CN110786859A - Emergency alarm method, device and system - Google Patents
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
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Abstract
The invention discloses a first-aid alarm method, device and system. Wherein, the method comprises the following steps: collecting a first action characteristic and/or a first sound characteristic of a user; inputting the first action characteristic and/or the first sound characteristic into a first identification model, and identifying whether the user has an emergency condition endangering the physical health of the user; in the case where the first recognition model recognizes that the user has an emergency situation that endangers the physical health of the user, an emergency alarm is performed. The invention solves the technical problem that the life safety of the user is threatened once an emergency occurs because no solution for the emergency of the user of the intelligent home is provided in the related technology.
Description
Technical Field
The invention relates to the field of intelligent home furnishing, in particular to a first-aid alarm method, a first-aid alarm device and a first-aid alarm system.
Background
The intelligent home is the mainstream direction of the development of the current electrified equipment, the intelligent home has the advantages that the intelligent home can interact with a user, along with the development of the intelligent home and artificial intelligence, only the distance can be communicated and interacted with the user through the internet in a remote mode, various conditions of the user in the using process can be processed, the higher exclusive rate in China is also a power factor for promoting the development of the intelligent home, but a condition exists, the user has sudden situations when using the intelligent home, such as sudden diseases and the like, as is well known, the onset age of various diseases is generally low-aged, modern people lack of movement, the probability of illness is greatly increased, and in case of sudden diseases in using the intelligent home, the intelligent home needs to detect and determine and perform emergency alarm.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides a first-aid alarm method, a first-aid alarm device and a first-aid alarm system, which are used for at least solving the technical problem that the life safety of a user is threatened once an emergency happens because no solution for the emergency of the user at an intelligent home exists in the related technology.
According to an aspect of an embodiment of the present invention, there is provided a first aid alarm method including: collecting a first action characteristic and/or a first sound characteristic of a user; inputting the first action characteristic and/or the first sound characteristic into a first recognition model, and recognizing whether the user has an emergency condition endangering the physical health of the user, wherein the first recognition model is obtained by machine learning training by using a plurality of groups of data, and each group of data in the plurality of groups of data comprises: the first action characteristic and/or the first sound characteristic and the emergency condition identification result corresponding to the first action characteristic and/or the first sound characteristic; and when the first recognition model recognizes that the user has an emergency, performing emergency alarm.
Optionally, when the recognition model recognizes that the user has an emergency, the method includes: sending a response confirmation, wherein the response confirmation is used for confirming whether an emergency alarm is needed or not to the user; determining whether a second action characteristic and/or a second sound characteristic is received in response to the acknowledgement; and in the case that the second action characteristic and/or the second sound characteristic which answers the answer confirmation is not received, performing emergency alarm.
Optionally, in a case where the second action characteristic and/or the second sound characteristic that answers the answer acknowledgement is received, the method includes: inputting the second action characteristic and/or the second sound characteristic into a second recognition model, and recognizing whether the user affirms the acknowledgement to alarm for emergency treatment, wherein the second recognition model is obtained by machine learning training by using a plurality of groups of data, and each group of data in the plurality of groups of data comprises: the second action characteristic and/or the second sound characteristic and the identification result corresponding to the second action characteristic and/or the second sound characteristic and answering the answer confirmation; and when the second recognition model recognizes that the user gives an alarm after confirming the response, giving an emergency alarm.
Optionally, the acquiring the continuous first action characteristic and/or the first sound characteristic of the user comprises: collecting images for extracting action characteristics of a user and/or audio for extracting sound characteristics of the user; the first motion feature is extracted from the image and/or the first sound feature is extracted from the audio.
Optionally, when the first recognition model recognizes that the user has an emergency, the method, after performing emergency alarm, includes: receiving physiological data of a user; the physiological data, and the image and/or audio, are sent to a medical institution performing emergency work.
Optionally, when the second recognition model recognizes that the user gives an alarm after confirming the response, the alarming for emergency treatment includes: sending a first aid request to a medical institution; sending the personal information of the user and the position of the user.
According to another aspect of an embodiment of the present invention, there is provided an emergency alert device including: the acquisition module is used for acquiring a first action characteristic and/or a first sound characteristic of a user; a first recognition module, configured to input the first motion feature and/or the first sound feature into a first recognition model, and recognize whether the user has an emergency condition that endangers the physical health of the user, where the first recognition model is obtained by machine learning training using multiple sets of data, and each set of data in the multiple sets of data includes: the first action characteristic and/or the first sound characteristic and the emergency condition identification result corresponding to the first action characteristic and/or the first sound characteristic; and the first alarm module is used for carrying out emergency alarm under the condition that the first identification model identifies that the user has an emergency.
Optionally, the alarm device further includes: the system comprises a sending module, a receiving module and a sending module, wherein the sending module is used for sending a response confirmation, and the response confirmation is used for confirming whether emergency alarm is needed or not to a user; the judging module is used for judging whether a second action characteristic and/or a second sound characteristic which responds to the response confirmation is received or not; and the second alarm module is used for alarming for emergency treatment under the condition that the second action characteristic and/or the second sound characteristic which is used for answering the answer confirmation is not received.
Optionally, the alarm device further includes: a second recognition module, configured to input the second motion characteristic and/or the second sound characteristic into a second recognition model, and recognize whether the user affirms the acknowledgement for emergency alert, wherein the second recognition model is obtained by machine learning training using multiple sets of data, and each set of data in the multiple sets of data includes: the second action characteristic and/or the second sound characteristic and the identification result corresponding to the second action characteristic and/or the second sound characteristic and answering the answer confirmation; and the third alarm module is used for giving an emergency alarm when the second identification model identifies the user to give an alarm after confirming the response.
According to another aspect of an embodiment of the present invention, there is provided an emergency alert system, including: collection system and first aid alarm device, wherein, first aid alarm device is any one of the device in the above-mentioned.
In the embodiment of the invention, the first action characteristic and/or the first sound characteristic of the user are/is collected in a mode of identifying the action and/or the sound of the user and determining whether the user has an emergency; inputting the first action characteristic and/or the first sound characteristic into a first identification model, and identifying whether the user has an emergency condition endangering the physical health of the user; the first recognition model recognizes that the emergency situation endangering the body health of the user occurs to the user, and carries out emergency alarm, and the purpose of recognizing whether the emergency situation endangering the body health of the user occurs to the user is achieved through the first recognition model, so that the technical effect of effectively recognizing the emergency situation occurring to the user is achieved, and the technical problem that the life safety of the user is threatened once the emergency situation occurs due to the fact that no solution for the emergency situation occurs to the user at the smart home in the related technology is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a flow chart of a method of emergency alert according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an emergency alert device according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In accordance with an embodiment of the present invention, there is provided a method embodiment of an emergency alert method, it being noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system, such as a set of computer-executable instructions, and that, although a logical order is illustrated in the flowchart, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
Fig. 1 is a flowchart of a first aid alerting method according to an embodiment of the present invention, as shown in fig. 1, the method including the steps of:
step S102, collecting a first action characteristic and/or a first sound characteristic of a user;
step S104, inputting the first action characteristic and/or the first sound characteristic into a first recognition model, and recognizing whether the user has an emergency condition endangering the body health of the user, wherein the first recognition model is obtained by using a plurality of groups of data through machine learning training, and each group of data in the plurality of groups of data comprises: the first action characteristic and/or the first sound characteristic and an emergency condition identification result corresponding to the first action characteristic and/or the first sound characteristic;
and step S106, when the first recognition model recognizes that the user has an emergency, giving an emergency alarm.
In the embodiment of the invention, the first action characteristic and/or the first sound characteristic of the user are/is collected in a mode of identifying the action and/or the sound of the user and determining whether the user has an emergency; inputting the first action characteristic and/or the first sound characteristic into a first identification model, and identifying whether the user has an emergency condition endangering the physical health of the user; the first recognition model recognizes that the emergency situation endangering the body health of the user occurs to the user, and carries out emergency alarm, and the purpose of recognizing whether the emergency situation endangering the body health of the user occurs to the user is achieved through the first recognition model, so that the technical effect of effectively recognizing the emergency situation occurring to the user is achieved, and the technical problem that the life safety of the user is threatened once the emergency situation occurs due to the fact that no solution for the emergency situation occurs to the user at the smart home in the related technology is solved.
The first action characteristic and/or the first sound characteristic are/is used for identifying whether the user has an emergency or not by the identification model. In the identification process, the identification can be carried out according to the action; such as a user tripping, slipping situation. May be based on voice recognition; for example, a user may be scared or hit by a dropped ceiling and may make a sound. It is also possible to combine sound and action for identification, for example, in the case of a user hit by the ceiling, the user may fall or squat.
The first action characteristic and/or the first sound characteristic of the user are/is acquired through the acquisition device, the picture containing the action characteristic of the user can be acquired through the image acquisition device or the infrared acquisition device, and the first action characteristic can be extracted and acquired from the picture. The sound collection device or the vibration collection device can collect the audio frequency containing the sound information of the user, and can extract the sound characteristics of the user from the collected sound information. The acquisition device may also acquire vital signs of the user, e.g. a sign detector or the like.
The first recognition model is a recognition model that can be machine-learned, such as a convolutional neural network recognition model, obtained by machine learning training using multiple sets of data, and is trained, for example, by multiple sets of data until the model converges, and has a recognition capability between input data and output data. Each set of data in the plurality of sets of data includes: the first action characteristic and/or the first sound characteristic and an emergency condition identification result corresponding to the first action characteristic and/or the first sound characteristic; for example, the action characteristic of a fall corresponds to an emergency of the fall, i.e., an emergency occurs; the squatting action characteristics correspond to no emergency or emergency; the voice of the user with loud voice and pain corresponds to the occurrence of an emergency. It should be noted that the input features and the output results, i.e. whether an emergency has occurred, must be determined, for example, in the case of a certain fall, without the user being injured and without pain. I.e. no injury, although falling. However, when performing model training, it is necessary to determine whether an emergency situation occurs.
In the case where the first recognition model recognizes that the user has an emergency situation that endangers the physical health of the user, the first aid alarm is performed. When the user is in an emergency state which endangers the physical health of the user, namely when the model is trained, the user is considered to be in the emergency state only when the physical health of the user is endangered. In the above embodiment, it is assumed that the user is not injured although falling down, and that an unexpected situation that endangers the physical health of the user does not occur. In case of confirming that the user has an emergency situation endangering the user's physical health, the emergency call is automatically dialed and the address, vital signs, scene pictures, videos, etc. of the user, actions and/or data advantageous to the rescue user are transmitted to the emergency center.
Optionally, in the case that the recognition model recognizes that the user has an emergency condition that endangers the physical health of the user, the method includes the following steps before alarming: sending a response confirmation, wherein the response confirmation is used for confirming whether emergency alarm is needed to the user; judging whether a second action characteristic and/or a second sound characteristic which responds to the response confirmation is received or not; and performing emergency alarm when the second action characteristic and/or the second sound characteristic which answer the answer confirmation is not received.
In case of recognizing the user's emergency, in order to reduce the recognition error of the recognition model and the probability of false alarm, the user is acknowledged before the alarm. The response confirmation is issued, for example, by issuing a query voice, asking the user to make a voice query, or asking the user to make a query by displaying text or multimedia on a display screen. The user is asked if an emergency alert is required. If the user's response is not received, the user's life health is considered, and the default is that the user's life health is seriously impaired to fail to respond.
In the above embodiment, if the user makes a voice response, or a motion response. If the need of emergency alarm is confirmed in the reply, emergency alarm is performed. If it is confirmed in the reply that the first aid is not necessary, the first aid alarm is not performed. And in the case of the voice response and/or the motion response of the user, receiving a second motion characteristic and/or a second sound characteristic responding to the response confirmation, inputting the second motion characteristic and/or the second sound characteristic into a second recognition model, and recognizing whether the user responds to the response confirmation or not for emergency warning, wherein the second recognition model is obtained by machine learning training by using a plurality of groups of data, and each group of data in the plurality of groups of data comprises: the second action characteristic and/or the second sound characteristic, and the identification result corresponding to the second action characteristic and/or the second sound characteristic and answering the answer confirmation; and if the second identification model identifies that the user affirms to alarm, the emergency treatment alarm is carried out.
Optionally, the acquiring the continuous first action characteristic and/or the first sound characteristic of the user comprises: collecting images for extracting action characteristics of a user and/or audio for extracting sound characteristics of the user; the first motion feature is extracted from the image and/or the first sound feature is extracted from the audio.
Since the user is in a state of change in sound and/or motion when an emergency occurs, and the recognition process is more accurate and stable based on a series of motions or sound recognition results. In the present embodiment, the sound characteristic and the motion characteristic are both continuously changed over a period of time.
Optionally, after the first recognition model recognizes that the user has an emergency condition that endangers the physical health of the user, the method further includes: receiving physiological data of a user; the physiological data, as well as the images and/or audio, are sent to the medical institution performing the emergency work.
The physiological data, i.e. vital parameters of the user, such as heart rate, pulse, blood pressure, etc. Before receiving the physiological data, the life detection device detects the physiological data of the user, the life monitoring data can be a single instrument, or a life detection component formed by combining a plurality of monitoring instruments, for example, an infrared sensor can monitor the body temperature and the like of the user.
Optionally, when the second recognition model recognizes that the user is alerted in response to the positive acknowledgement, alerting the emergency comprises: sending a first aid request to a medical institution; sending the personal information of the user and the position of the user.
The personal information of the user is transmitted, which is beneficial for medical institutions to know the case in use and reasonably predict and prevent possible complications of the emergency. The location is convenient for emergency personnel of the medical institution to quickly arrive.
FIG. 2 is a schematic diagram of a first aid alarm device according to an embodiment of the present invention; as shown in fig. 2, the emergency alert device 20 includes: an acquisition module 22, a first identification module 24 and a first alarm module 26. The emergency alert device 20 will be described in detail below.
The acquisition module 22 is used for acquiring a first action characteristic and/or a first sound characteristic of a user; a first recognition module 24, connected to the acquisition module 22, for inputting the first motion feature and/or the first sound feature into a first recognition model, and recognizing whether the user has an emergency condition that endangers the physical health of the user, wherein the first recognition model is obtained by machine learning training using a plurality of sets of data, each set of data in the plurality of sets of data includes: the first action characteristic and/or the first sound characteristic and an emergency condition identification result corresponding to the first action characteristic and/or the first sound characteristic; and a first alarm module 26 connected to the first recognition module 24 for alarming for emergency treatment in case that the first recognition module recognizes that the user has an emergency situation endangering the physical health of the user.
Optionally, the emergency alert device 20 further comprises: the sending module is used for sending a response confirmation, and the response confirmation is used for confirming whether emergency alarm is needed or not to the user; a judging module, configured to judge whether a second action feature and/or a second sound feature that responds to the response acknowledgement is received; and the second alarm module is used for alarming for emergency treatment under the condition that the second action characteristic and/or the second sound characteristic which is used for answering the answer confirmation is not received.
Optionally, the emergency alert device 20 further comprises: and the second identification module is used for inputting a second action characteristic and/or a second sound characteristic into a second identification model and identifying whether the user affirms to alarm for emergency treatment or not, wherein the second identification model is obtained by using a plurality of groups of data through machine learning training, and each group of data in the plurality of groups of data comprises: the second action characteristic and/or the second sound characteristic, and the identification result corresponding to the second action characteristic and/or the second sound characteristic and answering the answer confirmation; and the third alarm module is used for giving an emergency alarm under the condition that the second identification model identifies the user to give an alarm by confirming the positive response.
According to another aspect of an embodiment of the present invention, there is provided an emergency alert system, including: collection system and first aid alarm device, wherein, first aid alarm device is any one's device in the above-mentioned.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A method of emergency alert comprising:
collecting a first action characteristic and/or a first sound characteristic of a user;
inputting the first action characteristic and/or the first sound characteristic into a first recognition model, and recognizing whether the user has an emergency condition endangering the physical health of the user, wherein the first recognition model is obtained by machine learning training by using a plurality of groups of data, and each group of data in the plurality of groups of data comprises: the first action characteristic and/or the first sound characteristic and the emergency condition identification result corresponding to the first action characteristic and/or the first sound characteristic;
and when the first recognition model recognizes that the user has an emergency, performing emergency alarm.
2. The method of claim 1, wherein in the event that the recognition model recognizes that an emergency condition occurs in the user, prior to alerting comprises:
sending a response confirmation, wherein the response confirmation is used for confirming whether an emergency alarm is needed or not to the user;
determining whether a second action characteristic and/or a second sound characteristic is received in response to the acknowledgement;
and in the case that the second action characteristic and/or the second sound characteristic which answers the answer confirmation is not received, performing emergency alarm.
3. The method according to claim 2, wherein, in case of receiving a second action characteristic and/or a second sound characteristic in reply to the acknowledgement, comprising:
inputting the second action characteristic and/or the second sound characteristic into a second recognition model, and recognizing whether the user affirms the acknowledgement to alarm for emergency treatment, wherein the second recognition model is obtained by machine learning training by using a plurality of groups of data, and each group of data in the plurality of groups of data comprises: the second action characteristic and/or the second sound characteristic and the identification result corresponding to the second action characteristic and/or the second sound characteristic and answering the answer confirmation;
and when the second recognition model recognizes that the user gives an alarm after confirming the response, giving an emergency alarm.
4. The method of claim 1, wherein capturing a user's continuous first motion characteristic and/or first sound characteristic comprises:
collecting images for extracting action characteristics of a user and/or audio for extracting sound characteristics of the user;
the first motion feature is extracted from the image and/or the first sound feature is extracted from the audio.
5. The method of claim 4, wherein after the first recognition model recognizes that the emergency condition occurs in the user, performing an emergency alert, comprising:
receiving physiological data of a user;
the physiological data, and the image and/or audio, are sent to a medical institution performing emergency work.
6. The method according to any one of claims 1 to 5, wherein in case the second identification model identifies that the user is alerted positive to the acknowledgement, alerting the emergency comprises:
sending a first aid request to a medical institution;
sending the personal information of the user and the position of the user.
7. An emergency alert device, comprising:
the acquisition module is used for acquiring a first action characteristic and/or a first sound characteristic of a user;
a first recognition module, configured to input the first motion feature and/or the first sound feature into a first recognition model, and recognize whether the user has an emergency condition that endangers the physical health of the user, where the first recognition model is obtained by machine learning training using multiple sets of data, and each set of data in the multiple sets of data includes: the first action characteristic and/or the first sound characteristic and the emergency condition identification result corresponding to the first action characteristic and/or the first sound characteristic;
and the first alarm module is used for carrying out emergency alarm under the condition that the first identification model identifies that the user has an emergency.
8. The apparatus of claim 7, wherein the alarm device further comprises:
the system comprises a sending module, a receiving module and a sending module, wherein the sending module is used for sending a response confirmation, and the response confirmation is used for confirming whether emergency alarm is needed or not to a user;
the judging module is used for judging whether a second action characteristic and/or a second sound characteristic which responds to the response confirmation is received or not;
and the second alarm module is used for alarming for emergency treatment under the condition that the second action characteristic and/or the second sound characteristic which is used for answering the answer confirmation is not received.
9. The apparatus of claim 8, wherein the alarm device further comprises:
a second recognition module, configured to input the second motion characteristic and/or the second sound characteristic into a second recognition model, and recognize whether the user affirms the acknowledgement for emergency alert, wherein the second recognition model is obtained by machine learning training using multiple sets of data, and each set of data in the multiple sets of data includes: the second action characteristic and/or the second sound characteristic and the identification result corresponding to the second action characteristic and/or the second sound characteristic and answering the answer confirmation;
and the third alarm module is used for giving an emergency alarm when the second identification model identifies the user to give an alarm after confirming the response.
10. An emergency alert system, comprising: collection system and emergency alert device, wherein the emergency alert device is the device of any one of claims 7 to 9.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116229581A (en) * | 2023-03-23 | 2023-06-06 | 珠海市安克电子技术有限公司 | Intelligent interconnection first-aid system based on big data |
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| CN103514720A (en) * | 2013-09-06 | 2014-01-15 | 徐州海虹建筑工程机械有限公司 | Emergency alarm device of mobile phone |
| CN104574815A (en) * | 2015-01-28 | 2015-04-29 | 西安酷派软件科技有限公司 | First-aid informing method and first-aid informing device based on intelligent wearable equipment |
| CN105468145A (en) * | 2015-11-18 | 2016-04-06 | 北京航空航天大学 | Robot man-machine interaction method and device based on gesture and voice recognition |
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| CN116229581A (en) * | 2023-03-23 | 2023-06-06 | 珠海市安克电子技术有限公司 | Intelligent interconnection first-aid system based on big data |
| CN116229581B (en) * | 2023-03-23 | 2023-09-19 | 珠海市安克电子技术有限公司 | Intelligent interconnection first-aid system based on big data |
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