CN117499241A - Intelligent supervision data dynamic processing method and system - Google Patents
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Abstract
The application discloses a dynamic processing method and a system for intelligent supervision data, wherein the method comprises the following steps: acquiring supervision monitoring data uploaded by a plurality of intelligent terminal devices; determining the importance level of the corresponding supervision event according to the supervision monitoring data; determining bandwidth allocation priority of the supervision event according to the importance level and the data stream size; and carrying out bandwidth allocation on the data stream of the corresponding supervision event according to the bandwidth allocation priority, and then uploading the data stream. According to the scheme, the confirmation of the corresponding bandwidth allocation priority is realized based on the importance level of the supervision event, so that the corresponding data stream is uploaded according to the allocated bandwidth after the data stream of the supervision event is subjected to bandwidth allocation according to the priority level, the monitoring data corresponding to the supervision event with higher importance level can be scheduled to upload the data preferentially, the abundant bandwidth resources are guaranteed preferentially, and the efficiency and quality of the supervision data uploading with high importance level are improved.
Description
Technical Field
The invention relates to a data processing technology of constructional engineering, in particular to a dynamic processing method and system for intelligent supervision data.
Background
The supervision of the construction project is provided for ensuring the rationality and compliance of the quality, safety, progress, funds and the like of the construction project, and is responsible for the supervision by an independent third party organization. In general, supervision works are performed by professional staff to obtain various conditions in the current construction project, such as construction progress, quality detection conditions of various nodes/links in the construction process, material consumption conditions, and capital investment/expenditure conditions, through checking construction conditions in the field, consulting engineering data documents, interviewing personnel on a construction site, or telephone communication.
Along with the development of digital technology and intelligent automation technology, the supervision information data related in the supervision work can be collected and uploaded in real time through a plurality of different intelligent automation terminals, so that the efficiency of the supervision work is improved, and the conclusion of whether to change the original building planning or not is quickly made according to the condition of the currently monitored building engineering. In the data transmission scenario of various intelligent automation terminals, in order to achieve reasonable and efficient utilization of bandwidth resources, bandwidth allocation is generally implemented according to attributes of a data stream (such as a source/destination IP address, a destination port number, a protocol number, a data volume, etc.) and/or a current state of a bandwidth (such as a current throughput, a packet loss rate, stability, etc.). However, when the bandwidth dynamic allocation method is applied to the scene of the supervision work, event data with low importance degree is scheduled to be remotely uploaded to a server of the supervision monitoring center preferentially, event data with high importance degree is delayed to be uploaded, even the situation that data is lost easily occurs in the transmission process, so that timeliness of event uploading and/or data integrity rate with high importance degree can be reduced, and efficiency of responding to corresponding follow-up implementation measures for the uploaded monitoring situation is reduced.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art. Therefore, the invention provides a method and a system for dynamically processing intelligent supervision data.
In a first aspect, an embodiment of the present application provides a method for dynamically processing intelligent supervision data, where the method includes:
acquiring supervision monitoring data uploaded by a plurality of intelligent terminal devices;
determining the importance level of the corresponding supervision event according to the supervision monitoring data;
determining the bandwidth allocation priority of the supervision event according to the importance level and the data stream size of the supervision event;
and after the bandwidth allocation priority is used for allocating the bandwidth of the data stream of the corresponding supervision event, uploading the data stream of the supervision event according to the allocated bandwidth.
In some embodiments, the determining, according to the proctorial monitoring data, the importance level of the corresponding proctorial event specifically includes:
determining event attributes of corresponding supervision events according to the supervision monitoring data, wherein the event attributes at least comprise security attributes, compliance attributes, quality attributes, progress attributes and/or conventional attributes;
and determining the importance level of the proctoring event according to at least one event attribute.
In some embodiments, the determining the importance level of the proctoring event according to at least one event attribute specifically includes:
calculating an important value of the determined event attribute of the supervision event; the importance value is calculated by the following formula:
I＝s*ω1+l*ω2+q*ω3+p*ω4+r*ω5
wherein s represents a corresponding value of whether or not there is a security attribute; l represents a corresponding value of whether there is a compliance attribute; q represents a corresponding value of whether or not there is a quality attribute; p represents a corresponding value of whether or not there is a progress attribute; r represents a corresponding numerical value of whether or not there is a conventional attribute; ω1 represents a weight coefficient corresponding to the security attribute; ω2 represents a weight coefficient corresponding to the compliance attribute; ω3 represents a weight coefficient corresponding to the quality attribute; ω4 represents a weight coefficient corresponding to the progress attribute; ω5 represents a weight coefficient corresponding to a conventional attribute; ω1 > ω2+ω3+ω4+ω5; ω2 > ω3+ω4+ω5; ω3 > ω4+ω5; ω4 > ω5;
and determining the corresponding importance level according to the importance value of the supervision event.
In some embodiments, the determining the importance level of the proctoring event according to at least one event attribute specifically includes:
constructing an input data matrix by using the safety attribute, the compliance attribute, the quality attribute, the progress attribute and the conventional attribute;
and inputting the input data matrix into a training model for processing, and outputting the importance level of the corresponding supervision event.
In some embodiments, the proctoring event with the importance level higher than or equal to the preset level is a first proctoring event, and the proctoring event with the importance level lower than the preset level is a second proctoring event; and determining the bandwidth allocation priority of the supervision event according to the importance level and the data stream size of the supervision event, wherein the bandwidth allocation priority comprises the following specific steps:
determining the bandwidth allocation priority of a first supervision event according to the importance level and the data stream size of the first supervision event;
and setting the uploading time of the second supervision event in a preset bandwidth idle period so as to enable the data stream of the second supervision event to be uploaded in the preset bandwidth idle period.
In some embodiments, the acquiring the supervision monitoring data uploaded by the plurality of intelligent terminal devices specifically includes:
when at least two supervision monitoring data uploaded by the intelligent terminal equipment correspond to the same supervision event, screening out the supervision monitoring data meeting the preset conditions.
In some embodiments, the intelligent terminal device includes a camera device and a smoke monitoring device; when at least two supervision monitoring data uploaded by the intelligent terminal equipment correspond to the same supervision event, screening out the supervision monitoring data meeting the preset conditions, wherein the method specifically comprises the following steps:
when the supervision events determined according to the monitoring data of the camera equipment and the smoke monitoring device belong to the same fire event, screening out supervision detection data with highest priority according to the priority of the file types of the supervision monitoring data, wherein the priority of the video file types is more than or equal to the priority of the image file types is more than or equal to the priority of the audio file types.
In some embodiments, the importance level of the proctoring event and the data stream size are proportional to the bandwidth allocation priority.
In a second aspect, an embodiment of the present application provides a system for dynamically processing intelligent supervision data, where the system includes:
the intelligent terminal equipment is used for realizing monitoring of the supervision event and uploading supervision monitoring data obtained by monitoring to the data transmission processing device;
the data transmission processing apparatus comprises at least one processor for performing steps implementing a method as described above.
In a third aspect, embodiments of the present application provide a computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method as described above.
The application can realize the following technical effects: according to the method, the importance levels of the corresponding supervision events are confirmed for the supervision monitoring data uploaded by the plurality of intelligent terminal devices, and then the corresponding bandwidth is distributed according to the determined importance levels and the data stream sizes of the monitoring data corresponding to the supervision events after the corresponding bandwidth distribution priorities are determined, so that the data stream of the supervision events is uploaded according to the distributed bandwidths.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the description of the embodiments will be briefly described.
FIG. 1 is a flowchart illustrating steps of an embodiment of a method for dynamically processing intelligent supervision data according to an embodiment of the present disclosure;
FIG. 2 is a flowchart illustrating steps of the method in step S2 in an embodiment of a method for dynamically processing intelligent supervision data according to the present disclosure;
fig. 3 is a schematic structural diagram of a dynamic processing system for intelligent supervision data according to an embodiment of the present disclosure.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the present application more clear, the technical solutions of the present application will be clearly and completely described by implementation with reference to the accompanying drawings in the examples of the present application, and it is apparent that the described examples are some, but not all, examples of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
With the development of digital technology and intelligent automation technology, many different intelligent automation terminals are used to develop construction work in the present construction engineering, such as a terrace construction robot, a concrete finishing robot, a building cleaning robot, an indoor and outdoor automatic spraying robot, a material automatic transfer robot, an automatic mixer, an automatic crane, a floor (materials such as ceramic tile and wood board) automatic paving robot, etc., meanwhile, in order to further improve the intelligent automation degree of the construction engineering, the supervision work also uses a plurality of different brake automation terminals to realize the monitoring of related objects and upload the monitored data in real time, thereby improving the efficiency of the supervision work, wherein the monitoring function module can be directly and intensively arranged in the above-mentioned robot for construction work, and can also be realized by using additional independent devices, such as aerial photographing devices for monitoring the construction engineering, smoke sensors for monitoring indoor space, environment monitoring devices for monitoring the environmental temperature/humidity/brightness/dust particles, audio devices for recording the employee interview content, attendance checking devices, and node real-time monitoring devices for staff progress.
In the data transmission scenario of various intelligent automation terminals, in order to achieve reasonable and efficient utilization of bandwidth resources, bandwidth allocation is generally implemented according to attributes of a data stream (such as a source/destination IP address, a destination port number, a protocol number, a data volume, etc.) and/or a current state of a bandwidth (such as a current throughput, a packet loss rate, stability, etc.). However, when the bandwidth dynamic allocation method is applied to the scene of the supervision work, event data with low importance degree is scheduled to be remotely uploaded to a server of the supervision monitoring center preferentially, event data with high importance degree is delayed to be uploaded, and the situation that data are lost or data transmission fails in the transmission process due to the fact that the allocated available bandwidth is too small in the transmission process occurs, so that timeliness and stability of event uploading with high importance degree are reduced, and efficiency of responding corresponding follow-up implementation measures for the uploaded monitoring situation is reduced. Therefore, in order to solve the problem, the scheme of the application provides a data transmission scheme capable of dynamically processing the supervision data based on the importance level of the supervision event.
Referring to fig. 1, a method for dynamically processing intelligent supervision data includes the following steps.
S1, acquiring supervision and monitoring data uploaded by a plurality of intelligent terminal devices.
Specifically, for the supervision monitoring data, the above mentioned monitoring function module may be used to monitor the target object in real time to obtain corresponding supervision monitoring data, where the supervision monitoring data may include: 1. safety data such as fire safety problems at construction sites, electricity safety problems, whether personnel enter the construction sites to wear safety helmets, whether equipment facilities at the construction sites have tilting and falling problems, and the like; 2. compliance data, for example, by comparing the detection data of the construction materials/finished construction products at the construction site with the detection standards prescribed by the building laws and regulations/projects, thereby determining whether the current construction materials/finished construction products are in compliance; 3. quality data such as whether an exterior wall paint has areas of missing spray, quality monitoring of paint material (e.g., whether deterioration, whether dry humidity is suitable for paint/discard/retune, etc.); 4. the progress data, for example, is obtained by identifying the current monitored construction state, comparing the identification result with the preset construction progress to determine whether the current construction progress is within the reasonable progress requirement, and at this time, the progress data can be the comparison result; 5. conventional data such as personnel attendance data at the construction site, conventionally recorded diary data, cost data of consumables, and the like. It should be noted that, for these supervision and monitoring data, the monitoring and identification technical means may be implemented by various existing technologies as required, so the embodiment is not limited in detail.
In addition, for the above-mentioned supervision and monitoring data, the file type thereof includes a video file, an image file, an audio file, a text/document file, and the like.
Moreover, from the supervision monitoring data, supervision events related to different event attributes can be determined, for example, automatic aerial monitoring is carried out on the construction site through a camera arranged on the unmanned aerial vehicle, after image recognition is carried out on aerial video monitoring data, if fire and smoke characteristics exist in recognition results, the current fire situation of the construction site is judged, the supervision event at the moment is recognized as a fire event, and the attribute of the event is configured as a safety attribute; or if the recognition result includes not only safety problems but also compliance, quality, progress and/or regularity problems after image recognition is performed by using video monitoring data obtained by aerial photography/video monitoring data obtained by shooting by other shooting devices arranged on different terminals or different construction sites, the attribute of the supervision event is configured as at least one of safety attribute, compliance attribute, quality attribute, progress attribute and regularity attribute accordingly. That is, for a proctoring event corresponding to proctoring monitoring data, it may be configured with at least one event attribute.
In addition, for the supervision monitoring data collected by different intelligent terminal devices, the supervision monitoring data collected by two different intelligent terminal devices may all belong to the same supervision event, at this time, screening and selecting the supervision monitoring data meeting the preset condition, namely selecting the supervision monitoring data uploaded by one of the intelligent terminal devices for monitoring and collecting, wherein the preset condition for selecting is mainly formulated based on the content amount which can be expressed by the supervision monitoring data, for example, the content amount which can be expressed by the video is larger than the content amount which can be expressed by the audio, and then the required supervision monitoring data can be screened out according to the type of the data file which can be monitored and collected by the intelligent terminal device.
Thus, for the step S1, it may specifically include:
and S101, screening out the supervision monitoring data meeting preset conditions when at least two supervision monitoring data uploaded by the intelligent terminal equipment correspond to the same supervision event.
Specifically, for the preset conditions, the preset conditions may include a data size, a data file type, basic information of the intelligent terminal device (such as a set position of the device), etc., for example, when both the supervision monitoring data uploaded by the a intelligent terminal device and the supervision monitoring data uploaded by the b intelligent terminal device refer to the same supervision matters, the supervision monitoring data with a large data size (because the content that the data with a large data size can be expressed is more) is selected, for example, the supervision monitoring data uploaded by the a intelligent terminal device; or selecting the file type as the supervision monitoring data of the video file on the basis of the same data volume; or, under the condition that the data quantity and the file type are the same, the supervision monitoring data uploaded by the intelligent terminal equipment with the setting position closer to the occurrence place of the event is selected (because the quality of the monitoring data monitored and collected by the intelligent terminal equipment with the position closer to the occurrence place of the event is better). Therefore, for the preset condition, the preset condition is mainly used for selecting the data with higher quality and richer data content as the supervision monitoring data of the subsequent uploading, so that the uploading of the redundant monitoring data belonging to the same supervision event can be avoided, and the data processing efficiency is improved on the basis of ensuring the transmission quality requirement, that is, the supervision monitoring data screened in the step is the data stream corresponding to the supervision event required to be uploaded in the subsequent step S4.
Further specifically, the intelligent terminal equipment comprises a camera device and a smoke monitoring device; when at least two pieces of supervision monitoring data uploaded by the intelligent terminal equipment correspond to the same supervision event, screening out the supervision monitoring data meeting the preset conditions, namely, step S101, which specifically comprises the following steps:
when the supervision events determined according to the monitoring data of the camera equipment and the smoke monitoring device belong to the same fire event, screening out supervision detection data with highest priority according to the priority of the file types of the supervision monitoring data, wherein the priority of the video file types is more than or equal to the priority of the image file types is more than or equal to the priority of the audio file types.
Specifically, when the smoke monitoring device arranged in the area a monitors that smoke exists, the smoke monitoring device can send the supervision monitoring data of the fire disaster in the area a, and the camera arranged on the unmanned plane or the camera fixedly arranged in the area a can also identify the supervision monitoring data of the fire disaster in the area a after video shooting and image identification are carried out on the video at the same time, therefore, the data monitored and collected by the camera equipment and the smoke monitoring device all correspond to the same supervision event (the same fire event), and in view of the fact that the information contained in the video data is better than the data information of other types, the supervision monitoring data uploaded by the camera equipment are selected as the supervision monitoring data corresponding to the characterization event, and when the subsequent determination is carried out on the fire event, the supervision monitoring data of the camera equipment can be uploaded.
It should be noted that, for the data obtained by monitoring the smoke monitoring device, the data may be stored in a server at the construction site, and when needed, a transmission instruction is issued by a background server of the monitoring center to enable the data of the smoke monitoring device to be uploaded in an idle period.
Further, since a construction site may have a fire in the construction site and various materials/devices are piled up on the construction site, but a video shot by a camera device on an unmanned plane only shoots scattered smoke, as well as a smoke monitoring device, which monitors only the scattered smoke, and the monitored smoke may not be emitted due to the occurrence of a fire igniting an object, in order to avoid false triggering of a supervision event for a fire, the implementation steps in some embodiments may include the following steps for determining that the supervision event belongs to a fire event.
S1011, acquiring first video data, wherein the first video data is obtained by shooting by first camera equipment arranged on an unmanned plane, and the first camera equipment is a common color CCD camera.
And S1012, acquiring first smoke data, wherein the first smoke data are obtained by monitoring and acquiring by a smoke monitoring device, and the smoke monitoring device is fixedly arranged on a corresponding place area, so that when the first smoke data are obtained by monitoring, the first smoke data can comprise identification data used for indicating that smoke exists or does not exist.
S1013, smoke image recognition is carried out on the first video data to obtain a smoke recognition result.
Specifically, the smoke recognition result includes that the images in the video contain smoke, and the images in the video do not contain smoke; the smoke image recognition algorithm is mainly used for recognizing the characteristic region of smoke and does not relate to the recognition of the characteristic region of fire;
s1014, when the smoke identification result is that smoke exists in an image in a video, and/or the first smoke data contains identification data used for indicating that the smoke exists, controlling the unmanned aerial vehicle to fly to a place area displayed in the first video data or the layout position of a smoke monitoring device, and starting a second camera device arranged on the unmanned aerial vehicle to shoot so as to obtain first thermal imaging image data; wherein the second image capturing apparatus is a thermal imaging capturing apparatus.
Specifically, since many materials are placed on the construction site and based on diversity of building designs, many dead zones exist on the construction site, so that when a fire occurs, only smoke can be monitored and whether a fire actually exists or not can not be monitored in many times, and when a general CCD color image is used for fire identification, namely, fire characteristic area identification is carried out on the image, when the fire characteristics are identified, the fire is relatively large (because the fire is generally exposed to barriers, and can be identified from the image), so that early detection and resolution of the fire are not facilitated. Therefore, when the smoke recognition result is that the images in the video contain smoke, and/or the first smoke data contains identification data for representing that the smoke exists, according to a place area displayed in the first video data or a layout position of the smoke monitoring device (the layout position belongs to a certain position of the place area), the unmanned plane is controlled to fly close to the place area, fly to a place close to the place where the smoke emits and bypass a barrier/barrier, a thermal imaging camera arranged on the unmanned plane is started to shoot at the moment, then the shot thermal imaging image is subjected to image recognition of a flame temperature area, and when the temperature corresponding to the temperature area existing in the thermal imaging image is recognized to be within a preset flame temperature threshold range, the current monitored supervision event can be determined to be a fire event, and the event attribute is a safety attribute.
S1015, after the flame temperature area is identified from the first thermal imaging image, the supervision events corresponding to the monitored data shot by the first shooting device and the second shooting device on the unmanned plane and the data monitored by the smoke monitoring device can be determined to be the same fire event.
Therefore, when a fire disaster occurs in a place area, the shooting equipment of the unmanned plane and the smoke monitoring device of the place area can monitor and obtain corresponding monitoring data, and then the supervision events corresponding to the monitoring data of the shooting equipment and the smoke monitoring device can be configured to be the same event, and based on the fact that files acquired by the shooting equipment are video/image data, the data monitored by the smoke monitoring device are only document data, so that uploading of the monitoring data of the shooting equipment is considered. In addition, in this embodiment, the unmanned aerial vehicle can be controlled to fly close to the place area according to the place area displayed in the first video data or the layout position of the smoke monitoring device, and the flame area is identified only by using the thermal imaging diagram, so that the timeliness of fire disaster identification can be greatly improved, and because the unmanned aerial vehicle can be shot close to the scene, the shot image can be clearer and can bypass the barrier/obstacle, so that the accuracy of the flame area identification result can be greatly improved.
S2, determining the importance level of the corresponding supervision event according to the supervision monitoring data.
Specifically, the supervision event may have at least one event attribute, such as a security attribute, a compliance attribute, a quality attribute, a progress attribute, and a regular attribute, where the importance of the security attribute > the importance of the compliance attribute > the importance of the quality attribute > the importance of the progress attribute > the importance of the regular attribute, so the importance level of the supervision event may be determined according to the importance of the event attribute and the importance of the different event attribute of the currently monitored and identified monitoring event, where the higher the importance of the event attribute of the supervision event, the higher the importance level of the supervision event.
Thus, in some embodiments, referring to fig. 2, step S2 may specifically include the following sub-steps.
S201, determining event attributes of corresponding supervision events according to the supervision monitoring data, wherein the event attributes at least comprise security attributes, compliance attributes, quality attributes, progress attributes and/or conventional attributes.
S202, determining the importance level of the supervision event according to at least one event attribute.
In some embodiments, the implementation of step S202 may be in two ways.
Mode 1: step S202 determines the importance level by calculation of the importance value, and specifically includes the following substeps.
S2021, calculating an important value of the determined event attribute of the supervision event.
In some embodiments, as the importance of the security attribute > the importance of the quality attribute > the importance of the progress attribute > the importance of the regular attribute, the importance value corresponding to the security attribute > the importance value corresponding to the quality attribute > the importance value corresponding to the progress attribute > the importance value corresponding to the regular attribute, that is:
when the event attribute of the supervision event comprises a security attribute, the important value of the event attribute of the supervision event is a first important value;
when the event attribute of the supervision event does not contain the safety attribute and contains the compliance attribute, the important value of the event attribute of the supervision event is a second important value;
when the event attribute of the supervision event does not contain the safety attribute, the compliance attribute and the quality attribute, the important value of the event attribute of the supervision event is a third important value;
when the event attribute of the supervision event does not contain the safety attribute, the compliance attribute and the quality attribute and contains the progress attribute, the important value of the event attribute of the supervision event is a fourth important value;
when the event attribute of the supervision event does not contain the safety attribute, the compliance attribute, the quality attribute and the progress attribute and contains the progress attribute, the important value of the event attribute of the supervision event is a fifth important value;
wherein the first importance value > the second importance value > the third importance value > the fourth importance value > the fifth importance value. The importance value and the importance level are in a proportional relation, that is, the larger the importance value is, the higher the corresponding importance level is.
In some embodiments, the importance value of the event attribute for the proctoring event may be calculated by the following formula:
I＝s*ω 1 +l*ω 2 +q*ω 3 +p*ω 4 +r*ω 5
wherein s represents a corresponding value of whether or not there is a security attribute; l represents a corresponding value of whether there is a compliance attribute; q represents a corresponding value of whether or not there is a quality attribute; p represents a corresponding value of whether or not there is a progress attribute; r represents a corresponding numerical value of whether or not there is a conventional attribute; omega 1 The weight coefficient corresponding to the safety attribute is represented; omega 2 The weight coefficient corresponding to the compliance attribute is represented; omega 3 The weight coefficient corresponding to the quality attribute is represented; omega 4 The weight coefficient corresponding to the progress attribute is represented; omega 5 The weight coefficient corresponding to the conventional attribute is represented; omega 1 ＞ω 2 +ω 3 +ω 4 +ω 5 ；ω 2 ＞ω 3 +ω 4 +ω 5 ；ω 3 ＞ω 4 +ω 5 ；ω 4 ＞ω 5 。ω 1 、ω 2 、ω 3 、ω 4 、ω 5 All are positive numbers.
For the corresponding value of s, l, q, p, r, the value is 0 or 1, when the value is 0, it indicates that the supervision event does not have the corresponding event attribute, whereas when the value is 1, it indicates that the supervision event has the corresponding event attribute, for example, when the supervision event has only the security attribute, i1=1×ω 1 +0*ω 2 +0*ω 3 +0*ω 4 +0*ω 5 The method comprises the steps of carrying out a first treatment on the surface of the I2=0×ω when the supervision event has compliance properties and quality properties 1 +1*ω 2 +1*ω 3 +0*ω 4 +0*ω 5 The method comprises the steps of carrying out a first treatment on the surface of the I3=1×ω when the proctoring event has security and regular properties 1 +0*ω 2 +0*ω 3 +0*ω 4 +1*ω 5 . Obviously, I3 > I1 > I2, so that when the monitored event has at least 2 event attributes, the calculation formula can be used to quickly calculate the importance value, i.e. to facilitate further subdividing the importance level of the monitored event, for example, when the event attributes of two monitored events both include safety attributes, if one of the event attributes further includes compliance attributes (i.e. the safety problem occurring in the monitored event also involves compliance), and the other monitored event does not involve compliance, the safety problem occurring in one monitored event is more severe than the safety problem occurring in the other monitored event, so that the importance level of one monitored event including the safety attributes and the compliance attributes should be higher than the importance level of the other monitored event including only the safety attributes.
S2022, determining a corresponding importance level according to the importance value of the supervision event.
Specifically, the importance value and the importance level are in a proportional relationship, that is, the larger the importance value is, the higher the corresponding importance level is. Therefore, the method can be used for different values according to the calculated importance value
Mode 2: step S202 outputs the corresponding importance level by training the model, and specifically includes the following substeps.
S2023, constructing an input data matrix by the security attribute, the compliance attribute, the quality attribute, the progress attribute and the conventional attribute.
Specifically, for the input data matrix, it may be [ s×ω ] 1 ，l*ω 2 ，q*ω 3 ，p*ω 4 ，r*ω 5 ]Similarly, when the corresponding value of s, l, q, p, r is 0 or 1, the value of 0 indicates that the supervision event does not have the corresponding event attribute, and vice versaWhen the value is 1, it indicates that the supervision event has the corresponding event attribute, so that, for example, when s and l are both 0, then there is no security attribute and no compliance attribute, the input data matrix is [0, 1 ] 3 ，1*ω 4 ，1*ω 5 ]。
S2024, inputting the input data matrix into a training model for processing, and outputting the importance level of the corresponding supervision event.
Specifically, for the training model, the event attribute of the historical supervision event and the corresponding historical importance level are used for training, so that the trained training model can be actually used for running, and the corresponding importance level can be output after the input data matrix of the event attribute contained in the actual supervision event is input into the training model for processing.
For the importance level confirmation methods of the above methods 1 and 2, the memory resources required by the method 1 are less and the requirements on the hardware device are not high, while the accuracy of the method 2 is higher, so for the user end, it can be selected according to the actual situation, of course, both the method 1 and the method 2 can be implemented on the device, and then in the actual operation process, the dynamic selection of the method 1 and the method 2 can be performed according to the current device state, thereby realizing the confirmation of the importance level.
And S3, determining the bandwidth allocation priority of the supervision event according to the importance level and the data stream size of the supervision event.
Specifically, for bandwidth allocation priority, it mainly contains scheduling priority, that is, the higher the importance level, the more preferentially it is scheduled for bandwidth allocation to upload data.
Further, considering some data with lower importance degree, such as conventional data not related to safety, compliance, quality and progress, for example, conventional supervision events such as personnel absences, that is, when the event attribute of the supervision event only includes conventional attributes, the corresponding supervision monitoring data essence can be directly configured in a preset bandwidth idle period to upload, for example, the data with lower importance degree is uploaded at 11-12 pm and with idle bandwidth, so that the supervision events with lower importance degree do not need to be considered each time in the process of determining the bandwidth allocation priority of each supervision event, and the data processing efficiency is further improved.
Therefore, for step S3, it may specifically include:
s301, determining the bandwidth allocation priority of a first supervision event according to the importance level and the data stream size of the first supervision event.
For the above step S301, it may include:
s3011, determining bandwidth allocation priority of a first supervision event according to the importance level of the first supervision event, wherein the importance level of the first supervision event and the corresponding bandwidth allocation priority are in a proportional relation;
s3012, when the importance levels of at least two first supervision events are the same, enabling the bandwidth allocation priorities of the at least two first supervision events to be in a proportional relation with the size of the data stream; specifically, in at least two first supervision events with the same importance level, the larger the data quantity of the data stream to be uploaded is, namely the higher the corresponding priority is, so that on the premise of uploading the supervision event with the larger importance level, the monitoring data with the larger data quantity can be preferentially allocated with more bandwidth, the situation that data loss or data transmission failure occurs due to the fact that the data quantity is large but the allocated bandwidth is too small can be reduced, and the stability and quality of event uploading with the high importance level are improved.
S302, the uploading time of the second supervision event is set in a preset bandwidth idle period, so that the data stream of the second supervision event is uploaded in the preset bandwidth idle period.
The supervision events with the importance level higher than or equal to the preset level are first supervision events, and the supervision events with the importance level lower than the preset level are second supervision events. Specifically, in this embodiment, for the second proctorial event, it may refer to a proctorial event whose event attribute only includes a conventional attribute, where the proctorial event corresponds to an importance value ω 5 The corresponding importance level is the nth importance level, then byAnd (3) setting a preset level, and screening the second supervision event. Of course, in view of the difference of the event attributes, the corresponding importance levels are different, and in other embodiments, the actual value of the preset level may be set according to the actual requirement, so as to screen out the required supervision event to be used as the second supervision event.
It can be seen that for bandwidth allocation priority, it may be proportional to both the importance level of the proctoring event and the data stream size.
And S4, after the bandwidth allocation priority is carried out on the data stream of the corresponding supervision event, uploading the data stream of the supervision event according to the allocated bandwidth.
Specifically, according to the bandwidth allocation priority determined in the step 3, namely the scheduling priority, the supervision monitoring data corresponding to the corresponding supervision event is uploaded with the allocated bandwidth.
Referring to fig. 3, the present application further provides a system for dynamically processing intelligent supervision data, the system comprising:
the intelligent terminal equipment is used for realizing supervision event monitoring and uploading supervision monitoring data obtained by monitoring to the data transmission processing device;
data transmission processing apparatus comprising at least one processor for performing the steps of the method according to any of the method embodiments described above.
The intelligent terminal equipment can be intelligent terminal equipment with an intelligent monitoring function only, or intelligent terminal equipment with other functions (such as various building automation functions and automatic voice and video recording and identifying functions) besides the intelligent monitoring function.
The number of the processors may be at least 1, at least any step in the above method embodiments may be performed, and when the number is at least two, at least two processors may be connected in communication, not limited to wired or wireless communication, and the at least one processor may be connected in communication with various intelligent terminal devices. In addition, for the processor, it may be a central processing unit (Central Processing Unit, CPU), but also other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Furthermore, the present application provides a computer readable storage medium storing a computer program for executing steps of implementing the above-mentioned method embodiments by a processor.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not limit the implementation process of the embodiment of the present application in any way.
Note that the above is only a preferred embodiment of the present application and the technical principle applied. Those skilled in the art will appreciate that the present application is not limited to the particular embodiments described herein, but is capable of numerous obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the present application. Therefore, while the present application has been described in connection with the above embodiments, the present application is not limited to the above embodiments, but may include many other equivalent embodiments without departing from the spirit of the present application, the scope of which is defined by the scope of the appended claims.
Claims (10)
1. A dynamic processing method for intelligent supervision data is characterized by comprising the following steps:
acquiring supervision monitoring data uploaded by a plurality of intelligent terminal devices;
determining the importance level of the corresponding supervision event according to the supervision monitoring data;
determining the bandwidth allocation priority of the supervision event according to the importance level and the data stream size of the supervision event;
and after the bandwidth allocation priority is used for allocating the bandwidth of the data stream of the corresponding supervision event, uploading the data stream of the supervision event according to the allocated bandwidth.
2. The method according to claim 1, wherein the determining the importance level of the corresponding proctorial event according to the proctorial monitoring data specifically includes:
determining event attributes of corresponding supervision events according to the supervision monitoring data, wherein the event attributes at least comprise security attributes, compliance attributes, quality attributes, progress attributes and/or conventional attributes;
and determining the importance level of the proctoring event according to at least one event attribute.
3. The method according to claim 2, wherein said determining the importance level of the proctorial event based on at least one of the event attributes, comprises:
calculating an important value of the determined event attribute of the supervision event; the importance value is calculated by the following formula:
I＝s*ω 1 +l*ω 2 +q*ω 3 +p*ω 4 +r*ω 5
wherein s represents a corresponding value of whether or not there is a security attribute; l represents a corresponding value of whether there is a compliance attribute; q represents a corresponding value of whether or not there is a quality attribute; p represents a corresponding value of whether or not there is a progress attribute; r represents a corresponding numerical value of whether or not there is a conventional attribute; omega 1 The weight coefficient corresponding to the safety attribute is represented; omega 2 The weight coefficient corresponding to the compliance attribute is represented; omega 3 The weight coefficient corresponding to the quality attribute is represented; omega 4 The weight coefficient corresponding to the progress attribute is represented; omega 5 The weight coefficient corresponding to the conventional attribute is represented; omega 1 ＞ω 2 +ω 3 +ω 4 +ω 5 ；ω 2 ＞ω 3 +ω 4 +ω 5 ；ω 3 ＞ω 4 +ω 5 ；ω 4 ＞ω 5 ；
And determining the corresponding importance level according to the importance value of the supervision event.
4. The method according to claim 2, wherein said determining the importance level of the proctorial event based on at least one of the event attributes, comprises:
constructing an input data matrix by using the safety attribute, the compliance attribute, the quality attribute, the progress attribute and the conventional attribute;
and inputting the input data matrix into a training model for processing, and outputting the importance level of the corresponding supervision event.
5. The method of claim 1, wherein the proctoring event having an importance level greater than or equal to a predetermined level is a first proctoring event, and wherein the proctoring event having an importance level less than the predetermined level is a second proctoring event; and determining the bandwidth allocation priority of the supervision event according to the importance level and the data stream size of the supervision event, wherein the bandwidth allocation priority comprises the following specific steps:
determining the bandwidth allocation priority of a first supervision event according to the importance level and the data stream size of the first supervision event;
and setting the uploading time of the second supervision event in a preset bandwidth idle period so as to enable the data stream of the second supervision event to be uploaded in the preset bandwidth idle period.
6. The method of claim 1, wherein the obtaining the supervision and monitoring data uploaded by the plurality of intelligent terminal devices specifically includes:
when at least two supervision monitoring data uploaded by the intelligent terminal equipment correspond to the same supervision event, screening out the supervision monitoring data meeting the preset conditions.
7. The method according to claim 6, wherein the intelligent terminal equipment comprises a camera device and a smoke monitoring device; when at least two supervision monitoring data uploaded by the intelligent terminal equipment correspond to the same supervision event, screening out the supervision monitoring data meeting the preset conditions, wherein the method specifically comprises the following steps:
when the supervision events determined according to the monitoring data of the camera equipment and the smoke monitoring device belong to the same fire event, screening out supervision detection data with highest priority according to the priority of the file types of the supervision monitoring data, wherein the priority of the video file types is more than or equal to the priority of the image file types is more than or equal to the priority of the audio file types.
8. The method of any of claims 1-7, wherein the importance level and data flow size of the proctoring event are proportional to the bandwidth allocation priority.
9. An intelligent supervision data dynamic processing system, characterized in that the system comprises:
the intelligent terminal equipment is used for realizing monitoring of the supervision event and uploading supervision monitoring data obtained by monitoring to the data transmission processing device;
data transmission processing apparatus comprising at least one processor for performing the steps of implementing the method according to any one of claims 1 to 8.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 8.
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Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106162109A (en) * | 2016-08-30 | 2016-11-23 | 浙江大华技术股份有限公司 | A kind of remote monitoring method and monitoring device |
| CN108182547A (en) * | 2018-01-29 | 2018-06-19 | 广东至衡工程管理有限公司 | Project supervision supervisory systems |
| CN108683673A (en) * | 2018-05-22 | 2018-10-19 | 厦门港湾咨询监理有限公司 | Long-range multiple terminals Supervision Organization work service managing and control system |
| CN109413205A (en) * | 2018-12-04 | 2019-03-01 | 北京诺士诚国际工程项目管理有限公司 | A kind of management data uploading method and device |
| CN109784750A (en) * | 2019-01-28 | 2019-05-21 | 珠海金慧科技有限公司 | Finishing progress and the unmanned long-range policing algorithm of quality |
| CN209785110U (en) * | 2019-07-16 | 2019-12-13 | 建基工程咨询有限公司 | data transmission system for supervision |
| CN112270521A (en) * | 2020-10-14 | 2021-01-26 | 广东展诚工程咨询有限公司 | Engineering supervision system based on online real-time information exchange |
| CN114140999A (en) * | 2021-11-16 | 2022-03-04 | 广东重工建设监理有限公司 | Engineering supervision system based on communication of Internet of things |
| CN114580877A (en) * | 2022-02-25 | 2022-06-03 | 中建安工程管理有限公司 | Engineering supervision safety monitoring method and system |
| CN115271511A (en) * | 2022-08-10 | 2022-11-01 | 吴媛 | Method for supervising construction engineering quality |
| CN115345491A (en) * | 2022-08-17 | 2022-11-15 | 李路敏 | Intelligent supervision system for communication engineering |
| KR102489400B1 (en) * | 2022-09-28 | 2023-01-18 | 방재웅 | Smart supervision and construction project management system for efficient construction management |
| CN116384667A (en) * | 2023-03-18 | 2023-07-04 | 江苏嘉裕工程管理咨询有限公司 | Engineering supervision monitoring system |
| CN116644943A (en) * | 2023-07-26 | 2023-08-25 | 湖南湘江城市运营管理有限公司 | Engineering supervision data management system based on Internet of things |
| CN116797151A (en) * | 2022-03-15 | 2023-09-22 | 周璨 | Engineering supervision system utilizing artificial intelligence mode |
-
2023
- 2023-11-03 CN CN202311456754.3A patent/CN117499241A/en active Pending
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106162109A (en) * | 2016-08-30 | 2016-11-23 | 浙江大华技术股份有限公司 | A kind of remote monitoring method and monitoring device |
| CN108182547A (en) * | 2018-01-29 | 2018-06-19 | 广东至衡工程管理有限公司 | Project supervision supervisory systems |
| CN108683673A (en) * | 2018-05-22 | 2018-10-19 | 厦门港湾咨询监理有限公司 | Long-range multiple terminals Supervision Organization work service managing and control system |
| CN109413205A (en) * | 2018-12-04 | 2019-03-01 | 北京诺士诚国际工程项目管理有限公司 | A kind of management data uploading method and device |
| CN109784750A (en) * | 2019-01-28 | 2019-05-21 | 珠海金慧科技有限公司 | Finishing progress and the unmanned long-range policing algorithm of quality |
| CN209785110U (en) * | 2019-07-16 | 2019-12-13 | 建基工程咨询有限公司 | data transmission system for supervision |
| CN112270521A (en) * | 2020-10-14 | 2021-01-26 | 广东展诚工程咨询有限公司 | Engineering supervision system based on online real-time information exchange |
| CN114140999A (en) * | 2021-11-16 | 2022-03-04 | 广东重工建设监理有限公司 | Engineering supervision system based on communication of Internet of things |
| CN114580877A (en) * | 2022-02-25 | 2022-06-03 | 中建安工程管理有限公司 | Engineering supervision safety monitoring method and system |
| CN116797151A (en) * | 2022-03-15 | 2023-09-22 | 周璨 | Engineering supervision system utilizing artificial intelligence mode |
| CN115271511A (en) * | 2022-08-10 | 2022-11-01 | 吴媛 | Method for supervising construction engineering quality |
| CN115345491A (en) * | 2022-08-17 | 2022-11-15 | 李路敏 | Intelligent supervision system for communication engineering |
| KR102489400B1 (en) * | 2022-09-28 | 2023-01-18 | 방재웅 | Smart supervision and construction project management system for efficient construction management |
| CN116384667A (en) * | 2023-03-18 | 2023-07-04 | 江苏嘉裕工程管理咨询有限公司 | Engineering supervision monitoring system |
| CN116644943A (en) * | 2023-07-26 | 2023-08-25 | 湖南湘江城市运营管理有限公司 | Engineering supervision data management system based on Internet of things |
Non-Patent Citations (2)
| Title |
|---|
| 李琳琳;曹凯滨;谢伟秋;: "可视化监理平台的研究与实现", 测绘与空间地理信息, no. 01, 25 January 2014 (2014-01-25) * |
| 董玉友;张钢;: "建设项目施工现场实时监理影像信息系统", 电子测量技术, no. 08, 15 August 2007 (2007-08-15) * |
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