CN113321084B - Method and device for determining scheduling program - Google Patents
Method and device for determining scheduling program Download PDFInfo
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- CN113321084B CN113321084B CN202110587101.3A CN202110587101A CN113321084B CN 113321084 B CN113321084 B CN 113321084B CN 202110587101 A CN202110587101 A CN 202110587101A CN 113321084 B CN113321084 B CN 113321084B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/3407—Setting or modification of parameters of the control system
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/24—Control systems with regulation, i.e. with retroactive action, for influencing travelling speed, acceleration, or deceleration
- B66B1/2408—Control systems with regulation, i.e. with retroactive action, for influencing travelling speed, acceleration, or deceleration where the allocation of a call to an elevator car is of importance, i.e. by means of a supervisory or group controller
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/3415—Control system configuration and the data transmission or communication within the control system
- B66B1/3446—Data transmission or communication within the control system
- B66B1/3461—Data transmission or communication within the control system between the elevator control system and remote or mobile stations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/60—Software deployment
- G06F8/65—Updates
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/40—Details of the change of control mode
- B66B2201/402—Details of the change of control mode by historical, statistical or predicted traffic data, e.g. by learning
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B50/00—Energy efficient technologies in elevators, escalators and moving walkways, e.g. energy saving or recuperation technologies
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Abstract
The invention discloses a method and a device for determining a scheduling program, which are applied to a cloud server, wherein the method comprises the following steps: judging whether an elevator is accessed; judging whether a specific scheduling program corresponding to the elevator is stored in the elevator or not under the condition of accessing the elevator, wherein the specific scheduling program is associated with the operation rule of the elevator; and under the condition that the specific scheduling program is not stored in the elevator, acquiring a preset scheduling program stored in the cloud server, and sending the preset scheduling program to the elevator as the specific scheduling program. The elevator is connected to the cloud server, the accurate scheduling program of the elevator is rapidly acquired based on big data or similar principles through the cloud server, and the scheduling program is timely and remotely updated according to the operation data of the elevator, so that the accuracy of the scheduling program is effectively improved, and personalized experience of users is met.
Description
Technical Field
The invention relates to the technical field of elevator control, in particular to a method and a device for determining a scheduling program.
Background
With the continuous improvement of the living standard of people, elevators become common equipment in the lives of people.
The elevator travels up and down in the hoistway under control of the elevator control system in response to a user's elevator taking demand. Along with the continuous growth of users, one elevator is configured in a building, so that the elevator can not meet the elevator taking requirement of people, and the elevator is jammed, so that in order to solve the technical problems, technicians configure a plurality of elevators in the building, and group control is performed on the plurality of elevators through a group control algorithm.
In order to better respond to the elevator taking demand of a user and improve the dispatching control efficiency of the elevator, instead of simply directly calling the elevator to the corresponding floor according to the calling instruction of the user, technicians put forward a group control algorithm of the elevator. Along with the continuous development of the technology, the group control algorithm is also continuously developed and continuously optimized, so that various group control algorithms are promoted.
However, in the practical application process, the group control algorithm of the elevator is determined by an elevator manufacturer and stored in the elevator when the elevator leaves the factory, i.e. the selection right of the group control algorithm of the elevator is determined by the elevator manufacturer and is determined before the elevator is used. Obviously, the usage rules and the usage demands of the elevators under different usage scenes are different, for example, the usage rules of the elevators in houses, office buildings and markets often have large differences, and the conventional elevator group control algorithm determining method cannot meet the actual demands of users.
Disclosure of Invention
In order to overcome the technical problems in the prior art, the embodiment of the invention provides a determination method and a determination device for a scheduling program, which are used for quickly acquiring an accurate scheduling program of an elevator based on big data or similar principles through a cloud server by accessing the elevator into the cloud server and timely and remotely updating the scheduling program according to the operation data of the elevator, so that the accuracy of the scheduling program is effectively improved and the personalized experience of users is met.
In order to achieve the above object, an embodiment of the present invention provides a method for determining a scheduler, applied to a cloud server, the method including: judging whether an elevator is accessed; judging whether a specific scheduling program corresponding to the elevator is stored in the elevator or not under the condition that the elevator is determined to be accessed, wherein the specific scheduling program is associated with the operation rule of the elevator; and under the condition that the specific scheduling program is not stored in the elevator, acquiring a preset scheduling program stored in the cloud server, and sending the preset scheduling program to the elevator as the specific scheduling program.
Preferably, the method further comprises: judging whether an update program of the specific scheduling program is stored in the cloud server or not under the condition that the specific scheduling program is stored in the elevator; if yes, updating operation is carried out on the specific scheduling program based on the updating program; judging whether the updating operation is completed or not; in the case where it is determined that the update operation is completed, the update program is regarded as the specific scheduler.
Preferably, the acquiring the preset scheduling program stored in the cloud server includes: acquiring the geographic position of the elevator and the building type of a building in which the elevator is positioned; acquiring similar elevators in similar buildings similar to the building type near the geographic location; judging whether a similar specific scheduling program of the similar elevator is stored or not; if yes, determining the similar specific scheduling program as the preset scheduling program; otherwise, acquiring a general scheduling program corresponding to the building type, and determining the general scheduling program as the preset scheduling program.
Preferably, the method further comprises: judging whether the operation data of the elevator is acquired or not, wherein the operation data is the operation data of the elevator in a preset time period; under the condition that the operation data is acquired, an elevator control model is established; learning the operation data based on the elevator control model to obtain a learned model; and optimizing the specific scheduling program based on the learned model to obtain an updating program of the specific scheduling program.
Preferably, the preset time period includes at least one unit period, each of the unit periods includes a plurality of reference periods, and the method further includes: before learning the operation data based on the elevator control model, carrying out aggregation processing on the operation data in each unit period according to a preset aggregation algorithm to obtain aggregated operation data; optimizing the operation data of each reference period based on the aggregated operation data to obtain optimized operation data; acquiring an operation curve of the elevator in the preset time period based on the optimized operation data; and learning the running curve based on the elevator control model.
Correspondingly, the embodiment of the invention also provides a device for determining the scheduling program, which comprises: the first judging unit is used for judging whether the elevator is accessed; a second judging unit, configured to judge whether a specific scheduler corresponding to the elevator is stored in the elevator, where the specific scheduler is associated with an operation rule of the elevator, in a case where access to the elevator is determined; and the first determining unit is used for acquiring a preset scheduling program stored in the cloud server and sending the preset scheduling program to the elevator as the specific scheduling program under the condition that the specific scheduling program is not stored in the elevator.
Preferably, the apparatus further comprises a second determining unit, the second determining unit comprising: the first judging module is used for judging whether the cloud server stores an updating program of the specific scheduling program or not under the condition that the specific scheduling program is stored in the elevator; the updating module is used for executing updating operation on the specific scheduling program based on the updating program if yes; the second judging module is used for judging whether the updating operation is completed or not; and the first determining module is used for taking the updating program as the specific scheduling program under the condition that the updating operation is determined to be completed.
Preferably, the first determining unit includes: the first acquisition module is used for acquiring the geographic position of the elevator and the building type of a building in which the elevator is positioned; a second acquisition module for acquiring similar elevators in similar buildings similar to the building type in the vicinity of the geographic location; the second determining module is used for judging whether a similar specific scheduling program of the similar elevator is stored or not; if yes, determining the similar specific scheduling program as the preset scheduling program; otherwise, acquiring a general scheduling program corresponding to the building type, and determining the general scheduling program as the preset scheduling program.
Preferably, the apparatus further comprises a program updating unit for: judging whether the operation data of the elevator is acquired or not, wherein the operation data is the operation data of the elevator in a preset time period; under the condition that the operation data is acquired, an elevator control model is established; learning the operation data based on the elevator control model to obtain a learned model; and optimizing the specific scheduling program based on the learned model to obtain an updating program of the specific scheduling program.
Preferably, the preset time period includes at least one unit period, each of the unit periods includes a plurality of reference periods, and the program updating unit is further configured to: before learning the operation data based on the elevator control model, carrying out aggregation processing on the operation data in each unit period according to a preset aggregation algorithm to obtain aggregated operation data; optimizing the operation data of each reference period based on the aggregated operation data to obtain optimized operation data; acquiring an operation curve of the elevator in the preset time period based on the optimized operation data; and learning the running curve based on the elevator control model.
Through the technical scheme provided by the invention, the invention has at least the following technical effects:
the elevator is connected with the cloud server, so that the elevator is allowed to remotely and accurately determine the accurate scheduling program of the elevator based on big data stored in the cloud server or scheduling programs similar to the elevator, and the accuracy of the scheduling program of the elevator is effectively improved; on the other hand, the operation data of the elevator in a fixed time period are learned, instead of real-time learning and real-time optimization, the long-term use rule and the short-term use habit change of the elevator can be effectively considered, and a more accurate dispatching program optimization effect is realized.
Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain, without limitation, the embodiments of the invention. In the drawings:
FIG. 1 is a flowchart of a specific implementation of a method for determining a scheduler according to an embodiment of the present invention;
FIG. 2 is a flowchart of a specific implementation of acquiring a preset scheduler in a method for determining a scheduler according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a scheduler determining apparatus according to an embodiment of the present invention.
Detailed Description
The following describes the detailed implementation of the embodiments of the present invention with reference to the drawings. It should be understood that the detailed description and specific examples, while indicating and illustrating the invention, are not intended to limit the invention.
The terms "system" and "network" in embodiments of the invention may be used interchangeably. "plurality" means two or more, and "plurality" may also be understood as "at least two" in this embodiment of the present invention. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/", unless otherwise specified, generally indicates that the associated object is an "or" relationship. In addition, it should be understood that in the description of embodiments of the present invention, the words "first," "second," and the like are used merely for distinguishing between the descriptions and not be construed as indicating or implying a relative importance or order.
Referring to fig. 1, an embodiment of the present invention provides a method for determining a scheduler, which is applied to a cloud server, and the method includes:
s10) judging whether an elevator is accessed;
s20) judging whether a specific scheduling program corresponding to the elevator is stored in the elevator or not under the condition that the elevator is determined to be accessed, wherein the specific scheduling program is associated with the operation rule of the elevator;
s30) in the case where the specific scheduler is not stored in the elevator, acquiring a preset scheduler stored in the cloud server, and transmitting the preset scheduler as the specific scheduler to the elevator.
In one possible implementation manner, the cloud server monitors whether the elevator is accessed in real time, for example, in the first embodiment, after the elevator is installed and started, that is, a connection is established with the cloud server, and the cloud server can determine that the elevator is accessed in the subsequent operation process; in a second embodiment, the elevator is operated in an off-line operation after installation and start-up, and after a period of operation the elevator establishes a connection with the cloud server via the communication network, for example by sending an access request to the cloud server to access the cloud server, after which the cloud server determines to access the elevator.
After determining that the elevator is accessed, the cloud server determines whether a specific scheduler corresponding to the elevator is stored in the elevator, and in the embodiment of the invention, the specific scheduler is a personalized scheduler associated with the operation rule of the elevator, for example, the cloud server is connected with 50 elevators at the same time, so that the specific schedulers of the 50 elevators should be different from each other, and each specific scheduler of the elevators is a scheduler optimized according to the operation rule of the elevator.
For example, in the embodiment of the present invention, the cloud server monitors that a certain elevator currently accessed is not stored with a specific scheduler, for example, the elevator is just installed and started for the first time, so that a preset scheduler stored in the cloud server is directly acquired, for example, the preset scheduler may be a preset scheduler preset in the cloud server by a technician according to the current technical development or the actual situation of the elevator and matched with the elevator, and the preset scheduler is sent to the elevator as a specific scheduler, where the preset scheduler includes an elevator real-time scheduler, and the elevator real-time scheduler includes any one of, but not limited to, an earliest deadline priority algorithm, a SCAN-EDF algorithm, a PI (Priority Inversion) algorithm, and an FD-SCAN (Feasible Deadline SCAN) algorithm.
Further, in an embodiment of the present invention, the method further includes: judging whether an update program of the specific scheduling program is stored in the cloud server or not under the condition that the specific scheduling program is stored in the elevator; if yes, updating operation is carried out on the specific scheduling program based on the updating program; judging whether the updating operation is completed or not; in the case where it is determined that the update operation is completed, the update program is regarded as the specific scheduler.
In the embodiment of the invention, the elevator is connected with the cloud server, so that a more matched dispatching program can be sent to the elevator according to the development condition of the current dispatching technology or the actual condition of the elevator, instead of adopting a fixed dispatching program, the dispatching program is not required to be updated by a technician to the site after the fixed dispatching program is arranged for the elevator, the latest and most matched dispatching programs used by the elevator are ensured, and the dispatching control accuracy is improved.
On the other hand, by connecting the elevator with the cloud server, once the updated scheduling program corresponding to the elevator exists, the scheduling program of the elevator is updated immediately, so that the real-time performance of the scheduling program in the elevator is further improved, the intelligent degree of the elevator is improved, and the user experience is improved.
Referring to fig. 2, in an embodiment of the present invention, the obtaining a preset scheduler stored in the cloud server includes:
s31) acquiring the geographic position of the elevator and the building type of a building in which the elevator is positioned;
s32) obtaining similar elevators in similar buildings similar to the building type near the geographical location;
s33) judging whether a similar specific scheduler of the similar elevator is stored;
s341), if yes, determining the similar specific scheduling program as the preset scheduling program;
s342) if not, acquiring a universal scheduler corresponding to the building type, and determining the universal scheduler as the preset scheduler.
In one possible implementation, the cloud server determines that a specific scheduler corresponding to an elevator is not stored in the accessed elevator, and thus obtains a preset scheduler from the cloud server. However, in the practical application process, although there are numerous general-purpose schedulers in the prior art, each of the numerous general-purpose schedulers has advantages and disadvantages, so although the accuracy of the elevator scheduler can be improved by setting the best-matching general-purpose scheduler for the elevator, the general-purpose scheduler is still not the best scheduler generated based on the actual operation rule of the elevator. Therefore, in the embodiment of the invention, the method for determining the scheduling program of the elevator is further optimized, and the geographic position of the elevator and the building type of the building where the elevator is located are firstly obtained in the process of determining the specific scheduling program of the elevator from the preset scheduling program stored in the cloud server by combining the territory and the similarity of the use of the elevator.
For example, the above-mentioned geographic location and building type may be input into the cloud server by a technician before the elevator is installed, at which time the cloud server queries similar elevators in similar buildings similar to the building type in the vicinity of the geographic location according to the geographic location, and further determines whether a specific scheduler, i.e., a similar specific scheduler, of the similar elevators is stored. In the embodiment of the invention, the cloud server inquires that a similar elevator exists within a distance of 0.3km of the geographic position of the elevator, and a specific scheduling program of the similar elevator is stored in the cloud server, so that the similar specific scheduling program is used as a preset scheduling program of the current elevator.
In the embodiment of the invention, by combining the characteristic that similar elevators have similar operation rules, a more accurate similar scheduling program is configured for the current elevator based on a cloud technology or a big data technology, compared with the prior art adopting a general scheduling program, the accuracy and the accuracy of the determined scheduling program are further improved, the scheduling program adopted by the newly installed elevator can conform to the use habit of passengers in a building and the operation rule of the elevator, the user experience is greatly improved, and the intelligent degree of the elevator is improved.
In an embodiment of the present invention, the method further includes: judging whether the operation data of the elevator is acquired or not, wherein the operation data is the operation data of the elevator in a preset time period; under the condition that the operation data is acquired, an elevator control model is established; learning the operation data based on the elevator control model to obtain a learned model; and optimizing the specific scheduling program based on the learned model to obtain an updating program of the specific scheduling program.
Further, in an embodiment of the present invention, the preset time period includes at least one unit period, each unit period includes a plurality of reference periods, and the method further includes: before learning the operation data based on the elevator control model, carrying out aggregation processing on the operation data in each unit period according to a preset aggregation algorithm to obtain aggregated operation data; optimizing the operation data of each reference period based on the aggregated operation data to obtain optimized operation data; acquiring an operation curve of the elevator in the preset time period based on the optimized operation data; and learning the running curve based on the elevator control model.
In one possible implementation manner, the cloud server finds that the specific scheduling program of the elevator is not stored in the elevator in the process of inquiring the specific scheduling program of the elevator, and the specific scheduling program of the elevator is not stored in the cloud server, and similar specific scheduling programs are not inquired, so that the cloud server can be firstly configured in the general scheduling program corresponding to the building type for the elevator, and in the actual running process of the elevator, the running data of the elevator is obtained according to the preset time period, and data learning is performed. The elevator is used with strong randomness, but the overall usage rule of the elevator in a certain building is stable, so that the influence on the normal operation of the elevator caused by real-time acquisition of elevator operation data and real-time optimization of a scheduling program is avoided, and meanwhile, the elevator operation data can be timely responded to the change of the elevator operation requirement, the elevator operation data can be acquired according to a preset time period, data learning is performed, after the operation data learning of the current time period is completed, the operation data of the current time period can be cleared, and the operation data of the next time period can be continuously acquired.
For example, the preset time period may be set by a technician according to actual experience, for example, may be half a month or one month, and at least one unit period is included in each preset time period, for example, the unit period is one week, and each unit period includes a plurality of reference periods, for example, the reference period is one day. For example, at a moment, the cloud server acquires operation data uploaded by the elevator, the operation data is operation data of the elevator in the previous month, at this time, the cloud server sorts the data, for example, the data is divided according to a unit period to be divided into data of 4 unit periods, then, aggregation processing is performed on the operation data in each unit period according to a preset aggregation algorithm, so as to obtain corresponding aggregated operation data, then, the operation data of each reference period is optimized according to the aggregated operation data, for example, deviation data which is obviously deviated from the aggregated operation data is removed, so as to obtain optimized operation data, then, the operation curve of the elevator in the preset time period is obtained after integrating the optimized operation data, and at this time, the cloud server can perform data learning according to the operation curve.
For example, the cloud server may first establish an elevator control model, then input the operation curve into the elevator control model for intelligent learning, for example, the elevator control model is a deep learning model, and a post-learning model is obtained after the deep learning is performed on the operation curve, where the cloud server optimizes a specific scheduler stored in an elevator according to the post-learning model. In the running process or the elevator re-accessing process of the cloud server, the cloud server can inquire whether the elevator stores the update program, if not, the update program is issued to the elevator to update the specific scheduling program of the elevator in real time.
According to the embodiment of the invention, the operation data of the elevator is acquired and learned according to the preset time period, so that the unification of the short-term use habit change and the long-term use rule of the elevator can be considered, the more accurate optimization of the elevator dispatching program is realized, the accuracy and the intellectualization of elevator dispatching are improved, and the user experience is improved.
Further, since the use of the elevator has a stable use rule in a large time period and temporary or accidental changes may exist in a small time period, the operation rule of the elevator is analyzed and a corresponding operation curve is obtained by adopting the time periods of a plurality of steps, so that the personalized use rule of the elevator in each time period can be accurately obtained, personalized optimization of the scheduling program is performed instead of adopting a fixed scheduling program or a universal scheduling program, the intelligent degree and accuracy in the process of determining the scheduling program of the elevator are improved, and the personalized demands of users are met.
The following describes a determination device for a scheduler provided in an embodiment of the present invention with reference to the accompanying drawings.
Referring to fig. 3, based on the same inventive concept, an embodiment of the present invention provides a scheduler determining apparatus, including: the first judging unit is used for judging whether the elevator is accessed; a second judging unit, configured to judge whether a specific scheduler corresponding to the elevator is stored in the elevator, where the specific scheduler is associated with an operation rule of the elevator, in a case where access to the elevator is determined; and the first determining unit is used for acquiring a preset scheduling program stored in the cloud server and sending the preset scheduling program to the elevator as the specific scheduling program under the condition that the specific scheduling program is not stored in the elevator.
In an embodiment of the present invention, the apparatus further includes a second determining unit, where the second determining unit includes: the first judging module is used for judging whether the cloud server stores an updating program of the specific scheduling program or not under the condition that the specific scheduling program is stored in the elevator; the updating module is used for executing updating operation on the specific scheduling program based on the updating program if yes; the second judging module is used for judging whether the updating operation is completed or not; and the first determining module is used for taking the updating program as the specific scheduling program under the condition that the updating operation is determined to be completed.
In an embodiment of the present invention, the first determining unit includes: the first acquisition module is used for acquiring the geographic position of the elevator and the building type of a building in which the elevator is positioned; a second acquisition module for acquiring similar elevators in similar buildings similar to the building type in the vicinity of the geographic location; the second determining module is used for judging whether a similar specific scheduling program of the similar elevator is stored or not; if yes, determining the similar specific scheduling program as the preset scheduling program; otherwise, acquiring a general scheduling program corresponding to the building type, and determining the general scheduling program as the preset scheduling program.
In an embodiment of the present invention, the apparatus further includes a program update unit, where the program update unit is configured to: judging whether the operation data of the elevator is acquired or not, wherein the operation data is the operation data of the elevator in a preset time period; under the condition that the operation data is acquired, an elevator control model is established; learning the operation data based on the elevator control model to obtain a learned model; and optimizing the specific scheduling program based on the learned model to obtain an updating program of the specific scheduling program.
In an embodiment of the present invention, the preset time period includes at least one unit period, each unit period includes a plurality of reference periods, and the program updating unit is further configured to: before learning the operation data based on the elevator control model, carrying out aggregation processing on the operation data in each unit period according to a preset aggregation algorithm to obtain aggregated operation data; optimizing the operation data of each reference period based on the aggregated operation data to obtain optimized operation data; acquiring an operation curve of the elevator in the preset time period based on the optimized operation data; and learning the running curve based on the elevator control model.
The foregoing details of the optional implementation of the embodiment of the present invention have been described in detail with reference to the accompanying drawings, but the embodiment of the present invention is not limited to the specific details of the foregoing implementation, and various simple modifications may be made to the technical solution of the embodiment of the present invention within the scope of the technical concept of the embodiment of the present invention, and these simple modifications all fall within the protection scope of the embodiment of the present invention.
In addition, the specific features described in the above embodiments may be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, various possible combinations of embodiments of the present invention are not described in detail.
Those skilled in the art will appreciate that all or part of the steps in implementing the methods of the embodiments described above may be implemented by a program stored in a storage medium, including instructions for causing a single-chip microcomputer, chip or processor (processor) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In addition, any combination of various embodiments of the present invention may be performed, so long as the concept of the embodiments of the present invention is not violated, and the disclosure of the embodiments of the present invention should also be considered.
Claims (8)
1. A method for determining a scheduler, applied to a cloud server, the method comprising:
judging whether an elevator is accessed;
judging whether a specific scheduling program corresponding to the elevator is stored in the elevator or not under the condition that the elevator is determined to be accessed, wherein the specific scheduling program is associated with the operation rule of the elevator;
under the condition that the specific scheduling program is not stored in the elevator, acquiring a preset scheduling program stored in the cloud server, and sending the preset scheduling program to the elevator as the specific scheduling program;
the obtaining the preset scheduling program stored in the cloud server includes:
acquiring the geographic position of the elevator and the building type of a building in which the elevator is positioned;
acquiring similar elevators in similar buildings similar to the building type near the geographic location;
judging whether a similar specific scheduling program of the similar elevator is stored or not;
if yes, determining the similar specific scheduling program as the preset scheduling program;
otherwise, acquiring a general scheduling program corresponding to the building type, and determining the general scheduling program as the preset scheduling program.
2. The method according to claim 1, wherein the method further comprises:
judging whether an update program of the specific scheduling program is stored in the cloud server or not under the condition that the specific scheduling program is stored in the elevator;
if yes, updating operation is carried out on the specific scheduling program based on the updating program;
judging whether the updating operation is completed or not;
in the case where it is determined that the update operation is completed, the update program is regarded as the specific scheduler.
3. The method according to claim 1, wherein the method further comprises:
judging whether the operation data of the elevator is acquired or not, wherein the operation data is the operation data of the elevator in a preset time period;
under the condition that the operation data is acquired, an elevator control model is established;
learning the operation data based on the elevator control model to obtain a learned model;
and optimizing the specific scheduling program based on the learned model to obtain an updating program of the specific scheduling program.
4. A method according to claim 3, wherein the preset time period comprises at least one unit period, each unit period comprising a plurality of reference periods, the method further comprising:
before learning the operation data based on the elevator control model, carrying out aggregation processing on the operation data in each unit period according to a preset aggregation algorithm to obtain aggregated operation data;
optimizing the operation data of each reference period based on the aggregated operation data to obtain optimized operation data;
acquiring an operation curve of the elevator in the preset time period based on the optimized operation data;
and learning the running curve based on the elevator control model.
5. A scheduler determining apparatus, the apparatus comprising:
the first judging unit is used for judging whether the elevator is accessed;
a second judging unit, configured to judge whether a specific scheduler corresponding to the elevator is stored in the elevator, where the specific scheduler is associated with an operation rule of the elevator, in a case where access to the elevator is determined;
a first determining unit, configured to obtain a preset scheduler stored in a cloud server and send the preset scheduler to the elevator as the specific scheduler, where the specific scheduler is not stored in the elevator;
the first determination unit includes:
the first acquisition module is used for acquiring the geographic position of the elevator and the building type of a building in which the elevator is positioned;
a second acquisition module for acquiring similar elevators in similar buildings similar to the building type in the vicinity of the geographic location;
the second determining module is used for judging whether a similar specific scheduling program of the similar elevator is stored or not; if yes, determining the similar specific scheduling program as the preset scheduling program; otherwise, acquiring a general scheduling program corresponding to the building type, and determining the general scheduling program as the preset scheduling program.
6. The apparatus according to claim 5, further comprising a second determination unit comprising:
the first judging module is used for judging whether the cloud server stores an updating program of the specific scheduling program or not under the condition that the specific scheduling program is stored in the elevator;
the updating module is used for executing updating operation on the specific scheduling program based on the updating program if yes;
the second judging module is used for judging whether the updating operation is completed or not;
and the first determining module is used for taking the updating program as the specific scheduling program under the condition that the updating operation is determined to be completed.
7. The apparatus according to claim 5, further comprising a program update unit configured to:
judging whether the operation data of the elevator is acquired or not, wherein the operation data is the operation data of the elevator in a preset time period;
under the condition that the operation data is acquired, an elevator control model is established;
learning the operation data based on the elevator control model to obtain a learned model;
and optimizing the specific scheduling program based on the learned model to obtain an updating program of the specific scheduling program.
8. The apparatus of claim 7, wherein the preset time period comprises at least one unit period, each unit period comprising a plurality of reference periods, the program update unit further configured to:
before learning the operation data based on the elevator control model, carrying out aggregation processing on the operation data in each unit period according to a preset aggregation algorithm to obtain aggregated operation data;
optimizing the operation data of each reference period based on the aggregated operation data to obtain optimized operation data;
acquiring an operation curve of the elevator in the preset time period based on the optimized operation data;
and learning the running curve based on the elevator control model.
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