CN114821972A - Disaster early warning method, system, medium, and device for different user types - Google Patents
Disaster early warning method, system, medium, and device for different user types Download PDFInfo
- Publication number
- CN114821972A CN114821972A CN202210454114.8A CN202210454114A CN114821972A CN 114821972 A CN114821972 A CN 114821972A CN 202210454114 A CN202210454114 A CN 202210454114A CN 114821972 A CN114821972 A CN 114821972A
- Authority
- CN
- China
- Prior art keywords
- user
- early warning
- information
- disaster
- disaster early
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 59
- 230000009471 action Effects 0.000 claims description 46
- 230000006870 function Effects 0.000 claims description 45
- 208000032041 Hearing impaired Diseases 0.000 claims description 19
- 208000029257 vision disease Diseases 0.000 claims description 18
- 230000000007 visual effect Effects 0.000 claims description 13
- 230000000694 effects Effects 0.000 claims description 7
- 238000003860 storage Methods 0.000 claims description 5
- 206010047571 Visual impairment Diseases 0.000 claims description 3
- 238000009826 distribution Methods 0.000 claims description 3
- 230000004393 visual impairment Effects 0.000 claims description 3
- 238000004891 communication Methods 0.000 claims description 2
- 230000006735 deficit Effects 0.000 claims 1
- 208000016354 hearing loss disease Diseases 0.000 claims 1
- 208000016285 Movement disease Diseases 0.000 description 13
- 230000006399 behavior Effects 0.000 description 12
- 230000008859 change Effects 0.000 description 11
- 230000008569 process Effects 0.000 description 11
- 238000005516 engineering process Methods 0.000 description 7
- 230000006378 damage Effects 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 5
- 230000004044 response Effects 0.000 description 5
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000005286 illumination Methods 0.000 description 3
- 230000036578 sleeping time Effects 0.000 description 3
- 230000002618 waking effect Effects 0.000 description 3
- 208000016621 Hearing disease Diseases 0.000 description 2
- 238000013475 authorization Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 239000003086 colorant Substances 0.000 description 2
- 230000006698 induction Effects 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 238000010408 sweeping Methods 0.000 description 2
- 230000001960 triggered effect Effects 0.000 description 2
- 208000018982 Leg injury Diseases 0.000 description 1
- 208000013521 Visual disease Diseases 0.000 description 1
- 208000027418 Wounds and injury Diseases 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 230000001276 controlling effect Effects 0.000 description 1
- 230000034994 death Effects 0.000 description 1
- 231100000517 death Toxicity 0.000 description 1
- 230000001934 delay Effects 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 230000001815 facial effect Effects 0.000 description 1
- 230000001771 impaired effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 230000035939 shock Effects 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 239000002341 toxic gas Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/10—Alarms for ensuring the safety of persons responsive to calamitous events, e.g. tornados or earthquakes
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B7/00—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00
- G08B7/06—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00 using electric transmission, e.g. involving audible and visible signalling through the use of sound and light sources
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Life Sciences & Earth Sciences (AREA)
- Environmental & Geological Engineering (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geology (AREA)
- Alarm Systems (AREA)
Abstract
The invention is suitable for the technical field of disaster early warning, and provides a disaster early warning method, a system, a medium and equipment aiming at different user types, wherein the disaster early warning method aiming at different user types comprises the following steps: acquiring disaster early warning information; when the disaster early warning information meets preset disaster early warning conditions, user place information is obtained, user type information is obtained, the user place information is used for identifying whether a user is located in a preset place or not, and the user type information comprises information for carrying out classification identification according to the attributes of the user; and sending out an early warning prompt corresponding to the user type. The disaster early warning method, the disaster early warning system, the disaster early warning medium and the disaster early warning equipment for different types of users can perform disaster early warning on different types of users, ensure that disaster early warning information can timely and accurately inform the users aiming at different types of users, and are convenient for the users of different types to timely take reasonable measures to avoid risks, thereby more effectively reducing casualties and secondary disasters caused by disasters.
Description
Technical Field
The invention relates to the technical field of disaster early warning, in particular to a disaster early warning method, a disaster early warning system, a disaster early warning medium and disaster early warning equipment for different user types.
Background
Various natural disasters frequently occur in China every year, personal casualties and property loss caused by the natural disasters are huge every year, and the technical problem which needs to be solved at present is to establish and perfect a natural disaster early warning mechanism and reduce damage caused by the disasters so as to better deal with the influence of the various natural disasters.
The existing disaster early warning is presented and reported through large-scale terminal equipment such as broadcasting equipment or electronic large screens, wherein the traditional broadcasting equipment is strong in regional limitation, the coverage range of wireless frequency modulation broadcasting is limited, and the transmission of signals under severe weather environment cannot be guaranteed. A receiving system established by utilizing an electronic large screen has the disadvantages of high investment cost and limited coverage range, and is difficult for people to stand and carefully read published contents under the emergency condition. A set of digital voice disaster early warning broadcasting system jointly managed by four levels of city, county (district), town and village is established in rural areas, and an effective emergency broadcasting system is established in large public places, tourist attractions, large communities, urban traffic roads, subways, industrial and mining enterprises, office buildings and mansions with dense personnel and the like, so that disaster loss can be practically reduced. However, in a specific place, such as an office place, a home place, etc., it is often difficult to perform early warning and evacuation of a disaster in time and effectively due to factors such as a relatively close distance and a relatively closed space.
Meanwhile, when natural disasters occur, due to the fact that people are different in individuals, the existing template type disaster early warning mode is difficult to accurately guide the individuals of different types, and people cannot be well guided to avoid risks and disasters.
In summary, the technical problems in the prior art are as follows:
1. various natural disasters frequently occur in China every year, personal casualties and property losses caused by the natural disasters are huge every year, and the establishment of a perfect disaster early warning mechanism is a technical problem which needs to be solved urgently in the process of reducing disaster damage;
2. in the prior art, disaster early warning and reporting mainly exist in public places, disaster early warning for different types of personnel in relatively closed places is not provided, and the different types of personnel in the closed places cannot acquire disaster early warning information and corresponding danger avoiding prompts thereof in time;
3. in the prior art, disaster early warning information is presented and broadcasted in a template mode, and the receiving degree of a special group to the information is ignored, so that the special group cannot perform disaster emergency response well.
Disclosure of Invention
The invention aims to provide a disaster early warning method, a disaster early warning system, a disaster early warning medium and disaster early warning equipment for different users, so as to solve the problems in the prior art.
In a first aspect, the present invention provides a disaster early warning method for different user types, including the following steps:
step S10: acquiring disaster early warning information;
step S20: when the disaster early warning information meets preset disaster early warning conditions, user place information is obtained, user type information is obtained, the user place information is used for identifying whether a user is located in a preset place or not, and the user type information comprises information for carrying out classification identification according to the user attribute;
step S30: and sending out an early warning prompt corresponding to the user type.
Further, the early warning prompt is sent by at least one intelligent device located in the preset place.
Further, the early warning prompt also comprises a risk avoidance prompt, and the identification method of the user type comprises active entry and/or automatic identification.
Further, the user type information includes user state information, user action capability information, user age information and/or user identification information, the user state is used for identifying a user activity state, the user identification information includes auditory disorder information, visual disorder information, movement disorder information and/or general information, and the user action capability information includes completely independent action capability information, incompletely independent action capability information and completely independent action capability information; and the user action capacity information is jointly determined according to the user age information and the user identification information.
Further, when the user identification information is auditory disorder information, disaster early warning is performed at least through a visual prompting function of the intelligent device; when the user identification information is visual disorder information, disaster early warning is carried out at least through the sound broadcasting function of the intelligent equipment; when the user identification information is moving obstacle information, sending out an assistance risk avoiding prompt and/or an assistance action at least through a preset intelligent device, wherein the preset intelligent device is an intelligent device in a preset place and/or an intelligent device which is communicated with the preset place and has the nearest distance.
Further, the disaster warning information in step S10 includes a warning level and/or a predicted influence level.
Further, the disaster early warning information further includes early warning time, the estimated influence level includes a kind of influence and a kind of influence, when receiving the disaster early warning information, different disaster early warnings are provided according to the estimated influence level, the early warning time and the preset risk avoiding time, and the method includes: when the estimated influenced level is one kind of influence, the early warning time is longer than the preset danger avoiding time, and an evacuation danger avoiding prompt is sent out; when the estimated influence level is one type of influence, the early warning time is less than the preset danger avoiding time, and a nearby danger avoiding prompt is sent out; and when the estimated influence level is two types of influence, giving an influence prompt.
Further, the method for acquiring the user location information in step S20 includes: obtaining the position of the user and the position of a preset place through a matching method; the user position is obtained by the intelligent equipment which is carried by the user and has a positioning function, and/or is obtained by the intelligent equipment in a preset place through a camera, a sensor device and the like.
Further, the method also includes step S40: and sending the user type information, the user place information, the disaster early warning information and the early warning prompt to a receiving end of a user who is not located in the preset place.
In a second aspect, the invention provides a disaster early warning system, which comprises a disaster early warning information receiving module, a user place and user type acquiring module, and a disaster early warning information distributing module, wherein the disaster early warning information receiving module is used for acquiring disaster early warning information and judging whether the disaster early warning information meets preset disaster early warning conditions; the user place and user type acquisition module is used for identifying whether the user is in a preset place or not and carrying out classification identification according to the self attribute of the user; the disaster early warning information distribution module is used for sending out early warning prompts corresponding to the types of the users.
In a third aspect, the present invention provides a readable storage medium for storing a program, which when executed, is configured to implement the disaster early warning method for different user types.
In a fourth aspect, the present invention provides an electronic device, comprising: one or more processors; a memory having one or more programs stored thereon; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the disaster early warning method for different user types.
In summary, the present invention can achieve at least the following technical effects:
1. according to the disaster early warning system, disaster early warning is realized through the intelligent equipment, and intelligent induction, intelligent interconnection and other advantages of the intelligent equipment are creatively combined with the disaster early warning, so that the accurate transmission of the disaster early warning is ensured, the popular range of the disaster early warning is effectively expanded, the influence caused by the disaster is reduced, and a wider thought is provided for the combination of an intelligent technology and the disaster early warning;
2. according to the invention, whether the user is in the preset place or not is judged, and when the user is in the preset place, the intelligent equipment in the preset place carries out intelligent response, so that the user in the preset place can be ensured to receive the disaster early warning prompt in time, carry out emergency risk avoidance and emergency treatment, and reduce the occurrence of secondary disasters;
3. according to the invention, the user type is identified, and the early warning prompt corresponding to the user type is sent out, so that the early warning prompt mode and/or content corresponds to the user type, different early warning prompts are carried out on users of different user types, and the problem of limited audience caused by the template type disaster early warning mode is effectively avoided;
4. according to the invention, at least one intelligent device is arranged in the predetermined place, so that early warning prompt is provided in time, further, clear early warning prompt is provided for users in the predetermined place, the users in the predetermined place can be ensured to receive disaster early warning prompt timely and accurately, the users can conveniently take reasonable measures to avoid risks in time, and further, casualty and secondary disasters caused by disasters are effectively reduced;
5. according to the invention, the user types are divided into user age information, user state information, user behavior capability information and/or user identification information, and the characteristics of users under different user ages, different user states, different behavior capabilities and/or different user identifications are comprehensively considered, so that early warning prompt is performed in a targeted manner, and the users with different ages, different user states, different behavior capabilities and/or different user identifications can be ensured to obtain effective early warning prompt information and risk avoidance modes;
6. according to the invention, the user identification information is divided into auditory disorder information, visual disorder information, movement disorder information and/or conventional information, so that different early warning prompting modes and/or contents are made according to the characteristics of users with different user identifications, so that the users with different user identifications can timely and accurately acquire disaster early warning prompts, the disaster reduction effect is effectively avoided because users with part of user identifications cannot accurately obtain early warning prompting information in the prior art, and the method has positive social significance.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention or the description of the prior art will be briefly described below, it is obvious that the drawings described below are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flowchart of a disaster early warning method for different user types according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a disaster early warning system according to an embodiment of the present invention.
Detailed Description
The following description provides many different embodiments, or examples, for implementing different features of the invention. The particular examples set forth below are illustrative only and are not intended to be limiting.
Example 1:
an embodiment 1 of the present invention provides a disaster early warning method for different user types, as shown in fig. 1, including the following steps:
step S10: and acquiring disaster early warning information.
In an embodiment of the present invention, the types of disaster include, but are not limited to, earthquake, fire, landslide, debris flow, flood, storm, lightning, and/or ponding. Specifically, disaster early warning information is acquired, the disaster early warning information can be received and distributed to intelligent devices for central control devices arranged in a preset place, and the disaster early warning information can also be received for the intelligent devices respectively, wherein the disaster early warning information can be managed more conveniently through a receiving mode of the central control devices, and the problem that different early warning processes are different due to different receiving delays of the intelligent devices can also be avoided. Meanwhile, the calculation process of the disaster early warning information can be directly performed at a remote server (such as an early warning center, a cloud server and the like), and can also be performed locally by a central control device or an intelligent device.
Step S20: and when the disaster early warning information meets the preset disaster early warning condition, acquiring user place information and user type information, wherein the user place information is used for identifying whether a user is located in a preset place, and the user type information comprises information for carrying out classification identification according to the user attribute.
The predetermined location may be a relatively closed and/or private location, and is not specifically limited herein, for illustrative purposes, the predetermined location may be a bedroom, living room, kitchen and/or bathroom within a home, or an office or factory within an enterprise. The preset place and/or the user type can be obtained in advance and can be automatically identified under the condition of pre-authorization, so that the disaster early warning efficiency is improved.
By acquiring the user types, the early warning prompt corresponding to the user types is sent out, so that the early warning prompt modes and/or contents correspond to the user types, different early warning prompts are carried out on users of different user types, and the problems that audiences are limited and accurate early warning cannot be carried out due to template type disaster early warning modes are effectively avoided.
The method for acquiring whether the user is located in the preset place can be used for carrying out video identification through the camera, and for the normally open camera, after disaster early warning information is received, the camera is triggered to rotate to quickly identify whether people exist in a picture; aiming at an unopened camera, after disaster early warning information is received, the camera is triggered to be opened and automatically rotates to quickly identify whether a person exists in an area; in addition, in order to quickly identify the position information of the user, the position of the user can be identified through the intelligent wearable device, specifically, the current position of the intelligent wearable device is obtained, if the user is at home, the relative position between the intelligent wearable device and the central control device is identified, and the room where the user is located is determined by combining a house type diagram, wherein the house type diagram can be that the user is led into the central control device in advance, or can be that the central control device is automatically generated according to the specific information of the intelligent device, such as the position information, path information and environment information collected by a camera, a sensor, the intelligent wearable device and the like, and the sweeping robot is generated according to a cleaning path. In addition, whether the user is at home or not can be identified through the inherent functions of intelligent equipment such as infrared induction and intelligent gateways.
Whether the user is located in the preset place or not is judged, so that the relevant instruction is issued to the intelligent equipment in the preset place, the instruction comprises the control of the intelligent equipment to be switched on or switched off or other types of responses, the occurrence of secondary disasters caused by the current disasters can be reduced while disaster early warning is guaranteed, and the energy saving and the efficiency are higher.
Step S30: and sending out an early warning prompt corresponding to the user type.
The intelligent equipment is characterized in that the intelligent equipment is used for comprehensively linking various intelligent terminals by taking an indoor space as a platform and utilizing the network communication technology, the automatic control technology, the audio and video technology, the Internet of things technology and other leading-edge technologies. Different intelligent terminals in the intelligent equipment can be controlled and adjusted through the central control equipment. The indoor space may be one or more of a closed space, a static space, a dynamic space, a variable space, a fixed space, a structural space and/or a fuzzy space, and the indoor space is not particularly limited, and any space capable of being configured with an intelligent device may be used as an implementation platform of the present invention.
Realize the calamity early warning through smart machine, creatively combine together smart machine high efficiency, intelligent response, intelligent interconnected's advantage and calamity early warning to for more timely calamity early warning provides the possibility, effectively enlarged the popular scope of calamity early warning, indicate the user more accurately, reduced the loss and the influence that the calamity brought the user, provide wider thinking for realizing the combination of intelligent technology and calamity early warning.
When the intelligent device is carried by the user, the intelligent device is only required to identify the predetermined place, and corresponding early warning prompts are provided for the user by combining different predetermined places and user types. At the moment, the portable intelligent device can identify the user through the preset user type, and through the preset information such as the household type map, the city information and the floor of the preset place, the positioning information of the user is jointly judged in combination with the early warning, and the early warning prompt suitable for the user type and the preset scene is sent.
Further, the early warning prompt is sent by at least one intelligent device located in the preset place.
At least one intelligent device is arranged in the preset place, early warning prompts are timely provided, and then clear early warning prompts are provided for users in the preset place before the users are affected by disasters, so that the users in the preset place can timely and accurately receive the disaster early warning prompts, the users can timely take reasonable measures to avoid risks, casualties and secondary disasters caused by the disasters are effectively reduced, and the emergency risk avoiding capacity of the users is improved.
The deployment position and the deployment information of the intelligent device can be manually input for a user by acquiring the place where the intelligent device is located, specifically, the specific method for acquiring the deployment positions of various intelligent devices and the properties of the deployment rooms can be used for enabling the central control device to acquire the relative position between the intelligent device and the central control device and judge the deployment position of the intelligent device by combining with a user-type diagram.
Further, the early warning prompt also comprises a risk avoidance prompt, and the identification method of the user type comprises active entry and/or automatic identification.
The early warning prompt includes but is not limited to early warning information broadcast and danger avoidance prompt. The early warning information broadcasting function can be correspondingly set according to the function of the intelligent device, the voice broadcasting function refers to the function of text broadcasting, and the basic sound production function refers to the function of sending out sounds with different tones and frequencies or only sending out digital broadcasting or only sending out appointed sounds.
Further, when the smart machine possesses the illumination function, the voice broadcast function, basic sound production function, the vibration function, screen display function and/or automatic switch function, illumination function can be opened and early warning is carried out through the mode of giving out light or light scintillation, voice broadcast function can be opened and disaster early warning information is reported through the pronunciation, the mode of content such as danger avoiding suggestion carries out the early warning, basic sound production function can be opened and early warning is carried out through the sound that sends different tone or frequency or through sending down the timing, vibration function can be opened and early warning is carried out through the vibration that sends the same or different frequency, screen display function can be opened and early warning is carried out through the mode of screen display disaster early warning information, the mode of content such as danger avoiding suggestion, the accessible is opened the mode of smart machine and is sent the early warning, if: opening the intelligent door and window, closing the dangerous equipment and the dangerous source.
Meanwhile, a danger avoiding prompt can be sent, the danger avoiding prompt can be realized through the functions of the intelligent equipment, and different danger avoiding prompts are set according to different preset places, user types, disaster types and/or emergency situations of disasters. For example, before being hit by an earthquake, the specific risk avoidance prompt may be: selecting narrow spaces such as a kitchen, a toilet and the like to avoid shock, or searching firm furniture such as a corner, an office table and the like which are easy to form a triangular space; away from the exterior walls, doors and windows and balconies; the elevator is not needed, and the building can not be jumped blindly. For low-floor users, when the user is in a kitchen or a toilet, the early warning level is yellow, orange or red, and the early warning time is enough to evacuate to the outside of the building, the specific danger avoiding prompt may be: please extinguish the open fire and turn off the faucet, move to the open place outside the building through the stairs.
In addition, the risk avoidance prompt may further include: the user is prompted about the position of the family emergency pack, the water source and the fire-fighting equipment and the surrounding refuge places, the prompt can be carried out through voice broadcasting, the prompt can be carried out through screen display, or the prompt can be carried out on the user through the voice broadcasting and the screen display, or the prompt can be carried out on the user and the fire-fighting equipment and the surrounding refuge places simultaneously. The risk avoidance prompt contents can be automatically subjected to voice broadcast and/or screen prompt for the system, and can also be subjected to voice broadcast after being actively inquired by the user.
When prompting is carried out through voice broadcasting, prompting is carried out in the broadcasting process, and the prompting strategy can be directly switched to danger avoiding prompting after the prompting of the early warning information is finished; certainly, the user can also be prompted through double tracks or double sound tracks, or the user can be prompted through switching of the sound tracks, namely, the epicenter position, the early warning time and the influence level in the early warning information are broadcasted firstly, the disaster early warning information and the danger avoiding prompt are broadcasted, and then the position of a family emergency pack, a water source or fire fighting equipment is broadcasted. Additionally, in order to avoid the situation that the prompt information is too complicated, the user can not prompt the positions of the family emergency bag, the water source and the fire-fighting equipment by voice in the countdown process of early warning, but display the specific positions on the screen. Meanwhile, in the early warning process under the non-countdown condition, early warning information and auxiliary danger avoiding information such as the positions of a user family emergency pack, a water source, fire-fighting equipment, a peripheral refuge place and the like can be completed through voice broadcasting at one time, and the user can be guaranteed to obtain related information in time.
The automatic identification in the user type identification means that the intelligent device identifies the user type through an intelligent identification function carried by the intelligent device under the condition that the user is pre-authorized, a specific identification mode is not limited, and for explaining the situation, preferably, the intelligent device with the image identification function is used for identifying user behaviors and user images so as to judge information such as gender, age, posture, state and the like of the user.
The active entry in the user type identification refers to a user type obtained by the intelligent device from the outside under the condition of user pre-authorization, the obtaining way can be sharing, data inheritance, pre-stored information and the like of another device, the purpose of automatically identifying the user type is only used here, and the obtaining mode is not particularly limited.
In specific application, the identification mode of the user type is usually executed by adopting a method of simultaneously carrying out active entry and automatic acquisition, which is beneficial to improving the accuracy of user type identification, thereby providing more accurate early warning prompt.
According to the embodiment of the invention, the user type is identified, and the early warning prompt corresponding to the user type is sent out, so that the early warning prompt mode and/or content corresponds to the user type, different early warning prompts are carried out on users of different user types, and the problem of limited audiences caused by the template type disaster early warning mode is effectively avoided.
Further, the user type information includes user state information, user action capability information, user age information and/or user identification information, the user state is used for identifying a user activity state, the user identification information includes auditory disorder information, visual disorder information, movement disorder information and/or general information, and the user action capability information includes completely independent action capability information, incompletely independent action capability information and completely independent action capability information; and the user action capacity information is jointly determined according to the user age information and the user identification information.
Further, whether visual and auditory disorders exist in the user identification information or not and movement disorders are also identified and acquired through information prestored by the user in the intelligent wearing device and the camera. The auditory disorder information, the visual disorder information, the movement disorder information and/or the conventional information in the user identification information have real-time performance, and the user is required to input the information manually in time to update corresponding information and/or the intelligent equipment is required to monitor (such as automatic camera identification) in real time to acquire and update the movement disorder information, for example, the movement disorder information can include users who are in a movement disorder state in stages, such as pregnant women and leg injuries. By dividing the user identification information into auditory disorder information, visual disorder information, movement disorder information and/or conventional information, different early warning prompting modes and/or contents are made according to the characteristics of users with different user identifications, so that the users with different user identifications can receive disaster early warning information, the users with various user types can be guaranteed to receive disaster early warning in time and strive for more risk avoiding opportunities in time, the problem that the early warning information cannot be accurately and timely obtained by users with individual types in the prior art, the actual effects of early warning and disaster reduction are reduced is effectively avoided, and the method has positive social significance.
Optionally, if the user portrait uploaded by the user contains age information, saving the age information of the user; if the user image uploaded by the user does not contain age information, the age information is recognized through facial recognition and body state recognition and is corrected by the user.
Specifically, if the intelligent device can identify the user identification information, the user types are divided by the user identification information; if the intelligent device can recognize both the age information and the identification information of the user, the user types are divided by combining the age information and the identification information of the user, namely, the user action capacity information is determined according to the age information and the identification information of the user, the user action capacity information comprises the information of completely independent action capacity, the information of incompletely independent action capacity and the information of completely independent action capacity, and the user types are further divided into the users without completely independent action capacity, the users with incompletely independent action capacity and the users with completely independent action capacity.
The user age information can be preset as an infant (0-4 years), a child (5-11 years), a teenager (12-18 years), a young adult (19-35 years), a middle age (36-59 years) and an old age (more than 60 years) according to the latest Chinese standard age classification, the action capacity of the user can be determined jointly by combining the user identification information, for example, the intelligent device can be preset with age information including 0-4 years and 60 years and/or a user identified as movement disorder as completely independent action capacity, the age information including 5-11 years and/or a user identified as hearing disorder and visual disorder as incompletely independent action capacity, the age information including 12-59 years and a user identified as conventional information as completely independent action capacity, and the user can adjust the age information corresponding to each user action capacity information according to actual conditions The age range is preset. Certainly, in order to guarantee the accuracy of the information, the user can adjust and confirm the information by himself, and the relevant information in the system is guaranteed to be in accordance with the actual situation so as to guarantee that the system can provide accurate and targeted early warning prompts.
When the user action capacity information is completely without independent action capacity, the user without independent action capacity usually accompanies other users without independent action capacity, the early warning prompt at the moment includes a prompt for reminding other users with independent action capacity to take the users without independent action capacity together for danger avoidance, and the users without independent action capacity are not forgotten, whether in the earthquake early warning process or in the early warning process of landslide, debris flow, flood, urban waterlogging or fire, if the danger avoidance prompt is increased: please care the caregivers to take the children/the old to avoid danger and disaster. When the user information is old people, the user needs to be informed of related relatives or carers besides early warning and prompting, and the informing mode can be intelligent outbound, short message, telephone, informing, APP prompting and the like.
Under the conflagration condition, smart machine autoalarm informs all users that fruit is broken and withdraws outside the building along fire control passageway or safe passageway, does not greedy property, does not take the elevator, covers the nose with wet towel, and low appearance is creeping, prevents the poison gas. When the user can not escape, the user is prompted to use clothes or cloth strips with bright colors and greatly shake from the window in the daytime; at night, the user is prompted to make a notice of frequently flashing lights by using a flashlight or a mobile phone.
When the flood occurs, the users on the low floors need to be evacuated upwards in time, the users on the low floors are informed to search the refuge place from the high place according to the early warning level, when the users are old people or children, the evacuation speed is low, and the users on the adjacent floors can be prompted to help the old people or the children to search the refuge place from the high place in time in the corridor. Meanwhile, the indoor user is reminded to close the door and window and keep away from the door and window. When the debris flow occurs, the user is prompted to go downstairs in time, and the device is transversely withdrawn along the direction in which the debris flow is possibly poured to a stable high place of the base for refuge.
Further, in the embodiment of the present invention, the user state information may be obtained by detecting the user state according to the time information in combination with the smart wearable device (such as a sports bracelet, a smart watch, and the like), the camera, and the like, and the specific warning prompting method may be determined by determining the position, waking state, or sleeping state of the user according to the user state information. Specifically, when the user is detected to be in a bedroom, the user is differentially pre-warned according to preset sleeping time from 13 hours to 14 hours, sleeping time from 23 hours to 7 days, non-sleeping time at other time, disaster types, pre-warning levels and the like, for example, when the pre-warning level is blue and the user is in a sleeping state, the pre-warning process only carries out screen prompt and sound prompt for the intelligent device (at least one of intelligent devices such as a sports bracelet, an intelligent watch, a sound box and a mobile phone), and when the user is in a waking state, the intelligent device simultaneously carries out sound prompt and screen prompt; when the early warning level is yellow and the user is in a sleep state, the early warning process is that the intelligent device (at least one of intelligent devices such as a sports bracelet, an intelligent watch, an intelligent sound box and a mobile phone) carries out sound prompt, and when the user is in a waking state, the intelligent device simultaneously carries out sound prompt and screen prompt; when the early warning level is orange or red and the user is in a sleep state, because of the high early warning level, the early warning process needs to be strongly prompted until the user wakes up, at the moment, all lamps flicker under the control of the intelligent switch or at least one lamp is normally on (a top lamp or a desk lamp), other lamps flicker, the intelligent sound box sends out sound for broadcasting, the volume is automatically increased, and the like.
By acquiring user age information, user state information, user action capacity information and/or user identification information of user types and comprehensively considering characteristics of users under different user ages, different user states, different action capacities and/or different user identifications, early warning prompt is performed in a targeted manner, and effective pre-disaster prompt and risk avoidance modes of users with different ages, different user states, different action capacities and/or different user identifications can be guaranteed.
Further, when the user identification information is auditory disorder information, disaster early warning is performed at least through a visual prompting function of the intelligent device; when the user identification information is visual disorder information, disaster early warning is carried out at least through the sound broadcasting function of the intelligent equipment; when the user identification information is moving obstacle information, sending out an assistance risk avoiding prompt and/or an assistance action at least through a preset intelligent device, wherein the preset intelligent device is an intelligent device in a preset place and/or an intelligent device which is communicated with the preset place and has the nearest distance. The auxiliary action described above may be an action that can facilitate evacuation of a user who has moved obstacle information, such as automatically unlocking a door lock.
Further, when the user identification information is auditory disorder information, disaster early warning is performed at least through a visual prompting function of the intelligent device, and at the moment, visual prompting can be emphasized, for example, a user whose user identification information is auditory disorder information is prompted in a mode that visual change of a strobe lamp is large; when the user identification information is the visual obstacle information, disaster early warning is performed at least through the sound broadcasting function of the intelligent device, at the moment, auditory prompting can be emphasized, for example, the volume is amplified or vibration is increased, and a user with the user identification information being the visual obstacle information is prompted by adopting more prompting sound (for example, a warning ring tone).
The visual prompting function of the intelligent device can be an illumination function of the intelligent device, and the specific implementation method comprises the following steps: the intelligent equipment with the lighting function emits light with different light intensities, colors and/or frequencies, so that early warning prompt is performed for users who can obtain visual prompt information. When the user identification information is auditory disorder information, the prompting mode can be further enhanced, such as modes of large light intensity change, large color change, fast frequency and the like attract the attention of auditory disorder users, and meanwhile, information such as disaster types, disaster emergency degrees, danger avoidance prompts and the like can be transmitted to the auditory disorder users in a mode of international common disaster early warning information through the light intensity, color and frequency change, for example, Morse codes are represented by changes with different lengths. Meanwhile, when the user with auditory disorder is only a user with lower auditory acuity, on the premise of adopting visual prompt, the attention of the user with lower auditory acuity can be brought by the modes of increasing the sound intensity change, increasing the frequency change, improving the sound of content broadcasting and the like. Of course, when the visually impaired user is only amblyopic or semi-blind, the attention of the user with amblyopic or semi-blind can be drawn by increasing the color change, the light intensity change, the vibration intensity change, and the like, on the premise of using the auditory cue.
The sound broadcasting function of the intelligent equipment can be a voice broadcasting function or a basic sound production function of the intelligent equipment, and the specific implementation method comprises the following steps: the voice broadcasting function or the basic sound production function with the intelligent device can send out sounds with different sound intensities, different frequencies and/or different contents, so that early warning prompt can be carried out for a user capable of obtaining voice prompt information. When the user identification information is the visual impairment information, the above prompting methods can be further enhanced, such as increasing the sound intensity change, increasing the frequency change, improving the content broadcast sound, and the like, to draw the attention of the visual impairment user.
In addition, when the number of people in the predetermined place is large, if the user identification is the user of the hearing disorder information and/or the visual disorder information, the visual prompt and/or the sound prompt need to be emphasized to ensure that the relevant people acquire the early warning information and the danger avoiding prompt. Meanwhile, the person whose user identification is the conventional information needs to be prompted to assist the person whose user identification is the auditory disorder information and/or the visual disorder information to avoid danger.
And when the user identification information is moving obstacle information, performing corresponding early warning prompt according to early warning time, early warning level and/or floor. Meanwhile, the disaster early warning method for the mobile obstacle user is biased to assist the mobile obstacle user to avoid the danger by other people, such as prompting other people in the predetermined place to assist the mobile obstacle user to avoid the danger, or prompting other people near the predetermined place to assist the mobile obstacle user to avoid the danger or evacuate. Specifically, when a fire disaster occurs, the user with the movement obstacle is prompted to enter a ventilated room and store water, the mouth and the nose are covered by a wet towel, and other personnel are informed to assist rescue or alarm in time. Certainly, the obstacle-moving user can avoid risks without obstacles and without assistance of other personnel, for example, when the obstacle-moving user is in an intelligent electric wheelchair, the risk can be avoided by himself, and the user can actively supplement related information to the system to ensure the accuracy of the early warning information and the risk avoiding strategy received by the user.
According to the embodiment of the invention, the user identification information is divided into the auditory disorder information, the visual disorder information, the movement disorder information and/or the conventional information, so that different pre-warning prompting modes and/or contents are set according to the characteristics of users with different user identifications, so that the users with different user identifications can timely and accurately obtain disaster early warning prompts, the users can conveniently and timely take reasonable measures to avoid risks, and injuries and deaths and losses caused by disasters are effectively reduced.
Further, the disaster warning information in step S10 includes a warning level and/or a predicted influence level.
The early warning levels are used for judging the influence degree of the disaster per se and can be divided into a plurality of early warning levels according to the severity degree; estimating the influence level to quantitatively judge the influence degree of the disaster on the area of the preset place; there may be a mapping correspondence between the early warning level and the estimated level of influence.
Further, in step S10, when the early warning level is greater than the early warning level threshold and/or the estimated influence level is greater than the estimated influence level threshold, it is determined that the disaster early warning information satisfies the preset disaster early warning condition.
The early warning level threshold value is the lowest level of the intelligent equipment for executing the disaster early warning prompt, and when the early warning level is the same as or exceeds the early warning level threshold value, namely the disaster early warning information meets the preset disaster early warning condition, the intelligent equipment starts an early warning mode to prompt the disaster early warning.
The estimated influence level threshold value is the lowest estimated influence level of the intelligent equipment for executing the disaster early warning prompt, and when the estimated influence level is greater than or equal to the estimated influence level threshold value, namely the disaster early warning information meets the preset disaster early warning condition, the intelligent equipment performs the disaster early warning prompt.
Furthermore, the disaster early warning information also comprises early warning time, and the estimated influence level comprises a first kind of influence and a second kind of influence, wherein the first kind of influence is the influence level with substantive influence and substantive damage to the local; the second kind of influence is the influence level which has influence on the local and can not generate substantial damage; it should be noted that, the estimated affected level may be determined by an early warning level, for example, a type of disaster early warning information whose effect is that the early warning level is red or orange; the second kind of influence is the early warning information with the early warning level of blue or yellow. When receiving calamity early warning information, according to estimating influenced grade, early warning time and predetermine the calamity early warning that keeps away time and provide different calamity early warnings, include: when the influence grade is estimated to be one kind of influence, the early warning time is longer than the preset danger avoiding time, and evacuation danger avoiding prompt is sent out; when the estimated influenced level is influenced by one kind, the pre-alarm time is less than the preset danger avoiding time, and a nearby danger avoiding prompt is sent out; and when the estimated influence level is two types of influence, giving an influence prompt.
The specific numerical value of the preset risk avoiding time is determined by various factors such as a building structure, a safe passage, floors, disaster types, user types and the like of a preset place. For different disaster types, the preset danger avoiding time is different, for example, when the floor of a preset place is 10 floors (the total floor height is 20 floors), the preset danger avoiding time of an earthquake is shorter than that of a torrential flood; the preset risk avoiding time is different for different user types, and is longer than that of conventional information. Certainly, the preset risk avoiding time may be calculated by combining the system with the user data, or may be set manually, and during the manual setting, the risk avoiding time of the user may be obtained through exercise as the preset risk avoiding time. Certainly, the preset danger avoiding time of the users living on the same floor is different according to the positions of the building structure and the safe passage.
In this embodiment, when the preset risk avoiding time is 30 seconds, and when the actual early warning time is greater than 30 seconds and the estimated influence level is a type of influence, the risk avoiding prompt received by the user is an evacuation risk avoiding prompt, which is evacuated to an open position, and the specific broadcast risk avoiding policy content may be: please extinguish the open fire and turn off the faucet, move to the open place outside the building through the stairs. When the actual early warning time is less than 30 seconds, the danger avoiding prompt received by the user is a near danger avoiding prompt, the user is far away from the suspended lamp or other objects, and the user searches for the triangular area to avoid danger (the specific early warning prompt content can be that the user needs to be far away from the suspended object or the lamp and moves to the bedside or the table bottom to avoid danger). When the influence level is estimated to be two types of influence, the user receives an influence prompt, namely the user is prompted that a disaster is coming, and psychological preparation is made.
Further, the method for acquiring the user location information in step S20 includes: obtaining the position of the user and the position of a preset place through a matching method; the user position is obtained by the intelligent equipment which is carried by the user and has a positioning function, and/or is obtained by the intelligent equipment in a preset place through a camera and a sensor device.
Further, risk avoiding time of different disasters is preset for each user in the intelligent device or the central control device, and when the early warning information is received, the early warning time and the risk avoiding time are compared to carry out different risk avoiding prompts. And taking the disaster type as an earthquake example, informing users with the risk avoiding time being longer than the early warning time to evacuate to the open position outside the building for risk avoidance in time, and informing users with the risk avoiding time being shorter than the early warning time to avoid risks nearby. Certainly, when the number of users in the predetermined place is multiple, the user with the longest risk avoiding time is taken as a standard to send out the risk avoiding prompt to inform all users; in addition, when the user identification information in the predetermined place is auditory disorder information, visual disorder information, movement disorder information and/or user behavior ability information of a user with no behavior ability at all, and the user identification information is conventional information and/or user behavior ability information of a user with no behavior ability at all, the comprehensive risk avoiding time can be obtained, wherein the comprehensive risk avoiding time is the risk avoiding time required by the conventional information and/or the user with no behavior ability to assist the user identification information to be auditory disorder information, visual disorder information, movement disorder information and/or user behavior ability information of the user with no behavior ability to avoid risks. When the number of the users is multiple and the user behavior capability is multiple, the comprehensive risk avoiding time and the early warning time can be compared to send out the risk avoiding prompt. It should be noted that the risk avoiding time preset by each user may be actively input by the user, or may be automatically generated according to the past exercise result, and the comprehensive risk avoiding time is automatically generated according to the past exercise result. The earthquake is taken as an example and the preset place is a private house for explanation, and other types of disasters can be obtained through simple analogy reasoning, and the method specifically comprises the following steps:
when the user is in the living room, before an earthquake comes, the user is preferably prompted to evacuate to an open place to avoid danger as soon as possible, and then the user is informed of being far away from a hanging object.
When the user is in the bedroom, the user may be in a sleep state in the bedroom, and the sound at this time prompts the volume to be increased or the user is waken through vibration of the intelligent wearable device. The specific danger avoiding prompt is as follows: informing a user to get away from a hanging object before an earthquake comes, and informing the user to evacuate outdoors in time when the early warning time is longer than the danger avoiding time; and when the early warning time is less than the risk avoiding time, prompting the user to search for the risk avoiding in the triangular area nearby (for example, avoid under a dining table).
When the user is in the kitchen, before an earthquake comes, and when the early warning time is longer than the danger avoiding time, informing the user of evacuating outdoors in time; when the early warning time is less than the danger avoiding time, informing a user to move to a toilet or search a triangular area in time for danger avoiding; and the user is informed to be far away from the outer wall, the door and the window and the balcony, and is far away from sharp objects and high-temperature objects, an elevator is not needed, and the user cannot jump the building blindly.
Further, the method also includes step S40: and sending the user type information, the user place information, the disaster early warning information and the early warning prompt to a user receiving end which is not positioned in the preset place.
In this embodiment of the present invention, the specific step of step S40 may be that the intelligent device in the predetermined location uploads the acquired user type information, user location information, disaster warning information, and the issued warning prompt to the control center, and then the control center transmits the user type information, the user location information, the disaster warning information, and the warning prompt to the association subsystem (i.e., a receiving end) for storage, analysis, and use, and the intelligent device in the predetermined location may also transmit the acquired user type information, the user location information, the disaster warning information, and the issued warning prompt to the association subsystem, where the association subsystem is a user system associated with the user-side account outside the rescue system, such as: when the user place information is a house, the intelligent device is associated with a plurality of users at the same time, and when a disaster occurs in the area where the house is located, the intelligent device can send user type information, disaster early warning information and/or user place information under the influence of the disaster to all associated users in a voice recording, video recording, character and other modes, and send notification information to a user receiving end which is not located in the preset place to inform the affected condition and the current state of the users in the preset place. Of course, the intelligent device may also directly send a notification message to the receiving terminals of all users associated with the intelligent device without passing through the control center, so as to inform the affected situation and the current state of the users in the predetermined place. Under the normal condition, most of the associated users of the intelligent devices in the house are family members, and the related information in the house is sent to the associated users, so that the family members can conveniently acquire the disaster situation in the house or other family members in time, and the intelligent device is also beneficial to other family members to get in contact with rescue workers in time to assist in rescue.
Meanwhile, the control center can transmit the user type information, the user place information and the disaster early warning information to the rescue system, so that the rescue system can distribute timely, and rescue personnel and rescue resources can be regulated and controlled. Specifically, the intelligent device can transmit user type information and user place information in modes of sound recording, video recording, characters and the like; the user place information can be uploaded through the intelligent equipment with the positioning function or the space recognition function, the intelligent equipment with the positioning recognition function can be intelligent wearable equipment, and the intelligent equipment with the space recognition function can be a sweeping robot, a router and the like. The intelligent equipment with the space identification function can store in advance or identify in real time the intelligent equipment with the actual living space to transmit the actual living space of the room to a disaster relief department to assist in disaster relief.
The user type information can further comprise user life sign information, the user life sign information can be uploaded to a rescue department through intelligent equipment, when rescue workers are close to the people to be rescued, the position information of the rescuers is obtained through intelligent wearable equipment, the positions and distances between the people to be rescued are calculated by the rescue workers according to the position information of the rescuers, meanwhile, the rescue workers can be intelligently prompted in a sound or light mode, and the rescue workers can search and rescue the people to be rescued in real time conveniently. Meanwhile, the intelligent device carried by the user can also send a vibration prompt to prompt the person to be rescued to keep clear-headed.
Example 2:
as shown in fig. 1, an embodiment 2 of the present invention provides a disaster early warning system, which includes a disaster early warning information receiving module, a user place and user type obtaining module, and a disaster early warning information distributing module, where the disaster early warning information receiving module is configured to obtain disaster early warning information and determine whether the disaster early warning information satisfies a preset disaster early warning condition; the user place and user type acquisition module is used for identifying whether the user is in a preset place or not and carrying out classification identification according to the self attribute of the user; the disaster early warning information distribution module is used for sending out early warning prompts corresponding to the types of the users.
The embodiment also comprises a central control module, wherein the central control module is used for receiving and distributing disaster early warning information and controlling the on-off or response of all intelligent equipment; the central control module can be used for setting an early warning level threshold value and/or pre-estimating an affected level threshold value, a user can also input the earthquake fortification level of a building where a preset place is located through the central control module, and at the moment, the central control module can automatically generate a related threshold value. The central control module can be a special intelligent central control device, and can also be an electronic device with high intelligence degree, such as a mobile phone, a flat panel, a television or a sound box.
Example 3:
embodiment 3 of the present invention provides a readable storage medium, which is used for storing a program, and when the program is executed, the readable storage medium is used for implementing the disaster early warning method for different user types.
Example 4:
an embodiment 4 of the present invention provides an electronic device, including: one or more processors; a memory having one or more programs stored thereon; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement a disaster early warning method for different user types as described.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (12)
1. A disaster early warning method aiming at different user types is characterized by comprising the following steps:
step S10: acquiring disaster early warning information;
step S20: when the disaster early warning information meets preset disaster early warning conditions, user place information is obtained, user type information is obtained, the user place information is used for identifying whether a user is located in a preset place or not, and the user type information comprises information for carrying out classification identification according to the user attribute;
step S30: and sending out an early warning prompt corresponding to the user type.
2. A disaster early warning method for different user types according to claim 1, wherein the early warning prompt is issued by at least one intelligent device located in the predetermined site.
3. The method as claimed in claim 1, wherein the early warning prompt further comprises a risk avoidance prompt, and the identification method of the user type comprises active entry and/or automatic identification.
4. A disaster early warning method for different user types according to one of claims 1 to 3, wherein the user type information comprises user status information for identifying a user activity status, user action capability information, user age information, and/or user identification information comprising hearing impairment information, visual impairment information, movement impairment information, and/or general information, the user action capability information comprises completely non-independent action capability information, incompletely independent action capability information, and completely independent action capability information; and the user action capacity information is jointly determined according to the user age information and the user identification information.
5. The disaster early warning method for different user types according to claim 4, wherein when the user identification information is auditory disorder information, disaster early warning is performed at least through a visual prompt function of the smart device; when the user identification information is visual disorder information, disaster early warning is carried out at least through the sound broadcasting function of the intelligent equipment; when the user identification information is moving obstacle information, sending out an assistance risk avoiding prompt and/or an assistance action at least through a preset intelligent device, wherein the preset intelligent device is an intelligent device in a preset place and/or an intelligent device which is communicated with the preset place and has the nearest communication distance.
6. The disaster early warning method for different user types according to one of claims 1 to 5, wherein the disaster early warning information in step S10 comprises early warning level and/or estimated influence level.
7. The method as claimed in claim 6, wherein the disaster warning information further includes warning time, the estimated influence level includes one type of influence and two types of influence, and when receiving the disaster warning information, different disaster warnings are provided according to the estimated influence level, the warning time and the preset risk avoidance time, including:
when the estimated influence level is one kind of influence, the early warning time is longer than the preset danger avoiding time, and an evacuation danger avoiding prompt is sent out;
when the estimated influence level is one kind of influence, the early warning time is less than the preset danger avoiding time, and a nearby danger avoiding prompt is sent out;
and when the estimated influence level is two types of influence, giving an influence prompt.
8. The disaster early warning method for different user types according to claim 2, wherein the method for acquiring the user location information in step S20 comprises: obtaining the position of a user and the position of a preset place through a matching method; the user position is obtained by the intelligent equipment which is carried by the user and has a positioning function, and/or is obtained by the intelligent equipment in a preset place through a camera, a sensor device and the like.
9. The disaster early warning method for different user types as claimed in claim 8, further comprising the step S40: and sending the user type information, the user place information, the disaster early warning information and the early warning prompt to a receiving end of a user who is not located in the preset place.
10. A disaster early warning system is characterized by comprising a disaster early warning information receiving module, a user place and user type acquiring module and a disaster early warning information distributing module, wherein the disaster early warning information receiving module is used for acquiring disaster early warning information and judging whether the disaster early warning information meets preset disaster early warning conditions or not; the user place and user type acquisition module is used for identifying whether the user is in a preset place or not and carrying out classification identification according to the self attribute of the user; and the disaster early warning information distribution module is used for sending out early warning prompts corresponding to the types of the users.
11. A readable storage medium storing a program which, when executed, implements a disaster warning method for different user types according to one of claims 1 to 9.
12. An electronic device, comprising: one or more processors; a memory having one or more programs stored thereon; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the disaster early warning method for different user types as recited in one of claims 1-9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210454114.8A CN114821972A (en) | 2022-04-27 | 2022-04-27 | Disaster early warning method, system, medium, and device for different user types |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210454114.8A CN114821972A (en) | 2022-04-27 | 2022-04-27 | Disaster early warning method, system, medium, and device for different user types |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114821972A true CN114821972A (en) | 2022-07-29 |
Family
ID=82510317
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210454114.8A Pending CN114821972A (en) | 2022-04-27 | 2022-04-27 | Disaster early warning method, system, medium, and device for different user types |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114821972A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH1040425A (en) * | 1996-07-23 | 1998-02-13 | Toshiba Corp | Station work device |
| CN102939791A (en) * | 2010-05-17 | 2013-02-20 | 塔塔咨询服务有限公司 | Hand-held communication aid for individuals with auditory, speech and visual impairments |
| KR101271154B1 (en) * | 2011-12-14 | 2013-06-04 | (주)휴먼케어 | Audio guiding device for the blind |
| CN105185052A (en) * | 2015-10-22 | 2015-12-23 | 上海斐讯数据通信技术有限公司 | Kitchen security monitoring and control system and method |
| CN111524321A (en) * | 2020-04-21 | 2020-08-11 | 中国科学院、水利部成都山地灾害与环境研究所 | Geological disaster early warning method |
| CN113345206A (en) * | 2021-06-01 | 2021-09-03 | 东营职业学院 | Application method of earthquake disaster early warning information in IoT (Internet of things) equipment |
-
2022
- 2022-04-27 CN CN202210454114.8A patent/CN114821972A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH1040425A (en) * | 1996-07-23 | 1998-02-13 | Toshiba Corp | Station work device |
| CN102939791A (en) * | 2010-05-17 | 2013-02-20 | 塔塔咨询服务有限公司 | Hand-held communication aid for individuals with auditory, speech and visual impairments |
| KR101271154B1 (en) * | 2011-12-14 | 2013-06-04 | (주)휴먼케어 | Audio guiding device for the blind |
| CN105185052A (en) * | 2015-10-22 | 2015-12-23 | 上海斐讯数据通信技术有限公司 | Kitchen security monitoring and control system and method |
| CN111524321A (en) * | 2020-04-21 | 2020-08-11 | 中国科学院、水利部成都山地灾害与环境研究所 | Geological disaster early warning method |
| CN113345206A (en) * | 2021-06-01 | 2021-09-03 | 东营职业学院 | Application method of earthquake disaster early warning information in IoT (Internet of things) equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11995976B2 (en) | Owner controlled evacuation system | |
| KR101099655B1 (en) | Fire sensing system with wireless communications and position tracking functions | |
| Proulx | Occupant behaviour and evacuation | |
| CN104793504B (en) | A kind of intelligent apartment for elderly people system | |
| US8970365B2 (en) | Evacuation system | |
| US20150015401A1 (en) | Owner controlled evacuation system | |
| CN206181101U (en) | Intelligence camping room based on camping internet of things | |
| CN105809884B (en) | One kind is in residence accident monitor system | |
| WO2020191755A1 (en) | Implementation method for smart home and smart device | |
| Nilsson et al. | Influencing exit choice in the event of a fire evacuation | |
| US20240087441A1 (en) | Building security and emergency detection and advisement system | |
| Alesii et al. | Short range wireless solutions enabling ambient assisted living to support people affected by the Down syndrome | |
| CN208273142U (en) | Endowment apartment security configuration system | |
| CN114821972A (en) | Disaster early warning method, system, medium, and device for different user types | |
| JP2004206290A (en) | Bathroom monitoring device | |
| CN209845012U (en) | Scenic spot wisdom guide card | |
| CN202309846U (en) | Large-range joint defense telephone networked alarm system for community | |
| CN215501978U (en) | Intelligent home monitoring system | |
| CN205827802U (en) | A kind of Multifunctional doorplate | |
| CN115188156A (en) | Toilet personnel safety detection device and method | |
| CN117893161A (en) | Campus security intelligent management system | |
| KR101616742B1 (en) | The hybrid emergency situation notification system by using emergency shelters | |
| TWM634058U (en) | Multifunctional socket integrated with escape guidance function | |
| CN114246765A (en) | Thing-identifying obstacle-avoiding early warning navigation bar | |
| WO2020223967A1 (en) | Active intelligent control method and system, and intelligent apparatus |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |