CN113473085A - Video monitoring identification system based on artificial intelligence technology - Google Patents
Video monitoring identification system based on artificial intelligence technology Download PDFInfo
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- CN113473085A CN113473085A CN202110746094.7A CN202110746094A CN113473085A CN 113473085 A CN113473085 A CN 113473085A CN 202110746094 A CN202110746094 A CN 202110746094A CN 113473085 A CN113473085 A CN 113473085A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 35
- 238000005516 engineering process Methods 0.000 title claims abstract description 22
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 20
- 230000007613 environmental effect Effects 0.000 claims abstract description 61
- 230000002159 abnormal effect Effects 0.000 claims abstract description 32
- 238000004891 communication Methods 0.000 claims description 33
- 238000012806 monitoring device Methods 0.000 claims description 27
- 238000010248 power generation Methods 0.000 claims description 8
- 230000003993 interaction Effects 0.000 claims description 7
- 238000012549 training Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 3
- 238000000034 method Methods 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004590 computer program Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 230000006378 damage Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
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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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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/06—Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
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Abstract
The present disclosure relates to the field of monitoring and identification technologies, and in particular, to a video monitoring and identification system based on an artificial intelligence technology. The monitoring equipment collects the environmental data of the monitored equipment and sends the collected environmental data to the server, and the server identifies whether the environmental data is abnormal data; when the environmental data is abnormal data, the server sends alarm information to the terminal equipment, so that the staff can observe the environmental information around the monitored equipment in time, and the abnormal condition is processed in time when the surrounding environment of the monitored equipment is abnormal, and safety accidents are avoided.
Description
Technical Field
The present disclosure relates to the field of monitoring and identification technologies, and in particular, to a video monitoring and identification system based on an artificial intelligence technology.
Background
In important point locations such as a residential area, a factory, a construction site, an intersection, a field and the like, for the purposes of safety, scientific research and the like, the field environment, affairs, figure actions and the like are often required to be identified so as to judge whether the surrounding environment of the important point locations is safe or not, and therefore safety monitoring is carried out on the important point locations. Taking the power industry as an example, in the process of high-voltage power transmission, a viaduct or tunnel mode is usually adopted for wiring and conveying in the field, and because the field environment is complex and cannot be monitored manually in real time at present, high-voltage electric shock hurting accidents, cable damage caused by brutal construction and other accidents occur in the field.
Disclosure of Invention
In order to solve at least one of the above technical problems, the present disclosure provides a video surveillance identification system based on artificial intelligence technology, the system comprising: monitoring equipment, communication equipment, a server and terminal equipment;
the monitoring equipment is configured to collect environmental data of monitored equipment and send the environmental data to the server through the communication equipment;
the communication equipment is configured to provide communication connection for the monitoring equipment and the server, and the server and the terminal equipment;
the server is configured to judge whether the environment data are abnormal data, and when the environment data are abnormal data, alarm information is sent to the terminal equipment.
Optionally, the server includes an identification server and a service server;
the monitoring device is configured to send the environment data to the identification server through the communication device;
the identification server is loaded with a plurality of identification models and is configured to identify the environmental data according to the identification models so as to judge whether the environmental data is abnormal data;
when the environment data is abnormal data, the identification server is further configured to send the environment data to the business server;
the service server is configured to send alarm information to the terminal device after receiving the environment data.
Optionally, the identification server is further configured to identify monitored device information corresponding to the environmental data according to the environmental data, and send the monitored device information to the service server when the environmental data is abnormal data.
Optionally, the service server is further configured to correspondingly store the environment data and the monitored device information.
Optionally, the service server is further configured to send the environmental data and the monitored device information when sending alarm information to the terminal device.
Optionally, the terminal device is configured to, after receiving the environment data and the monitored device information, correspondingly store the environment data and the monitored device information.
Optionally, the service server stores a matching relationship between the monitoring device and the terminal device;
the monitoring device is further configured to collect audio information around the monitored device, and the terminal device is further configured to collect audio information around the terminal device;
and the monitoring equipment and the terminal equipment realize the interaction of audio information through the service server.
Optionally, the video monitoring and identifying system based on the artificial intelligence technology further includes a power supply device configured to supply power to the monitoring device, the communication device, the server and the terminal device.
Optionally, the power supply device is one or more of a new energy power generation apparatus, a primary battery, a secondary battery, and a 220V ac power supply.
Optionally, the environment data includes acquisition time information of the environment data.
The beneficial effects brought by the technical scheme provided by the embodiment of the disclosure at least can include:
the monitoring equipment collects the environmental data of the monitored equipment and sends the collected environmental data to the server, and the server identifies whether the environmental data is abnormal data; when the environmental data is abnormal data, the server sends alarm information to the terminal equipment, so that the staff can observe the environmental information around the monitored equipment in time, and the abnormal condition is processed in time when the surrounding environment of the monitored equipment is abnormal, and safety accidents are avoided.
Drawings
In order to more clearly illustrate the embodiments or prior art solutions of the present disclosure, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious that the drawings in the following description are included in and constitute a part of this specification, and other drawings can be obtained by those skilled in the art without inventive effort from these drawings. For convenience of description, only portions relevant to the present disclosure are shown in the drawings.
FIG. 1 is a schematic diagram of a video surveillance identification system based on artificial intelligence technology provided by an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a transmission path of environmental data in an embodiment of the disclosure;
FIG. 3 is a schematic flow chart of constructing a recognition model in an embodiment of the present disclosure;
fig. 4 is a schematic flow chart of voice interaction between a monitoring device and a terminal device in the embodiment of the present disclosure.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions in the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are some embodiments of the present disclosure, not all embodiments, and features in the embodiments and implementations in the present disclosure may be combined with each other without conflict. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
The embodiment of the disclosure provides a video monitoring and identifying system based on an artificial intelligence technology. As shown in fig. 1, the system includes: monitoring equipment, communication equipment, a server and terminal equipment;
the monitoring equipment is configured to collect the environmental data of the monitored equipment and send the environmental data to the server through the communication equipment;
the communication equipment is configured to provide communication connection for the monitoring equipment and the server, and the server and the terminal equipment;
the server is configured to judge whether the environmental data are abnormal data, and when the environmental data are abnormal data, send alarm information to the terminal device.
In a possible implementation manner, the monitored device may be industrial devices or products such as a power transformer and an automobile, or the monitored device may also be various devices existing in areas such as a cell gate and a corner of an intersection, or even an invisible device such as a cable buried underground. The monitoring device may be a camera installed around the monitored device, and the monitoring device may acquire environmental data of the monitored device in real time, periodically, or aperiodically. The environment data of the monitored device can be photos or videos around the monitored device or comprise the photos and the videos at the same time, and the video information around the monitored device can comprise real-time audio information.
As shown in fig. 1, the monitoring device may send the acquired or collected environment data to the communication device, and then the communication device sends the environment data to the server. Alternatively, the monitoring device may also send the environmental data directly to the server. In this case, the communication device is only used to provide a communication connection for the monitoring device and the server. The communication equipment can be wired communication equipment and/or wireless communication equipment suitable for industrial control environments.
In one possible implementation, the server may include an identification server and a service server. The identification server can receive environment data of the monitored equipment collected or obtained by the monitoring equipment, and a plurality of identification models can be loaded in the identification server. After the identification server receives the environmental data of the monitored device, whether the received environmental data is abnormal data or not can be judged according to the identification model. When the identification server determines that the environmental data is abnormal data, the abnormal environmental data can be sent to the service server, so that the service server can send alarm information to the terminal according to the abnormal environmental data.
In a possible implementation manner, the identification server may further identify monitored device information corresponding to the received environment data according to the received environment data. For example, the identification server may extract the main features of the monitored device in the environment data, thereby determining which monitored device the environment data is. Or, when the monitoring device sends the environment data to the communication device, the monitored device information may be sent to the communication device together. The identification server may first determine which monitored device the environmental data is, and then determine whether the received environmental data is abnormal data according to the identification model corresponding to the monitored device. As shown in fig. 2, when the identification server determines that the received environment data is abnormal data, the environment data and monitored device information corresponding to the environment data may be sent to the service server. The monitored device information may be information such as name, number, ID identification code, etc. of the monitored device.
Fig. 3 shows a flow chart of constructing the recognition model by taking a mobile machinery shop as an example. Taking fig. 3 as an example, when constructing the recognition model, a large number of pictures containing the monitored device may be obtained to construct the data set. The data set can include pictures of monitored equipment of various types, and the pictures of the monitored equipment in the data set are all pictures of normal surrounding environment of the monitored equipment. After the data set is constructed, the data set, or the pictures in the data set, may be input into a basic training model for training, and a category data file and a model data file may be output. The category data refers to different classes of objects present in the picture, e.g. different classes of objects for men, women and children. The model data is corresponding to a certain type of object, and the model data may be display content of the certain type of object in the picture. For example, the child object corresponds to certain model data. After the training of the pictures in the data set is completed, a target file can be input into the recognition model, and whether the satisfaction degree of the output result meets a preset threshold value is judged. When the satisfaction degree of the output result of the target file meets a preset threshold value, the accuracy of the recognition model is high; and when the satisfaction degree of the output result of the target file does not meet the preset threshold value, the accuracy of the recognition model is poor, and the training needs to be carried out again. The satisfaction degree of the output result comprises scores of two dimensions, namely the matching degree of the monitored equipment in the output result and the monitored equipment in the target file, and the accuracy of normal/abnormal judgment of the environmental data of the monitored equipment, namely the satisfaction degree of the output result reflects the accuracy of the identified monitored equipment and the accuracy of normal/abnormal judgment of the environmental data around the monitored equipment. In practical applications, there may be a plurality of monitored devices, and for each monitored device, a corresponding recognition model may be established by using the method shown in fig. 3. The specific value of the preset threshold can be set by a worker according to actual needs. For example, the preset threshold may be 90% or 95%, etc.
After the service server receives the environment data sent by the identification server, the service server can directly send the environment data to the terminal device and send alarm information to the terminal device at the same time. After the service server receives the environment data sent by the identification server and the monitored device information corresponding to the environment data, the service server can send the environment data and the monitored device information corresponding to the environment data to the terminal device, and send alarm information to the terminal device at the same time. By sending alarm information and environmental data to the terminal equipment, the terminal equipment manager can be reminded that abnormal conditions exist in the surrounding environment of the monitored equipment corresponding to the environmental data, so that the manager can be prompted to investigate the surrounding environment of the monitored equipment in time, and harm is prevented or loss is reduced as far as possible. In addition, after receiving the environmental data and the monitored equipment information sent by the identification server, the service server can correspondingly store the environmental data and the monitored equipment information, so that the environmental data and the monitored equipment information can be conveniently called and maintained by later workers.
In one possible implementation, the environment data of the monitored device acquired by the monitoring device may include acquisition time information of the environment data. For example, a photo or a video of the monitored environment acquired by the monitoring device may contain a time watermark, or the acquisition time of the environment data may be used as independent information to form the environment data together with the photo or the video.
In a possible implementation manner, after receiving the environmental data and the monitored device information sent by the service server, the terminal device may correspondingly store the environmental data and the monitored device information, and may also correspondingly store the alarm information corresponding to the environmental data, so as to facilitate management of the management personnel on the historical data. In a possible implementation manner, the terminal device includes a display screen, and a manager of the terminal device can check the environmental data of the monitored device, the information of the monitored device, the corresponding alarm information, and the like through the display screen.
In one possible implementation, as shown in fig. 4, voice interaction may be performed between the monitoring device and the terminal device. Before the monitoring device and the terminal device perform voice interaction, an association matching relationship may be established for the monitoring device and the terminal device through the service server and based on the communication support provided by the communication device, and the service server may store the matching relationship between each monitored device and the terminal device. The monitoring equipment can collect audio information around the monitored equipment and send the collected audio information to the service server through the communication equipment, and the service server can send the audio information to the terminal equipment after receiving the audio information. After receiving the audio information collected by the monitoring device, the terminal device may play the audio information. Meanwhile, the terminal device may also collect audio information (e.g., audio information from a manager), and send the collected audio information to the service server through the communication device, and the service server may send the audio information to the monitoring device after receiving the audio information. After the monitoring equipment receives the audio information from the terminal equipment, the audio information can be played, so that real-time audio interaction between the monitoring equipment and the terminal equipment can be realized. For example, through the real-time audio interaction function between the monitoring device and the terminal device, the manager of the terminal device can directly warn or drive away people around the monitored device, thereby avoiding the occurrence of safety accidents as much as possible.
In a possible implementation manner, the video monitoring and identifying system based on the artificial intelligence technology provided by this embodiment further includes a power supply device. The power supply device is configured to supply power to the monitoring device, the communication device, the server, and the terminal device. Wherein, the power supply equipment can be one or more of a new energy power generation device, a primary battery, a secondary battery, a 220V alternating current power supply and the like. For example, the new energy power generation device may be a solar power generation device, a wind power generation device, a tidal power generation device, or the like. When the monitoring equipment is installed outdoors, the new energy power generation device can be adopted to supply power for the monitoring equipment. Alternatively, a primary battery, a secondary battery, a 220V ac power supply, or the like may be used to supply power to the monitoring device. For communication equipment, servers and terminal equipment, appropriate power supply equipment can be selected to supply power to the communication equipment, the servers and the terminal equipment. In one possible implementation, the monitoring device may periodically or aperiodically transmit its battery data to the server via the communication device and then to the terminal device. When the server (for example, a business server) judges that the battery power of the monitoring device is lower than the reference threshold value through a built-in program, alarm information can be sent to a manager of the terminal device through the terminal device. Through monitoring supervisory equipment's battery data, terminal equipment's managers can in time know supervisory equipment's electric quantity in service behavior. The specific value of the reference threshold can be set by a worker according to actual needs. For example, the reference threshold may be 20% or 30%, etc.
In one possible implementation, the identification server and the traffic server may each include a processor and a memory. The memory may store computer program instructions, and when the computer program instructions are executed by the processor, the functions of the identification server and the service server are realized.
By using the video monitoring and identifying system based on the artificial intelligence technology provided by the embodiment of the disclosure, the monitoring device can collect the environmental data of the monitored device and send the collected environmental data to the identifying server, the identifying server identifies the monitored device corresponding to the environmental data, and the identifying server judges whether the received environmental data is abnormal data according to the identifying model corresponding to the monitored device; when the environmental data are abnormal data, the identification server can send the environmental data to the service server, then the service server sends the environmental data to the terminal equipment, and the service server sends alarm information to the terminal equipment, so that a worker can be prompted to timely handle abnormal conditions around the monitored equipment, and safety accidents are avoided.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. The above-described method embodiments are merely illustrative, wherein the modules described as separate components may or may not be physically separate, and the functions of the modules may be implemented in one or more software and/or hardware when implementing the embodiments of the present specification. And part or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
In the description herein, reference to the description of the terms "one embodiment/mode," "some embodiments/modes," "example," "specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment/mode or example is included in at least one embodiment/mode or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to be the same embodiment/mode or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments/modes or examples. Furthermore, the various embodiments/aspects or examples and features of the various embodiments/aspects or examples described in this specification can be combined and combined by one skilled in the art without conflicting therewith.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
It will be understood by those skilled in the art that the foregoing embodiments are merely for clarity of illustration of the disclosure and are not intended to limit the scope of the disclosure. Other variations or modifications may occur to those skilled in the art, based on the foregoing disclosure, and are still within the scope of the present disclosure.
Claims (10)
1. A video monitoring and identification system based on artificial intelligence technology is characterized in that the system comprises: monitoring equipment, communication equipment, a server and terminal equipment;
the monitoring equipment is configured to collect environmental data of monitored equipment and send the environmental data to the server through the communication equipment;
the communication equipment is configured to provide communication connection between the monitoring equipment and the server and between the server and the terminal equipment;
the server is configured to judge whether the environment data are abnormal data, and when the environment data are abnormal data, alarm information is sent to the terminal equipment.
2. The artificial intelligence technology based video surveillance identification system of claim 1, wherein the server includes an identification server and a business server;
the monitoring device is configured to send the environment data to the identification server through the communication device;
the identification server is loaded with a plurality of identification models and is configured to identify the environmental data according to the identification models so as to judge whether the environmental data is abnormal data;
when the environment data is abnormal data, the identification server is further configured to send the environment data to the business server;
the service server is configured to send alarm information to the terminal device after receiving the environment data.
3. The video monitoring and identifying system based on artificial intelligence technology according to claim 2, wherein the identifying server is further configured to identify monitored device information corresponding to the environmental data according to the environmental data, and when the environmental data is abnormal data, send the monitored device information to the service server.
4. The artificial intelligence technology based video surveillance identification system of claim 3, wherein the business server is further configured to store the environmental data and the monitored device information correspondingly.
5. The artificial intelligence technology based video surveillance recognition system of claim 3, wherein the business server is further configured to send the environmental data and the monitored device information when sending alarm information to the terminal device.
6. The video monitoring and identifying system based on artificial intelligence technology according to claim 5, wherein the terminal device is configured to store the environment data and the monitored device information after receiving the environment data and the monitored device information.
7. The video monitoring and identifying system based on artificial intelligence technology as claimed in claim 2, wherein said service server stores said monitoring device and said terminal device to establish a matching relationship;
the monitoring device is further configured to collect audio information around the monitored device, and the terminal device is further configured to collect audio information around the terminal device;
and the monitoring equipment and the terminal equipment realize the interaction of audio information through the service server.
8. The artificial intelligence technology based video surveillance identification system of claim 1, further comprising a power supply device configured to supply power to the surveillance device, the communication device, the server, and the terminal device.
9. The video surveillance identification system based on artificial intelligence technology of claim 8, characterized in that the power supply equipment is one or more of a new energy power generation device, a primary battery, a secondary battery and a 220V ac power supply.
10. The video surveillance identification system based on artificial intelligence technology of any of claims 1-9, wherein the environmental data includes time information of acquisition of the environmental data.
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Application publication date: 20211001 |