Elevator call distribution

Abstract

According to one aspect, a method for elevator call allocation in an elevator group including a plurality of elevator cars is provided. The method includes detecting a logistics operation associated with an elevator car, the elevator car being stationary at a floor, and in response to detecting the logistics operation, restricting allocation of a new elevator call to the elevator cars in the elevator group.

Description

Background Art

[0001] Elevators in buildings can be used to transport passengers and various deliveries. Typically, a passenger can make a destination call, a floor call, or a car call, and the passenger is transported to the selected destination floor. Sometimes an elevator may be reserved for an extended period of time, and the duration may be unknown and difficult to estimate accurately, for example, when furniture or other large items are loaded into the elevator. This may mean that some users on nearby floors, for example, may have to wait a long time because their call may have been assigned to the same elevator that is temporarily unavailable to serve them. Summary of the invention

[0002] According to a first aspect, a method for elevator call allocation in an elevator group comprising a plurality of elevator cars is provided. The method comprises detecting a logistic operation associated with an elevator car, the elevator car being stationary at a floor, and in response to detecting the logistic operation, restricting allocation of new elevator calls to the elevator cars in the elevator group.

[0003] In an implementation form of the first aspect, the method further comprises obtaining data related to elevator door operation monitoring and / or elevator car position monitoring, and detecting a logistics operation associated with the elevator car based at least in part on the data.

[0004] In an implementation form of the first aspect, the method further includes obtaining data related to at least one usage pattern associated with a door of the elevator car; and detecting a logistic operation associated with the elevator car based at least in part on the data.

[0005] In an implementation form of the first aspect, the at least one usage mode includes at least one of: a usage mode associated with how long the door remains open, a usage mode associated with a closing-reopening cycle of the door, and a usage mode associated with a door opening button.

[0006] In an implementation of the first aspect, the method further includes detecting a logistics operation based at least in part on signaling transmitted in the elevator control system.

[0007] In an implementation form of the first aspect, the method further comprises detecting a logistics operation based at least in part on data associated with monitoring the elevator car and / or a lobby area associated with the elevator car.

[0008] In an implementation of the first aspect, the method further comprises detecting logistics operations associated with the elevator car using at least in part a trained machine learning model, wherein the trained machine learning model is trained at least in part based on local usage data associated with the elevator group.

[0009] In an implementation form of the first aspect, the method further comprises detecting logistics operations associated with the elevator car using at least in part a trained machine learning model, the trained machine learning model being trained at least in part based on usage data associated with at least one other elevator group.

[0010] In an implementation form of the first aspect, the method also includes detecting logistics operations associated with the elevator car at least in part using a trained machine learning model, wherein the trained machine learning model is trained at least in part based on at least one elevator door parameter associated with the loading call.

[0011] In an implementation form of the first aspect, in response to detecting the logistic operation, restricting the allocation of new elevator calls to elevator cars in the elevator group includes removing the elevator car from active elevator call allocations.

[0012] In an implementation form of the first aspect, in response to detecting the logistic operation, limiting the allocation of new elevator calls to elevator cars in the elevator group includes adjusting availability estimates associated with the elevator cars.

[0013] In an implementation of the first aspect, the method further comprises obtaining a prediction of an end of the logistics operation and resuming allocating calls to the elevator car based on the prediction, the prediction being based at least in part on monitoring the elevator car and / or a lobby area associated with the elevator car.

[0014] In an implementation of the first aspect, the method further comprises detecting the end of the logistics operation and resuming allocating calls to the elevator cars.

[0015] According to a second aspect, a system is provided comprising means for detecting a logistic operation associated with an elevator car, the elevator car being stationary at a floor, and means for limiting allocation of new elevator calls to elevator cars in an elevator group in response to detecting the logistic operation.

[0016] In an implementation of the second aspect, the system further comprises means for obtaining data related to elevator door operation monitoring and / or elevator car position monitoring, and means for detecting logistics operations associated with the elevator car based at least in part on the data.

[0017] In an implementation form of the second aspect, the system further comprises means for obtaining data relating to at least one usage mode associated with an elevator car door, and means for detecting a logistic operation associated with the elevator car based at least in part on the data.

[0018] In an implementation form of the second aspect, the at least one usage mode includes at least one of: a usage mode associated with how long the door remains open, a usage mode associated with a closing-reopening cycle of the door, and a usage mode associated with a door opening button.

[0019] In an implementation of the second aspect, the system further comprises means for detecting a logistics operation based at least in part on signaling transmitted in the elevator control system.

[0020] In an implementation form of the second aspect, the system further comprises means for detecting a logistics operation based at least in part on data associated with monitoring the elevator car and / or a lobby area associated with the elevator car.

[0021] In an implementation of the second aspect, the system further comprises means for detecting logistics operations associated with an elevator car using at least in part a trained machine learning model, wherein the trained machine learning model is trained at least in part based on local usage data associated with the elevator group.

[0022] In an implementation of the second aspect, the system further comprises a device for detecting logistics operations associated with an elevator car using at least in part a trained machine learning model, wherein the trained machine learning model is trained at least in part based on usage data associated with at least one other elevator group.

[0023] In an implementation of the second aspect, the system also includes a device for detecting logistics operations associated with an elevator car using at least in part a trained machine learning model, wherein the trained machine learning model is trained at least in part based on at least one elevator door parameter associated with a loading call.

[0024] In an implementation form of the second aspect, the means for limiting the assignment of new elevator calls to elevator cars in the elevator group in response to detecting a logistic operation is configured to remove the elevator car from the active elevator call assignments.

[0025] In an implementation form of the second aspect, the means for limiting the allocation of new elevator calls to elevator cars in the elevator group in response to detecting a logistic operation is configured to adjust availability estimates associated with the elevator cars.

[0026] In an implementation of the second aspect, the system further comprises means for obtaining a prediction of the end of a logistics operation based at least in part on monitoring the elevator car and / or a lobby area associated with the elevator car, and means for resuming allocation of calls to the elevator car based on the prediction.

[0027] In an implementation of the second aspect, the system further comprises means for detecting the end of the logistics operation and means for resuming the allocation of calls to the elevator cars.

[0028] According to a third aspect, there is provided a computer program comprising instructions for causing a device to perform the method of the first aspect.

[0029] According to a fourth aspect, there is provided a computer readable medium comprising a computer program comprising instructions for causing an apparatus to perform the method of the first aspect.

[0030] According to a fifth aspect, there is provided an apparatus for use during construction time of at least one elevator car of an elevator system in a building, the building comprising a plurality of floors. The apparatus comprises:

[0031] at least one processor and at least one memory storing instructions that, when executed by the at least one processor, cause the device to perform:

[0032] A logistic operation associated with an elevator car is detected, the elevator car being stationary at a floor, and in response to detecting the logistic operation, allocation of new elevator calls to elevator cars in the elevator group is restricted. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings, which are included to provide a further understanding of the present invention and constitute a part of this specification, illustrate embodiments of the present invention and together with the description help explain the principles of the present invention. In the drawings:

[0034] Figure 1 An example of an elevator system according to an example embodiment is shown.

[0035] Figure 2 An example of a method according to an example embodiment is shown.

[0036] Figure 3 A block diagram of a system according to an example embodiment is shown. DETAILED DESCRIPTION

[0037] Various examples and embodiments discussed herein disclose a solution for elevator call allocation in an elevator group including a plurality of elevator cars. A logistics operation associated with an elevator car, which is stationary at a floor, may be detected. The term "logistics operation" as used herein may refer to an operation or event involving, for example, the movement of personnel, bulk deliveries, or construction time use of an elevator, wherein the event may reserve an elevator for an extended period of time, the duration of which may be unknown and difficult to accurately estimate, and thus the event may be time-consuming. In an example embodiment, there may be a predefined time limit after which an event may be considered "time-consuming" or marked as a "logistics process." In response to detecting a logistics operation, the allocation of new elevator calls to elevator cars in the elevator group may be restricted.

[0038] Figure 1 An example of an elevator system according to an example embodiment is shown. The elevator system includes an elevator group controller 100 connected to elevator controllers 102A, 102B, 102C. Each elevator controller 102A, 102B, 102C controls its respective elevator car 104A, 104B, 104C. The elevator group controller 100 may be configured to assign calls to the elevator cars 104A, 104B, 104C. In an example embodiment, the elevator group controller 100 may be configured to implement the functionality discussed below in various example embodiments. In another example embodiment, the functionality may be implemented in part by the elevator group controller 100 and in part by at least one device or entity connected to the elevator group controller 100.

[0039] Figure 2 An example of a method for elevator call distribution in an elevator group comprising a plurality of elevator cars is shown.

[0040] At 200, a logistic operation associated with an elevator car, which is stationary at a floor, may be detected. The term "logistic operation" may refer to an event involving, for example, the movement of people, a large shipment, or construction time use of an elevator, wherein the event may hold the elevator for an extended period of time, the duration of which may be unknown and difficult to accurately estimate. The detection may be based on, for example, information provided by the elevator system itself and / or information obtained by the elevator system from an external device or system.

[0041] At 202, in response to detecting a logistic operation, assignment of new elevator calls to elevator cars in an elevator group may be restricted.

[0042] In an exemplary embodiment, data related to elevator door operation monitoring and / or elevator car position monitoring may be obtained, and a logistics operation associated with the elevator car may be detected based at least in part on the data. An elevator controller associated with the elevator car or an external device may monitor the position of the elevator door and / or the elevator car, and the elevator controller may transmit data regarding the monitoring to an elevator group controller. For example, the elevator car may have been stationary for a first predetermined time limit, and its door may have been open for a second predetermined time limit. This may be used as a trigger to detect a logistics operation.

[0043] In an exemplary embodiment, data related to at least one usage pattern associated with a door of an elevator car may be obtained, and a logistic operation associated with the elevator car may be detected based at least in part on the data. The term "usage pattern" may refer to any pattern involving one or more entities associated with an elevator car, such as how long an elevator door remains open, a close-reopen cycle of an elevator door, use of an elevator door open button, etc. When a logistic operation usage pattern is detected, call distribution in an elevator group may be altered so that, for example, an elevator call distribution engine run by an elevator group controller does not distribute calls to elevators that have been reserved for an unforeseeable long period of time.

[0044] In an exemplary embodiment, a logistic operation may be detected based at least in part on signaling transmitted in an elevator control system. For example, protocol signaling or other messages used in an elevator control system may include information based on which a logistic operation may be detected. When a logistic operation is detected, the information may be relayed to an elevator call allocation engine in an elevator group controller that manages the allocation of elevator cars to elevator calls. The elevator group controller may, for example, drop an unavailable elevator from an active allocation until the abnormal situation is over, or adjust an availability estimate of an elevator car in an elevator call allocation algorithm.

[0045] In an exemplary embodiment, a logistics operation may be detected based at least in part on data associated with monitoring an elevator car and / or a lobby area associated with the elevator car. For example, at least one device external to the elevator system (e.g., at least one camera of the surveillance system) may provide information based on which a prediction of when the logistics operation will end may be performed. The entity that determines the prediction based on data from at least one device external to the elevator system may then relay the prediction to the elevator group controller so that elevator call allocations may be planned accordingly.

[0046] In an exemplary embodiment, a logistics operation associated with an elevator car may be detected using at least in part a trained machine learning model that is trained at least in part based on local usage data associated with an elevator group. The local usage data may provide data from the same building when a logistics operation is detected, and what indicators pointing to the logistics operation are recorded for the logistics operation. For example, an elevator door may have been open for a long time, an elevator door open button is repeatedly used, etc. This data may then be used to train a machine learning model.

[0047] In an example embodiment, the logistics operations associated with the elevator cars are at least partially trained using a machine learning model that is trained at least in part based on usage data associated with at least one other elevator group. The other elevator groups may be elevator groups residing in different buildings, different cities, or even different countries, etc. Certain features of the identified logistics operations may be similarly applied between different elevator groups, and this data may then be used to train the machine learning model.

[0048] In an exemplary embodiment, logistic operations associated with an elevator car may be detected at least in part using a trained machine learning model, which was trained at least in part based on at least one elevator door parameter associated with a loading call. Some elevators or elevator systems may offer the possibility to indicate a special loading call when an elevator call is made. When a loading call has been received, for example the operation of the door operator and the door opening time may be recorded, and this information may then be used to train a machine learning model, which may then recognize loading situations even in the case where no explicit loading call has been received.

[0049] In an exemplary embodiment, in response to detecting a logistic operation, limiting the assignment of new elevator calls to elevator cars in the elevator group may include removing elevator cars from active elevator call assignments or adjusting availability estimates associated with elevator cars. This may provide the advantage that elevator calls are not assigned to elevator cars that may not be able to service calls within a reasonable time.

[0050] In an exemplary embodiment, a prediction of the end of a logistics operation can be obtained, the prediction being based at least in part on monitoring an elevator car and / or a lobby area associated with the elevator car, and allocation of calls to the elevator car can be resumed based on the prediction. For example, an external device (e.g., a surveillance camera) can monitor the elevator car and / or the lobby area associated with the elevator car, and can provide a prediction of when the logistics operation will end based on data provided by the external device. The prediction can be performed by some device of the elevator system or a device external to the elevator system. The device can transmit the prediction to the elevator group controller so that the elevator call allocation can be planned accordingly.

[0051] In an exemplary embodiment, the end of the logistics operation can be detected, and the allocation of calls to the elevator car can be resumed. For example, the detection can be performed when it is detected that the elevator door of the elevator car has been closed. In another exemplary embodiment, it can be detected that the loading at the source floor and the unloading at the destination floor have been performed, and in response thereto, the allocation of calls to the elevator car can be resumed. In another exemplary embodiment, a timer with a predefined time (e.g., 1-5 minutes or any suitable timer value) can be used, and the detection can be performed when the timer expires. In an exemplary embodiment, the value of the timer can depend on the items transported with the elevator car, such as the type, weight and / or quantity of the items.

[0052] Figure 3 A block diagram of a system 300 according to an example embodiment is shown. The system 300 may include, for example, a controller, a computer or a group of controllers, computers or other system entities configured to implement the above-mentioned features. In an exemplary embodiment, the system 300 may be integrated as part of an elevator controller, an elevator group controller or an elevator drive, as a separate circuit board / module or as integrated hardware. In another exemplary embodiment, the system 300 may be implemented, for example, using an additional software module in an elevator controller, an elevator group controller or an elevator drive. In other words, the system 300 may refer to, for example, an elevator controller, an elevator group controller or an elevator drive configured to implement the above-mentioned features. The system 300 may be configured to detect a logistics operation associated with an elevator car, the elevator car being stationary at a floor, and in response to detecting the logistics operation, restrict the allocation of new elevator calls to elevator cars in the elevator group.

[0053] System 300 may include one or more processors 302 and one or more memories 304 including computer program code. System 300 may also include at least one communication interface 308 configured to provide wireless and / or wired connections. Although system 300 is depicted as including only one processor 302, system 300 may include more than one processor. In an example embodiment, memory 304 is capable of storing instructions, such as an operating system and / or various applications.

[0054] In addition, the processor 302 is capable of executing the stored instructions. In an example embodiment, the processor 302 may be embodied as a multi-core processor, a single-core processor, or a combination of one or more multi-core processors and one or more single-core processors. For example, the processor 302 may be embodied as one or more of a variety of processing devices, such as a coprocessor, a microprocessor, a controller, a digital signal processor (DSP), a processing circuit with or without an accompanying DSP, or various other processing devices including integrated circuits, such as, for example, an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), a microcontroller unit (MCU), a hardware accelerator, a dedicated computer chip, etc. In an example embodiment, the processor 302 may be configured to perform hard-coded functions. In an example embodiment, the processor 302 is implemented as an executor of software instructions, wherein the instructions may specifically configure the processor 302 to perform the algorithms and / or operations described herein when the instructions are executed.

[0055] The memory 304 may be embodied as one or more volatile memory devices, one or more non-volatile memory devices, and / or a combination of one or more volatile memory devices and non-volatile memory devices. For example, the memory 304 may be embodied as a semiconductor memory (such as a mask ROM, a PROM (programmable ROM), an EPROM (erasable PROM), a flash ROM, a RAM (random access memory), etc.).

[0056] In an embodiment, at least one memory 304 may store program instructions 306 that, when executed by at least one processor 302, cause system 300 to perform the functions of the various embodiments discussed herein. Furthermore, in an embodiment, at least one of processor 302 and memory 304 may constitute means for implementing the functions discussed.

[0057] One or more of the examples and exemplary embodiments discussed above may implement a solution that reduces the waiting time on nearby stair landings because no new elevator calls are assigned to elevators for which logistics operations have been detected.

[0058] The example embodiments may be implemented in software, hardware, application logic, or a combination of software, hardware, and application logic. The example embodiments may store information related to the various methods described herein. The information may be stored in one or more memories, such as a hard disk, an optical disk, a magneto-optical disk, a RAM, etc. One or more databases may store information for implementing the example embodiments. The database may be organized using data structures (e.g., records, tables, arrays, fields, graphs, trees, lists, etc.) included in one or more memories or storage devices listed herein. The methods described with respect to the example embodiments may include appropriate data structures for storing data collected and / or generated by the methods of the devices and subsystems of the example embodiments in one or more databases.

[0059] The components of the example embodiments may include a computer-readable medium or memory for storing instructions programmed according to the teachings and for storing data structures, tables, records and / or other data described herein. In an example embodiment, the application logic, software or instruction set is maintained on any of a variety of conventional computer-readable media. In the context of this document, a "computer-readable medium" may be any medium or component that can contain, store, communicate, propagate or transmit instructions for use by an instruction execution system, device or equipment (such as a computer) or in combination with an instruction execution system, device or equipment (such as a computer). A computer-readable medium may include a computer-readable storage medium, which may be any medium or device that can contain or store instructions for use by an instruction execution system, device or equipment (such as a computer) or in combination with it. A computer-readable medium may include any suitable medium that participates in providing instructions to a processor for execution. Such a medium may take many forms, including but not limited to non-volatile media, volatile media, transmission media, etc.

[0060] Although the basic novel features applied to the preferred embodiments thereof have been shown and described and pointed out, it should be understood that various omissions, substitutions and changes in the form and details of the described apparatus and methods may be made by those skilled in the art without departing from the spirit of the present disclosure. For example, it is expressly intended that all combinations of those elements and / or method steps that perform substantially the same function in substantially the same manner to achieve the same results are within the scope of the present disclosure. In addition, it should be recognized that the structures and / or elements and / or method steps shown and / or described in conjunction with any disclosed form or embodiment can be incorporated into any other disclosed or described or suggested form or embodiment as a general matter of design choice. In addition, the device plus function clause is intended to cover the structures described herein as performing the functions described, and not only covers structural equivalents, but also covers equivalent structures.

[0061] Applicants hereby disclose in isolation each individual feature described herein and any combination of two or more such features, as long as such feature or combination can be performed based on the present specification as a whole according to the common knowledge of those skilled in the art, regardless of whether such feature or combination of features solves any problem disclosed herein, and without limiting the scope of the claims. Applicants point out that the disclosed aspects / embodiments may consist of any such individual feature or combination of features. In view of the foregoing description, it will be apparent to those skilled in the art that various modifications may be made within the scope of the present disclosure.

Claims

1. A method for distributing elevator calls in an elevator group comprising a plurality of elevator cars, the method include: detecting a logistic operation associated with an elevator car, the elevator car being stationary at a floor; and In response to detecting the logistic operation, assigning new elevator calls to the elevator cars in the elevator group is restricted.

2. The method according to claim 1, further comprising: include: obtaining data related to elevator door operation monitoring and / or elevator car position monitoring; and A logistics operation associated with the elevator car is detected based at least in part on the data.

3. The method according to claim 1 or 2, further comprising: include: obtaining data related to at least one usage pattern associated with a door of the elevator car; and A logistics operation associated with the elevator car is detected based at least in part on the data.

4. The method according to claim 3, in, The at least one usage mode includes at least one of the following: usage patterns associated with how long the door remains open; a usage pattern associated with a closing-reopening cycle of the door; and The usage mode associated with the door opening button.

5. The method according to any one of claims 1 to 4, further comprising: include: The logistics operation is detected based at least in part on signaling transmitted in an elevator control system.

6. The method according to any one of claims 1 to 5, further comprising: include: The logistics operation is detected based at least in part on data associated with monitoring the elevator car and / or a lobby area associated with the elevator car.

7. The method according to any one of claims 1 to 6, further comprising: include: Logistic operations associated with the elevator cars are detected at least in part using a trained machine learning model trained at least in part based on local usage data associated with the elevator group.

8. The method according to any one of claims 1 to 6, further comprising: include: Logistic operations associated with the elevator car are detected at least in part using a trained machine learning model trained at least in part based on usage data associated with at least one other elevator group.

9. The method according to any one of claims 1 to 6, further comprising: include: A logistic operation associated with the elevator car is detected at least in part using a trained machine learning model trained at least in part based on at least one elevator door parameter associated with a loading call.

10. The method according to any one of claims 1 to 9, in, In response to detecting the logistic operation, limiting the allocation of new elevator calls to the elevator cars in the elevator group comprises: The elevator car is removed from the active elevator call assignments.

11. The method according to any one of claims 1 to 9, in, In response to detecting the logistic operation, limiting the allocation of new elevator calls to the elevator cars in the elevator group comprises: An availability estimate associated with the elevator car is adjusted.

12. The method according to any one of claims 1 to 11, further comprising: include: obtaining a prediction of an end of a logistics operation, the prediction based at least in part on monitoring the elevator car and / or a lobby area associated with the elevator car; and Assigning calls to the elevator cars is resumed based on the prediction.

13. The method according to any one of claims 1 to 11, further comprising: include: detecting the end of the logistics operation; and The allocation of calls to the elevator cars is resumed.

14. A system, include: means for detecting logistic operations associated with an elevator car, said elevator car being stationary at a floor; and Means for limiting the allocation of new elevator calls to the elevator cars in the elevator group in response to detecting the logistic operation.

15. The system according to claim 14, further comprising: include: Means for obtaining data related to elevator door operation monitoring and / or elevator car position monitoring; and Means for detecting a logistics operation associated with the elevator car based at least in part on the data.

16. The system according to claim 14 or 15, further comprising: include: means for obtaining data related to at least one usage pattern associated with a door of an elevator car; and Means for detecting a logistics operation associated with the elevator car based at least in part on the data.

17. The system according to claim 16, in, The at least one usage mode includes at least one of the following: usage patterns associated with how long the door remains open; a usage pattern associated with a closing-reopening cycle of the door; and The usage mode associated with the door opening button.

18. The system according to any one of claims 14 to 17, further comprising: include: Means for detecting a logistics operation based at least in part on signaling transmitted in an elevator control system.

19. The system according to any one of claims 14 to 18, further comprising: include: Means for detecting the logistics operation based at least in part on data associated with monitoring the elevator car and / or a lobby area associated with the elevator car.

20. The system according to any one of claims 14-19, further comprising: include: Means for detecting logistic operations associated with the elevator car using, at least in part, a trained machine learning model trained at least in part based on local usage data associated with the elevator group.

21. The system according to any one of claims 14-19, further comprising: include: Means for detecting logistic operations associated with the elevator car using, at least in part, a trained machine learning model trained at least in part based on usage data associated with at least one other elevator group.

22. The system according to any one of claims 14-19, further comprising: include: Means for detecting logistics operations associated with the elevator car using, at least in part, a trained machine learning model trained at least in part based on at least one elevator door parameter associated with a loading call.

23. The system of any one of claims 14-22, wherein the means for assigning a new elevator call to the elevator car in the elevator group in response to detecting the logistical operating constraint is configured to remove the elevator car from active elevator call assignments.

24. The system of any of claims 14-22, wherein the means for assigning a new elevator call to the elevator car in the elevator group in response to detecting the logistical operating constraint is configured to adjust an availability estimate associated with the elevator car.

25. The system according to any one of claims 14-24, further comprising: include: means for obtaining a prediction of the end of a logistics operation, the prediction being based at least in part on monitoring an elevator car and / or a lobby area associated with the elevator car; and Means for resuming allocation of calls to the elevator cars based on the prediction.

26. The system according to any one of claims 14-24, further comprising: include: A device for detecting the end of the logistics operation; and Means for resuming allocation of calls to said elevator cars.

27. A computer program comprising instructions for causing an apparatus to perform a method according to any one of claims 1 to 13.

28. A computer readable medium comprising a computer program comprising instructions for causing an apparatus to perform a method according to any one of claims 1 to 13.

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