CN115964645B - Big data-based information processing method and system - Google Patents
Big data-based information processing method and system Download PDFInfo
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Abstract
The invention is applicable to the field of computers, and provides an information processing method and system based on big data, wherein the method comprises the following steps: acquiring target supervision information, wherein the target supervision information comprises information to be supervised of a target area, the information to be supervised comprises a sub-area to be supervised and supervision behaviors based on the sub-area to be supervised, the sub-area to be supervised comprises an abnormal sub-area which accords with the characteristics of the abnormal area in the target area, and the characteristics of the abnormal area are used for representing the existence of abnormal working parameters and/or abnormal behavior characteristics in at least one sub-area; detecting whether the supervision behavior is matched with the sub-region to be supervised; when the supervision behavior is detected to be unmatched with the sub-region to be supervised, central alarm information is generated, and the beneficial effects of the embodiment of the application are that: and the release and implementation of the third party intervention operation instruction aiming at the abnormal situation are promoted, and the guarantee is provided for the standard operation and the safe production.
Description
Technical Field
The invention belongs to the field of computers, and particularly relates to an information processing method and system based on big data.
Background
Industrial safety production is very important, and production safety consists of personal safety and property safety, and each safety accident can bring property loss, even threaten the personal safety of vast personnel, for example, when related operations are carried out in areas such as power stations, intelligent construction sites, workshops and the like, advanced technical means are used for continuously improving the safety operation level.
In the prior art, a perfect video monitoring system is arranged so as to analyze, monitor and evidence critical risk operation points in an operation area, thereby eliminating on-site dangerous sources.
However, the above-mentioned prior art method only plays a role in post evidence collection, has poor timeliness, and cannot monitor behaviors of management personnel in time.
Disclosure of Invention
The embodiment of the invention aims to provide an information processing method and system based on big data, which aim to solve the problems in the background technology.
The embodiment of the invention is realized in such a way that, on one hand, the information processing method based on big data comprises the following steps:
acquiring target supervision information, wherein the target supervision information comprises information to be supervised of a target area, the information to be supervised comprises a sub-area to be supervised and supervision behaviors based on the sub-area to be supervised, the sub-area to be supervised comprises an abnormal sub-area which accords with the characteristics of the abnormal area in the target area, and the characteristics of the abnormal area are used for representing the existence of abnormal working parameters and/or abnormal behavior characteristics in at least one sub-area;
Detecting whether the supervision behavior is matched with the sub-region to be supervised;
when the supervision behavior is detected to be unmatched with the sub-area to be supervised, generating central alarm information, wherein the unmatched supervision behavior and the unmatched sub-area to be supervised comprise: and the sub-area to be supervised is not confirmed by operation within a first preset time period, or after the sub-area to be supervised is confirmed by operation, no improved feedback information is received within a second preset time period, wherein the improved feedback information comprises third party recovery intervention information which is identified to be specific to abnormal working parameters and/or abnormal behavior characteristics in the abnormal sub-area, and the third party recovery intervention information is generated according to a third party intervention operation instruction.
As a further aspect of the present invention, the method further includes:
the method comprises the steps of obtaining pre-positioning information of a supervisor, wherein the supervisor comprises a subregion and a supervisor center for setting the supervisor;
detecting whether a first supervision requirement exists by a supervision person based on the pre-positioning information;
when a first supervision requirement of a supervision person is detected, locating a first subarea covered by the first supervision requirement in the subarea, wherein the first supervision requirement is used for representing that the supervision person has a delay supervision requirement or exchanges the supervision requirement;
Detecting the matching degree between the characteristic of the working parameter of the first subarea and the supervision characteristic in a set period before the current moment, and generating a pre-supervision matching result;
and generating a demand treatment indication according to the first supervision demand and the pre-supervision matching result, wherein the demand treatment indication is used for representing whether the first supervision demand is qualified or not.
As still further aspect of the present invention, the detecting the matching degree between the feature of the working parameter of the first sub-area and the supervision feature in the set period before the current time, and generating the pre-supervision matching result specifically includes:
identifying an abnormal change time node of the working parameters of the first subarea in a set period before the current moment;
identifying response time periods and comparison operation handling information corresponding to the abnormal change time nodes, wherein the comparison operation handling information corresponds to abnormal types of the abnormal change time nodes;
acquiring supervision operation information of a first subarea in a set period before the current moment;
judging whether the supervision operation information accords with the response time period and the contrast operation treatment information respectively;
if yes, generating a first pre-supervision matching result, wherein the first pre-supervision matching result is used for representing pre-supervision matching;
Otherwise, generating a second pre-supervision matching result, wherein the second pre-supervision matching result is used for representing that the pre-supervision is not matched.
As a still further aspect of the present invention, the method further includes:
when the front supervision matching result is detected to be a first front supervision matching result, identity authentication is carried out on supervision personnel of at least two parties corresponding to the first supervision requirement;
when the identity authentication result meets the identity setting condition, sending prompt information about the first supervision requirement, and acquiring the consent information of supervision personnel of at least two corresponding parties;
and generating a first demand treatment indication according to the first pre-supervision matching result and the agreement information, wherein the first demand treatment indication is used for representing that the first supervision demand is qualified.
As a further aspect of the present invention, the method further includes:
traversing historical behavior record information of a target area;
counting suspicious occurrence bits of abnormal behaviors in the target area according to the traversing result;
acquiring a supplementary mark bit of a target area;
the method comprises the steps of obtaining a sub-area to be identified of abnormal behavior characteristics, detecting the sub-area to be identified to generate an abnormal sub-area conforming to the abnormal area characteristics, wherein the identification priority of suspicious occurrence bits in the sub-area to be identified is the highest priority, and the sub-area to be identified comprises suspicious occurrence bits and supplementary marking bits.
As a further aspect of the present invention, the method further includes:
when detecting that the subregion to be supervised is confirmed by operation, generating a third party intervention operation instruction matched with the abnormal subregion;
issuing a third-party intervention operation instruction to a first terminal shared by a plurality of abnormal subareas so as to instruct the first terminal to forward the third-party intervention operation instruction to all second terminals in the abnormal subareas, wherein the plurality of second terminals are in real-time communication connection with a certain first terminal, and the second terminal is a terminal where a movable target in the abnormal subarea is located;
when the second terminal meets the intervention setting condition, the second terminal is instructed to send intervention operation prompt information and feed the intervention operation prompt information back to the corresponding first terminal, the corresponding first terminal is instructed to take the second terminal as a recognition positioning point, the intervention operation information of a movable target corresponding to the second terminal is started to be recognized, when the intervention operation information is recognized to be in accordance with the operation information in the intervention operation instruction of a third party, the corresponding intervention operation is recorded, the intervention information is generated, the intervention setting condition comprises that operation starting information is received;
And indicating the corresponding first terminal to report the third party recovery intervention information.
As a further aspect of the present invention, the method further includes:
the central alarm information is distinguished into alarm levels according to different detection conditions, wherein the different detection conditions comprise a first detection condition and a second detection condition, the first detection condition comprises that the sub-area to be supervised is not confirmed by operation within a first preset duration, the second detection condition comprises that no improvement feedback information is received within a second preset duration, and the alarm level corresponding to the first detection condition is lower than the alarm level corresponding to the second detection condition.
As a further aspect of the present invention, in another aspect, an information processing system based on big data, the system includes:
the supervision information acquisition and distinguishing unit is used for: acquiring target supervision information, wherein the target supervision information comprises information to be supervised of a target area, the information to be supervised comprises a sub-area to be supervised and supervision behaviors based on the sub-area to be supervised, the sub-area to be supervised comprises an abnormal sub-area which accords with the characteristics of the abnormal area in the target area, and the characteristics of the abnormal area are used for representing the existence of abnormal working parameters and/or abnormal behavior characteristics in at least one sub-area;
A match detection unit configured to: detecting whether the supervision behavior is matched with the sub-region to be supervised;
a condition distinguishing and alarming unit for: when the supervision behavior is detected to be unmatched with the sub-area to be supervised, generating central alarm information, wherein the unmatched supervision behavior and the unmatched sub-area to be supervised comprise: and the sub-area to be supervised is not confirmed by operation within a first preset time period, or after the sub-area to be supervised is confirmed by operation, no improved feedback information is received within a second preset time period, wherein the improved feedback information comprises third party recovery intervention information which is identified to be specific to abnormal working parameters and/or abnormal behavior characteristics in the abnormal sub-area, and the third party recovery intervention information is generated according to a third party intervention operation instruction.
As a further aspect of the present invention, the system further includes:
the traversing unit is used for traversing the historical behavior record information of the target area;
a statistics unit for: counting suspicious occurrence bits of abnormal behaviors of the target area according to the traversing result;
a supplementary acquisition unit for: acquiring a supplementary mark bit of a target area;
a detection and generation unit for: the method comprises the steps of obtaining a sub-area to be identified of abnormal behavior characteristics, detecting the sub-area to be identified to generate an abnormal sub-area conforming to the abnormal area characteristics, wherein the identification priority of suspicious occurrence bits in the sub-area to be identified is the highest priority, and the sub-area to be identified comprises suspicious occurrence bits and supplementary marking bits.
The information processing method and system based on big data provided by the embodiment of the invention extract the information to be supervised of a target area by acquiring the target supervision information, wherein the information to be supervised comprises a sub-area to be supervised and a supervision behavior based on the sub-area to be supervised, the sub-area to be supervised comprises an abnormal sub-area which accords with the characteristics of the abnormal area in the target area, the characteristics of the abnormal area are used for representing that abnormal working parameters and/or abnormal behavior characteristics exist in at least one sub-area, and when the supervision behavior and the sub-area to be supervised are not matched, central alarm information is generated, and the supervision behavior and the sub-area to be supervised are not matched and comprise: the method comprises the steps that operation confirmation is not obtained in a sub-area to be supervised in a first preset time period, or after the sub-area to be supervised is subjected to operation confirmation, improvement feedback information is not received in a second preset time period, the improvement feedback information comprises third party recovery intervention information which is identified in an abnormal sub-area and aims at abnormal working parameters and/or abnormal behavior characteristics, and the third party recovery intervention information is generated according to a third party intervention operation instruction; the working parameters and the behavior characteristics closely related to the safety production information are monitored in real time, so that the abnormal subareas to be monitored are ensured to be confirmed in time, and the intervention operation instruction of a third party is prompted to be issued in time; furthermore, by tracking, prompting and identifying the improvement operation, timely implementation of the intervention recovery of the third party after the instruction of the intervention operation of the third party is released is promoted, and guarantee is provided for standard operation and safe production.
Drawings
Fig. 1 is a main flow chart of an information processing method based on big data.
Fig. 2 is a flowchart of preprocessing for generating a result of pre-supervision matching in a big data based information processing method.
Fig. 3 is a flowchart of generating a pre-supervision matching result in a big data based information processing method.
Fig. 4 is a flowchart of reporting third party recovery intervention information in a big data based information processing method.
Fig. 5 is a schematic diagram of a big data based information processing system.
Fig. 6 is a schematic diagram of a big data based information processing system.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Specific implementations of the invention are described in detail below in connection with specific embodiments.
The information processing method and system based on big data provided by the invention solve the technical problems in the background technology.
As shown in fig. 1, a main flow chart of a big data based information processing method according to an embodiment of the present invention includes:
Step S10: acquiring target supervision information, wherein the target supervision information comprises information to be supervised of a target area, the information to be supervised comprises a sub-area to be supervised and supervision behaviors based on the sub-area to be supervised, the sub-area to be supervised comprises an abnormal sub-area which accords with the characteristics of the abnormal area in the target area, and the characteristics of the abnormal area are used for representing the existence of abnormal working parameters and/or abnormal behavior characteristics in at least one sub-area; the detection of abnormal working parameters and/or abnormal behavior characteristics can be performed by combining massive recorded data in a target area, so that the effect of big data is fully exerted; the target area is generally an area corresponding to a safety work and production requirement, such as a dust-free workshop, an electric power area and the like; the target area can be divided into a plurality of subareas according to actual personnel distribution, actual working requirements and the like, the subarea to be supervised is at least one of the subareas, and only the subarea with abnormality is the subarea to be supervised, so that the abnormal condition in the subarea is not solved, for example, the vibration noise of main production equipment indicates abnormal sound; for another example, the action of removing the safety helmet and smoking exist on the station; for another example, a workshop dust concentration alarm alarms; the supervision behavior based on the supervision sub-area generally indicates (the supervision personnel) whether to confirm the abnormal situations (such as confirming by feeding back to the early warning of the abnormal situations of the large screen of the target area) timely or whether to eliminate the related abnormal situations within a specified time (which can be reflected in no alarm or early warning, etc.), which is also the reflection of the abnormal behavior characteristics, the abnormal behavior characteristics generally meet the behavior attributes, and the behavior attributes include: attribute of production operation violation and attribute of untimely (or unqualified) supervision confirmation; an attribute of untimely or unqualified intervention;
Step S11: detecting whether the supervision behavior is matched with the sub-region to be supervised;
step S12: when the supervision behavior is detected to be unmatched with the sub-area to be supervised, generating central alarm information, wherein the unmatched supervision behavior and the unmatched sub-area to be supervised comprise: and the sub-area to be supervised is not confirmed by operation within a first preset time period, or after the sub-area to be supervised is confirmed by operation, no improved feedback information is received within a second preset time period, wherein the improved feedback information comprises third party recovery intervention information which is identified to be specific to abnormal working parameters and/or abnormal behavior characteristics in the abnormal sub-area, and the third party recovery intervention information is generated according to a third party intervention operation instruction.
The mismatching of the supervision behavior and the subareas to be supervised may be that the abnormal situation is not improved at all, and the abnormal situation is generally caused by untimely early warning confirmation and early warning release of supervision personnel; it is also possible that the operation and maintenance personnel on site do not implement in time according to the operation indication information after receiving the operation indication information; or, the operation behaviors of other operation and maintenance personnel under abnormal conditions are not supervised, so that the improvement progress is slow; specifically, when applied in practice, the specific supervision flow includes: first: after the subarea to be supervised is found and the information to be confirmed is sent out, the information to be confirmed is not confirmed within a first preset time period, and in this case, the improvement action of the subarea to be supervised generally does not occur; second,: if the information to be confirmed is sent out and the information is confirmed, a third party intervention operation instruction is issued to inform a supervisory person or an operation and maintenance person, which is equivalent to the requirement of personally performing intervention operation after giving an operation prompt or transmitting the operation prompt to other professionals on site, and the third party intervention recovery information is identified, the third party intervention recovery information is obtained not by performing operation, but rather has a certain degree of agreement with the third party intervention operation instruction, and the operation is basically performed according to the third party intervention operation instruction. For example, for vibration noise of the main production equipment, it may be that resonance inspection is first performed on equipment at a contact portion with the main production equipment, and before abnormal noise cancellation is identified, if operation at the contact portion is present, it may be determined that third party recovery intervention information is present; for example, the action of taking off the safety helmet exists on the station, the action of smoking can be that the safety helmet is correctly worn after the close contact between the supervisory personnel and the corresponding personnel is detected, the existence of the smoking is not existed, and the existence of the third party recovery intervention information can be determined, for example, the workshop dust concentration alarm can be used for alarming before the alarm is released, and the existence of the third party recovery intervention information can be determined after the human intervention check of the ventilation system is identified.
When the method is applied, the target supervision information is obtained, the information to be supervised of the target area is extracted, the information to be supervised comprises a sub-area to be supervised and supervision behaviors based on the sub-area to be supervised, the sub-area to be supervised comprises an abnormal sub-area which accords with the characteristics of the abnormal area in the target area, the characteristics of the abnormal area are used for representing that abnormal working parameters and/or abnormal behavior characteristics exist in at least one sub-area, and when the supervision behaviors are not matched with the sub-area to be supervised, central alarm information is generated, and the mismatch between the supervision behaviors and the sub-area to be supervised comprises: the method comprises the steps that operation confirmation is not obtained in a sub-area to be supervised in a first preset time period, or after the sub-area to be supervised is subjected to operation confirmation, improvement feedback information is not received in a second preset time period, the improvement feedback information comprises third party recovery intervention information which is identified in an abnormal sub-area and aims at abnormal working parameters and/or abnormal behavior characteristics, and the third party recovery intervention information is generated according to a third party intervention operation instruction; the working parameters and the behavior characteristics closely related to the safety production information are monitored in real time, so that the abnormal subareas to be monitored are ensured to be confirmed in time, and the intervention operation instruction of a third party is prompted to be issued in time; further, by tracking, prompting and identifying the improvement operation, timely implementation of the intervention recovery of a third party after the instruction of the intervention operation of the third party is issued is promoted, and the requirement of timeliness is met; after the monitoring center and/or the target area alarms, constraint can be formed by issuing and timely implementing the third party intervention operation instruction through subsequent decisions (such as punishment measures and initiating high-level remote work instructions) of the monitoring center, and meanwhile, relevant management staff in the target area are supervised, so that guarantee can be provided for standard operation and safe production.
As shown in fig. 2, as a preferred embodiment of the present invention, the method further includes:
step S20: the method comprises the steps of obtaining pre-positioning information of a supervisor, wherein the supervisor comprises a subregion and a supervisor center for setting the supervisor;
step S21: detecting whether a first supervision requirement exists by a supervision person based on the pre-positioning information;
step S22: when a first supervision requirement of a supervision person is detected, locating a first subarea covered by the first supervision requirement in the subarea, wherein the first supervision requirement is used for representing that the supervision person has a delay supervision requirement or exchanges the supervision requirement;
step S23: detecting the matching degree between the characteristic of the working parameter of the first subarea and the supervision characteristic in a set period before the current moment, and generating a pre-supervision matching result;
step S24: and generating a demand treatment indication according to the first supervision demand and the pre-supervision matching result, wherein the demand treatment indication is used for representing whether the first supervision demand is qualified or not.
It will be appreciated that so-called pre-positioning information is typically sent by the next supervisor, i.e. is actively sent, and it is necessary to locate, by means of the pre-positioning information, a first sub-area covered by the first regulatory requirement in the sub-area, the first sub-area being one of the sub-areas; only if the result of the pre-supervision matching indicates that the previous supervision personnel basically operates correctly and basically has no error, the delayed supervision or the change supervision is possible, otherwise, the former supervision personnel may cause the concentration degree of the work to be reduced because of the overlong supervision time, and in this case, the supervision or the change supervision is forced to be delayed and dangerous.
As shown in fig. 3, as a further development of the previous embodiment, the detecting the matching degree between the feature of the working parameter of the first sub-area and the supervision feature in the set period before the current time, and generating the pre-supervision matching result specifically includes:
step S231: identifying an abnormal change time node of the working parameters of the first subarea in a set period before the current moment;
step S232: identifying response time periods and comparison operation handling information corresponding to the abnormal change time nodes, wherein the comparison operation handling information corresponds to abnormal types of the abnormal change time nodes;
step S233: acquiring supervision operation information of a first subarea in a set period before the current moment;
step S234: judging whether the supervision operation information accords with the response time period and the contrast operation treatment information respectively; the comparison operation processing information is the more accurate supervision operation information; for example, if the current indicating number of the branch circuit where the fuse is located is found to be 0, and if the high-low voltage side fuse of the transformer is possibly blown, the low-voltage side switch should be pulled first, whether the low-voltage side bus has a fault or not is checked, and then the load is poured to a standby station for changing (the switching information of the low-voltage side switch and the transition information of the load can be recorded); for another example, if the dust concentration in the workshop is found to be increased, the working condition of the exhaust system should be checked (the fault recovery time node of the exhaust system or the opening information of the main exhaust control cabinet can be recorded);
Step S235: if yes, generating a first pre-supervision matching result, wherein the first pre-supervision matching result is used for representing pre-supervision matching;
step S236: otherwise, generating a second pre-supervision matching result, wherein the second pre-supervision matching result is used for representing that the pre-supervision is not matched.
According to the embodiment, starting from the working parameters of the first subarea in the set period before the current moment, searching a corresponding burst time point, and setting a response period according to the general response speed to the emergency, so that in the response period, whether the supervision information in the first subarea accords with the control operation treatment information is determined, namely, whether the corresponding operation of the supervision operation information is made according to the characteristics of the working parameters of the first subarea or not is determined from three dimensions of time, place and parameter types, and under the condition that the conditions accord with each other, the front supervision matching is indicated, in other words, the former supervision personnel has the condition that the delay supervision requirement or the change supervision requirement exists, and the theoretical possibility that the latter supervision personnel continue supervision for the latter supervision personnel exists, namely, the latter supervision personnel can replace the former supervision personnel or directly change the work later.
As a preferred embodiment of the present invention, the method further comprises:
step S30: when the front supervision matching result is detected to be a first front supervision matching result, identity authentication is carried out on supervision personnel of at least two parties corresponding to the first supervision requirement;
step S31: when the identity authentication result meets the identity setting condition, sending prompt information about the first supervision requirement, and acquiring the consent information of supervision personnel of at least two corresponding parties; the identity authentication herein may be authentication based on at least one kind of biometric information, such as face recognition authentication, fingerprint verification, iris recognition, etc.; the identity authentication result meets the set identity setting condition, and indicates that the corresponding personnel with successful identity authentication accords with the setting of the supervision shift;
step S32: and generating a first demand treatment indication according to the first pre-supervision matching result and the agreement information, wherein the first demand treatment indication is used for representing that the first supervision demand is qualified.
It should be understood that the first pre-supervision matching result indicates that the basic condition of supervision delay or supervision exchange is basically provided at present, so that the first pre-supervision matching result is implemented only according to the actual intention of the relevant personnel, and the first supervision requirement is qualified to indicate that the basic condition and the intention of the personnel can be met, so that the rationality of supervision delay or supervision exchange is fully ensured.
The embodiment is fully implemented in combination with historical big data, and the method further comprises:
step S40: traversing historical behavior record information of a target area; the historical behavior record information may be record information of abnormal behavior in a period of time before, for example, in hot summer, the behavior that personnel easily stay and gather at the position of the ventilation opening for a long time; in some blind areas which are difficult to find, the behavior of smoking or the behavior of removing a safety helmet is easy to exist;
step S41: counting suspicious occurrence bits of abnormal behaviors in the target area according to the traversing result;
step S42: acquiring a supplementary mark bit of a target area; the supplementary marking position is generally supplemented by personnel of a supervision center and is used for effectively supplementing the suspicious occurrence position so as to avoid bad habit and the like of some illegal personnel known by the supervision personnel;
step S43: the method comprises the steps of obtaining a sub-area to be identified of abnormal behavior characteristics, detecting the sub-area to be identified to generate an abnormal sub-area conforming to the abnormal area characteristics, wherein the identification priority of suspicious occurrence bits in the sub-area to be identified is the highest priority, and the sub-area to be identified comprises suspicious occurrence bits and supplementary marking bits. When at least one abnormal behavior is identified in the subarea to be identified through abnormal distribution (gathering distribution, the individuals are in a non-working area) of the personnel or the markers of the abnormal behavior (such as a handheld safety helmet, cigarettes appear on a certain appearance part of the human body), the subarea where the abnormal behavior is located is indicated to be the abnormal subarea.
It can be understood that the implementation provides a method for effectively identifying a general subarea, which can improve the effectiveness and practicability of identification, directly hit suspicious occurrence positions, fully exert the effect of big data and play a role of identifying and solving firstly.
As shown in fig. 4, considering that in a general case, the improvement on the sub-area to be supervised should be earlier and better, the solution optimization is performed according to the present embodiment on the basis of the foregoing embodiment, and specifically, the method further includes:
step S50: when detecting that the subregion to be supervised is confirmed by operation, generating a third party intervention operation instruction matched with the abnormal subregion; that is, the third party intervention operation instruction may include a solution to the abnormal situation in the abnormal area, such as going to area a for job diffusion supervision; resonance examination is carried out aiming at abnormal sound of the equipment in the area B; dissuading the behavior that the safety helmet in the area C is not worn normally;
step S51: issuing a third-party intervention operation instruction to a first terminal shared by a plurality of abnormal subareas so as to instruct the first terminal to forward the third-party intervention operation instruction to all second terminals in the abnormal subareas, wherein the plurality of second terminals (can be) are in real-time communication connection with a certain first terminal, and the second terminals are terminals where movable targets in the abnormal subareas are located; in general, a first terminal in common may be arranged for all abnormal sub-areas, for example, four abcd block areas are divided according to geographical distribution and job types of a target area, and each block area includes a plurality of sub-areas, so that a plurality of abnormal sub-areas in the plurality of sub-areas may be formed; the abnormal subareas in each block area can share at least one first terminal, and at least one terminal carried by the moving target is arranged in a single abnormal subarea; a movable target can be shared between the two abnormal subareas, and can monitor at least two abnormal subareas when necessary, wherein the movable target can be a monitor, a professional operation and maintenance person or a working robot in the embodiment;
Step S52: when the second terminal meets the intervention setting condition, the second terminal is instructed to send intervention operation prompt information and feed the intervention operation prompt information back to the corresponding first terminal, the corresponding first terminal is instructed to take the second terminal as a recognition positioning point, the intervention operation information of a movable target corresponding to the second terminal is started to be recognized, when the intervention operation information is recognized to be in accordance with the operation information in the intervention operation instruction of a third party, the corresponding intervention operation is recorded, the intervention information is generated, the intervention setting condition comprises that operation starting information is received; the setting of the setting condition mainly meets the start of the intervention operation, is also the start of the intervention operation identification, and can meet the effective identification of the intervention operation of the movable target; it should be understood that the intervention operation information conforms to the operation information in the third party intervention operation instruction, and indicates that the abnormal operation parameter is recovered or an operation is being performed (for example, the same operation or a similar operation as the operation in the third party intervention operation instruction is detected, the set similarity should be satisfied for the same operation or the similar operation), and for the former case, the degree of abnormal vibration is reduced, for example; the operation of the area A is respectively reset; the wearing of the safety helmet in the area C tends to be standard; in the latter case, for example, resonance detection apparatus operation is detected; the operation facility is moved to a standard position; the safety helmet in the area C is inserted for righting and the like;
Step S53: and indicating the corresponding first terminal to report the third party recovery intervention information. And finally, the third party recovery intervention information can be reported to the supervision center, and of course, operation prompts caused by inaccurate identification exist for some activity targets, and the operation prompt information can be directly reported through the second terminal. The one-to-many and many-to-one communication mode can ensure the rapid issuing and timely reporting of information, so that a supervision center is not required to directly establish communication with each terminal (second terminal) under normal conditions.
It can be understood that the notification of correct improvement of the sub-area to be supervised can be issued by the first terminal and the second terminal at the same time to form the prompt and supervision of the movable target, so that not only can the effective operation prompt be quickly and conveniently made, but also the intervention recovery intervention information of the third party can be quickly reported to form the closed-loop supervision of issuing-prompt-reporting, and the improvement of the abnormal working parameters and/or the abnormal behavior characteristics can be fully ensured.
In view of the responsiveness of the decision made by the monitoring center, multiple indiscriminate alert messages may cause insufficient response, and therefore, a preferred embodiment is presented, the method further comprising:
Step S60: the central alarm information is distinguished into alarm levels according to different detection conditions, wherein the different detection conditions comprise a first detection condition and a second detection condition, the first detection condition comprises that the sub-area to be supervised is not confirmed by operation within a first preset duration, the second detection condition comprises that no improvement feedback information is received within a second preset duration, and the alarm level corresponding to the first detection condition is lower than the alarm level corresponding to the second detection condition.
In fact, whether the sub-area to be supervised is confirmed by operation or not, the objective is to eliminate the abnormal information, that is, to finally detect the improvement feedback information, which indicates that the abnormal situation is being improved, so that, for the first detection condition and the second detection condition, the alarm level of the second detection condition should be higher than that of the first detection condition, and if the central alarm information for the first detection condition and the second detection condition is received almost simultaneously in a short time, the alarm level of the second detection condition should be increased to give more importance, and, for example, it may be represented by an increase in the sound of the alarm, an increase in the alarm time, a change in the color of the alarm (for example, from yellow to red), or the like, and a specific manner may be selected one or several, which is not limited herein.
As another preferred embodiment of the present invention, as shown in fig. 5, in another aspect, an information processing system based on big data, the system comprising:
a supervision information acquisition and differentiation unit 101 for: acquiring target supervision information, wherein the target supervision information comprises information to be supervised of a target area, the information to be supervised comprises a sub-area to be supervised and supervision behaviors based on the sub-area to be supervised, the sub-area to be supervised comprises an abnormal sub-area which accords with the characteristics of the abnormal area in the target area, and the characteristics of the abnormal area are used for representing the existence of abnormal working parameters and/or abnormal behavior characteristics in at least one sub-area;
a match detection unit 102 for: detecting whether the supervision behavior is matched with the sub-region to be supervised;
a condition discriminating and warning unit 103 for: when the supervision behavior is detected to be unmatched with the sub-area to be supervised, generating central alarm information, wherein the unmatched supervision behavior and the unmatched sub-area to be supervised comprise: and the sub-area to be supervised is not confirmed by operation within a first preset time period, or after the sub-area to be supervised is confirmed by operation, no improved feedback information is received within a second preset time period, wherein the improved feedback information comprises third party recovery intervention information which is identified to be specific to abnormal working parameters and/or abnormal behavior characteristics in the abnormal sub-area, and the third party recovery intervention information is generated according to a third party intervention operation instruction.
As a further development, as shown in fig. 6, the system further comprises:
a traversing unit 201, configured to traverse the historical behavior record information of the target area;
a statistics unit 202, configured to: counting suspicious occurrence bits of abnormal behaviors of the target area according to the traversing result;
a supplementary acquisition unit 203 for: acquiring a supplementary mark bit of a target area;
a detection and generation unit 204 for: the method comprises the steps of obtaining a sub-area to be identified of abnormal behavior characteristics, detecting the sub-area to be identified to generate an abnormal sub-area conforming to the abnormal area characteristics, wherein the identification priority of suspicious occurrence bits in the sub-area to be identified is the highest priority, and the sub-area to be identified comprises suspicious occurrence bits and supplementary marking bits.
The embodiment of the invention provides an information processing method based on big data, and provides an information processing system based on big data, by acquiring target supervision information, extracting information to be supervised of a target area, wherein the information to be supervised comprises a subregion to be supervised and supervision behaviors based on the subregion to be supervised, the subregion to be supervised comprises an abnormal subregion conforming to abnormal region characteristics in the target area, the abnormal region characteristics are used for representing abnormal working parameters and/or abnormal behavior characteristics in at least one subregion, and when the supervision behaviors and the subregion to be supervised are not matched, central alarm information is generated, and the supervision behaviors and the subregion to be supervised are not matched, wherein the abnormal region characteristics include: the method comprises the steps that operation confirmation is not obtained in a sub-area to be supervised in a first preset time period, or after the sub-area to be supervised is subjected to operation confirmation, improvement feedback information is not received in a second preset time period, the improvement feedback information comprises third party recovery intervention information which is identified in an abnormal sub-area and aims at abnormal working parameters and/or abnormal behavior characteristics, and the third party recovery intervention information is generated according to a third party intervention operation instruction; the working parameters and the behavior characteristics closely related to the safety production information are monitored in real time, so that the abnormal subareas to be monitored are ensured to be confirmed in time, and the intervention operation instruction of a third party is prompted to be issued in time; further, by tracking prompt and identification of improvement operation, timely implementation of the third party intervention operation instruction after release of the third party intervention recovery is promoted.
In order to be able to load the method and system described above to function properly, the system may include more or less components than those described above, or may combine some components, or different components, in addition to the various modules described above, for example, may include input and output devices, network access devices, buses, processors, memories, and the like.
The processor may be a central processing unit (CentralProcessingUnit, CPU), other general purpose processors, digital signal processors (DigitalSignalProcessor, DSP), application specific integrated circuits (ApplicationSpecificIntegratedCircuit, ASIC), off-the-shelf programmable gate arrays (Field-ProgrammableGateArray, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is a control center of the above system, and various interfaces and lines are used to connect the various parts.
The memory may be used to store a computer and a system program and/or module, and the processor may perform the various functions described above by running or executing the computer program and/or module stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function (such as an information acquisition template presentation function, a product information distribution function, etc.), and the like. The storage data area may store data created according to the use of the berth status display system (e.g., product information acquisition templates corresponding to different product types, product information required to be released by different product providers, etc.), and so on. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart memory card (SmartMediaCard, SMC), secure digital (SecureDigital, SD) card, flash card (FlashCard), at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in various embodiments may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (6)
1. An information processing method based on big data, the method comprising:
acquiring target supervision information, wherein the target supervision information comprises information to be supervised of a target area, the information to be supervised comprises a sub-area to be supervised and supervision behaviors based on the sub-area to be supervised, the sub-area to be supervised comprises an abnormal sub-area which accords with the characteristics of the abnormal area in the target area, and the characteristics of the abnormal area are used for representing the existence of abnormal working parameters and/or abnormal behavior characteristics in at least one sub-area;
detecting whether the supervision behavior is matched with the sub-region to be supervised;
when the supervision behavior is detected to be unmatched with the sub-area to be supervised, generating central alarm information, wherein the unmatched supervision behavior and the unmatched sub-area to be supervised comprise: the sub-area to be supervised is not confirmed by operation within a first preset time period;
or after the sub-area to be supervised is confirmed by operation, no improvement feedback information is received within a second preset time period; the improved feedback information comprises identifying third party recovery intervention information aiming at abnormal working parameters and/or abnormal behavior characteristics in an abnormal subarea, wherein the third party recovery intervention information is generated according to a third party intervention operation instruction; the method further comprises the step of indicating the corresponding first terminal to report the third party recovery intervention information, wherein the step of indicating the corresponding first terminal to report the third party recovery intervention information specifically comprises the following steps: when detecting that the subregion to be supervised is confirmed by operation, generating a third party intervention operation instruction matched with the abnormal subregion; issuing a third-party intervention operation instruction to a first terminal shared by a plurality of abnormal subareas so as to instruct the first terminal to forward the third-party intervention operation instruction to all second terminals in the abnormal subareas, wherein the second terminals are terminals where movable targets in the abnormal subareas are located; when the second terminal meets the intervention setting condition, the second terminal is instructed to send intervention operation prompt information and feed the intervention operation prompt information back to the corresponding first terminal, the corresponding first terminal is instructed to take the second terminal as a recognition positioning point, the intervention operation information of a movable target corresponding to the second terminal is started to be recognized, when the intervention operation information is recognized to be in accordance with the operation information in the intervention operation instruction of a third party, the corresponding intervention operation is recorded, the intervention information is generated, the intervention setting condition comprises that operation starting information is received; wherein identifying that the interventional operation information corresponds to the operational information in the third party interventional operation indication comprises: detecting an operation meeting the set similarity with an operation in the third-party intervention operation instruction; indicating the corresponding first terminal to report the intervention information of the third party recovery;
The method further comprises the steps of: the method comprises the steps of obtaining pre-positioning information of a supervisor, wherein the supervisor comprises a subregion and a supervisor center for setting the supervisor; detecting whether a first supervision requirement exists by a supervision person based on the pre-positioning information; when a first supervision requirement of a supervision person is detected, locating a first subarea covered by the first supervision requirement in the subarea, wherein the first supervision requirement is used for representing that the supervision person has a delay supervision requirement or exchanges the supervision requirement; detecting the matching degree between the characteristic of the working parameter of the first subarea and the supervision characteristic in a set period before the current moment, and generating a pre-supervision matching result; generating a demand treatment indication according to the first supervision demand and the pre-supervision matching result, wherein the demand treatment indication is used for representing whether the first supervision demand is qualified or not; the method for generating the front supervision matching result specifically comprises the following steps of: identifying an abnormal change time node of the working parameters of the first subarea in a set period before the current moment; identifying response time periods and comparison operation handling information corresponding to the abnormal change time nodes, wherein the comparison operation handling information corresponds to abnormal types of the abnormal change time nodes; acquiring supervision operation information of a first subarea in a set period before the current moment; judging whether the supervision operation information accords with the response time period and the contrast operation treatment information respectively; if yes, generating a first pre-supervision matching result, wherein the first pre-supervision matching result is used for representing pre-supervision matching; otherwise, generating a second pre-supervision matching result, wherein the second pre-supervision matching result is used for representing that the pre-supervision is not matched.
2. The big data based information processing method according to claim 1, characterized in that the method further comprises:
when the front supervision matching result is detected to be a first front supervision matching result, identity authentication is carried out on supervision personnel of at least two parties corresponding to the first supervision requirement;
when the identity authentication result meets the identity setting condition, sending prompt information about the first supervision requirement, and acquiring the consent information of supervision personnel of at least two corresponding parties;
and generating a first demand treatment indication according to the first pre-supervision matching result and the agreement information, wherein the first demand treatment indication is used for representing that the first supervision demand is qualified.
3. The big data based information processing method according to claim 1, characterized in that the method further comprises:
traversing historical behavior record information of a target area;
counting suspicious occurrence bits of abnormal behaviors in the target area according to the traversing result;
acquiring a supplementary mark bit of a target area;
the method comprises the steps of obtaining a sub-area to be identified of abnormal behavior characteristics, detecting the sub-area to be identified to generate an abnormal sub-area conforming to the abnormal area characteristics, wherein the identification priority of suspicious occurrence bits in the sub-area to be identified is the highest priority, and the sub-area to be identified comprises suspicious occurrence bits and supplementary marking bits.
4. A big data based information processing method according to any of claims 1-3, wherein the method further comprises:
the central alarm information is distinguished into alarm levels according to different detection conditions, wherein the different detection conditions comprise a first detection condition and a second detection condition, the first detection condition comprises that the sub-area to be supervised is not confirmed by operation within a first preset duration, the second detection condition comprises that no improvement feedback information is received within a second preset duration, and the alarm level corresponding to the first detection condition is lower than the alarm level corresponding to the second detection condition.
5. An information processing system based on big data, the system comprising:
the supervision information acquisition and distinguishing unit is used for: acquiring target supervision information, wherein the target supervision information comprises information to be supervised of a target area, the information to be supervised comprises a sub-area to be supervised and supervision behaviors based on the sub-area to be supervised, the sub-area to be supervised comprises an abnormal sub-area which accords with the characteristics of the abnormal area in the target area, and the characteristics of the abnormal area are used for representing the existence of abnormal working parameters and/or abnormal behavior characteristics in at least one sub-area;
A match detection unit configured to: detecting whether the supervision behavior is matched with the sub-region to be supervised;
a condition distinguishing and alarming unit for: when the supervision behavior is detected to be unmatched with the sub-area to be supervised, generating central alarm information, wherein the unmatched supervision behavior and the unmatched sub-area to be supervised comprise: the sub-area to be supervised is not confirmed by operation within a first preset time period, or after the sub-area to be supervised is confirmed by operation, the improvement feedback information is not received within a second preset time period, the improvement feedback information comprises the third party recovery intervention information which is identified in the abnormal sub-area and aims at abnormal working parameters and/or abnormal behavior characteristics, the third party recovery intervention information is generated according to the third party intervention operation instruction,
wherein, the condition distinguishes and the alarm unit, still is used for: the method comprises the steps of indicating the corresponding first terminal to report the third party recovery intervention information, wherein the step of indicating the corresponding first terminal to report the third party recovery intervention information specifically comprises the following steps: when detecting that the subregion to be supervised is confirmed by operation, generating a third party intervention operation instruction matched with the abnormal subregion; issuing a third-party intervention operation instruction to a first terminal shared by a plurality of abnormal subareas so as to instruct the first terminal to forward the third-party intervention operation instruction to all second terminals in the abnormal subareas, wherein the second terminals are terminals where movable targets in the abnormal subareas are located; when the second terminal meets the intervention setting condition, the second terminal is instructed to send intervention operation prompt information and feed the intervention operation prompt information back to the corresponding first terminal, the corresponding first terminal is instructed to take the second terminal as a recognition positioning point, the intervention operation information of a movable target corresponding to the second terminal is started to be recognized, when the intervention operation information is recognized to be in accordance with the operation information in the intervention operation instruction of a third party, the corresponding intervention operation is recorded, the intervention information is generated, the intervention setting condition comprises that operation starting information is received; wherein identifying that the interventional operation information corresponds to the operational information in the third party interventional operation indication comprises: detecting an operation meeting the set similarity with an operation in the third-party intervention operation instruction; indicating the corresponding first terminal to report the intervention information of the third party recovery;
Wherein the system is further for: the method comprises the steps of obtaining pre-positioning information of a supervisor, wherein the supervisor comprises a subregion and a supervisor center for setting the supervisor; detecting whether a first supervision requirement exists by a supervision person based on the pre-positioning information; when a first supervision requirement of a supervision person is detected, locating a first subarea covered by the first supervision requirement in the subarea, wherein the first supervision requirement is used for representing that the supervision person has a delay supervision requirement or exchanges the supervision requirement; detecting the matching degree between the characteristic of the working parameter of the first subarea and the supervision characteristic in a set period before the current moment, and generating a pre-supervision matching result; generating a demand treatment indication according to the first supervision demand and the pre-supervision matching result, wherein the demand treatment indication is used for representing whether the first supervision demand is qualified or not; the method for generating the front supervision matching result specifically comprises the following steps of: identifying an abnormal change time node of the working parameters of the first subarea in a set period before the current moment; identifying response time periods and comparison operation handling information corresponding to the abnormal change time nodes, wherein the comparison operation handling information corresponds to abnormal types of the abnormal change time nodes; acquiring supervision operation information of a first subarea in a set period before the current moment; judging whether the supervision operation information accords with the response time period and the contrast operation treatment information respectively; if yes, generating a first pre-supervision matching result, wherein the first pre-supervision matching result is used for representing pre-supervision matching; otherwise, generating a second pre-supervision matching result, wherein the second pre-supervision matching result is used for representing that the pre-supervision is not matched.
6. The big data based information handling system of claim 5, wherein the system further comprises:
the traversing unit is used for traversing the historical behavior record information of the target area;
a statistics unit for: counting suspicious occurrence bits of abnormal behaviors of the target area according to the traversing result;
a supplementary acquisition unit for: acquiring a supplementary mark bit of a target area;
a detection and generation unit for: the method comprises the steps of obtaining a sub-area to be identified of abnormal behavior characteristics, detecting the sub-area to be identified to generate an abnormal sub-area conforming to the abnormal area characteristics, wherein the identification priority of suspicious occurrence bits in the sub-area to be identified is the highest priority, and the sub-area to be identified comprises suspicious occurrence bits and supplementary marking bits.
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