WO2022213297A1 - 一种安防监控方法、装置、电子设备及存储介质 - Google Patents
一种安防监控方法、装置、电子设备及存储介质 Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 48
- 238000000034 method Methods 0.000 title claims abstract description 44
- 206010000117 Abnormal behaviour Diseases 0.000 claims abstract description 110
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- 238000004458 analytical method Methods 0.000 claims abstract description 27
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- 230000015654 memory Effects 0.000 claims description 31
- 230000006399 behavior Effects 0.000 claims description 29
- 238000009434 installation Methods 0.000 claims description 20
- 238000010183 spectrum analysis Methods 0.000 claims description 7
- 238000012806 monitoring device Methods 0.000 claims description 5
- 238000010586 diagram Methods 0.000 description 16
- 238000012545 processing Methods 0.000 description 9
- 230000006870 function Effects 0.000 description 8
- 238000004590 computer program Methods 0.000 description 7
- 238000012986 modification Methods 0.000 description 5
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- 230000002159 abnormal effect Effects 0.000 description 3
- 239000013307 optical fiber Substances 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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- the present application relates to the field of security technology, and in particular, to a security monitoring method, device, electronic device and storage medium.
- Embodiments of the present application provide a security monitoring method, device, electronic device, and storage medium, which are used to solve the problem in the related art that the security of monitoring is difficult to be guaranteed due to the existence of monitoring dead angles when using video data for security monitoring.
- an embodiment of the present application provides a security monitoring method, including:
- Whether there is an abnormality around the microphone is determined according to whether there is abnormal behavior matching the audio data.
- audio analysis is performed on the audio data to obtain audio features of the audio data, including:
- Semantic analysis is performed on the audio data to obtain semantic features of the audio data.
- the audio features of the audio data are compared with the saved audio features when the abnormal behavior occurs to determine whether there is an abnormal behavior matching the audio data, including:
- the method further includes:
- the semantic features of the audio data are compared with the saved semantic features when the abnormal behavior occurs. The semantic features are compared;
- it also includes:
- the installation location information of the microphone and the behavior description information corresponding to the abnormal behavior are sent to the server, so as to trigger the server to issue an alarm.
- it also includes:
- alarm information is sent, where the alarm information includes installation location information of the microphone and behavior description information corresponding to the abnormal behavior.
- an embodiment of the present application provides a security monitoring device, including:
- the acquisition module is used to acquire the audio data collected by the microphone
- an analysis module for performing audio analysis on the audio data to obtain audio features of the audio data
- a comparison module for comparing the audio feature of the audio data with the saved audio feature when abnormal behavior occurs, to determine whether there is an abnormal behavior matching the audio data
- a determination module configured to determine whether there is abnormality around the microphone according to whether there is abnormal behavior matching the audio data.
- the analysis module is specifically used for:
- Semantic analysis is performed on the audio data to obtain semantic features of the audio data.
- the alignment module is specifically used to:
- the comparison module is further used for:
- the semantic features of the audio data are compared with the saved semantic features when the abnormal behavior occurs. The semantic features are compared;
- it also includes:
- the sending module is configured to send the installation location information of the microphone and the behavior description information corresponding to the abnormal behavior to the server if it is determined that there is an abnormality around the microphone, so as to trigger the server to issue an alarm.
- it also includes:
- a sending module configured to send alarm information if it is determined that there is an abnormality around the microphone, where the alarm information includes installation location information of the microphone and behavior description information corresponding to the abnormal behavior.
- an embodiment of the present application provides a Raspberry Pi, including any of the above-mentioned devices.
- an embodiment of the present application provides an electronic device, including: at least one processor, and a memory communicatively connected to the at least one processor, wherein:
- the memory stores instructions executable by at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the above-mentioned security monitoring method.
- an embodiment of the present application provides a storage medium.
- the electronic device can execute the above security monitoring method.
- the audio data collected by the microphone is acquired, the audio data is subjected to audio analysis, the audio characteristics of the audio data are obtained, and the audio characteristics of the audio data are compared with the saved audio characteristics when abnormal behavior occurs to determine whether There is an abnormal behavior that matches the audio data, and then it is determined whether there is an abnormality around the microphone according to whether there is an abnormal behavior that matches the audio data.
- a solution for using audio data for security monitoring is provided. Since the audio data is less affected by the building structure and the layout of items, it can better deal with the monitoring dead angle problem existing in video monitoring, so the monitoring security can be improved. ensure.
- FIG. 1 is a schematic diagram of a security monitoring scenario provided by an embodiment of the present application
- FIG. 2 is a schematic diagram of another security monitoring scenario provided by an embodiment of the present application.
- FIG. 3 is a flowchart of a security monitoring method provided by an embodiment of the present application.
- FIG. 4 is a schematic process diagram of a security monitoring method provided by an embodiment of the present application.
- FIG. 5 is a schematic structural diagram of a security monitoring device provided by an embodiment of the present application.
- FIG. 6 is a schematic diagram of a hardware structure of an electronic device for implementing a security monitoring method according to an embodiment of the present application.
- the embodiments of the present application provide a security monitoring method, device, electronic device and storage medium.
- FIG. 1 is a schematic diagram of a security monitoring scenario provided by an embodiment of the application, including a microphone and an electronic device, wherein:
- the electronic equipment is used to obtain the audio data collected by the microphone, perform audio analysis on the audio data, obtain the audio characteristics of the audio data, and then compare the audio characteristics of the audio data with the saved audio characteristics when abnormal behavior occurs to determine Whether there is an abnormal behavior matching the audio data, and then determining whether there is an abnormality around the microphone according to whether there is an abnormal behavior matching the audio data.
- abnormal behaviors such as window-breaking behavior, door-breaking behavior, calling for help, etc.
- sounds when these abnormal behaviors occur.
- the electronic device may be a server or a Raspberry Pi.
- the server can be connected to multiple microphones; and when the electronic device is a Raspberry Pi, a Raspberry Pi can be connected to one, two, three or more microphones, and a tree
- the connection between the Raspberry Pi and several microphones can be determined by the technician according to the audio data processing capability of the Raspberry Pi and the speed at which the Raspberry Pi obtains audio data.
- the electronic device ie the server or the Raspberry Pi
- the electronic device is also used to send alarm information after it is determined that there is an abnormality around the microphone, so that security personnel can deal with the abnormal behavior in time, wherein the alarm information may include pre-stored information.
- the installation location information of the microphone and the behavior description information of the abnormal behavior are also used to send alarm information after it is determined that there is an abnormality around the microphone, so that security personnel can deal with the abnormal behavior in time, wherein the alarm information may include pre-stored information.
- the audio data is less affected by the building structure and the layout of items, it can better deal with the monitoring dead angle problem existing in video monitoring, so the monitoring security can be improved. ensure.
- the alarm information carrying the installation location information of the microphone and the behavior description information of the abnormal behavior is sent, so that the relevant personnel can timely and comprehensively understand the abnormal situation, and also help the relevant personnel to deal with the abnormality in a timely and accurate manner.
- the security monitoring system may further include a server connected to the Raspberry Pi, and the Raspberry Pi can use the User Datagram Protocol (UDP) through the network port. Communicate with the server.
- UDP User Datagram Protocol
- n is an integer, where:
- Each microphone used to collect audio data
- Each Raspberry Pi is used to obtain the audio data collected by the microphone connected to itself, perform audio analysis on the audio data to obtain the audio characteristics of the audio data, and then compare the audio characteristics of the audio data with the saved audio when abnormal behavior occurs. The features are compared to determine whether there is an abnormal behavior matching the audio data, and according to whether there is an abnormal behavior matching the audio data, it is determined whether there is an abnormality around the microphone.
- Each Raspberry Pi can also be used to send the installation location information of the microphone and the behavior description information corresponding to the abnormal behavior to the server after it is determined that there is an abnormality around the microphone connected to itself.
- the server is used to send an alarm after receiving the installation location information of the microphone and the behavior description information of the abnormal behavior sent by any Raspberry Pi, so that the security personnel can deal with the abnormal behavior in time.
- each Raspberry Pi analyzes and processes the audio data collected by the microphone connected to itself in real time to determine whether there is an abnormality around the microphone, without having to process all the audio data by the server, which can reduce the data processing pressure of the server, and , all audio data are processed by different Raspberry Pis, and the real-time performance is also better.
- Different Raspberry Pis are independent of each other. When the number of microphones needs to be expanded, it is only necessary to increase the corresponding Raspberry Pi, and the scalability is better.
- any Raspberry Pi determines that there is an abnormality around the microphone, it sends the installation location information of the microphone and the behavior description information of the abnormal behavior to the server to trigger the server to issue an alarm. Personnel handle exceptions in a timely and correct manner, and the user experience is better.
- the overall size of the Raspberry Pi is small, so it is easy to be embedded in various buildings, and it is more convenient to use.
- the installation position of the microphone can be predetermined by the technician according to the building structure and layout of the building to be monitored. Generally, the microphone can cover the building to be monitored.
- FIG. 3 is a flowchart of a security monitoring method provided by an embodiment of the present application. The method is applied to the electronic device of FIG. 1 or to the Raspberry Pi of FIG. 2 , and the method includes the following steps.
- step S301 audio data collected by a microphone is acquired.
- the audio data collected by the microphone may be acquired regularly, or the audio data collected by the microphone may be acquired irregularly, which is determined by the technical personnel according to the actual situation, which is not limited in the examples of this application.
- step S302 audio analysis is performed on the audio data to obtain audio features of the audio data.
- the call for help when there is a call for help in a building, it will also be accompanied by some specific sounds "such as help! Help!, and the spectrum characteristics of the call for help can be obtained by spectrum analysis of these sounds. Moreover, these sounds may also contain some semantic information, so these sounds can also be semantically analyzed, so as to obtain the semantic features of calling for help. That is, the sound accompanying the call for help may have spectral characteristics and/or semantic characteristics.
- performing audio analysis on the audio data to obtain the audio features of the audio data may be: performing spectrum analysis on the audio data to obtain the spectrum features of the audio data, and/or performing semantic analysis on the audio data to obtain the audio data of the audio data. Semantic features.
- step S303 the audio feature of the audio data is compared with the saved audio feature when the abnormal behavior occurs, so as to determine whether there is an abnormal behavior matching the audio data.
- the sound accompanying each preset behavior has certain spectral characteristics, so the spectral characteristics of the audio data can be compared with the saved spectral characteristics when each abnormal behavior occurs. If the similarity between the spectral feature and the spectral feature when the abnormal behavior occurs is higher than the first preset value, it is determined that the abnormal behavior matches the audio data.
- the spectral characteristics of the acquired audio data can be compared with the saved spectral characteristics when the abnormal behavior occurs, and the difference between the two can be determined. After the spectral similarity between them is higher than the first preset value, it can be determined that the abnormal behavior matches the acquired audio data.
- the semantic features of the audio data are also obtained, after it is determined that the similarity between the spectral features of the obtained audio data and the spectral features when any abnormal behavior occurs is higher than the first preset value, the obtained The semantic features of the audio data are compared with the stored semantic features when the abnormal behavior occurs, and after it is determined that the semantic similarity between the two is higher than the second preset value, it is then determined that the abnormal behavior matches the audio data. .
- the spectral characteristics of the acquired audio data can be compared with the saved spectral characteristics when the abnormal behavior occurs, and then the spectral similarity between the two can be determined.
- the semantic features of the acquired audio data are compared with the stored semantic features when the abnormal behavior occurs, and it is determined that the semantic similarity between the two is also higher than that of the second preset value. After setting the value, it is determined that the abnormal behavior matches the audio data.
- step S304 it is determined whether there is abnormality around the microphone according to whether there is abnormal behavior matching the audio data.
- if it is determined that there is an abnormal behavior matching the audio data it can be determined that there is an abnormality around the microphone; if it is determined that there is no abnormal behavior matching the audio data, it can be determined that there is no abnormality around the microphone.
- step S305 may also be included.
- step S305 if it is determined that there is an abnormality around the microphone, alarm information is sent, where the alarm information includes installation location information of the microphone and behavior description information corresponding to the abnormal behavior.
- step S306 may also be included.
- step S306 if it is determined that there is an abnormality around the microphone, the installation location information of the microphone and the behavior description information corresponding to the abnormal behavior are sent to the server to trigger the server to issue an alarm.
- the monitoring method provided by the embodiment of the present application is described below by taking the application scenario of FIG. 2 as an example.
- FIG. 4 is a schematic process diagram of a security monitoring method provided by an embodiment of the present application, wherein:
- the microphone is used to collect audio data and send the collected audio data to the Raspberry Pi connected to itself;
- the Raspberry Pi is used to determine whether the audio data collected by the microphone contains the sound of abnormal behavior. If not, discard the current audio data; if so, send the microphone installation location information and behavior description information of the abnormal line. to the server.
- the server is configured to send alarm information after receiving the installation location information of the microphone and the behavior description information of the abnormal row.
- the electronic device may include multiple functional modules, and each functional module may include software, hardware, or a combination thereof.
- FIG. 5 is a schematic structural diagram of a security monitoring device provided by an embodiment of the present application, including an acquisition module 501 , an analysis module 502 , a comparison module 503 , and a determination module 504 .
- an acquisition module 501 configured to acquire audio data collected by a microphone
- An analysis module 502 configured to perform audio analysis on the audio data to obtain audio features of the audio data
- a comparison module 503 for comparing the audio feature of the audio data with the saved audio feature when abnormal behavior occurs, to determine whether there is an abnormal behavior matching the audio data;
- a determination module 504, configured to determine whether there is abnormality around the microphone according to whether there is abnormal behavior matching the audio data.
- the analysis module 502 is specifically used for:
- Semantic analysis is performed on the audio data to obtain semantic features of the audio data.
- the comparison module 503 is specifically used for:
- the comparison module 503 is further configured to:
- the semantic features of the audio data are compared with the saved semantic features when the abnormal behavior occurs. The semantic features are compared;
- it also includes:
- the sending module 505 is configured to send the installation location information of the microphone and the behavior description information corresponding to the abnormal behavior to the server if it is determined that there is an abnormality around the microphone, so as to trigger the server to issue an alarm.
- it also includes:
- the sending module 505 is configured to send alarm information if it is determined that there is an abnormality around the microphone, where the alarm information includes installation location information of the microphone and behavior description information corresponding to the abnormal behavior.
- modules in the embodiments of the present application is schematic, and is only a logical function division. In actual implementation, there may be other division methods.
- the functional modules in the embodiments of the present application may be integrated into a processor It can also exist physically alone, or two or more modules can be integrated into one module.
- the coupling between the various modules may be implemented through some interfaces, which are usually electrical communication interfaces, but may be mechanical interfaces or other forms of interfaces. Therefore, modules described as separate components may or may not be physically separate, and may be located in one place or distributed in different locations on the same or different devices.
- the above-mentioned integrated modules can be implemented in the form of hardware, and can also be implemented in the form of software function modules.
- the electronic device includes physical devices such as a transceiver 601 and a processor 602, wherein the processor 602 may be a central processing unit (Central Processing Unit, CPU) , microprocessors, application-specific integrated circuits, programmable logic circuits, large-scale integrated circuits, or digital processing units, etc.
- the transceiver 601 is used for data transmission and reception between electronic devices and other devices.
- the electronic device may further include a memory 603 for storing software instructions executed by the processor 602, and of course other data required by the electronic device, such as identification information of the electronic device, encryption information of the electronic device, user data, and the like.
- the memory 603 may be a volatile memory (Volatile Memory), such as a random-access memory (Random-Access Memory, RAM); the memory 603 may also be a non-volatile memory (Non-Volatile Memory), such as a read-only memory (Read- Only Memory (ROM), Flash Memory (Flash Memory), Hard Disk Drive (HDD) or Solid-State Drive (SSD), or the memory 603 is capable of carrying or storing instructions or data structures in the form of desired program code and any other medium that can be accessed by a computer, but is not limited thereto.
- the memory 603 may be a combination of the above-described memories.
- the specific connection medium between the processor 602, the memory 603, and the transceiver 601 is not limited in this embodiment of the present application.
- the embodiment of the present application only takes the connection between the memory 603 , the processor 602 and the transceiver 601 through the bus 604 as an example for description.
- the bus is represented by a thick line in FIG. 6 . It is a schematic illustration and is not intended to be limiting.
- the bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of presentation, only one thick line is used in FIG. 6, but it does not mean that there is only one bus or one type of bus.
- the processor 602 can be a dedicated hardware or a processor running software. When the processor 602 can run software, the processor 602 reads the software instructions stored in the memory 603, and under the drive of the software instructions, executes the preceding embodiments. The security monitoring method involved.
- Embodiments of the present application further provide a Raspberry Pi, including the security monitoring device involved in the foregoing embodiments.
- An embodiment of the present application further provides a storage medium, when an instruction in the storage medium is executed by a processor of an electronic device, the electronic device can execute the security monitoring method involved in the foregoing embodiments.
- various aspects of the security monitoring method provided by the present application can also be implemented in the form of a program product, and the program product includes program codes, and when the program product runs on an electronic device , the program code is used to make the electronic device execute the security monitoring method involved in the foregoing embodiments.
- the program product may employ any combination of one or more readable media.
- the readable medium may be a readable signal medium or a readable storage medium.
- the readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or a combination of any of the above.
- readable storage media include: electrical connections with one or more wires, portable disks, hard disks, RAM, ROM, Erasable Programmable Read-Only Memory (Erasable Programmable Read-Only Memory) Only Memory, EPROM), flash memory, optical fiber, compact disk read only memory (Compact Disk Read Only Memory, CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
- the program product used for security monitoring in the embodiments of the present application may adopt a CD-ROM and include program codes, and may run on a computing device.
- the program product of the present application is not limited thereto, and in this document, a readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.
- a readable signal medium may include a propagated data signal in baseband or as part of a carrier wave, carrying readable program code therein. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.
- a readable signal medium can also be any readable medium, other than a readable storage medium, that can transmit, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
- the program code embodied on the readable medium can be transmitted by any suitable medium, including but not limited to wireless, wireline, optical fiber cable, radio frequency (RF), etc., or any suitable combination of the above.
- suitable medium including but not limited to wireless, wireline, optical fiber cable, radio frequency (RF), etc., or any suitable combination of the above.
- Program code for carrying out the operations of the present application may be written in any combination of one or more programming languages, including object-oriented programming languages—such as Java, C++, etc., as well as conventional procedural A programming language such as the "C" language or similar programming language.
- the program code may execute entirely on the user computing device, partly on the user device, as a stand-alone software package, partly on the user computing device and partly on a remote computing device, or entirely on the remote computing device or server execute on.
- the remote computing device may be connected to the user computing device through any kind of network, such as a Local Area Network (LAN) or Wide Area Network (WAN), or, alternatively, may be connected to an external computing device (eg using an internet service provider to connect via the internet).
- LAN Local Area Network
- WAN Wide Area Network
- the embodiments of the present application may be provided as a method, a system, or a computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
- computer-usable storage media including, but not limited to, disk storage, CD-ROM, optical storage, etc.
- These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions
- the apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.
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Abstract
一种安防监控方法、装置、电子设备及存储介质，属于安防技术领域，该方法包括：获取麦克风采集的音频数据（S301），对音频数据进行音频分析，得到音频数据的音频特征（S302），将音频数据的音频特征与保存的出现异常行为时的音频特征进行比对，以确定是否存在与音频数据匹配的异常行为（S303），进而根据是否存在与音频数据匹配的异常行为，确定麦克风周围是否存在异常（S304 ）。这样，提供了一种利用音频数据进行安防监控的方案，由于音频数据受建筑结构和物品布局的影响比较小，可较好地应对视频监控所存在的监控死角问题，所以可使监控安全性得到保证。
Description
本申请涉及安防技术领域，尤其涉及一种安防监控方法、装置、电子设备及存储介质。
随着社会经济的快速发展，楼宇数量大幅增加。为了便于楼宇管理也为了保证楼宇安全，对楼宇进行安防监控是十分有必要的。
相关技术中，在对楼宇进行安防监控时，均是利用摄像头采集楼宇内外的视频数据，分析视频数据来发现楼宇的安全隐患。然而，楼宇内外的建筑结构和物品布局一般都是比较复杂的，摄像头难免会有监控死角，获取不到监控死角的视频数据，就无法对楼宇进行全面监控，监控的安全性也就难以得到保障。
发明内容
本申请实施例提供一种安防监控方法、装置、电子设备及存储介质，用以解决相关技术中在利用视频数据进行安防监控时由于存在监控死角而导致监控的安全性难以得到保障的问题。
第一方面，本申请实施例提供一种安防监控方法，包括：
获取麦克风采集的音频数据；
对所述音频数据进行音频分析，得到所述音频数据的音频特征；
将所述音频数据的音频特征与保存的出现异常行为时的音频特征进行比对，以确定是否存在与所述音频数据匹配的异常行为；
根据是否存在与所述音频数据匹配的异常行为，确定所述麦克风周围是否存在异常。
在一些可能的实施方式中，对所述音频数据进行音频分析，得到所述音 频数据的音频特征，包括：
对所述音频数据进行频谱分析，得到所述音频数据的频谱特征；和/或
对所述音频数据进行语义分析，得到所述音频数据的语义特征。
在一些可能的实施方式中，将所述音频数据的音频特征与保存的出现异常行为时的音频特征进行比对，以确定是否存在与所述音频数据匹配的异常行为，包括：
将所述音频数据的频谱特征与保存的出现每种异常行为时的频谱特征进行比对；
若确定所述音频数据的频谱特征与出现所述异常行为时的频谱特征之间的相似度高于第一预设值，则确定所述异常行为与所述音频数据匹配。
在一些可能的实施方式中，若还得到所述音频数据的语义特征，则还包括：
在确定所述音频数据的频谱特征与出现所述异常行为时的频谱特征之间的相似度高于第一预设值之后，将所述音频数据的语义特征与保存的出现所述异常行为时的语义特征进行比对；
若确定所述音频数据的语义特征与出现所述异常行为时的语义特征之间的相似度高于第二预设值，则确定所述异常行为与所述音频数据匹配。
在一些可能的实施方式中，还包括：
若确定所述麦克风周围存在异常，则向服务器发送所述麦克风的安装位置信息和对应异常行为的行为描述信息，以触发所述服务器进行告警。
在一些可能的实施方式中，还包括：
若确定所述麦克风周围存在异常，则发送告警信息，所述告警信息中包含所述麦克风的安装位置信息和对应异常行为的行为描述信息。
第二方面，本申请实施例提供一种安防监控装置，包括：
获取模块，用于获取麦克风采集的音频数据；
分析模块，用于对所述音频数据进行音频分析，得到所述音频数据的音频特征；
比对模块，用于将所述音频数据的音频特征与保存的出现异常行为时的音频特征进行比对，以确定是否存在与所述音频数据匹配的异常行为；
确定模块，用于根据是否存在与所述音频数据匹配的异常行为，确定所述麦克风周围是否存在异常。
在一些可能的实施方式中，所述分析模块具体用于：
对所述音频数据进行频谱分析，得到所述音频数据的频谱特征；和/或
对所述音频数据进行语义分析，得到所述音频数据的语义特征。
在一些可能的实施方式中，所述比对模块具体用于：
将所述音频数据的频谱特征与保存的出现每种异常行为时的频谱特征进行比对；
若确定所述音频数据的频谱特征与出现所述异常行为时的频谱特征之间的相似度高于第一预设值，则确定所述异常行为与所述音频数据匹配。
在一些可能的实施方式中，若还得到所述音频数据的语义特征，则所述比对模块还用于：
在确定所述音频数据的频谱特征与出现所述异常行为时的频谱特征之间的相似度高于第一预设值之后，将所述音频数据的语义特征与保存的出现所述异常行为时的语义特征进行比对；
若确定所述音频数据的语义特征与出现所述异常行为时的语义特征之间的相似度高于第二预设值，则确定所述异常行为与所述音频数据匹配。
在一些可能的实施方式中，还包括：
发送模块，用于若确定所述麦克风周围存在异常，则向服务器发送所述麦克风的安装位置信息和对应异常行为的行为描述信息，以触发所述服务器进行告警。
在一些可能的实施方式中，还包括：
发送模块，用于若确定所述麦克风周围存在异常，则发送告警信息，所述告警信息中包含所述麦克风的安装位置信息和对应异常行为的行为描述信息。
第三方面，本申请实施例提供一种树莓派，包括上述任一所述的装置。
第四方面，本申请实施例提供一种电子设备，包括：至少一个处理器，以及与所述至少一个处理器通信连接的存储器，其中：
存储器存储有可被至少一个处理器执行的指令，该指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行上述安防监控方法。
第五方面，本申请实施例提供一种存储介质，当所述存储介质中的指令由电子设备的处理器执行时，所述电子设备能够执行上述安防监控方法。
本申请实施例中，获取麦克风采集的音频数据，对音频数据进行音频分析，得到音频数据的音频特征，将音频数据的音频特征与保存的出现异常行为时的音频特征进行比对，以确定是否存在与音频数据匹配的异常行为，进而根据是否存在与音频数据匹配的异常行为，确定麦克风周围是否存在异常。这样，提供了一种利用音频数据进行安防监控的方案，由于音频数据受建筑结构和物品布局的影响比较小，可较好地应对视频监控所存在的监控死角问题，所以可使监控安全性得到保证。
此处所说明的附图用来提供对本申请的进一步理解，构成本申请的一部分，本申请的示意性实施例及其说明用于解释本申请，并不构成对本申请的不当限定。在附图中：
图1为本申请实施例提供的一种安防监控的场景示意图；
图2为本申请实施例提供的又一种安防监控的场景示意图；
图3为本申请实施例提供的一种安防监控方法的流程图；
图4为本申请实施例提供的一种安防监控方法的过程示意图；
图5为本申请实施例提供的一种安防监控装置的结构示意图；
图6为本申请实施例提供的一种用于实现安防监控方法的电子设备的硬件结构示意图。
为了解决相关技术中在利用视频数据进行安防监控时由于存在监控死角而导致监控的安全性难以得到保障的问题，本申请实施例提供了一种安防监控方法、装置、电子设备及存储介质。
以下结合说明书附图对本申请的优选实施例进行说明，应当理解，此处所描述的优选实施例仅用于说明和解释本申请，并不用于限定本申请，并且在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。
图1为本申请实施例提供的一种安防监控的场景示意图，包括麦克风和电子设备，其中：
麦克风，用于采集音频数据；
电子设备，用于获取麦克风采集的音频数据，对音频数据进行音频分析，得到音频数据的音频特征，然后，将音频数据的音频特征与保存的出现异常行为时的音频特征进行比对，以确定是否存在与音频数据匹配的异常行为，进而根据是否存在与音频数据匹配的异常行为，确定麦克风周围是否存在异常。
其中，异常行为如破窗行为、破门行为、呼救行为等，在发生这些异常行为时通常都伴随有声音。
具体实施时，电子设备可以是服务器也可以是树莓派。并且，当电子设备是服务器时，服务器可与多个麦克风相连；而当电子设备是树莓派时，一个树莓派可与一个、两个、三个或更多个麦克风相连，而一个树莓派与几个麦克风相连可由技术人员根据树莓派的音频数据处理能力和树莓派获取音频数据的速度确定。
该种情况下，电子设备(即服务器或树莓派)，还用于在确定麦克风周围存在异常之后，发送告警信息以便安防人员可及时对异常行为进行处理，其中，告警信息中可以包含预先存储的麦克风的安装位置信息和异常行为的行为描述信息。
这样，提供了一种利用音频数据进行安防监控的方案，由于音频数据受 建筑结构和物品布局的影响比较小，可较好地应对视频监控所存在的监控死角问题，所以可使监控安全性得到保证。并且，在确定麦克风周围存在异常时，发送携带麦克风的安装位置信息和异常行为的行为描述信息的告警信息，可以使相关人员及时全面地了解异常情况，也利于相关人员及时准确地处理异常。
在一些可能的实施方式中，当电子设备是树莓派时，安防监控系统还可以包括与树莓派相连的服务器，树莓派可通过网口以用户数据报协议(User Datagram Protocol，UDP)与服务器进行通信。
图2为本申请实施例提供的又一种安防监控的场景示意图，包括n个麦克风、n个树莓派和一个服务器，一个麦克风和一个树莓派相连(实际上一个麦克风也可以和不止一个树莓派相连)，每个树莓派均和服务器相连，n为整数，其中：
每个麦克风，用于采集音频数据；
每个树莓派，用于获取与自身相连的麦克风采集的音频数据，对音频数据进行音频分析，得到音频数据的音频特征，然后，将音频数据的音频特征与保存的出现异常行为时的音频特征进行比对，以确定是否存在与音频数据匹配的异常行为，根据是否存在与音频数据匹配的异常行为，确定麦克风周围是否存在异常。
每个树莓派，还可用于在确定与自身相连的麦克风周围出现异常之后，向服务器发送该麦克风的安装位置信息和对应异常行为的行为描述信息。
服务器，用于在接收到任一树莓派发送的麦克风的安装位置信息和异常行为的行为描述信息后，进行告警以便安防人员可及时对异常行为进行处理。
这样，由各树莓派分别对与自身相连的麦克风采集的音频数据实时进行分析处理，以确定麦克风周围是否存在异常，而不必由服务器处理所有的音频数据，可减轻服务器的数据处理压力，并且，所有的音频数据由不同的树莓派分散处理，实时性也比较好。而不同树莓派之间相互独立，当需要扩展麦克风的数量时只需增加相应的树莓派即可，扩展性也比较好。而任一树莓 派在确定麦克风周围存在异常时，将麦克风的安装位置信息和异常行为的行为描述信息发送给服务器以触发服务器进行告警，可使相关人员及时全面地了解异常情况，也利于相关人员及时正确地处理异常，用户体验比较好。此外，树莓派的整体体积小，易于嵌入各类楼宇内，使用起来也比较方便。
需要说明的是，在图1和图2中，麦克风的安装位置可由技术人员根据进行监控的楼宇的建筑结构和布局预先确定，一般地，麦克风可覆盖需要进行监控的楼宇。
图3为本申请实施例提供的一种安防监控方法的流程图，该方法应用于图1的电子设备中或应用于图2的树莓派中，且该方法包括以下步骤。
在步骤S301中，获取麦克风采集的音频数据。
具体实施时，可定期获取麦克风采集的音频数据，也可不定期获取麦克风采集的音频数据，具体由技术人员根据实际情况确定，本申请实例对此不做限定。
在步骤S302中，对音频数据进行音频分析，得到音频数据的音频特征。
以破窗行为为例，当楼宇内出现破窗行为时，会伴随一些特定的声音如“砰！砰！”，分析这些声音的频谱特征即可得到出现破窗行为时的频谱特征。破门行为与此类似，在此不再赘述。
以呼救行为为例，当楼宇内出现呼救行为时，也会伴随一些特定的声音“如救命！救命！”，对这些声音进行频谱分析即可得到出现呼救行为时的频谱特征。并且，这些声音中可能还会包含一些语义信息，所以还可对这些声音进行语义分析，从而得到出现呼救行为时的语义特征。即，出现对呼救行为时伴随的声音可以具有频谱特征和/或语义特征。
基于上述分析可知，对音频数据进行音频分析，得到音频数据的音频特征可以是：对音频数据进行频谱分析，得到音频数据的频谱特征，和/或，对音频数据进行语义分析，得到音频数据的语义特征。
在步骤S303中，将音频数据的音频特征与保存的出现异常行为时的音频特征进行比对，以确定是否存在与音频数据匹配的异常行为。
一般地，出现每种预设行为时所伴随的声音都具有一定的频谱特征，所以可以将音频数据的频谱特征与保存的出现每种异常行为时的频谱特征进行比对，若确定音频数据的频谱特征与出现该种异常行为时的频谱特征之间的相似度高于第一预设值，则确定该种异常行为与音频数据匹配。
比如，对于破门行为、破窗行为和呼救行为中的任一种异常行为，可以将获取的音频数据的频谱特征与保存的出现该种异常行为时的频谱特征进行比对，在确定两者之间的频谱相似度高于第一预设值之后，即可判定该种异常行为与获取的音频数据匹配。
而当还获得有音频数据的语义特征时，在确定获取的音频数据的频谱特征与出现任一异常行为时的频谱特征之间的相似度高于第一预设值之后，还可将获取的音频数据的语义特征与保存的出现该种异常行为时的语义特征进行比对，在确定两者之间的语义相似度高于第二预设值之后，再判定该种异常行为与音频数据匹配。
比如，对于呼救行为这种通常伴随一定语义的异常行为，可以将获取的音频数据的频谱特征与保存的出现该种异常行为时的频谱特征进行比对，在确定两者之间的频谱相似度高于第一预设值之后，再将获取的音频数据的语义特征与保存的出现该种异常行为时的语义特征进行比对，在确定两者之间的语义相似度也高于第二预设值之后，再判定该种异常行为与音频数据匹配。
这样，在确定获取的音频数据的频谱特征与出现任一异常行为时的频谱特征的相似度高于第一预设值、且获取的音频数据的语义特征与出现该种异常行为时的语义特征的相似度高于第二预设值时，判断该种异常行为与获取的音频数据匹配，可提高异常行为判定的准确性。
在步骤S304中，根据是否存在与音频数据匹配的异常行为，确定麦克风周围是否存在异常。
具体实施时，若确定存在与音频数据匹配的异常行为，则可判断麦克风周围存在异常；若确定不存在与音频数据匹配的异常行为，则可判断麦克风周围不存在异常。
当该方法应用于图1的电子设备中时，还可包含步骤S305。
在步骤S305中，若确定麦克风周围存在异常，则发送告警信息，该告警信息中包含麦克风的安装位置信息和对应异常行为的行为描述信息。
当该方法应用于图2的树莓派中时，还可包含步骤S306。
在步骤S306中，若确定麦克风周围存在异常，则向服务器发送麦克风的安装位置信息和对应异常行为的行为描述信息，以触发服务器进行告警。
下面以图2的应用场景为例对本申请实施例提供的监控方法进行说明。
图4是本申请实施例提供的一种安防监控方法的过程示意图，其中：
麦克风，用于采集音频数据，并将采集的音频数据发送给与自身相连的树莓派；
树莓派，用于判断麦克风采集的音频数据中是否包含出现异常行为时的声音，若否，则丢弃本次的音频数据；若是，则将麦克风的安装位置信息和异常行的行为描述信息发送给服务器。
服务器，用于在接收到麦克风的安装位置信息和异常行的行为描述信息后，发送告警信息。
当本申请实施例中提供的方法以软件或硬件或软硬件结合实现的时候，电子设备中可以包括多个功能模块，每个功能模块可以包括软件、硬件或其结合。
图5为本申请实施例提供的一种安防监控装置的结构示意图，包括获取模块501、分析模块502、比对模块503、确定模块504。
获取模块501，用于获取麦克风采集的音频数据；
分析模块502，用于对所述音频数据进行音频分析，得到所述音频数据的音频特征；
比对模块503，用于将所述音频数据的音频特征与保存的出现异常行为时的音频特征进行比对，以确定是否存在与所述音频数据匹配的异常行为；
确定模块504，用于根据是否存在与所述音频数据匹配的异常行为，确定所述麦克风周围是否存在异常。
在一些可能的实施方式中，所述分析模块502具体用于：
对所述音频数据进行频谱分析，得到所述音频数据的频谱特征；和/或
对所述音频数据进行语义分析，得到所述音频数据的语义特征。
在一些可能的实施方式中，所述比对模块503具体用于：
将所述音频数据的频谱特征与保存的出现每种异常行为时的频谱特征进行比对；
若确定所述音频数据的频谱特征与出现所述异常行为时的频谱特征之间的相似度高于第一预设值，则确定所述异常行为与所述音频数据匹配。
在一些可能的实施方式中，若还得到所述音频数据的语义特征，则所述比对模块503还用于：
在确定所述音频数据的频谱特征与出现所述异常行为时的频谱特征之间的相似度高于第一预设值之后，将所述音频数据的语义特征与保存的出现所述异常行为时的语义特征进行比对；
若确定所述音频数据的语义特征与出现所述异常行为时的语义特征之间的相似度高于第二预设值，则确定所述异常行为与所述音频数据匹配。
在一些可能的实施方式中，还包括：
发送模块505，用于若确定所述麦克风周围存在异常，则向服务器发送所述麦克风的安装位置信息和对应异常行为的行为描述信息，以触发所述服务器进行告警。
在一些可能的实施方式中，还包括：
发送模块505，用于若确定所述麦克风周围存在异常，则发送告警信息，所述告警信息中包含所述麦克风的安装位置信息和对应异常行为的行为描述信息。
本申请实施例中对模块的划分是示意性的，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，另外，本申请各实施例中的各功能模块可以集成在一个处理器中，也可以是单独物理存在，也可以两个或两个以上模块集成在一个模块中。各个模块相互之间的耦合可以是通过一些接口实现， 这些接口通常是电性通信接口，但是也不排除可能是机械接口或其它的形式接口。因此，作为分离部件说明的模块可以是或者也可以不是物理上分开的，既可以位于一个地方，也可以分布到同一个或不同设备的不同位置上。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。
图6为本申请实施例提供的一种电子设备的结构示意图，该电子设备包括收发器601以及处理器602等物理器件，其中，处理器602可以是一个中央处理单元(Central Processing Unit，CPU)、微处理器、专用集成电路、可编程逻辑电路、大规模集成电路、或者为数字处理单元等等。收发器601用于电子设备和其他设备进行数据收发。
该电子设备还可以包括存储器603用于存储处理器602执行的软件指令，当然还可以存储电子设备需要的一些其他数据，如电子设备的标识信息、电子设备的加密信息、用户数据等。存储器603可以是易失性存储器(Volatile Memory)，例如随机存取存储器(Random-Access Memory，RAM)；存储器603也可以是非易失性存储器(Non-Volatile Memory)，例如只读存储器(Read-Only Memory，ROM)，快闪存储器(Flash Memory)，硬盘(Hard Disk Drive，HDD)或固态硬盘(Solid-State Drive，SSD)、或者存储器603是能够用于携带或存储具有指令或数据结构形式的期望的程序代码并能够由计算机存取的任何其他介质，但不限于此。存储器603可以是上述存储器的组合。
本申请实施例中不限定上述处理器602、存储器603以及收发器601之间的具体连接介质。本申请实施例在图6中仅以存储器603、处理器602以及收发器601之间通过总线604连接为例进行说明，总线在图6中以粗线表示，其它部件之间的连接方式，仅是进行示意性说明，并不引以为限。所述总线可以分为地址总线、数据总线、控制总线等。为便于表示，图6中仅用一条粗线表示，但并不表示仅有一根总线或一种类型的总线。
处理器602可以是专用硬件或运行软件的处理器，当处理器602可以运行软件时，处理器602读取存储器603存储的软件指令，并在所述软件指令 的驱动下，执行前述实施例中涉及的安防监控方法。
本申请实施例还提供了一种树莓派，包括前述实施例中涉及的安防监控装置。
本申请实施例还提供了一种存储介质，当所述存储介质中的指令由电子设备的处理器执行时，所述电子设备能够执行前述实施例中涉及的安防监控方法。
在一些可能的实施方式中，本申请提供的安防监控方法的各个方面还可以实现为一种程序产品的形式，所述程序产品中包括有程序代码，当所述程序产品在电子设备上运行时，所述程序代码用于使所述电子设备执行前述实施例中涉及的安防监控方法。
所述程序产品可以采用一个或多个可读介质的任意组合。可读介质可以是可读信号介质或者可读存储介质。可读存储介质例如可以是但不限于电、磁、光、电磁、红外线、或半导体的系统、装置或器件，或者任意以上的组合。可读存储介质的更具体的例子(非穷举的列表)包括：具有一个或多个导线的电连接、便携式盘、硬盘、RAM、ROM、可擦式可编程只读存储器(Erasable Programmable Read-Only Memory，EPROM)、闪存、光纤、光盘只读存储器(Compact Disk Read Only Memory，CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。
本申请实施例中用于安防监控的程序产品可以采用CD-ROM并包括程序代码，并可以在计算设备上运行。然而，本申请的程序产品不限于此，在本文件中，可读存储介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。
可读信号介质可以包括在基带中或者作为载波一部分传播的数据信号，其中承载了可读程序代码。这种传播的数据信号可以采用多种形式，包括但不限于电磁信号、光信号或上述的任意合适的组合。可读信号介质还可以是可读存储介质以外的任何可读介质，该可读介质可以发送、传播或者传输用于由指令执行系统、装置或者器件使用或者与其结合使用的程序。
可读介质上包含的程序代码可以用任何适当的介质传输，包括但不限于无线、有线、光缆、射频(Radio Frequency，RF)等等，或者上述的任意合适的组合。
可以以一种或多种程序设计语言的任意组合来编写用于执行本申请操作的程序代码，所述程序设计语言包括面向对象的程序设计语言—诸如Java、C++等，还包括常规的过程式程序设计语言诸如“C”语言或类似的程序设计语言。程序代码可以完全地在用户计算设备上执行、部分地在用户设备上执行、作为一个独立的软件包执行、部分在用户计算设备上部分在远程计算设备上执行、或者完全在远程计算设备或服务器上执行。在涉及远程计算设备的情形中，远程计算设备可以通过任意种类的网络如局域网(Local Area Network，LAN)或广域网(Wide Area Network，WAN)连接到用户计算设备，或者，可以连接到外部计算设备(例如利用因特网服务提供商来通过因特网连接)。
应当注意，尽管在上文详细描述中提及了装置的若干单元或子单元，但是这种划分仅仅是示例性的并非强制性的。实际上，根据本申请的实施方式，上文描述的两个或更多单元的特征和功能可以在一个单元中具体化。反之，上文描述的一个单元的特征和功能可以进一步划分为由多个单元来具体化。
此外，尽管在附图中以特定顺序描述了本申请方法的操作，但是，这并非要求或者暗示必须按照该特定顺序来执行这些操作，或是必须执行全部所示的操作才能实现期望的结果。附加地或备选地，可以省略某些步骤，将多个步骤合并为一个步骤执行，和/或将一个步骤分解为多个步骤执行。
本领域内的技术人员应明白，本申请的实施例可提供为方法、系统、或计算机程序产品。因此，本申请可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本申请是参照根据本申请实施例的方法、装置(系统)、和计算机程序产 品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
尽管已描述了本申请的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例做出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本申请范围的所有变更和修改。
显然，本领域的技术人员可以对本申请进行各种改动和变型而不脱离本申请的精神和范围。这样，倘若本申请的这些修改和变型属于本申请权利要求及其等同技术的范围之内，则本申请也意图包含这些改动和变型在内。
Claims (15)
- 一种安防监控方法，其特征在于，包括：获取麦克风采集的音频数据；对所述音频数据进行音频分析，得到所述音频数据的音频特征；将所述音频数据的音频特征与保存的出现异常行为时的音频特征进行比对，以确定是否存在与所述音频数据匹配的异常行为；根据是否存在与所述音频数据匹配的异常行为，确定所述麦克风周围是否存在异常。
- 如权利要求1所述的方法，其特征在于，对所述音频数据进行音频分析，得到所述音频数据的音频特征，包括：对所述音频数据进行频谱分析，得到所述音频数据的频谱特征；和/或对所述音频数据进行语义分析，得到所述音频数据的语义特征。
- 如权利要求2所述的方法，其特征在于，将所述音频数据的音频特征与保存的出现异常行为时的音频特征进行比对，以确定是否存在与所述音频数据匹配的异常行为，包括：将所述音频数据的频谱特征与保存的出现每种异常行为时的频谱特征进行比对；若确定所述音频数据的频谱特征与出现所述异常行为时的频谱特征之间的相似度高于第一预设值，则确定所述异常行为与所述音频数据匹配。
- 如权利要求3所述的方法，其特征在于，若还得到所述音频数据的语义特征，则还包括：在确定所述音频数据的频谱特征与出现所述异常行为时的频谱特征之间的相似度高于第一预设值之后，将所述音频数据的语义特征与保存的出现所述异常行为时的语义特征进行比对；若确定所述音频数据的语义特征与出现所述异常行为时的语义特征之间的相似度高于第二预设值，则确定所述异常行为与所述音频数据匹配。
- 如权利要求1-4任一所述的方法，其特征在于，还包括：若确定所述麦克风周围存在异常，则向服务器发送所述麦克风的安装位置信息和对应异常行为的行为描述信息，以触发所述服务器进行告警。
- 如权利要求1-4任一所述的方法，其特征在于，还包括：若确定所述麦克风周围存在异常，则发送告警信息，所述告警信息中包含所述麦克风的安装位置信息和对应异常行为的行为描述信息。
- 一种安防监控装置，其特征在于，包括：获取模块，用于获取麦克风采集的音频数据；分析模块，用于对所述音频数据进行音频分析，得到所述音频数据的音频特征；比对模块，用于将所述音频数据的音频特征与保存的出现异常行为时的音频特征进行比对，以确定是否存在与所述音频数据匹配的异常行为；确定模块，用于根据是否存在与所述音频数据匹配的异常行为，确定所述麦克风周围是否存在异常。
- 如权利要求7所述的装置，其特征在于，所述分析模块具体用于：对所述音频数据进行频谱分析，得到所述音频数据的频谱特征；和/或对所述音频数据进行语义分析，得到所述音频数据的语义特征。
- 如权利要求8所述的装置，其特征在于，所述比对模块具体用于：将所述音频数据的频谱特征与保存的出现每种异常行为时的频谱特征进行比对；若确定所述音频数据的频谱特征与出现所述异常行为时的频谱特征之间的相似度高于第一预设值，则确定所述异常行为与所述音频数据匹配。
- 如权利要求9所述的装置，其特征在于，若还得到所述音频数据的语义特征，则所述比对模块还用于：在确定所述音频数据的频谱特征与出现所述异常行为时的频谱特征之间的相似度高于第一预设值之后，将所述音频数据的语义特征与保存的出现所述异常行为时的语义特征进行比对；若确定所述音频数据的语义特征与出现所述异常行为时的语义特征之间的相似度高于第二预设值，则确定所述异常行为与所述音频数据匹配。
- 如权利要求7-10任一所述的装置，其特征在于，还包括：发送模块，用于若确定所述麦克风周围存在异常，则向服务器发送所述麦克风的安装位置信息和对应异常行为的行为描述信息，以触发所述服务器进行告警。
- 如权利要求7-10任一所述的装置，其特征在于，还包括：发送模块，用于若确定所述麦克风周围存在异常，则发送告警信息，所述告警信息中包含所述麦克风的安装位置信息和对应异常行为的行为描述信息。
- 一种树莓派，其特征在于，包括如权利要求7-12任一所述的装置。
- 一种电子设备，其特征在于，包括：至少一个处理器，以及与所述至少一个处理器通信连接的存储器，其中：所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行如权利要求1-6任一所述的方法。
- 一种存储介质，其特征在于，当所述存储介质中的指令由电子设备的处理器执行时，所述电子设备能够执行如权利要求1-6任一所述的方法。
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115604049A (zh) * | 2022-12-14 | 2023-01-13 | 忆月启函（盐城）科技有限公司（Cn） | 一种用于家庭多功能监控的智能通信网络系统 |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106934970A (zh) * | 2017-03-30 | 2017-07-07 | 安徽森度科技有限公司 | 一种公共场所异常行为预警系统 |
| US10043085B2 (en) * | 2016-10-25 | 2018-08-07 | International Business Machines Corporation | Framework for analysis of body camera and sensor information |
| CN108961466A (zh) * | 2018-06-19 | 2018-12-07 | 宇龙计算机通信科技(深圳)有限公司 | 一种异常行为的采集方法和设备 |
| CN110148423A (zh) * | 2019-04-18 | 2019-08-20 | 广东思派康电子科技有限公司 | 一种计算机可读存储介质及能用于防盗的语音交互音箱 |
| CN112034728A (zh) * | 2020-10-09 | 2020-12-04 | 珠海市贝多图网络科技有限公司 | 一种基于zigbee的高安全性智能家居控制系统 |
-
2021
- 2021-04-07 WO PCT/CN2021/085777 patent/WO2022213297A1/zh active Application Filing
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10043085B2 (en) * | 2016-10-25 | 2018-08-07 | International Business Machines Corporation | Framework for analysis of body camera and sensor information |
| CN106934970A (zh) * | 2017-03-30 | 2017-07-07 | 安徽森度科技有限公司 | 一种公共场所异常行为预警系统 |
| CN108961466A (zh) * | 2018-06-19 | 2018-12-07 | 宇龙计算机通信科技(深圳)有限公司 | 一种异常行为的采集方法和设备 |
| CN110148423A (zh) * | 2019-04-18 | 2019-08-20 | 广东思派康电子科技有限公司 | 一种计算机可读存储介质及能用于防盗的语音交互音箱 |
| CN112034728A (zh) * | 2020-10-09 | 2020-12-04 | 珠海市贝多图网络科技有限公司 | 一种基于zigbee的高安全性智能家居控制系统 |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115604049A (zh) * | 2022-12-14 | 2023-01-13 | 忆月启函（盐城）科技有限公司（Cn） | 一种用于家庭多功能监控的智能通信网络系统 |
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