技术领域Technical Field
本发明涉及设备监控领域，尤其涉及一种智能锁夜间警报方法、装置及计算机设备。The present invention relates to the field of equipment monitoring, and in particular to a smart lock night alarm method, device and computer equipment.
背景技术Background technique
目前智能门锁已经广泛应用到寻常的住宅和办公楼等各个场景，用于进行安全控制。常见的智能锁中搭载了指纹、声音或者视频解锁的功能，可以通过不同的方式进行身份验证和智能解锁，在用户没有携带钥匙时提高了开启门禁的便捷性，但是在夜间情况存在多种危险情况，智能锁仅仅支持智能解锁，并不能满足多种风险状况的合理应对和警报，安全性严重不足。At present, smart door locks have been widely used in various scenarios such as ordinary residences and office buildings for security control. Common smart locks are equipped with fingerprint, voice or video unlocking functions, which can be authenticated and unlocked intelligently in different ways, which improves the convenience of opening the door when the user does not carry a key. However, there are many dangerous situations at night. Smart locks only support intelligent unlocking and cannot meet the reasonable response and alarm of various risk situations, and the security is seriously insufficient.
因此，如何夜间提高智能锁的安全性成为了亟待解决的技术问题。Therefore, how to improve the security of smart locks at night has become a technical problem that needs to be solved urgently.
上述内容仅用于辅助理解本发明的技术方案，并不代表承认上述内容是现有技术。The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art.
发明内容Summary of the invention
本发明的主要目的在于解决如何夜间提高智能锁的安全性的技术问题。The main purpose of the present invention is to solve the technical problem of how to improve the security of smart locks at night.
为实现上述目的，本发明提供了一种智能锁夜间警报方法，所述智能锁夜间警报方法包括以下步骤：To achieve the above object, the present invention provides a smart lock night alarm method, the smart lock night alarm method comprising the following steps:
采集夜间监控信息；Collect nighttime monitoring information;
根据所述夜间监控信息确定人脸识别结果；Determining a face recognition result according to the nighttime monitoring information;
根据所述人脸识别结果确定风险判定结果；Determine a risk assessment result based on the face recognition result;
根据所述风险判定结果进行夜间警报。A nighttime alarm is issued according to the risk determination result.
可选地，所述根据所述夜间监控信息确定人脸识别结果，包括：Optionally, determining the face recognition result according to the nighttime monitoring information includes:
根据所述夜间监控信息确定人脸识别信息；determining facial recognition information according to the nighttime monitoring information;
根据所述人脸识别信息确定首要识别目标和次要识别目标；Determining a primary recognition target and a secondary recognition target according to the face recognition information;
根据所述首要识别目标和所述次要识别目标确定人脸识别结果。A face recognition result is determined according to the primary recognition target and the secondary recognition target.
可选地，所述根据所述首要识别目标和所述次要识别目标确定人脸识别结果，包括：Optionally, determining the face recognition result according to the primary recognition target and the secondary recognition target includes:
对所述首要识别目标进行人脸识别，得到首要识别结果；Performing face recognition on the primary recognition target to obtain a primary recognition result;
在所述首要识别结果为识别通过时，对所述次要识别目标进行人脸识别，得到次要识别结果；When the primary recognition result is recognition passed, performing face recognition on the secondary recognition target to obtain a secondary recognition result;
根据所述首要识别结果和所述次要识别结果确定人脸识别结果。A face recognition result is determined according to the primary recognition result and the secondary recognition result.
可选地，所述根据所述人脸识别结果确定风险判定结果，包括：Optionally, determining a risk determination result according to the face recognition result includes:
根据所述人脸识别结果确定所述首要识别结果和所述次要识别结果；Determining the primary recognition result and the secondary recognition result according to the face recognition result;
根据所述首要识别结果和所述次要识别结果确定尾随风险判定结果；Determining a tailgating risk determination result according to the primary identification result and the secondary identification result;
根据所述首要识别结果确定醉酒风险判定结果；Determining a drunkenness risk determination result based on the primary identification result;
根据所述尾随风险判定结果和所述醉酒风险判定结果确定风险判定结果。A risk determination result is determined according to the tailgating risk determination result and the drunkenness risk determination result.
可选地，所述根据所述首要识别结果和所述次要识别结果确定尾随风险判定结果，包括：Optionally, determining the tailgating risk determination result according to the primary recognition result and the secondary recognition result includes:
根据所述首要识别结果确定主要识别人身份信息；Determine the identity information of the primary identifier based on the primary identification result;
根据所述次要识别结果确定次要识别人身份信息；Determining the secondary identifier identity information based on the secondary identification result;
根据所述主要识别人身份信息和所述次要识别人身份信息确定尾随风险判定结果。The tailgating risk determination result is determined based on the primary identifier identity information and the secondary identifier identity information.
可选地，所述根据所述主要识别人身份信息和所述次要识别人身份信息确定尾随风险判定结果，包括：Optionally, determining the tailgating risk determination result according to the primary identifier identity information and the secondary identifier identity information includes:
在所述主要识别人身份信息为白名单身份时，向所述首要识别目标发送验证指令；When the identity information of the primary identifier is a whitelist identity, sending a verification instruction to the primary identification target;
根据所述首要识别目标反馈的验证确认信息确定所述次要识别人身份信息的验证结果；Determine the verification result of the secondary identification person's identity information according to the verification confirmation information fed back by the primary identification target;
根据所述验证结果确定尾随风险判定结果。A tailgating risk determination result is determined according to the verification result.
可选地，所述根据所述首要识别结果确定醉酒风险判定结果，包括：Optionally, determining the drunkenness risk determination result according to the primary recognition result includes:
根据所述首要识别结果确定人脸识别图像；Determining a face recognition image according to the primary recognition result;
根据所述人脸识别图像确定夜间脸部灰度图像；Determine a nighttime facial grayscale image according to the facial recognition image;
根据所述夜间脸部灰度图像确定脸部颜色对比信息；Determining facial color contrast information according to the nighttime facial grayscale image;
根据所述脸部颜色对比信息确定醉酒风险判定结果Determine the drunkenness risk determination result according to the facial color comparison information
此外，为实现上述目的，本发明还提出一种智能锁夜间警报装置，所述智能锁夜间警报装置包括：In addition, to achieve the above-mentioned purpose, the present invention also proposes a smart lock night alarm device, the smart lock night alarm device comprising:
信息采集模块，用于采集夜间监控信息；Information collection module, used to collect nighttime monitoring information;
人脸识别模块，用于根据所述夜间监控信息确定人脸识别结果；A face recognition module, used to determine a face recognition result based on the nighttime monitoring information;
风险判定模块，用于根据所述人脸识别结果确定风险判定结果；A risk determination module, used to determine a risk determination result according to the face recognition result;
夜间警报模块，用于根据所述风险判定结果进行夜间警报。The night alarm module is used to issue a night alarm according to the risk determination result.
此外，为实现上述目的，本发明还提出一种计算机设备，所述计算机设备包括：存储器、处理器，所述处理器在运行所述存储器存储的计算机指令时，执行如上文所述的方法。In addition, to achieve the above object, the present invention further proposes a computer device, which includes: a memory and a processor, and when the processor runs the computer instructions stored in the memory, it executes the method described above.
此外，为实现上述目的，本发明还提出一种介质，包括指令，当所述指令在计算机设备上运行时，使得计算机设备执行如上文所述的方法。In addition, to achieve the above objective, the present invention further proposes a medium, comprising instructions, which, when executed on a computer device, enable the computer device to execute the method described above.
本发明采集夜间监控信息；根据所述夜间监控信息确定人脸识别结果；根据所述人脸识别结果确定风险判定结果；根据所述风险判定结果进行夜间警报。通过对夜间监控信息进行人脸识别和综合的风险判定确定是否进行夜间警报，从而实现基于人脸识别结果从多个维度进行风险判定，提高单个智能锁在夜间情况下的安全性。The present invention collects nighttime monitoring information; determines face recognition results based on the nighttime monitoring information; determines risk determination results based on the face recognition results; and issues nighttime alarms based on the risk determination results. By performing face recognition and comprehensive risk determination on the nighttime monitoring information to determine whether to issue a nighttime alarm, risk determination is performed from multiple dimensions based on face recognition results, thereby improving the safety of a single smart lock at night.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
图1是本申请实施例方案涉及的硬件运行环境的计算机设备结构示意图；FIG1 is a schematic diagram of a computer device structure of a hardware operating environment involved in an embodiment of the present application;
图2是本申请智能锁夜间警报方法第一实施例的流程示意图；FIG2 is a flow chart of a first embodiment of a method for nighttime alarm of a smart lock of the present application;
图3是本申请智能锁夜间警报方法第二实施例的流程示意图；FIG3 is a flow chart of a second embodiment of the night alarm method for a smart lock of the present application;
图4是本申请智能锁夜间警报装置第一实施例的结构框图。FIG4 is a structural block diagram of the first embodiment of the smart lock night alarm device of the present application.
本发明目的的实现、功能特点及优点将结合实施例，参照附图做进一步说明。The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings.
具体实施方式Detailed ways
为了使本申请的目的、技术方案及优点更加清楚明白，以下通过附图及实施例，对本申请进行进一步详细说明。应当理解，此处所描述的具体实施例仅用以解释本申请，并不用于限定本申请。In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below through the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
参照图1，图1为本发明实施例方案涉及的硬件运行环境的计算机设备结构示意图。Refer to FIG. 1 , which is a schematic diagram of a computer device structure of a hardware operating environment involved in an embodiment of the present invention.
如图1所示，计算机设备可以包括：处理器1001，例如中央处理器(CentralProcessing Unit，CPU)，通信总线1002、用户接口1003，网络接口1004，存储器1005。其中，通信总线1002用于实现这些组件之间的连接通信。用户接口1003可以包括显示屏(Display)、输入单元比如键盘(Keyboard)，可选用户接口1003还可以包括标准的有线接口、无线接口。网络接口1004可选的可以包括标准的有线接口、无线接口(如无线保真(Wireless-Fidelity，Wi-Fi)接口)。存储器1005可以是高速的随机存取存储器(RandomAccess Memory，RAM)，也可以是稳定的非易失性存储器(Non-Volatile Memory，NVM)，例如磁盘存储器。存储器1005可选的还可以是独立于前述处理器1001的存储装置。As shown in FIG1 , the computer device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM), or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.
本领域技术人员可以理解，图1中示出的结构并不构成对计算机设备的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。Those skilled in the art will appreciate that the structure shown in FIG. 1 does not constitute a limitation on the computer device, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.
如图1所示，作为一种存储介质的存储器1005中可以包括操作系统、网络通信模块、用户接口模块以及智能锁夜间警报程序。As shown in FIG. 1 , the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a smart lock night alarm program.
在图1所示的计算机设备中，网络接口1004主要用于与网络服务器进行数据通信；用户接口1003主要用于与用户进行数据交互；本发明计算机设备中的处理器1001、存储器1005可以设置计算机设备中，所述计算机设备通过处理器1001调用存储器1005中存储的智能锁夜间警报程序，并执行本发明实施例提供的智能锁夜间警报方法。In the computer device shown in Figure 1, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the computer device of the present invention can be set in the computer device, and the computer device calls the smart lock night alarm program stored in the memory 1005 through the processor 1001, and executes the smart lock night alarm method provided by the embodiment of the present invention.
本发明实施例提供了一种智能锁夜间警报方法，参照图2，图2为本发明智能锁夜间警报方法第一实施例的流程示意图。An embodiment of the present invention provides a smart lock night alarm method, referring to FIG. 2 , which is a schematic flow chart of a first embodiment of the smart lock night alarm method of the present invention.
本实施例中，所述智能锁夜间警报方法包括以下步骤：In this embodiment, the smart lock night alarm method includes the following steps:
步骤S10：采集夜间监控信息。Step S10: Collect nighttime monitoring information.
需要说明的是，本实施例的方案中，执行主体可以为任意的智能终端，例如：计算机、笔记本电脑、服务器或者智能手机，也可以为其他的具有信息处理功能的智能设备，本实施例对此不加以限定。It should be noted that in the solution of this embodiment, the execution subject can be any intelligent terminal, such as a computer, a laptop, a server or a smart phone, or other intelligent devices with information processing functions, which is not limited in this embodiment.
应理解的是，目前智能门锁已经广泛应用到寻常的住宅和办公楼等各个场景，用于进行安全控制。常见的智能锁中搭载了指纹、声音或者视频解锁的功能，可以通过不同的方式进行身份验证和智能解锁，在用户没有携带钥匙时提高了开启门禁的便捷性，但是在夜间情况存在多种危险情况，智能锁仅仅支持智能解锁，并不能满足多种风险状况的合理应对和警报，安全性严重不足。因此，如何夜间提高智能锁的安全性成为了亟待解决的技术问题。而采用本实施例的方案采集夜间监控信息；根据所述夜间监控信息确定人脸识别结果；根据所述人脸识别结果确定风险判定结果；根据所述风险判定结果进行夜间警报。通过对夜间监控信息进行人脸识别和综合的风险判定确定是否进行夜间警报，从而实现基于人脸识别结果从多个维度进行风险判定，提高单个智能锁在夜间情况下的安全性。It should be understood that smart door locks have been widely used in various scenarios such as ordinary residences and office buildings for security control. Common smart locks are equipped with fingerprint, sound or video unlocking functions, which can be used for identity authentication and smart unlocking in different ways, which improves the convenience of opening the door when the user does not carry a key. However, there are many dangerous situations at night. Smart locks only support smart unlocking and cannot meet the reasonable response and alarm of various risk conditions, and the security is seriously insufficient. Therefore, how to improve the security of smart locks at night has become a technical problem that needs to be solved urgently. The scheme of this embodiment is used to collect night monitoring information; determine the face recognition result according to the night monitoring information; determine the risk determination result according to the face recognition result; and perform a night alarm according to the risk determination result. By performing face recognition and comprehensive risk determination on the night monitoring information to determine whether to perform a night alarm, risk determination from multiple dimensions based on the face recognition result is achieved, thereby improving the security of a single smart lock at night.
在具体实施中，夜间监控信息指的是智能锁的视频采集模块，或者智能锁的外接视频采集设备采集到的申请解锁智能锁的识别视频信息。In a specific implementation, nighttime monitoring information refers to the identification video information of the smart lock that is applied to unlock the smart lock, which is collected by the video acquisition module of the smart lock or the external video acquisition device of the smart lock.
步骤S20：根据所述夜间监控信息确定人脸识别结果。Step S20: determining a face recognition result according to the nighttime monitoring information.
需要说明的是，在采集到了夜间监控信息之后，对夜间监控信息中的人脸识别信息进行拆分，从而得到对于门前的人脸识别的首要识别目标和次要识别目标，进而确定人脸识别结果。It should be noted that after collecting the nighttime monitoring information, the face recognition information in the nighttime monitoring information is split to obtain the primary recognition target and the secondary recognition target for the face recognition in front of the door, and then determine the face recognition result.
步骤S30：根据所述人脸识别结果确定风险判定结果。Step S30: Determine a risk assessment result based on the face recognition result.
应理解的是，在确定人脸识别结果之后，再根据人脸识别结果中的首要识别结果和次要识别结果对风险进行判定，从而确定此时的智能锁解锁场景中是否存在风险。It should be understood that after determining the face recognition result, the risk is judged based on the primary recognition result and the secondary recognition result in the face recognition result to determine whether there is a risk in the smart lock unlocking scenario at this time.
步骤S40：根据所述风险判定结果进行夜间警报。Step S40: issuing a night alarm according to the risk determination result.
在具体实施中，在得到风险判定结果之后，基于风险判定结果中存在两个判定结果，分别为尾随风险判定结果和醉酒风险判定结果，在尾随风险判定结果和醉酒风险判定结果中的任意一个为存在风险，或者尾随风险判定结果与醉酒风险判定结果均为存在风险时，向智能锁绑定的用户进行预警，并上传云平台进行广播预警。In the specific implementation, after obtaining the risk assessment result, based on the fact that there are two assessment results in the risk assessment result, namely, the following risk assessment result and the drunk risk assessment result, when any one of the following risk assessment result and the drunk risk assessment result is a risk, or when both the following risk assessment result and the drunk risk assessment result are a risk, an early warning is issued to the user bound to the smart lock, and the warning is uploaded to the cloud platform for broadcasting.
需要说明的是，在存在尾随风险时，在云平台进行上传报备，并向用户发送确认信息，在预设时间内没有收到回复时，自动报警。在存在醉酒风险时，向智能锁绑定的备用用户发送提醒，并解锁。It should be noted that when there is a risk of being followed, the cloud platform will upload a report and send a confirmation message to the user. If no reply is received within the preset time, an alarm will be automatically sounded. When there is a risk of drunkenness, a reminder will be sent to the backup user bound to the smart lock and the lock will be unlocked.
本实施例通过采集夜间监控信息；根据所述夜间监控信息确定人脸识别结果；根据所述人脸识别结果确定风险判定结果；根据所述风险判定结果进行夜间警报。通过对夜间监控信息进行人脸识别和综合的风险判定确定是否进行夜间警报，从而实现基于人脸识别结果从多个维度进行风险判定，提高单个智能锁在夜间情况下的安全性。This embodiment collects nighttime monitoring information; determines face recognition results based on the nighttime monitoring information; determines risk determination results based on the face recognition results; and issues nighttime alarms based on the risk determination results. By performing face recognition and comprehensive risk determination on the nighttime monitoring information to determine whether to issue a nighttime alarm, risk determination is performed from multiple dimensions based on face recognition results, thereby improving the safety of a single smart lock at night.
参考图3，图3为本发明智能锁夜间警报方法第二实施例的流程示意图。Refer to FIG. 3 , which is a flow chart of a second embodiment of a night alarm method for a smart lock according to the present invention.
基于上述第一实施例，本实施例智能锁夜间警报方法的所述步骤S20包括：Based on the first embodiment described above, step S20 of the smart lock night alarm method of this embodiment includes:
步骤S201：根据所述夜间监控信息确定人脸识别信息。Step S201: determining face recognition information according to the nighttime monitoring information.
需要说明的是，首先根据夜间监控信息确定人脸识别信息，具体的，根据夜间监控信息确定在视频画面中截取到的人脸画面，便于后续进行人脸识别。It should be noted that the face recognition information is first determined based on the nighttime monitoring information. Specifically, the face image captured in the video image is determined based on the nighttime monitoring information to facilitate subsequent face recognition.
步骤S202：根据所述人脸识别信息确定首要识别目标和次要识别目标。Step S202: determining a primary recognition target and a secondary recognition target according to the face recognition information.
应理解的是，在得到人脸识别信息之后，对人脸识别信息进行目标分类，即将识别到的人脸进行分类，将智能锁的视频采集设备中距离最近，人脸画面的面积最大的目标作为首要识别目标，将除去首要识别目标的其他目标作为次要识别目标。其中，次要识别目标可以为任意数目，例如：0个、1个或者2个，本实施例对此不加以限定。It should be understood that after obtaining the face recognition information, the face recognition information is subjected to target classification, that is, the recognized faces are classified, and the target with the closest distance and the largest face image area in the video acquisition device of the smart lock is taken as the primary recognition target, and the other targets except the primary recognition target are taken as secondary recognition targets. Among them, the secondary recognition targets can be any number, for example: 0, 1 or 2, which is not limited in this embodiment.
步骤S203：根据所述首要识别目标和所述次要识别目标确定人脸识别结果。Step S203: determining a face recognition result according to the primary recognition target and the secondary recognition target.
在具体实施中，在得到首要识别目标和次要识别目标之后，对首要识别目标和次要识别目标分别进行人脸识别和身份验证，得到了首要识别结果和次要识别结果，从而确定人脸识别结果。In a specific implementation, after obtaining the primary recognition target and the secondary recognition target, face recognition and identity verification are performed on the primary recognition target and the secondary recognition target respectively, and the primary recognition result and the secondary recognition result are obtained, thereby determining the face recognition result.
进一步的，为了准确的得到人脸识别结果，步骤S203包括：对所述首要识别目标进行人脸识别，得到首要识别结果；在所述首要识别结果为识别通过时，对所述次要识别目标进行人脸识别，得到次要识别结果；根据所述首要识别结果和所述次要识别结果确定人脸识别结果。Furthermore, in order to accurately obtain face recognition results, step S203 includes: performing face recognition on the primary recognition target to obtain a primary recognition result; when the primary recognition result is a passed recognition, performing face recognition on the secondary recognition target to obtain a secondary recognition result; determining the face recognition result based on the primary recognition result and the secondary recognition result.
需要说明的是，首先对首要识别目标进行人脸识别和身份验证，得到首要识别结果，首要识别结果中还包括了首要识别目标的人脸识别的结果，以及与预设的身份库中的名单进行比对的结果。It should be noted that the face recognition and identity verification are first performed on the primary identification target to obtain the primary identification result, which also includes the face recognition result of the primary identification target and the result of comparison with the list in the preset identity library.
应理解的是，在得到首要识别结果之后，如果首要识别结果为识别通过，则继续对次要识别目标进行人脸识别和身份验证，得到次要识别结果。如果首要识别结果为识别不通过，则直接进行夜间警报，此时的申请解锁的对象不为用户本人或者拥有权限的用户。具体的，识别是否通过的标准为将首要识别结果与后台数据库进行比对，确定是否为用户本人或者拥有权限的用户。It should be understood that after obtaining the primary recognition result, if the primary recognition result is a pass, the face recognition and identity verification of the secondary recognition target will be continued to obtain a secondary recognition result. If the primary recognition result is a fail, a night alarm will be directly issued, and the object of the unlocking application at this time is not the user himself or the user with permission. Specifically, the standard for whether the recognition is passed is to compare the primary recognition result with the background database to determine whether it is the user himself or the user with permission.
进一步的，在得到了人脸识别结果之后，为了准确的进行风险判定，根据所述人脸识别结果确定风险判定结果的步骤包括：根据所述人脸识别结果确定所述首要识别结果和所述次要识别结果；根据所述首要识别结果和所述次要识别结果确定尾随风险判定结果；根据所述首要识别结果确定醉酒风险判定结果；根据所述尾随风险判定结果和所述醉酒风险判定结果确定风险判定结果。Furthermore, after obtaining the face recognition result, in order to accurately perform risk assessment, the step of determining the risk assessment result based on the face recognition result includes: determining the primary recognition result and the secondary recognition result based on the face recognition result; determining the tailing risk assessment result based on the primary recognition result and the secondary recognition result; determining the drunk risk assessment result based on the primary recognition result; determining the risk assessment result based on the tailing risk assessment result and the drunk risk assessment result.
在具体实施中，首先拆分和调取出人脸识别结果中的首要识别结果和次要识别结果，然后基于首要识别结果和次要识别结果确定尾随风险判定结果，再基于首要识别结果进行醉酒风险判定结果，最后结合尾随风险判定结果和醉酒风险判定结果进行完整的风险判定结果的确定。In the specific implementation, the primary recognition result and the secondary recognition result in the face recognition result are first split and retrieved, and then the following risk determination result is determined based on the primary recognition result and the secondary recognition result, and then the drunk risk determination result is determined based on the primary recognition result, and finally the complete risk determination result is determined by combining the following risk determination result and the drunk risk determination result.
进一步的，为了准确的确定尾随风险判定结果，根据所述首要识别结果和所述次要识别结果确定尾随风险判定结果的步骤包括：根据所述首要识别结果确定主要识别人身份信息；根据所述次要识别结果确定次要识别人身份信息；根据所述主要识别人身份信息和所述次要识别人身份信息确定尾随风险判定结果。Furthermore, in order to accurately determine the tailgating risk determination result, the step of determining the tailgating risk determination result based on the primary identification result and the secondary identification result includes: determining the primary identifier identity information based on the primary identification result; determining the secondary identifier identity information based on the secondary identification result; determining the tailgating risk determination result based on the primary identifier identity information and the secondary identifier identity information.
需要说明的是，首先确定主要识别人身份信息，即首要识别结果中的人物的身份信息，结合次要识别结果中的次要识别人身份信息，判定是否存在尾随风险判定结果。It should be noted that the identity information of the primary identifier, that is, the identity information of the person in the primary identification result, is first determined, and combined with the identity information of the secondary identifier in the secondary identification result to determine whether there is a tailgating risk determination result.
应理解的是，具体判定是否存在尾随风险的判定结果的方式为：首先确定主要识别人身份信息是否为白名单身份，然后再确定次要识别人身份的验证结果，从而确定最终的尾随风险判定。It should be understood that the specific method for determining whether there is a tailgating risk is to first determine whether the primary identifier's identity information is a whitelist identity, and then determine the verification result of the secondary identifier's identity, thereby determining the final tailgating risk determination.
进一步的，为了分别进行主要识别人身份信息和次要识别人身份信息的身份验证确定尾随风险判定结果，根据所述主要识别人身份信息和所述次要识别人身份信息确定尾随风险判定结果的步骤包括：在所述主要识别人身份信息为白名单身份时，向所述首要识别目标发送验证指令；根据所述首要识别目标反馈的验证确认信息确定所述次要识别人身份信息的验证结果；根据所述验证结果确定尾随风险判定结果。Furthermore, in order to perform identity authentication of the primary identifier and the secondary identifier respectively to determine the tailgating risk determination result, the step of determining the tailgating risk determination result based on the primary identifier and the secondary identifier includes: when the primary identifier is a whitelist identity, sending a verification instruction to the primary identification target; determining the verification result of the secondary identifier based on the verification confirmation information fed back by the primary identification target; and determining the tailgating risk determination result based on the verification result.
在具体实施中，首先确定主要识别人身份信息中的身份是否为白名单身份，其中，白名单身份指的是预先设置并储存的允许解锁智能锁的身份。In a specific implementation, it is first determined whether the identity in the primary identifier's identity information is a whitelist identity, wherein the whitelist identity refers to a pre-set and stored identity that is allowed to unlock the smart lock.
需要说明的是，在确定主要识别人身份信息时，确定主要识别人为允许解锁的身份，此时继续确认次要识别人身份信息，从而确定是否存在尾随的风险。It should be noted that when determining the identity information of the primary identifier, the primary identifier is determined to be the identity allowed to unlock, and at this time, the identity information of the secondary identifier continues to be confirmed to determine whether there is a risk of being followed.
应理解的是，确认次要识别人身份信息是通过首要识别目标反馈的验证确认信息实现的，在确定主要识别人身份信息为白名单身份之后，通过智能锁向首要识别目标对应的智能终端发送验证指令，用于向首要识别目标确定跟随人的身份，其中，验证指令的形式可以为语音、密码或者手势等认证方式，本实施例对此不加以限定。在接收到首要识别目标根据验证指令反馈的验证确认信息之后，根据反馈的验证确认信息确认是否有效，以及首要识别目标是否认可次要识别目标为同行的人，从而确定是否存在尾随风险，进而得到尾随风险判定结果。It should be understood that the confirmation of the identity information of the secondary identification person is achieved through the verification confirmation information fed back by the primary identification target. After determining that the identity information of the primary identification person is a whitelist identity, a verification instruction is sent to the smart terminal corresponding to the primary identification target through the smart lock to determine the identity of the follower to the primary identification target, wherein the verification instruction can be in the form of voice, password or gesture authentication methods, which is not limited in this embodiment. After receiving the verification confirmation information fed back by the primary identification target according to the verification instruction, confirm whether it is valid according to the feedback verification confirmation information, and whether the primary identification target recognizes the secondary identification target as a person traveling with it, so as to determine whether there is a risk of tailing, and then obtain the tailing risk determination result.
进一步的，为了基于首要识别结果确定是否存在醉酒情况需要进行预警，根据所述首要识别结果确定醉酒风险判定结果的步骤包括：根据所述首要识别结果确定人脸识别图像和人物动作图像；根据所述人脸识别图像确定夜间脸部灰度图像；根据所述夜间脸部灰度图像确定脸部颜色对比信息；根据所述脸部颜色对比信息确定面部判定结果；根据所述人物动作图像判定是否存在醉酒行为，得到行为判定结果；根据所述面部判定结果和所述行为判定结果确定醉酒风险判定结果。Furthermore, in order to determine whether there is a drunken situation that requires an early warning based on the primary recognition result, the step of determining the drunken risk determination result based on the primary recognition result includes: determining a face recognition image and a character action image based on the primary recognition result; determining a nighttime face grayscale image based on the face recognition image; determining face color contrast information based on the nighttime face grayscale image; determining a face determination result based on the face color contrast information; determining whether there is drunken behavior based on the character action image to obtain a behavior determination result; and determining a drunken risk determination result based on the face determination result and the behavior determination result.
在具体实施中，首先根据首要识别结果确定人脸识别图像，即从首要识别结果中将人脸识别图像调取，得到人脸识别图像，由于此时为夜间场景，所以人脸识别图像的颜色展示并不完全，此时为了验证人脸的状态，将人脸识别图像进行灰度转换，得到夜间脸部灰度图像。In the specific implementation, the face recognition image is first determined according to the primary recognition result, that is, the face recognition image is retrieved from the primary recognition result to obtain the face recognition image. Since it is a night scene, the color display of the face recognition image is not complete. At this time, in order to verify the state of the face, the face recognition image is converted into grayscale to obtain a night face grayscale image.
需要说明的是，在一般情况下，人出现醉酒状况时，脸部颜色会显现出偏红色，而展现在夜间脸部灰度图像即为灰度更深，所以此时得到的夜间脸部灰度图像中可以展示出人脸识别图像中的对象在脸部颜色的变化，从而根据夜间脸部灰度图像确定脸部颜色对比信息。It should be noted that, under normal circumstances, when a person is drunk, the color of his face will appear reddish, and the grayscale image of the face displayed at night is a darker gray. Therefore, the night grayscale image of the face obtained at this time can show the changes in the facial color of the object in the face recognition image, thereby determining the facial color contrast information based on the night grayscale image of the face.
应理解的是，在得到了脸部颜色对比信息之后，根据所述脸部颜色对比信息确定颜色异常部位，此处的颜色异常部位为脸部颜色与普通的灰度颜色相比异常的部位。在确定了颜色异常部位之后，将颜色异常部位从画面中截取，然后计算颜色异常部位的图像面积，得到异常部位面积。It should be understood that after obtaining the facial color contrast information, the color abnormal part is determined according to the facial color contrast information, where the color abnormal part is a part of the face where the color is abnormal compared to the normal grayscale color. After determining the color abnormal part, the color abnormal part is intercepted from the picture, and then the image area of the color abnormal part is calculated to obtain the abnormal part area.
在具体实施中，在得到异常部位面积之后，确定异常部位面积与完整的人脸面积之间的差值，从而确定异常部位面积占完整人脸面积的百分比，作为异常颜色占比，最后根据异常颜色占比确定醉酒风险判定结果。In the specific implementation, after obtaining the area of the abnormal part, the difference between the area of the abnormal part and the area of the complete face is determined, so as to determine the percentage of the area of the abnormal part to the complete face area, which is used as the abnormal color ratio. Finally, the drunkenness risk judgment result is determined based on the abnormal color ratio.
需要说明的是，在确定异常颜色占比之后，将异常颜色占比与醉酒占比阈值进行比较，从而确定面部判定结果。具体的，在异常颜色占比大于或者等于醉酒占比阈值时，判定面部判定结果为存在醉酒风险。在异常颜色占比小于醉酒占比阈值时，判定面部判定结果为不存在醉酒风险。It should be noted that after determining the abnormal color ratio, the abnormal color ratio is compared with the drunkenness ratio threshold to determine the face determination result. Specifically, when the abnormal color ratio is greater than or equal to the drunkenness ratio threshold, the face determination result is determined to be a risk of drunkenness. When the abnormal color ratio is less than the drunkenness ratio threshold, the face determination result is determined to be no risk of drunkenness.
应理解的是，为了准确的判定是否存在醉酒风险，本实施例的方案中还可以从夜间监控信息中调取首要识别目标对应的人物动作图像，进而根据人物动作图像判定是否存在醉酒风险。It should be understood that in order to accurately determine whether there is a risk of drunkenness, the solution of this embodiment can also retrieve the character action image corresponding to the primary identification target from the night monitoring information, and then determine whether there is a risk of drunkenness based on the character action image.
在具体实施中，在获取到人物动作图像之后，根据人物动作图像确定首要识别目标是否存在醉酒行为，具体为：眼部视线移动迅速，且肢体动作幅度大或者不受控制等。In a specific implementation, after acquiring the character action image, it is determined whether the primary identification target has drunken behavior based on the character action image, specifically: the eye sight moves quickly, and the body movements are large or uncontrolled.
需要说明的是，在获取到人物动作图像之后，根据人物动作图像确定人物视线信息和肢体动作信息，然后根据人物视线信息确定视线移动信息和视线偏移速度，然后根据视线移动信息和视线偏移速度确定是否存在视线异常。具体的，在视线移动信息中的移动轨迹结合视线偏移速度结合云平台的大数据进行分析，确定是否为视线异常。It should be noted that after obtaining the character action image, the character's sight information and body movement information are determined according to the character action image, and then the sight movement information and sight deviation speed are determined according to the character's sight information, and then whether there is a sight abnormality is determined according to the sight movement information and the sight deviation speed. Specifically, the movement trajectory in the sight movement information is combined with the sight deviation speed and the big data of the cloud platform for analysis to determine whether there is a sight abnormality.
应理解的是，在得到肢体动作信息之后，将肢体动作信息进行拆解，得到动作幅度信息和动作速率信息，将动作幅度信息和动作速率信息输入到预先训练的动作分析模型中，判定肢体动作是否存在异常，具体的，动作分析模型为预先训练的深度学习模型，通过预先输入醉酒状态下的人的肢体动作样本作为训练集进行训练，可以根据动作幅度信息和动作速率信息进行分析，从而确定目标对象是否存在醉酒状态下的肢体动作异常。It should be understood that after obtaining the limb movement information, the limb movement information is disassembled to obtain movement amplitude information and movement rate information, and the movement amplitude information and movement rate information are input into a pre-trained movement analysis model to determine whether there is any abnormality in the limb movement. Specifically, the movement analysis model is a pre-trained deep learning model, which is trained by pre-inputting limb movement samples of people in a drunken state as a training set. It can be analyzed based on the movement amplitude information and movement rate information to determine whether the target object has abnormal limb movements in a drunken state.
在具体实施中，在确定了视线异常和肢体动作异常的异常判定结果之后，在视线异常和肢体动作异常中存在至少一项，则判定行为判定结果为存在醉酒行为。在视线异常和肢体动作异常中均不存在，则判定行为判定结果为不存在醉酒行为。In a specific implementation, after determining the abnormality determination results of abnormal vision and abnormal limb movement, if at least one of the abnormal vision and abnormal limb movement exists, the behavior determination result is determined to be the presence of drunken behavior. If neither the abnormal vision nor the abnormal limb movement exists, the behavior determination result is determined to be the absence of drunken behavior.
需要说明的是，在得到面部判定结果和行为判定结果之后，结合行为判定结果和面部判定结果确定最终的醉酒风险判定结果，具体的，如果行为判定结果和面部判定结果均为判定存在醉酒风险和醉酒行为，则醉酒风险判定结果为存在醉酒风险。It should be noted that after obtaining the facial judgment results and the behavioral judgment results, the final drunkenness risk judgment result is determined in combination with the behavioral judgment results and the facial judgment results. Specifically, if the behavioral judgment results and the facial judgment results both determine that there is a drunkenness risk and drunken behavior, then the drunkenness risk judgment result is that there is a drunkenness risk.
本实施例通过根据所述夜间监控信息确定人脸识别信息；根据所述人脸识别信息确定首要识别目标和次要识别目标；根据所述首要识别目标和所述次要识别目标确定人脸识别结果。通过这种方式，实现了在夜间视野不佳的情况下通过视频采集设备的夜间监控信息进行人脸识别，并分别对首要识别目标和次要识别目标分别进行身份验证，得到人脸识别结果，提高了智能锁的安全性，有效防止尾随等安全隐患。This embodiment determines the face recognition information according to the nighttime monitoring information; determines the primary recognition target and the secondary recognition target according to the face recognition information; and determines the face recognition result according to the primary recognition target and the secondary recognition target. In this way, face recognition is achieved through the nighttime monitoring information of the video acquisition device in the case of poor nighttime vision, and identity authentication is performed on the primary recognition target and the secondary recognition target respectively to obtain the face recognition result, thereby improving the security of the smart lock and effectively preventing safety hazards such as tailgating.
此外，本发明实施例还提出一种介质，所述存储介质上存储有智能锁夜间警报的程序，所述智能锁夜间警报的程序被处理器执行时实现如上文所述的智能锁夜间警报的方法的步骤。In addition, an embodiment of the present invention further proposes a medium, on which a program for a smart lock night alarm is stored. When the program for a smart lock night alarm is executed by a processor, the steps of the method for a smart lock night alarm as described above are implemented.
参照图4，图4为本发明智能锁夜间警报装置第一实施例的结构框图。Referring to FIG. 4 , FIG. 4 is a structural block diagram of a first embodiment of a night alarm device for a smart lock according to the present invention.
如图4所示，本发明实施例提出的智能锁夜间警报装置包括：As shown in FIG4 , the smart lock night alarm device provided in the embodiment of the present invention includes:
信息采集模块10，用于采集夜间监控信息。The information collection module 10 is used to collect nighttime monitoring information.
人脸识别模块20，用于根据所述夜间监控信息确定人脸识别结果。The face recognition module 20 is used to determine the face recognition result according to the nighttime monitoring information.
风险判定模块30，用于根据所述人脸识别结果确定风险判定结果。The risk determination module 30 is used to determine the risk determination result according to the face recognition result.
夜间警报模块40，用于根据所述风险判定结果进行夜间警报。The night alarm module 40 is used to issue a night alarm according to the risk determination result.
本实施例通过采集夜间监控信息；根据所述夜间监控信息确定人脸识别结果；根据所述人脸识别结果确定风险判定结果；根据所述风险判定结果进行夜间警报。通过对夜间监控信息进行人脸识别和综合的风险判定确定是否进行夜间警报，从而实现基于人脸识别结果从多个维度进行风险判定，提高单个智能锁在夜间情况下的安全性。This embodiment collects nighttime monitoring information; determines face recognition results based on the nighttime monitoring information; determines risk determination results based on the face recognition results; and issues nighttime alarms based on the risk determination results. By performing face recognition and comprehensive risk determination on the nighttime monitoring information to determine whether to issue a nighttime alarm, risk determination is performed from multiple dimensions based on face recognition results, thereby improving the safety of a single smart lock at night.
在一实施例中，所述人脸识别模块20，还用于根据所述夜间监控信息确定人脸识别信息；根据所述人脸识别信息确定首要识别目标和次要识别目标；根据所述首要识别目标和所述次要识别目标确定人脸识别结果。In one embodiment, the face recognition module 20 is further used to determine face recognition information based on the nighttime monitoring information; determine a primary recognition target and a secondary recognition target based on the face recognition information; and determine a face recognition result based on the primary recognition target and the secondary recognition target.
在一实施例中，所述人脸识别模块20，还用于对所述首要识别目标进行人脸识别，得到首要识别结果；在所述首要识别结果为识别通过时，对所述次要识别目标进行人脸识别，得到次要识别结果；根据所述首要识别结果和所述次要识别结果确定人脸识别结果。In one embodiment, the face recognition module 20 is also used to perform face recognition on the primary recognition target to obtain a primary recognition result; when the primary recognition result is recognition passed, perform face recognition on the secondary recognition target to obtain a secondary recognition result; and determine the face recognition result based on the primary recognition result and the secondary recognition result.
在一实施例中，所述风险判定模块30，还用于根据所述人脸识别结果确定所述首要识别结果和所述次要识别结果；根据所述首要识别结果和所述次要识别结果确定尾随风险判定结果；根据所述首要识别结果确定醉酒风险判定结果；根据所述尾随风险判定结果和所述醉酒风险判定结果确定风险判定结果。In one embodiment, the risk determination module 30 is further used to determine the primary recognition result and the secondary recognition result based on the face recognition result; determine the tailing risk determination result based on the primary recognition result and the secondary recognition result; determine the drunk risk determination result based on the primary recognition result; determine the risk determination result based on the tailing risk determination result and the drunk risk determination result.
在一实施例中，所述风险判定模块30，还用于根据所述首要识别结果确定主要识别人身份信息；根据所述次要识别结果确定次要识别人身份信息；根据所述主要识别人身份信息和所述次要识别人身份信息确定尾随风险判定结果。In one embodiment, the risk determination module 30 is further used to determine the primary identifier identity information based on the primary identification result; determine the secondary identifier identity information based on the secondary identification result; and determine the tailing risk determination result based on the primary identifier identity information and the secondary identifier identity information.
在一实施例中，所述风险判定模块30，还用于在所述主要识别人身份信息为白名单身份时，向所述首要识别目标发送验证指令；根据所述首要识别目标反馈的验证确认信息确定所述次要识别人身份信息的验证结果；根据所述验证结果确定尾随风险判定结果。In one embodiment, the risk determination module 30 is also used to send a verification instruction to the primary identification target when the identity information of the primary identification person is a whitelist identity; determine the verification result of the secondary identification person's identity information based on the verification confirmation information fed back by the primary identification target; and determine the trailing risk determination result based on the verification result.
在一实施例中，所述风险判定模块30，还用于根据所述首要识别结果确定人脸识别图像和人物动作图像；根据所述人脸识别图像确定夜间脸部灰度图像；根据所述夜间脸部灰度图像确定脸部颜色对比信息；根据所述脸部颜色对比信息确定面部判定结果；根据所述人物动作图像判定是否存在醉酒行为，得到行为判定结果；根据所述面部判定结果和所述行为判定结果确定醉酒风险判定结果。In one embodiment, the risk determination module 30 is further used to determine a face recognition image and a character action image based on the primary recognition result; determine a nighttime face grayscale image based on the face recognition image; determine face color contrast information based on the nighttime face grayscale image; determine a face determination result based on the face color contrast information; determine whether there is drunken behavior based on the character action image to obtain a behavior determination result; and determine a drunken risk determination result based on the face determination result and the behavior determination result.
应当理解的是，以上仅为举例说明，对本发明的技术方案并不构成任何限定，在具体应用中，本领域的技术人员可以根据需要进行设置，本发明对此不做限制。It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present invention. In specific applications, technicians in this field can make settings as needed, and the present invention does not limit this.
需要说明的是，以上所描述的工作流程仅仅是示意性的，并不对本发明的保护范围构成限定，在实际应用中，本领域的技术人员可以根据实际的需要选择其中的部分或者全部来实现本实施例方案的目的，此处不做限制。It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of them according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.
另外，未在本实施例中详尽描述的技术细节，可参见本发明任意实施例所提供的智能锁夜间警报方法，此处不再赘述。In addition, for technical details not described in detail in this embodiment, please refer to the smart lock night alarm method provided in any embodiment of the present invention, and will not be repeated here.
此外，需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者系统不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者系统所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者系统中还存在另外的相同要素。In addition, it should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.
上述本发明实施例序号仅仅为了描述，不代表实施例的优劣。The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质(如只读存储器(Read Only Memory，ROM)/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端设备(可以是手机，计算机，服务器，或者网络设备等)执行本发明各个实施例所述的方法。Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM)/RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.
以上仅为本发明的优选实施例，并非因此限制本发明的专利范围，凡是利用本发明说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本发明的专利保护范围内。The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410153696.5ACN118015736A (en) | 2024-02-02 | 2024-02-02 | Smart lock night alarm method, device and computer equipment |
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410153696.5ACN118015736A (en) | 2024-02-02 | 2024-02-02 | Smart lock night alarm method, device and computer equipment |
| Publication Number | Publication Date |
|---|---|
| CN118015736Atrue CN118015736A (en) | 2024-05-10 |
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410153696.5APendingCN118015736A (en) | 2024-02-02 | 2024-02-02 | Smart lock night alarm method, device and computer equipment |
| Country | Link |
|---|---|
| CN (1) | CN118015736A (en) |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109243030A (en)* | 2018-09-13 | 2019-01-18 | 浙江工业大学 | A kind of control method and system of night contactless access control system |
| CN111259787A (en)* | 2020-01-15 | 2020-06-09 | 杭州市第一人民医院 | Unlocking method, device, computer equipment and storage medium |
| CN112991592A (en)* | 2021-03-12 | 2021-06-18 | 广东好太太智能家居有限公司 | Alarm control method and device of intelligent door lock and intelligent door lock |
| CN113370786A (en)* | 2021-06-10 | 2021-09-10 | 桂林电子科技大学 | Vehicle-mounted drunk driving comprehensive detection system for unit vehicle based on multi-source information fusion |
| CN115731645A (en)* | 2021-08-27 | 2023-03-03 | 北京讯通安添通讯科技有限公司 | Access control management method, device, intelligent device and intelligent access control system |
| CN114120589A (en)* | 2021-11-16 | 2022-03-01 | 深圳市巨文科技有限公司 | Wireless Internet of things intelligent building management control method and system |
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| CN115588225A (en)* | 2022-10-25 | 2023-01-10 | 成都前宏科技股份有限公司 | Safety protection method, device and medium for identifying user based on intelligent camera |
| CN116353341A (en)* | 2023-05-04 | 2023-06-30 | 奇瑞汽车股份有限公司 | Methods and vehicles for preventing drunk driving |
| CN116884073A (en)* | 2023-07-21 | 2023-10-13 | 深圳熙卓科技有限公司 | Image recognition-based drinking detection method, device, medium and equipment |
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