future from the risk level analysis parameter;

a second display module configured to and display the predicted survival threat index on the permeability display unit.

Optionally, the apparatus further comprises:

a first response module configured to generate an early warning signal in response to a triggering event in which the survival threat index exceeds a predetermined threshold;

a transmitting module configured to transmit the identification of the head-mounted device, the current location, the survival threat index, and the risk level analysis parameter to a control center and/or other head-mounted devices within a predetermined range.

Optionally, the apparatus further comprises:

a second response module configured to perform a preset process of a life support system in response to a triggering event that the life threat index exceeds a predetermined threshold; the preset processing includes at least one of: starting a cooling module, accelerating oxygen supply, starting a lighting system and starting a navigation system.

Optionally, the apparatus further comprises:

a third response module configured to determine a threat factor corresponding to the survival threat index and present the survival threat index and the threat factor on the transparency display unit in response to a trigger event that the survival threat index exceeds a predetermined threshold.

Optionally, the apparatus further comprises:

a second acquisition module configured to acquire an environmental image;

a determining module configured to determine a life threat index of an object in an environment from the environment image;

a third display module configured to display the life threat index of the object superimposed on the object according to the orientation information of the head-mounted device when the object is displayed on the transmissive display unit.

Optionally, the apparatus further comprises:

the monitoring module is configured to monitor the running condition of a preset module arranged on the head-mounted equipment;

and the early warning module is configured to send out an early warning signal when the running condition of the preset module is abnormal.

Optionally, the first obtaining module includes:

and the second acquisition submodule is configured to acquire the analysis parameters of the risk degree detected by other preset head-mounted equipment through a data network.

The functions can be realized by hardware, and the functions can also be realized by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the above-described functions.

In one possible design, the risk monitoring device includes a memory and a processor, the memory is used for storing one or more computer instructions for supporting the risk monitoring device to execute the risk monitoring method in the first aspect, and the processor is configured to execute the computer instructions stored in the memory. The hazard monitoring apparatus may further comprise a communication interface for the hazard monitoring apparatus to communicate with other devices or a communication network.

In a third aspect, embodiments of the present disclosure provide a head-mounted device, including a transmissive display unit, a memory, and a processor; wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method steps of the first aspect.

In a fourth aspect, the disclosed embodiments provide a computer-readable storage medium for storing computer instructions for a hazard monitoring apparatus, which contains computer instructions for performing the hazard monitoring method of the first aspect.

The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:

the disclosed embodiment obtains the risk degree analysis parameters including environmental parameters and human vital sign data through a user such as a head-mounted device worn by a firefighter, and performs survival threat assessment on the obtained risk degree analysis parameters to determine the current survival threat index of the firefighter wearing the head-mounted device, and displays the survival threat index on a permeability display unit on the head-mounted device. Through this kind of mode, can confirm the existence threat index that the fire fighter faced according to the change of environment and fire fighter self health in real time, and then show the existence threat index on wearing equipment's permeability display element, make under the condition that does not influence fire fighter's naked eye and look over things around, show dangerous data for the fire fighter, can in time remind the fire fighter, make the fire fighter master the best opportunity of withdrawing, can improve fire fighter's safety guarantee dynamics greatly.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

Other features, objects, and advantages of the present disclosure will become more apparent from the following detailed description of non-limiting embodiments when taken in conjunction with the accompanying drawings. In the drawings:

FIG. 1 shows a flow diagram of a hazard monitoring method according to an embodiment of the present disclosure;

FIG. 2 shows a flow chart of step S102 according to the embodiment shown in FIG. 1;

FIG. 3 illustrates a flow diagram for predicting a survival threat index, according to an embodiment of the present disclosure;

FIG. 4 illustrates a flow diagram for generating early warning information according to an embodiment of the present disclosure;

FIG. 5 illustrates a flow diagram for determining a survival threat index from an environmental image, according to an embodiment of the present disclosure;

FIG. 6 illustrates a flow diagram of monitoring a preset module according to an embodiment of the present disclosure;

FIG. 7 illustrates a block diagram of a hazard monitoring device according to an embodiment of the present disclosure;

fig. 8 is a schematic structural diagram of an electronic device suitable for implementing a hazard monitoring method according to an embodiment of the present disclosure.

Detailed Description

Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Also, for the sake of clarity, parts not relevant to the description of the exemplary embodiments are omitted in the drawings.

In the present disclosure, it is to be understood that terms such as "including" or "having," etc., are intended to indicate the presence of the disclosed features, numbers, steps, behaviors, components, parts, or combinations thereof, and are not intended to preclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or combinations thereof may be present or added.

It should be further noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

Fig. 1 shows a flow diagram of a hazard monitoring method according to an embodiment of the present disclosure. As shown in fig. 1, the risk monitoring method is run on a head-mounted device, and the risk monitoring method includes the following steps S101 to S103:

in step S101, a risk degree analysis parameter is acquired; the risk degree analysis parameters comprise environmental parameters of an area where the head-mounted equipment is located and human body vital sign data of a user wearing the head-mounted equipment;

in step S102, performing survival threat assessment on the risk degree analysis parameter, and calculating to obtain a survival threat index; the survival threat index is used for indicating the possibility that the user is physically injured or killed under the current environment;

in step S103, the survival threat index is displayed on a transparency display unit on the head-mounted device.

In this embodiment, the head-mounted device may be an intelligent device capable of being worn on the head of a human body, and a processor, a memory, a display device, and other components may be disposed inside the head-mounted device. The display device can be a transparent display unit, and after the head-mounted equipment is worn on the head of a human body, the transparent display unit can be just positioned at the visible part of eyes, so that when data is displayed on the transparent display unit, the data on the transparent display unit can be viewed without manually moving the position of the head-mounted equipment and the like; meanwhile, the natural reflected light of the environmental object can normally pass through the permeable display unit, so that the user can check the surrounding environment and things through the permeable display unit without influencing the sight of the wearer. The transmissive display unit may also allow external optical fibers to pass through to convey the displayed image into the eye of the wearer simultaneously with the background light source, enabling modification and enhancement of the background image.

In this embodiment, the risk level analysis parameters include environmental parameters and human vital sign data. The environmental parameters may be various parameters of the environment surrounding the user wearing the head-mounted device, including temperature, humidity, oxygen rarefaction, brightness, concentration of harmful gases (such as carbon monoxide, methane, coal gas, and other chemically explosive gases), and the like; the environmental parameters can be detected by an environmental parameter detection module arranged on the head-mounted device or peripheral equipment in the area where the user wearing the head-mounted device is located. The human vital sign data may be parameters of a user wearing the head-mounted device that characterize his vital signs, including heart rate, pulse, body temperature, respiratory rate, sweat level, body posture (e.g., standing, lying, etc.); the human vital sign data can also be monitored by a sensor module arranged on the head-mounted device or a sensing device arranged on the body of a user wearing the head-mounted device.

In this embodiment, the risk degree analysis parameter is obtained from the peripheral device through the communication network, or obtained from a module provided on the head-mounted device, and the survival threat index currently facing the user wearing the head-mounted device is determined by analyzing the risk degree analysis parameter. A survival threat index. The survival threat index can be displayed on the permeability display unit of the head-mounted device, so that the user can observe the surrounding environment while looking at the danger degree data in real time, and the user is not hindered from implementing rescue work.

When the embodiment of the disclosure is applied to the field of fire fighting, the fatal problems that the life of a fireman is threatened or even sacrificed in the life saving process because the fireman cannot realize the danger degree of the surrounding environment in the process of rescuing property and the victim in a disaster-stricken site can be solved.

In the embodiment of the disclosure, a survival threat index is calculated by performing survival threat assessment on the risk degree analysis parameter. The survival threat index may be used to indicate the likelihood of physical injury or death that the user may be subjected to in the current environment, i.e., it may be determined whether the user's body is injured and how much injury the user is injured, etc. by the survival threat index, or it may also be determined how likely the user is fatal. And evaluating the risk degree analysis parameters by a threat evaluation method, and further obtaining the injury possibly suffered by the body of the user under the current environment and/or the degree of threat of the injury degree to the life of the user, namely the possibility of death. This optional mode is through obtaining the life threatening index that can characterize user's present life receives threatened degree, and the safety of the user who wears the head-mounted device is ensured to take certain measure when life threatening index indicates that user's life may face certain threat, guarantee user's life's safety.

In an optional implementation manner of this embodiment, the survival threat assessment is performed on the risk degree analysis parameter, and a survival threat index is calculated, which further includes the following steps:

In this alternative implementation, the threat assessment method may employ a predefined fitting function that is capable of calculating a survival threat index. And after the risk degree analysis parameters are obtained, inputting the risk degree analysis parameters into a predefined fitting function, and obtaining a survival threat index by the predefined fitting function through the risk degree analysis parameters. In the optional implementation mode, the predefined fitting function is obtained by fitting according to the historical risk degree analysis parameter and the casualty rate of the user under the parameter, so that the calculation formula is based on the value of the risk degree analysis parameter, and the casualty rate of the user under the risk degree analysis parameter can be accurately calculated. The survival threat index may be used to indicate a presumption of the likelihood that the user is physically harmed or killed in the current environment; the survival threat index may be a specific survival threat index based on one or more of the risk level analysis parameters, such as a threat index based on the temperature of the current environment; the survival threat index may also be a composite survival threat index based on a plurality of risk level analysis parameters, such as an explosion threat index based on the concentration of carbon monoxide in the environment and the temperature in the environment. The historical risk analysis parameters and the casualty rate may be derived from real experience or from a simulated field environment. By the embodiment, the survival threat index can be quickly obtained based on the predefined fitting function, and powerful early warning information is provided for the user.

In this embodiment, a threat index recognition model is trained in advance, after the risk degree analysis parameters are obtained, the risk degree analysis parameters are input into the threat index recognition model, and the threat index recognition model evaluates the risk degree analysis parameters to obtain a survival threat index. The threat index identification model may also classify the degree of risk into different grades, such as multiple grades of "fatal", "heavy injury", "mild injury", "safe", and the like, based on the survival threat index. The threat index recognition model can be obtained by training a machine learning model by utilizing a training sample in advance. The training samples can be danger degree analysis parameters obtained on the basis of a historical disaster site, when the threat index recognition model is trained, the danger degree analysis parameters obtained on the historical disaster site can be used as input, the danger degree corresponding to the casualty rate under the historical disaster site is used as output, and the parameters of the threat index recognition model are finally obtained through multiple times of training and optimization. In the evaluation stage, a final evaluation result can be obtained based on the trained model parameters of the threat index recognition model and the risk degree analysis parameters. By the method, the danger degree under the current danger degree analysis parameter can be predicted more accurately by using the machine learning algorithm, and timely and accurate early warning information is provided for the user.

In an optional implementation manner of this embodiment, the performing survival threat assessment on the risk degree analysis parameter and calculating to obtain a survival threat index includes:

In this optional implementation manner, respective corresponding calculation rules may be formulated for different types of risk degree analysis parameters, and different types of survival threat indexes may be calculated according to different types of risk degree analysis parameters and corresponding calculation rules. According to actual conditions, an independent calculation rule can be formulated for an independent risk degree analysis parameter, a survival threat index corresponding to the risk degree analysis parameter is obtained through calculation, and different risk analysis degree parameters can also correspond to the same calculation rule; of course, one calculation rule may also be used to calculate two or more risk degree analysis parameters at the same time to obtain the corresponding survival threat index. In one embodiment, the survival threat index includes at least one of: a temperature threat index, a harmful gas threat index, and an explosion threat index. The temperature threat index can be obtained based on the tolerance temperature of the human body and the current environment temperature, and if the current environment temperature exceeds the tolerance temperature of the human body, the temperature threat index exceeds a normal threshold value, which indicates that the danger degree is higher, and prompts a user to evacuate in time; the harmful gas threat index can be determined based on the concentration of harmful gases in the current environment and the tolerance degree of a human body to the harmful gases, wherein the harmful gases comprise but are not limited to carbon monoxide, methane, coal gas, other chemical explosive gases and the like; when the concentration of the harmful gas is higher than a certain value, the human body may be poisoned or explode; the explosion threat index may be determined based on whether an explosive object is ignited or the explosive gas concentration in the current environment, etc. Through the optional implementation mode, independent analysis or comprehensive analysis can be carried out on different risk degree analysis parameters in a targeted manner, a more accurate survival threat index is finally obtained, and the degree of security guarantee of the user can be increased.

In an optional implementation manner of this embodiment, the risk level analysis parameter further includes navigation data corresponding to a current location of the head-mounted device; as shown in fig. 2, the step S102 of evaluating the survival threat of the risk level analysis parameter and calculating a survival threat index further includes the following steps:

in step S201, determining a route for a user wearing the head-mounted device to escape from a current location and an environmental parameter related to the route according to the navigation data;

in step S202, an escape route threat index is determined based on the route and the route-related environmental parameters.

In this optional implementation manner, the head-mounted device may further obtain navigation information, and determine an escape route and an escape difficulty based on the obtained navigation information, map data of an environment where a user wearing the head-mounted device is located, and the like. The navigation information may be information of channels, exits, etc. around the area where the user is located. The environmental parameters related to the escape route include, for example, temperature, fire, smoke level, whether there is danger around the escape route, distance between routes, difficulty in walking, etc., the temperature on different escape routes can be obtained by thermal imaging, thermal radiation, etc., and the fire, smoke level, whether there is danger around the escape route, distance between routes, difficulty in walking, etc. can be determined by means of visual sensors, image analysis, etc. When the escape route threat index is determined, different escape route threat indexes can be generated based on different escape routes and related environmental parameters, or the optimal escape route is selected from the different escape routes to determine the escape route threat index. For example, the escape route is very long and there are obstacles (such as doors, stairs, etc.) along the way, such escape route is not smooth, but because there are no fire or other dangerous objects along the way, the threat index on the escape route is rather lower compared to the escape route with short distance but dangerous objects. The escape route threat index can be obtained according to a predefined fitting function or a pre-trained threat identification model, and can be specifically set according to the actual situation, without limitation. Through the optional implementation mode, the escape route and the corresponding escape route threat index can be provided for the user in real time, so that the user can conveniently escape.

In an optional implementation manner of this embodiment, the step S102 is a step of performing survival threat assessment on the risk degree analysis parameter, and calculating to obtain a survival threat index, and further includes the following steps:

step S103 of displaying the threat survival index on a transparent display unit on the head-mounted device, further comprising the steps of:

correspondingly presenting one or more routes and escape route threat indexes on the permeability display unit; or

In this optional implementation, multiple escape routes and corresponding environmental parameters may be generated based on the navigation information, the map information, and the like, and different escape route threat indices may be determined based on different escape routes. Displaying the determined escape route threat index and the corresponding escape route on a transparent display unit of the head-mounted equipment so that a user can select a proper route for escape; or the optimal route is determined based on the current position information of the head-mounted device and then presented on the permeability unit. The direction information comprises the current position, the current angle and the like of the head-mounted device, so that the user can escape at the fastest speed, the current direction of the user can be determined based on the position and the angle of the head-mounted device, an optimal escape route is determined for the user based on the direction of the user, and the optimal escape route is displayed on the transparent display unit, so that the user can be guided to escape along the escape route conveniently. Meanwhile, the escape route threat index corresponding to the optimal escape route can be displayed on the transparent display unit so as to prompt the danger degree of the escape of the user. Through the alternative implementation mode, all escape routes and corresponding threat indexes can be provided for the user, or the optimal escape route is provided to guide the user to escape as soon as possible.

In an optional implementation manner of this embodiment, the step S102, namely, performing survival threat assessment on the risk degree analysis parameter, and calculating to obtain a survival threat index, further includes the following steps:

determining an oxygen survival threat index according to the oxygen surplus; or

Determining a comprehensive survival threat index according to the oxygen margin and at least one other parameter in the risk degree analysis parameters; the oxygen allowance is obtained through an oxygen breathing system on the head-mounted equipment.

In this alternative implementation, the oxygen breathing system may be provided on the head-mounted device, or the head-mounted device may be able to communicate with the separate oxygen breathing system via the communication interface. The oxygen breathing system provides oxygen for a user wearing the head-mounted device, and the head-mounted device obtains oxygen surplus from the oxygen breathing system and determines an oxygen survival threat index according to the oxygen surplus. If harmful gas exists in the current environment or normal breathing cannot be performed due to other reasons such as thin oxygen and the like, and if the margin of an oxygen breathing system is low, the oxygen survival threat index can be set to be high so as to remind a user that the oxygen is insufficient and the user needs to escape as soon as possible; and if the oxygen margin is high or the oxygen breathing system is not needed to supply oxygen under the current environment, the oxygen survival threat index can be set to be low. In another embodiment, the oxygen balance may also be combined with one or more other of the risk level analysis parameters to generate a composite survival threat index. With this alternative implementation, a threat index is generated for the user by monitoring the oxygen balance in the oxygen breathing system to alert the user of the degree of risk currently being faced.

In an optional implementation manner of this embodiment, as shown in fig. 3, the method further includes the following steps:

in step S301, predicting a survival threat index within a future predetermined time range according to the risk degree analysis parameter;

in step S302, the predicted survival threat index is displayed on the permeability display unit.

In this alternative implementation, a survival threat index may be predicted over a future period of time based on historical data and current risk level analysis parameters. The specific prediction process can be carried out by matching the risk degree analysis parameters under the historical disaster and the time of the future period of time under the matched historical risk degree analysis parameters, and can also be predicted by a pre-trained prediction model. The prediction model can be obtained by training a machine learning model through simulated training samples or data under real historical disaster conditions and is used for predicting the survival threat index within a future time range. With this alternative implementation, the survival threat index at the next time may be predicted based on the current risk level analysis parameters to enable pre-action to be taken before the risk comes.

In an optional implementation manner of this embodiment, as shown in fig. 4, the method further includes:

in step S401, in response to a triggering event that the survival threat index exceeds a predetermined threshold, generating an early warning signal;

in step S402, the identification of the head-mounted device, the current location, the survival threat index and the risk level analysis parameter are transmitted to a control center and/or other head-mounted devices within a predetermined range.

In this alternative implementation, the survival threat index may be derived based on different risk level analysis parameters, and one or more risk level analysis parameters may correspond to one survival threat index. When a certain survival threat index exceeds a preset threshold value, an early warning signal can be generated to remind a user of possible threats; meanwhile, the identification, the position, the survival threat index and the corresponding danger degree analysis parameters of the current head-mounted equipment can be transmitted to the control center and/or other head-mounted equipment within a preset range. The control center can take emergency measures according to the received information to help a user wearing the current head-mounted equipment, or other head-mounted equipment can analyze according to the self condition after obtaining the information, and take measures to help the user wearing the current head-mounted equipment, or take self-rescue measures and the like under the condition that the safety of the user is possibly threatened. Through the optional implementation mode, the early warning information can be sent out for the user wearing the current head-mounted equipment in an emergency, and the user of a control center or other head-mounted equipment can be prompted to take corresponding measures, so that the safety of the user is further guaranteed.

In an optional implementation manner of this embodiment, the method further includes:

In this alternative implementation, when the survival threat index exceeds the predetermined threshold, some preprocessing may also be performed, such as starting some emergency equipment preset on the head-mounted device, or controlling some emergency equipment set in the current environment through network communication, etc. For example, turn on the cooling module, speed up the oxygen supply, turn on the lighting system, turn on the navigation system. The cooling module, the oxygen supply system lighting system, the navigation system and the like can be arranged on the head-mounted equipment or can be arranged under the current environment, and the head-mounted equipment can send control signals to the equipment through network communication. Through the optional implementation mode, emergency measures can be taken as soon as possible when danger occurs, so that the escape of a user is facilitated.

In this optional implementation manner, when the survival threat index exceeds the predetermined threshold, in the case that the survival threat index is determined by the multiple risk degree analysis parameters, firstly, which factor specifically presents a risk can be determined by means of analysis and the like, and after the threat factors are determined, the survival threat index and the threat factors whose index exceeds the predetermined threshold can be presented on the transparent display unit, so that the user can know the current risk factors, and guide the user to remove the risk or take escape measures as soon as possible.

In an optional implementation manner of this embodiment, as shown in fig. 5, the method further includes:

in step S501, an environment image is acquired;

in step S502, determining a survival threat index of an object in the environment according to the environment image;

in step S503, when an object is displayed on the transmissive display unit, the life threat index of the object is displayed on the object in a superimposed manner according to the orientation information of the head-mounted device.

In this optional implementation manner, an image acquisition module may be disposed on the head-mounted device, and acquire an image in the current environment in real time or under a preset trigger condition, and determine the survival threat index of the object in the current environment by analyzing and recognizing the environment image. The life threat index of an object may be an index of threat of the object to a user, e.g., a burning electronic product may explode, and thus the life threat index of the electronic product is high. When the object in the current environment is displayed to the user through the permeability unit, the survival threat index of the object can be displayed on the object in a superposed manner, and the survival threat index can be in the form of different numbers, different colors, different shapes or the combination of the numbers, the colors, the shapes and the like. For example, the life threat index of an object with a higher life threat index is displayed in red. The permeability display unit can enable objects in the surrounding environment to reflect and pass through, and meanwhile, images can be displayed on the permeability display unit, so that when the survival threat indexes are displayed on the corresponding objects in a superposed mode, the objects in the surrounding environment can be recognized through a target recognition method, and then the survival threat indexes corresponding to the objects are displayed at the positions of the recognized objects. The target identification can adopt a model identification method which is commonly used at present, the surrounding environment image is collected and input into a pre-trained target identification model, the target identification model further outputs the type and the position of a target object in the current environment, the target object can be tracked in real time, and meanwhile, the survival threat index which is displayed in a superposition mode is updated in real time based on the position change of the target object, so that the survival threat index changes along with the position change of the target object, and the target object seen by a user and the survival threat index synchronously move in a visual field. According to the selectable implementation mode, the survival threat index of the object is displayed on the object in a superposition mode while the object in the current environment is presented for the user, so that the danger degree of the user to the object can be clear at a glance, and the reaction capability of the user is accelerated.

In an optional implementation manner of this embodiment, as shown in fig. 6, the method further includes:

in step S601, monitoring an operating condition of a preset module provided on the head-mounted device;

in step S602, when the operating condition of the preset module is abnormal, an early warning signal is sent.

In this optional implementation manner, the head-mounted device may further monitor an operation condition of a preset module provided on the head-mounted device in real time, for example, a device for detecting an environmental parameter, a sensor for detecting vital sign data of a human body, a communication module, and the like. The survival threat index corresponding to different preset modules can be generated based on the operation conditions of the preset modules so as to indicate the possibility that the operation state of the preset modules is harmful or lethal to the body of the user. For example, when the communication module is abnormal and cannot communicate with the background control center, the life of the user is threatened because the user may not receive the warning information or the self-rescue information sent by the background control center, and the corresponding survival threat index is higher. When the preset module is abnormal, the early warning signal can be sent out to remind a user to take measures in time, and the condition that the user faces danger due to the failure of the preset module is avoided. The early warning signal can be an early warning image displayed on a head-mounted device permeability display unit, an early warning sound sent out, or flashing light of a warning lamp displayed on the head-mounted device. The early warning information may provide alerts for the user wearing the head-mounted device and other users around. The head-mounted equipment can be further provided with a key system for stopping monitoring, and when a user withdraws to a safe area, the monitoring can be closed through the key system, so that the head-mounted equipment can not monitor the analysis parameters of the danger degree any more and can not send out early warning information any more.

In an optional implementation manner of this embodiment, step S101, namely the step of obtaining the risk level analysis parameter, further includes the following steps:

In this optional implementation, the head-mounted device may further obtain, through the data network, for example, through a communication network such as a SIM card or bluetooth, a risk level analysis parameter detected by other surrounding head-mounted devices, so as to analyze a surrounding situation according to the risk level analysis parameter detected by other surrounding head-mounted devices, and further determine an influence of the surrounding situation on the head-mounted device, and determine a survival threat index. Through the optional implementation mode, the head-mounted device can also determine the survival threat index based on the ambient environment parameters, the human body life specific data and the like detected by other head-mounted devices, and the accuracy of the result is further improved.

The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods.

Fig. 7 shows a block diagram of a hazard monitoring apparatus according to an embodiment of the present disclosure, which may be implemented as part or all of an electronic device by software, hardware, or a combination of both. As shown in fig. 7, the danger monitoring apparatus includes a first obtaining module 701, a calculating module 702, and a first displaying module 703:

a first obtaining module 701 configured to obtain a risk degree analysis parameter; the risk degree analysis parameters comprise environmental parameters and human body vital sign data;

a calculating module 702 configured to perform survival threat assessment on the risk degree analysis parameter, and calculate a survival threat index; the survival threat index is used for indicating the possibility that the user is physically injured or killed under the current environment;

a first display module 703 configured to display the survival threat index on a transparent display unit on the head-mounted device.

In an optional implementation manner of this embodiment, the calculation module includes:

In an optional implementation manner of this embodiment, the risk level analysis parameter further includes navigation data corresponding to a current location of the head-mounted device; and the calculation module 702 further comprises:

In an optional implementation manner of this embodiment, the calculating module 702 further includes:

the first display module 703 includes:

In an optional implementation manner of this embodiment, the calculating module 702 includes:

In an optional implementation manner of this embodiment, the apparatus further includes the following steps:

In an optional implementation manner of this embodiment, the apparatus further includes:

a second acquisition module configured to acquire an environmental image;

In an optional implementation manner of this embodiment, the first obtaining module 701 includes:

The danger monitoring device in this embodiment corresponds to the danger monitoring method, and specific details can be referred to the description of the danger monitoring method, which is not described herein again.

FIG. 8 is a schematic diagram of a headset suitable for use in implementing a hazard monitoring method according to an embodiment of the present disclosure.

As shown in fig. 8, the head-mounted device 800 includes a Central Processing Unit (CPU)801 that can execute various processes in the embodiment shown in fig. 1 described above according to a program stored in a Read Only Memory (ROM)802 or a program loaded from a storage section 808 into a Random Access Memory (RAM) 803. In the RAM803, various programs and data necessary for the operation of the head-mounted device 800 are also stored. The CPU801, ROM802, and RAM803 are connected to each other via a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.

The following components are connected to the I/O interface 805: an input portion 806 including a keyboard, a mouse, and the like; an output portion 807 including a display device such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), a transmissive display unit, and the like, and a speaker; a storage portion 808 including a hard disk and the like; and a communication section 809 including a network interface card such as a LAN card, a modem, or the like. The communication section 809 performs communication processing via a network such as the internet. A drive 810 is also connected to the I/O interface 805 as necessary. A removable medium 811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 810 as necessary, so that a computer program read out therefrom is mounted on the storage section 808 as necessary.

In particular, according to embodiments of the present disclosure, the method described above with reference to fig. 1 may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a medium readable thereby, the computer program comprising program code for performing the hazard monitoring method of FIG. 1. In such an embodiment, the computer program may be downloaded and installed from a network via the communication section 809 and/or installed from the removable medium 811.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, a program segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units or modules described in the embodiments of the present disclosure may be implemented by software or hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.

As another aspect, the present disclosure also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus in the above-described embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the present disclosure.

The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is possible without departing from the inventive concept. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.

Claims

1. A method of hazard monitoring, the method operating on a head-mounted device, comprising:

2. The risk monitoring method of claim 1, wherein the assessing a survival threat against the risk level analysis parameter and calculating a survival threat index comprises:

3. The risk monitoring method of claim 1, wherein the assessing a survival threat against the risk level analysis parameter and calculating a survival threat index comprises:

4. The risk monitoring method of claim 1, wherein the assessing a survival threat against the risk level analysis parameter and calculating a survival threat index comprises:

5. The hazard monitoring method of claim 4, wherein said heterogeneous survival threat indices comprise at least one of:

6. The risk monitoring method according to any one of claims 1-5, wherein the risk level analysis parameters further include navigation data corresponding to a current location of the head-mounted device; wherein, carry out survival threat assessment to the degree of danger analysis parameter, calculate and obtain a survival threat index, still include:

7. The risk monitoring method of claim 6, wherein the risk level analysis parameter is evaluated for survival threat and a survival threat index is calculated, further comprising:

8. The risk monitoring method of claim 1, wherein the risk level analysis parameter is evaluated for survival threat and a survival threat index is calculated, further comprising:

9. The hazard monitoring method of claim 1, the method further comprising:

10. The hazard monitoring method of claim 1, the method further comprising:

11. The hazard monitoring method of claim 1, the method further comprising:

12. The hazard monitoring method of claim 1, the method further comprising:

13. The hazard monitoring method of claim 1, the method further comprising:

acquiring an environment image;

14. The hazard monitoring method of claim 1, the method further comprising:

15. The risk monitoring method of claim 1, wherein obtaining risk level analysis parameters comprises:

16. A hazard monitoring apparatus, the apparatus being disposed on a head-mounted device, comprising:

17. The hazard monitoring device of claim 16, said computing module comprising:

18. The hazard monitoring device of claim 16, said computing module comprising:

19. The hazard monitoring device of claim 16, said computing module comprising:

20. The hazard monitoring device of claim 19, wherein the survival threat index comprises at least one of:

21. The hazard monitoring apparatus of any one of claims 16-20, wherein the hazard level analysis parameters further comprise navigational data corresponding to a current location of the head-mounted device; wherein the computing module further comprises:

22. The hazard monitoring device of claim 21, the computing module further comprising:

the first display module includes:

23. The hazard monitoring device of claim 16, said computing module further comprising:

A fifth determining submodule configured to determine a composite survival threat index based on the oxygen margin and at least one other of the risk level analysis parameters;

24. The hazard monitoring device of claim 16, further comprising:

25. The hazard monitoring device of claim 16, said device further comprising:

26. The hazard monitoring device of claim 16, said device further comprising:

27. The hazard monitoring device of claim 16, said device further comprising:

28. The hazard monitoring device of claim 16, further comprising:

a second acquisition module configured to acquire an environmental image;

29. The hazard monitoring device of claim 16, further comprising:

30. The hazard monitoring device of claim 16, the first acquisition module comprising:

31. A head-mounted device comprising a transmissive display unit, a memory, and a processor; wherein,

the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method steps of claims 1-15.

32. A computer-readable storage medium having stored thereon computer instructions, characterized in that the computer instructions, when executed by a processor, implement the method steps of claims 1-15.