System and method for dynamically modifying capacity limits of an elevator car

Abstract

The invention is titled "System and method for dynamically modifying a capacity limit of an elevator car." An elevator system is disclosed having: a controller; an elevator car operatively connected to the controller; a first sensor configured to provide first sensor data to the controller, wherein the controller is configured to identify a capacity parameter of the elevator car, wherein the capacity parameter comprises one or more of: a loaded weight; a volume of available space; or a volume of occupied space; a second sensor configured to provide second sensor data to the controller, wherein the controller is configured to determine that a passenger remains outside the elevator car when the elevator car is stopped at a landing and its elevator doors are open; and wherein, as a function of the first sensor data and the second sensor data, the controller is configured to determine a reduced capacity limit for the elevator car as a function of the capacity parameter.

Description

BACKGROUND

[0001] Embodiments are directed to elevator systems, and more particularly to systems and methods for dynamically modifying a capacity limit of an elevator car.

[0002] An elevator car can be controlled to skip new floor call(s) when a occupancy capacity limit is reached. The reduced capacity limit can be based on a plurality of calls. However, passengers can avoid entering the elevator car even when it is below the reduced capacity limit, thereby reducing overall system efficiency. SUMMARY

[0003] An elevator system is disclosed, the elevator system comprising: a controller; an elevator car operatively connected to the controller; a first sensor configured to provide first sensor data to the controller, wherein the controller is configured to identify a capacity parameter of the elevator car, wherein the capacity parameter comprises one or more of: a weight of a load; a volume of available space; or a volume of occupied space; a second sensor configured to provide second sensor data to the controller, wherein the controller is configured to determine that a passenger remains outside the elevator car when the elevator car stops at a landing and its elevator doors are open; and wherein from the first sensor data and the second sensor data, the controller is configured to determine a reduced capacity limit for the elevator car as a function of the capacity parameter.

[0004] In addition to or as an alternative to one or more aspects of the system, the controller, the first sensor, and the second sensor are configured to communicate with each other over a wireless network.

[0005] In addition to or as an alternative to one or more aspects of the system, the controller is configured to determine the reduced capacity limit by applying a predetermined multiplier to the capacity parameter.

[0006] In addition to or as an alternative to one or more aspects of the system, the capacity parameter further comprises one or more of a time of day, a season, a geographic location, an occupancy type, and a building utilization.

[0007] In addition to or as an alternative to one or more aspects of the system, the occupancy type is one or more of cargo and passengers.

[0008] In addition to or as an alternative to one or more aspects of the system, the controller is configured to control the elevator car to ignore calls for service when the elevator car is at or above the reduced capacity limit.

[0009] In addition or as an alternative to one or more aspects of the system, the first sensor is located on the elevator car and is configured to communicate with the controller directly or via a cloud service, and the first sensor data is processed in whole or in part at one or more of the first sensor, the cloud service, and the controller.

[0010] In addition or as an alternative to one or more aspects of the system, one or more of a passenger count, a volume of the available space, and a volume of the occupied space are derived from processing the first sensor data.

[0011] In addition or as an alternative to one or more aspects of the system, the second sensor is on the elevator car or is located at the landing; and the second sensor communicates with the controller directly or via the cloud service, and the second sensor data is processed in whole or in part at one or more of the second sensor, the cloud service, and the controller.

[0012] In addition or as an alternative to one or more aspects of the system, the second sensor is a motion sensor or a depth sensor located on the landing.

[0013] In addition or as an alternative to one or more aspects of the system, when determining the reduced capacity limit, the controller is configured to: accumulate data related to passengers entering the elevator in response to a hall call as the elevator car approaches its design capacity limit or a predetermined reduced capacity limit; set the reduced capacity limit in relation to a predetermined boarding probability and set a margin of tolerance to be approximately the reduced capacity limit; determine whether passengers are entering the elevator car in response to a hall call; increase the reduced capacity limit by half the margin of tolerance of an upper capacity tolerance limit upon determining that passengers are entering the elevator in response to a hall call, or decrease the reduced capacity limit by half the margin of tolerance of a lower capacity tolerance limit upon determining that passengers are not entering the elevator in response to a hall call; determine whether the boarding probability is within an acceptable limit over time; and modify one or both of the margin of tolerance and the reduced capacity limit upon determining that the boarding probability is outside the acceptable limit over time.

[0014] Also disclosed is a method of controlling an elevator car of an elevator system with a controller operatively connected to the elevator car, the method comprising: identifying, at the controller, a capacity parameter of the elevator car as a function of first sensor data communicated via a first sensor, wherein the capacity parameter comprises at least one of: a loaded weight; a volume of available space; or a volume of occupied space; determining, at the controller, that a passenger remains outside the elevator car when the elevator car is stopped at a landing and its elevator doors are open as a function of second sensor data communicated via a second sensor; and determining, at the controller, a reduced capacity limit for the elevator car as a function of the capacity parameter from the first sensor data and the second sensor data.

[0015] In addition to or as an alternative to one or more aspects of the method, the controller, the first sensor, and the second sensor communicate with each other over a wireless network.

[0016] In addition to or as an alternative to one or more aspects of the method, determining the reduced capacity limit comprises applying a predetermined multiplier to the capacity parameter.

[0017] In addition to or as an alternative to one or more aspects of the method, the capacity parameter further comprises one or more of a time of day, a season, a geographic location, a type of occupancy, and a building utilization.

[0018] In addition to or as an alternative to one or more aspects of the method, the type of occupancy is one or more of cargo and passengers.

[0019] In addition to or as an alternative to one or more aspects of the method, the method further comprises: controlling, by the controller, the elevator car to ignore calls for service when the elevator car is at or above the reduced capacity limit.

[0020] In addition to or as an alternative to one or more aspects of the method, the first sensor is located on the elevator car; and the method comprises: communicating between the controller and the first sensor directly or via a cloud service, and processing the first sensor data in whole or in part at one or more of the first sensor, the cloud service, and the controller.

[0021] In addition to or as an alternative to one or more aspects of the method, the method further comprises: determining one or more of a passenger count, a volume of available space, and a volume of occupied space from the first sensor data.

[0022] In addition or as an alternative to one or more aspects of the method, the second sensor is on the elevator car or located at the landing; and the method further comprises: communicating between the second sensor and the controller directly or via the cloud service, and processing the second sensor data in whole or in part at one or more of the second sensor, the cloud service, and the controller.

[0023] In addition or as an alternative to one or more aspects of the method, the second sensor comprises a motion sensor or a depth sensor located at the landing.

[0024] In addition or as an alternative to one or more aspects of the method, when determining the reduced capacity limit, the method comprises the controller: accumulating data related to passengers entering the elevator in response to a hall call as the elevator car approaches its design capacity limit or a predetermined reduced capacity limit; setting the reduced capacity limit to be related to a predetermined boarding probability, and setting a capacity tolerance range to be about the reduced capacity limit; determining whether passengers are entering the elevator car in response to a hall call; increasing the reduced capacity limit by half the capacity tolerance range of an upper capacity tolerance limit upon determining that passengers are entering the elevator in response to a hall call, or decreasing the reduced capacity limit by half the capacity tolerance range of a lower capacity tolerance limit upon determining that passengers are not entering the elevator in response to a hall call; determining whether the boarding probability is within an acceptable limit over time; and modifying one or both of the capacity tolerance range and the reduced capacity limit upon determining that the boarding probability is outside the acceptable limit over time. BRIEF DESCRIPTION OF DRAWINGS

[0025] The present disclosure is illustrated by way of example and is not limited by the accompanying figures in which like reference numbers indicate similar elements.

[0026] Figure 1 is a schematic illustration of an elevator system in which various embodiments of the present disclosure can be employed;

[0027] Figure 2 is a further schematic illustration of an elevator system configured to dynamically modify a capacity limit of an elevator car; and

[0028] Figure 3 is a flowchart illustrating aspects of a method of dynamically modifying a capacity limit of an elevator car;

[0029] Figure 4 is a probability curve generated by a system for dynamically modifying a reduced capacity limit of an elevator car; and

[0030] Figures 5-9is an additional flowchart illustrating aspects of a method of dynamically modifying a reduced capacity limit of an elevator car. DETAILED DESCRIPTION

[0031] Figure 1 is a perspective view of an elevator system 101 including an elevator car 103, a counterweight 105, a tension member 107, a guide rail (or rail system) 109, a machine (or machine system) 111, a position reference system 113, and an electronic elevator controller (controller) 115. The elevator car 103 and the counterweight 105 are connected to each other by the tension member 107. The tension member 107 can include or be configured as, for example, a rope, a steel cable, and / or a coated steel belt. The counterweight 105 is configured to balance the load of the elevator car 103 and to facilitate movement of the elevator car 103 within an elevator shaft (or hoistway) 117 and along the guide rail 109 in parallel and in an opposite direction relative to the counterweight 105.

[0032] The tension member 107 engages the machine 111, which is part of a top head structure of the elevator system 101. The machine 111 is configured to control movement between the elevator car 103 and the counterweight 105. The position reference system 113 can be mounted on a fixed portion (such as a support or guide rail) at the top of the elevator shaft 117 and can be configured to provide a position signal related to the position of the elevator car 103 within the elevator shaft 117. In other embodiments, the position reference system 113 can be mounted directly to a moving assembly of the machine 111 or can be located in other positions and / or configurations, as known in the art. The position reference system 113 can be any device or mechanism for monitoring the position of the elevator car and / or counterweight, as known in the art. The position reference system 113 can be, for example, but is not limited to, an encoder, a sensor, or other system, and can include speed sensing, absolute position sensing, and the like, as will be appreciated by those skilled in the art.

[0033] The controller 115 is located in a controller room 121 of the elevator shaft 117 as shown and is configured to control operation of the elevator system 101 and, in particular, the elevator car 103. For example, the controller 115 can provide drive signals to the machine 111 to control acceleration, deceleration, leveling, stopping, and the like of the elevator car 103. The controller 115 can also be configured to receive position signals from the position reference system 113 or any other desired position reference device. The elevator car 103 can stop at one or more landings 125 as controlled by the controller 115 when moving up or down within the elevator shaft 117 along the guide rail 109. Although shown in the controller room 121, those skilled in the art will appreciate that the controller 115 can be positioned and / or configured in other locations or positions within the elevator system 101. In one embodiment, the controller can be located remotely or in the cloud.

[0034] The machine 111 can include a motor or similar driving mechanism. According to embodiments of the present disclosure, the machine 111 is configured to include an electrically driven motor. The power supply for the motor can be any power source including a power grid that is supplied to the motor in combination with other components. The machine 111 can include a traction sheave that exerts a force on the tension member 107 to move the elevator car 103 within the elevator shaft 117.

[0035] Although shown and described with a roped system including a tension member 107, elevator systems employing other methods and mechanisms to move the elevator car within the elevator shaft can employ embodiments of the present disclosure. For example, embodiments can be employed in a ropeless elevator system that uses a linear motor to exert motion on the elevator car. Embodiments can also be employed in a ropeless elevator system that uses a hydraulic lift to exert motion on the elevator car. Embodiments can also be employed in a ropeless elevator system that uses a self-propelled elevator car (e.g., an elevator car equipped with a friction wheel, pinch wheel, or traction wheel). Figure 1 The non-limiting examples presented are for illustrative and explanatory purposes only.

[0036] To optimize elevator car assignment performance, it can be valuable for the system to know the actual available space (volume) or weight in the elevator car (otherwise referred to as a cab). The system can utilize this information to estimate passenger count or passenger or cargo volume and estimate available space so as not to assign passengers to a car that will not enter due to overcrowding. As indicated below, capacity (or occupancy) limits can be a function of geographic environment, building type (e.g., commercial / residential), time of day, season, etc.

[0037] In particular, turning to Figure 2 , the elevator system 101 is located in a building 200 and includes an elevator car 103 that travels in a shaft 117 between landings generally indicated at 125 and including, for example, a first landing 125a and a second landing 125b to pick up and drop off passengers 210. The elevator system 101 includes a controller 115 and the elevator car 103 is operatively connected to the controller 115. The controller 115 can be on the elevator car or can be a dispatch controller located remotely as shown in Figure 1 .

[0038] The first sensor 220 can be configured to provide first sensor data to the controller 115 indicative of current elevator car capacity or occupancy as indicated below. The first sensor 220 can be located in the car 103 and can be, for example, a camera, a depth sensor, a floor pressure sensor, etc. Alternatively, the first sensor 220 can be located elsewhere. For example, the first sensor 220 can be a camera located in the shaft 117.Figure 1 A tension measurement system is illustrated in FIG. 1 as tension on the hoisting ropes of the traction members 107.

[0039] From the first sensor data, the controller 115 can be configured to identify a capacity parameter (or occupancy parameter) of the elevator car 103. The capacity parameter can represent information about the condition of elevator utilization that enables the controller 115 to determine a modified or reduced capacity limit. The capacity parameter can be a loaded weight, a volume of available space, or a volume of occupied space.

[0040] For example, if the first sensor 220 is a pressure or weight sensing implementation, the first sensor data can be utilized to identify a loaded weight in the elevator car 103. Alternatively, if the first sensor 220 is a camera or depth sensor, the first sensor data can be utilized to identify an occupancy volume in the elevator car 103. The first sensor 220 can be configured to communicate directly with the controller 115, for example, via a wired or wireless network connection 235 as indicated below or via a cloud service 240. The first sensor data can be processed in whole or in part by edge computing or at the cloud service 240 or the controller 115. The first sensor data can be transmitted in whole or in part in raw format, and portions of the first sensor data can be stitched together at different processing points along the transmission path between the first sensor 220 and the controller 115.

[0041] The second sensor 225 can be configured to provide second sensor data to the controller 115 indicative of passenger activity at the landing 125 reached by the car 103. The second sensor 225 can also be a camera, depth sensor, or floor pressure sensor located at the landing 125. Alternatively, the second sensor 225 can be a light curtain in the elevator door 230 and / or the lobby door, etc. (e.g., in the elevator door 230) in FIG. 1. In one embodiment, the first sensor is utilized instead of the second sensor to obtain this information. Figure 2

[0042] ​According to the second sensor data, the controller 115 can be configured to determine that at least one passenger remains outside the elevator car 103, e.g., at the landing 125, when the elevator car 103 stops at the landing 125 throughout the period the elevator doors 230 are open, and when the doors are closed. For example, the controller 115 can utilize standard protocols to determine when the elevator doors 230 are opened and closed at the landing 125. The controller 115 can then utilize the second sensor data to determine that at least one passenger at the landing 125 did not board the elevator car 103. This can be, for example, a binary determination that identifies whether a passenger was at the landing 125 when the doors were closed. The determination can also take into account whether passengers entered and exited the elevator car and how many passengers entered and exited the elevator car while the elevator car was at the landing 125. These determinations can take into account, for example, an instantaneous change or difference between initial and final passenger volume or weight at the landing when the elevator doors are open. The second sensor 225 can be configured to communicate directly with the controller 115, e.g., via a wired or wireless network connection 235 as indicated below, or via the cloud service 240. The second sensor data can be processed in whole or in part by edge computing or at the cloud service 240 or the controller 115. The second sensor data can be transmitted in whole or in part in raw format, and portions of the second sensor data can be spliced together at different processing points along the transmission path between the second sensor 225 and the controller 115.

[0043] Based on the first sensor data and the preprogrammed capacity data, the controller 115 can determine that the elevator car 103 has available capacity for more passengers. However, by also taking into account the second data, the controller 115 can determine that the elevator has reached its capacity based on passenger preferences. According to the first sensor data and the second sensor data, in contrast, the controller 115 can be configured to determine that the reduced capacity limit for the elevator car 103 is a function of the capacity parameter (actual loaded weight, occupied space, or available space). Thus, the controller 115 is configured to dynamically modify (e.g., reduce) the capacity limit of the elevator car 103 by utilizing the first sensor data and the second sensor data.

[0044] According to embodiments, the controller 115 can be configured to determine the reduced capacity limit by applying a predetermined multiplier to the capacity parameter. In an illustrative example, turning to Figure 3During periods of elevator peak, the reduced capacity limit G1may be calculated based on the determined capacity parameter G, in which case the car is considered to be at or near full load but not overloaded. At block 300, the car 103 is already at or near full load but not overloaded. At block 310, someone at the landing presses a hall call in another floor, and the car arrives at that floor and the elevator doors open. At block 320, a determination is made as to whether no one enters (or whether at least one passenger remains at the landing). If due to passengers entering (and, no one remaining at the landing), the determination is "no," the controller returns to block 300. If due to passengers not entering (or at least one passenger remaining), the determination is "yes," at block 330 the capacity parameter (e.g., G) at this time for the elevator car 103 is obtained. The elevator car 103 outputs a full load signal at block 340, and ignores the hall call. The car 103 runs to the next car call destination for each block 350. While passengers are exiting the car 103 and the elevator is still outputting the "full load" signal, at block 360 there is a determination as to whether the capacity parameter is less than the reduced capacity limit (G1), e.g., G is less than 0.9 (or another reduction factor). If at block 360, the determination is "no," the elevator remains full for each block 340, and will only run to car calls for each block 350, e.g., not to hall calls. If the determination at block 360 is "yes," for each block 370, the operating state returns to normal operation, e.g., the car is not overloaded even if at or near full load. As can be appreciated, the controller 115 can be configured to determine that the reduced capacity limit is a function of a preprogrammed or determined reduced capacity limit (e.g., less than or equal to ninety percent or other reduction factor), rather than a function of a subsequently measured capacity parameter.

[0045] As indicated above, the capacity parameter represents information about the conditions of elevator utilization that enable the controller to determine a modified or reduced capacity limit. According to embodiments, the capacity parameter can also include the time of day, the season, the geographic location, the occupancy type, and the building utilization. According to embodiments, the occupancy type can be one or more of cargo, passengers, and robots, which can be cleaning robots or other robots. That is, embodiments can consider beyond just the available space times weight or volume. Depending on the other identified variables, the system can more robustly identify when passengers in certain groups or passengers subject to certain environmental conditions can statistically feel an elevator car too crowded to enter. Such embodiments can be configured to learn actual limits that vary geographically and due to the use of the building (e.g., student dormitory versus hospital) even for the same size car. Thus, depending on these conditions, the controller 115 can reduce the capacity limit by a predetermined reduction factor without first having to go through the process shown in FIG. 3. Figure 3 Instead,Figure 3 The process shown in FIG. 1 can be utilized to fine-tune the reduced capacity limit that has otherwise been modified (reduced) based on time of day, season, geographic location, occupancy type, and building utilization.

[0046] According to embodiments, as indicated, the controller 115 can be configured to utilize the reduced capacity limit and control the elevator car 103 to ignore (e.g., disregard or not respond to) calls for service (hall calls) during such times that the elevator car 103 is at or above the reduced capacity limit.

[0047] According to embodiments, as indicated, the first sensor 220 can be on the elevator car 103 and can be configured to communicate directly with the controller 115, e.g., via a wired or wireless network connection 235 as indicated below or via the cloud service 240. The first sensor data can be processed in whole or in part at one or more of the first sensor 220, the cloud service 240, and the controller 115. Processed portions can be stitched together at the controller 115 in order to form compiled data. According to embodiments, one or more of a passenger count, a volume of available space, or a volume of occupied space can be derived from processing the first sensor data.

[0048] According to embodiments, the second sensor 225 can be on the elevator car 103 or located at the landing 125. The second sensor 225 can communicate directly with the controller 115 or via the cloud service 240. The second sensor data can be processed in whole or in part at one or more of the second sensor, the cloud service 240, and the controller 115. Processed portions can be stitched together at the controller 115 in order to form compiled data. According to embodiments, the second sensor 225 can be a motion sensor or a depth sensor located on the elevator car 103, such as in the elevator door 230 or on the landing. The second sensor 225 can also be a camera, a depth sensor, or a floor pressure sensor located at the landing 125. Alternatively, the second sensor 225 can be a light curtain in the elevator door 230 and / or the hall door, etc., e.g., Figure 2 The depth sensor can be configured to detect a body shape of a person, which the controller 115 identifies as a person waiting at the landing.

[0049] The above embodiments prepare the system to learn the load limit. The system utilizes volume sensors in both the car and the hall to detect when at least one passenger is left behind when the car is not boarded, so the system can sense whether some passengers are left behind in the hall. By detecting whether at least one person is left behind on substantially every boarding instance (i.e., hall call), the system can build up a profile of the building and the behavior of the passengers. Figure 4The probability curve 300 shown in the middle graphically represents the probability (Y-axis) of a passenger entering the elevator car (X-axis) based on, for example, the current passenger count or measured volume (used or available) in the elevator car.

[0050] The system goal is to approximately learn in the case of a curve that is suddenly downward, e.g., a learned limit (vertical line 320), which is a reduced capacity limit, which can represent a 90% boarding probability. When the car 103 is lightly loaded (left side 310 of graph 300), there is a high probability that someone will board the car. As the car becomes more full, the probability decreases. The goal can be to have passengers board the elevator car 90% of the time that a hall call is answered.

[0051] In the case of each completed boarding, the system can adjust the curve to the right to an upper bound capacity tolerance or upper limit 330 to increase the reduced capacity limit. Additionally, in the case of each uncompleted boarding, the system can adjust the curve to the left by substantially the same amount as the amount adjusted to the right to a lower bound capacity tolerance or lower limit 340 to decrease the reduced capacity limit. The amount adjusted to the left or right of the learned limit 320 can define an adjustment range or tolerance range 350, which itself can be learned and modified over time such that minimal overall adjustments are required to achieve a 90% (or approximately 90%) boarding probability. If the difference size of the tolerance range 350 between the reduced capacity limits 330 / 340 is too large, the probability of passenger boarding can drop to an unacceptable level, in which case the tolerance range 350 can be made smaller. If the boarding probability is much higher than 90%, the elevator can not be carrying enough passengers (which is also undesirable), in which case the tolerance range 350 can be made larger, and / or the learned limit 320 can be shifted to increase or decrease the reduced capacity limit. The size of the tolerance range 350 can initially be + / - 1% of the boarding probability. As one example, the adjustments to the tolerance range 350 and movement of the learned limit 320 can be in increments of a single percentage of the boarding probability. It should be appreciated that the boarding probability and tolerance range identified herein are merely exemplary, and the true values for each can be higher or lower than those identified herein.

[0052] A method of controlling an elevator car 103 of an elevator system 101 with a controller 115 that can be operatively connected to the elevator car 103 is also disclosed. Referring to Figure 5As shown in box 510, the method may include identifying capacity parameters of the elevator car 103 at the controller 115 based on first sensor data transmitted via the first sensor 220. As indicated, the capacity parameters may be: the weight carried; the volume of available space; or the volume of occupied space. In one embodiment, the capacity parameters may also include one or more of the time of day, season, geographic location, occupancy type, and building utilization. The occupancy type may be one or more of goods and passengers. Thus, depending on these conditions, the controller 115 may reduce the capacity limit by a predetermined reduction factor without first undergoing [further steps]. Figure 3 The process shown. Conversely. Figure 3 The illustrated process can be used to fine-tune capacity limits that have been modified (reduced) based on time of day, season, geographic location, occupancy type, and building utilization. As shown in box 520, the method may include, at controller 115, determining, based on second sensor data transmitted via second sensor 225, that passengers are still outside elevator car 103 when elevator car 103 stops at a landing and its elevator doors 230 are open. In one embodiment, controller 115, first sensor 220, and second sensor 225 communicate with each other via a wireless network 235 of the type identified below. As shown in box 530, the method may include, at controller 115, determining, based on first and second sensor data, a reduced capacity limit for elevator car 103 (e.g., relative to a design maximum capacity limit or a predetermined reduced capacity limit) as a function of a capacity parameter. For example, the capacity parameter could be the weight measured when people are not currently entering the elevator, and the capacity limit could be a predetermined reduction factor of the capacity parameter. In one embodiment, as shown in block 540, the method may include having the elevator car 103, controlled by the controller 115, ignore calls for service when the elevator car 103 is at or above a reduced capacity limit. In some embodiments, the system may continue operating until a lobby call, provided that at least one person rode the elevator during the last lobby call.

[0053] like Figure 6As shown in block 510A1, in one embodiment, block 510 can be further defined by block 510A1, which identifies that the method can include communicating between the controller 115 and the first sensor 220, which can be on the elevator car 103, directly or via the cloud service 240. As shown in block 510A2, the method can include processing the first sensor data, in whole or in part, at one or more of the first sensor 220, the cloud service 240, and the controller 115. The processed portions can be stitched together at the controller 115 to form compiled data. As shown in block 510A3, the method can include determining one or more of a passenger count, a volume of available space, and a volume of occupied space from the first sensor data.

[0054] Referring to Figure 7 As indicated, the second sensor 225 can be on the elevator car 103 or located at the landing 125. In one embodiment, block 520 can be further defined by block 520A1, which identifies that the method can include communicating between the second sensor 225 and the controller 115, directly or via the cloud service 240. As shown in block 520A2, the method can include processing the second sensor data, in whole or in part, at one or more of the second sensor 225, the cloud service 240, and the controller 115. The processed portions can be stitched together at the controller 115 to form compiled data. In one embodiment, the second sensor 225 can be a motion sensor or a depth sensor located on the elevator car 103 or at the landing 125.

[0055] As Figure 8 As shown in block 530A1, in one embodiment, block 530 can be further defined by block 530A1, which identifies that the method can include determining, by the controller 115, a reduced capacity limit by applying a predetermined multiplier to the capacity parameter. In one non-limiting example, the method can include determining, by the controller 115, that the reduced capacity limit can be less than or equal to ninety percent (or other reduction multiple) of a preprogrammed or determined capacity limit. Figure 9 A method for determining a reduced capacity limit based on the above, as shown in block 530A2, can include determining, by the controller 115, that the reduced capacity limit can be less than or equal to ninety percent (or other reduction multiple) of a preprogrammed or determined capacity limit. Figure 4Another embodiment of block 530 is defined or detailed with respect to the discussion above. As shown in block 530B1, the method can include the controller 115 accumulating data related to passengers entering the elevator car 103 in response to a hall call as the elevator car 103 approaches its design capacity limit or a predetermined reduced capacity limit (or other selected capacity limit). As shown in block 530B2, the method can include the controller 115 setting the reduced capacity limit related to a 90% (or other percentage) boarding probability that passengers will enter the car 103. The method can include the controller 115 setting a capacity tolerance range to be about the reduced capacity limit. The capacity tolerance range can be + / - 1% (or other percentage) of the boarding probability. As shown in block 530B3, the method can include the controller determining whether a passenger enters the elevator car 103 at each hall call to which it responds. If a passenger enters the elevator car 103 (yes at 530B3), as shown in block 530B4, the method can include the controller 115 increasing the reduced capacity limit by half of the tolerance range of the upper capacity tolerance limit. Otherwise (no at 530B3), as shown in block 530B5, the method can include the controller 115 decreasing the reduced capacity limit by half of the tolerance range of the lower capacity tolerance limit. At block 530B6, the method includes determining whether the boarding probability is within acceptable limits over time, such as hours or days (as non-limiting examples). If so (yes at 530B6), the controller 115 can return to block 540. Otherwise (no at 530B6), at block 530B7, the controller 115 can modify one or both of the capacity tolerance range (making it larger or smaller) and the reduced capacity limit (raising or lowering the limit).

[0056] In the above embodiments, the system 101 can utilize the actual available capacity in the elevator car 103 to determine a reduced capacity limit based on the number of passengers, cargo including luggage, time of day, season, geographic location, elevator usage, and so forth. This reduced capacity limit should avoid situations where passengers avoid entering the elevator at a certain landing because the elevator is perceived to be overly crowded. Thus, the system 101 can utilize various types of information to learn a reduced capacity limit that varies culturally, geographically, and due to the usage of the building, even for the same size elevator car 103 located elsewhere. For example, passengers in one geographic location, such as a crowded city or a densely populated university, can accept more densely crowded elevator cars, while those in more rural areas or hospitals can expect less crowded elevator cars. In addition to measuring the volume inside the car or passenger count to learn a reduced capacity limit, the system 101 can utilize sensors to detect when passengers in the corridor (or landing) decide not to board the elevator car 103. When passengers do not enter, an actual upper limit on capacity can be determined that can be less than a predetermined or preprogrammed capacity limit.

[0057] The reduced capacity (e.g., actual capacity) limit can also be determined by detecting and accounting for occupant types based on wider safety distances, such as robots, handicapped persons, or persons with support machinery. For example, certain groups of passengers can be more or less comfortable with robots in the elevator as a cleaning implementation or otherwise. The capacity limit can be based on the time of day, for example, people can be more willing to crowd into the elevator during peak hours in an office building. As a further practical example, the load-based capacity limit can be different during a winter peak due to the size of bulky clothing than during a summer peak. Thus, over crowding can occur due to the lesser weight of the load. In such a situation, when for example the car arrives at a floor call and no one boards even though the elevator load is below the predetermined capacity limit, the system can learn to reduce the overloading weight. The system can then adjust the capacity limit to for example a fractional percentage of the reduced capacity limit, such as ninety percent, to proceed under the same conditions including time of day, season, geographic location, and elevator usage type, such as an office building. The elevator car 103 can thereafter intentionally not respond to floor calls when the same conditions are met and the capacity is at or above the reduced capacity limit. More specifically, in such a situation, the system can transmit a "full" or "non-stop" signal to the controller 115 for the elevator car even though the actual weight in the elevator is less than the design capacity limit for the load.

[0058] The system 101 can utilize this information to learn effective full load limits that can be specific to a given building, and can adapt to changes in the amount of space occupied due to each call. The embodiments above can improve dispatch performance by maximizing utilization without assigning passengers to elevator cars 103 that can be perceived by the passengers as too full.

[0059] The sensor data identified herein can be obtained and processed individually or simultaneously and stitched together or combined, and can be processed in raw or compiled form. The sensor data can be processed on the sensor (e.g., via edge computing), by a controller identified or implicated herein, on a cloud service, or by a combination of one or more of these computing systems. The sensors can deliver data via wired or wireless transmission lines, applying one or more protocols as indicated below.

[0060] Wireless connections can apply protocols including Local Area Network (LAN or WLAN for wireless LAN) protocols. LAN protocols include WiFi technology based on the Institute of Electrical and Electronics Engineers (IEEE) Section 802.11 standard. Other applicable protocols include Low-Power WAN (LPWAN), which is a wireless wide area network (WAN) designed to allow long-range communication at a low bit rate to enable terminal devices to operate using battery power for extended periods (years). Long-Range WAN (LoRaWAN) is a type of LPWAN maintained by the LoRa Alliance, and is a Medium Access Control (MAC) layer protocol for transferring management messages and application messages between a network server and an application server, respectively. LAN and WAN protocols can generally be considered TCP / IP protocols (Transmission Control Protocol / Internet Protocol) for managing a computer system’s connection to the Internet. Wireless connections can also apply protocols including Personal Area Network (PAN) protocols. PAN protocols include, for example, Bluetooth Low Energy (BTLE), which is a wireless technology standard designed and marketed by the Bluetooth Special Interest Group (SIG) for exchanging data over short distances using short-wavelength radio waves. PAN protocols also include Zigbee, which is a technology based on the IEEE Section 802.15.4 protocol representing a suite of high-level communication protocols for creating personal area networks with small, low-power digital wireless radios for low-power low-bandwidth needs. Such protocols also include Z-Wave, which is a wireless communication protocol supported by the Z-Wave Alliance that uses mesh networking, applying low-power radio waves to communication between devices such as electrical appliances, allowing for wireless control of the devices.

[0061] Wireless connections can also include Radio Frequency Identification (RFID) technology for communicating with an integrated chip (IC) on, for example, an RFID smart card. Additionally, Sub-1 Ghz RF devices operate in the ISM (Industrial, Scientific, and Medical) band below Sub 1 Ghz (typically in the 769-935 MHz, 315 Mhz, and 468 Mhz frequency ranges). This band below 1 Ghz is particularly useful for RF IOT (Internet of Things) applications. The Internet of Things (IoT) describes a network of physical objects ("things") embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the Internet. Other LPWAN-IOT technologies include Narrow Band Internet of Things (NB-IOT) and Category M1 Internet of Things (Cat M1-IOT). Wireless communication for the disclosed system can include cellular, such as 2G / 3G / 4G (and so on). Other wireless platforms based on RFID technology include Near Field Communication (NFC), which is a set of communication protocols for low-speed communications, such as exchanging small amounts of data between electronic devices over a short distance. NFC standards are defined by ISO / IEC (defined below), the NFC Forum, and the GSMA (Global System for Mobile Communications) group. The above are not intended to limit the scope of wireless technologies that can be applicable.

[0062] The wired connection can include a connection (cable / interface) according to RS (Recommended Standard)-422 (also known as TIA / EIA-422), which is a technical standard supported by the Telecommunications Industry Association (TIA) and created by the Electronic Industries Alliance (EIA) that specifies electrical characteristics of digital signaling circuits. The wired connection can also include a connection (cable / interface) according to the RS-232 standard for serial communication transmission of data, which is formally defined between a DTE (Data Terminal Equipment) such as a computer terminal and a DCE (Data Circuit-terminating Equipment or Data Communications Equipment) such as a modem. The wired connection can also include a connection (cable / interface) according to the Modbus serial communication protocol managed by the Modbus Organization. Modbus is a master / slave protocol designed for use with its programmable logic controllers (PLCs) and is a commonly available means of connecting industrial electronics. The wireless connection can also include a connector (cable / interface) according to the PROFiBUS (Process Field Bus) standard managed by the PROFIBUS & PROFINET International (PI). The PROFiBUS, as a standard for fieldbus communication in automation technology, is published as part of IEC (International Electrotechnical Commission) 61158. The wired communication can also be over a Controller Area Network (CAN) bus. CAN is a vehicle bus standard allowing microcontrollers and devices to communicate with each other in applications without a host computer. CAN is a message-based protocol published by the International Organization for Standardization (ISO). The above is not intended to limit the scope of applicable wired technologies.

[0063] When data is transmitted between terminal processors as identified herein over a network, the data can be transmitted in raw form or can be processed in whole or in part at any of the terminal processors or intermediate processors (e.g., at a cloud service (e.g., where at least a portion of the transmission path is wireless) or other processor). The data can be parsed, partially or completely processed or compiled at any of the processors, and then can be spliced together or maintained as separate packets of information. Each processor or controller identified herein can be, but is not limited to, a single- or multi-processor system of any of a wide range of possible architectures, including graphics processing unit (GPU) hardware, digital signal processors (DSPs), application-specific integrated circuits (ASICs), central processing units (CPUs), or field programmable gate arrays (FPGAs) arranged homogenously or heterogeneously. The memory identified herein can be, but is not limited to, random access memory (RAM), read only memory (ROM), or other electronic, optical, magnetic or any other computer readable medium.

[0064] In addition to the processor and the non-volatile memory, the controller can also include one or more input and / or output (I / O) device interfaces communicatively coupled via an on-board (local) interface to communicate among other devices. The on-board interface can include, for example, but is not limited to, an on-board system bus including a control bus (for inter-device communication), an address bus (for physical addressing), and a data bus (for transferring data). That is, the system bus can enable electronic communication between the processor, the memory, and the I / O connections. The I / O connections can also include wired and / or wireless connections identified herein. The on-board interface can have additional elements, such as controllers, buffers (caches), drivers, repeaters, and receivers, to enable electronic communication, which are omitted for the sake of brevity. The memory can execute a program, access data, or look up a table or combination of each to facilitate its processing, all of which can be pre-stored or received from other computing devices, such as via cloud services or other network connections identified herein, during execution of its processes.

[0065] Embodiments can be in the form of processable procedures implemented by a processor and devices for practicing those procedures such as a processor. Embodiments can also be in the form of modules of computer code, for example, computer program code (e.g., a computer program product) containing instructions embodied in tangible media (e.g., non-transitory computer-readable media such as floppy diskettes, CD ROMs, hard drives, registers of a processor as firmware, or any other non-transitory computer-readable medium), wherein when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing the embodiment. Embodiments can also be in the form of computer program code, for example, whether stored in a storage medium, loaded into and / or executed by a computer, or transmitted over some transmission medium, whether by electrical wiring or cable, through optical fiber, or via electromagnetic radiation, wherein when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing exemplary embodiments. When implemented on a general-purpose microprocessor, the computer program code segments configure the microprocessor to create specific logic circuits.

[0066] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0067] Those skilled in the art will realize that the various example embodiments described herein are each capable of having some features replaced by other features, each described embodiment having certain features in common but differing in other features. Furthermore, to those skilled in the art will appreciate that the present disclosure is capable of being practiced by employing a variety of computer systems and components, software programs, and / or equipment. It is therefore intended that the disclosure not be limited to the described embodiments and / or configurations, but rather that the disclosure is to cover all modifications and variations of this disclosure provided they come within the scope of the appended claims and their equivalents.

Claims

1. An elevator system, comprising: Controller; An elevator car, which is operatively connected to the controller; A first sensor is configured to provide first sensor data to the controller, wherein the controller is configured to identify capacity parameters of the elevator car based on the first sensor data, wherein the capacity parameters include one or more of the following: the weight carried; the volume of available space; or the volume of occupied space; A second sensor is configured to provide second sensor data to the controller, wherein the controller is configured to determine, based on the second sensor data, that when the elevator car stops at a landing and its doors are open, the passenger is still outside the elevator car. as well as Specifically, based on the first sensor data and the second sensor data, the controller is configured to determine the reduced capacity limit of the elevator car as a function of the capacity parameter. When the reduced capacity limit is determined, the controller is configured to: As the elevator car approaches its design capacity limit or a predetermined reduced capacity limit, data related to passengers entering the elevator in response to a lobby call is accumulated; The reduced capacity limit is set to be related to a predetermined probability of boarding, and the tolerance range is set around the reduced capacity limit; Determine whether the probability of taking the ride is within an acceptable limit over time; and When it is determined that the probability of taking a ride is outside an acceptable limit over time, one or both of the tolerance range and the reduced capacity limit are modified.

2. The system of claim 1, wherein, The controller, the first sensor, and the second sensor are configured to communicate with each other via a wireless network.

3. The system according to claim 1, wherein: The controller is configured to determine the reduced capacity limit by applying a pre-determined multiplier to the capacity parameter.

4. The system according to claim 1, wherein: The capacity parameters also include time of day, season, geographical location, occupancy type, and one or more of the building's utilization; and The occupancy type is one or more of cargo, passengers, or robots.

5. The system according to claim 1, wherein: The controller is configured to control the elevator car to ignore service calls when the elevator car is at or above the reduced capacity limit.

6. The system according to claim 1, wherein: The first sensor is located on the elevator car and is configured to communicate with the controller directly or via a cloud service. The first sensor data is processed, in whole or in part, at one or more of the first sensor, the cloud service, and the controller.

7. The system according to claim 6, wherein: One or more of the passenger count, the volume of the available space, and the volume of the occupied space are derived from processing the first sensor data.

8. The system according to claim 6, wherein: The second sensor is located on the elevator car or at the landing; and The second sensor communicates with the controller directly or via the cloud service, and The second sensor data is processed, in whole or in part, at one or more of the second sensor, the cloud service, and the controller.

9. The system according to claim 8, wherein: The second sensor is a motion sensor or depth sensor located on the layer station.

10. The system according to claim 1, wherein: When the reduced capacity limit is determined, the controller is also configured to: Determine whether a passenger responds to a lobby call and enters the elevator car; and When it is determined that a passenger has entered the elevator car in response to a lobby call, the reduced capacity limit is increased by half the range of the upper capacity tolerance; otherwise, the reduced capacity limit is decreased by half the range of the lower capacity tolerance.

11. A method for controlling an elevator car of an elevator system using a controller, the controller being operatively connected to the elevator car, the method comprising: The controller identifies the capacity parameters of the elevator car based on first sensor data transmitted via a first sensor, wherein the capacity parameters include at least one of the following: the weight carried; the volume of available space; or the volume of occupied space; The controller determines, based on second sensor data transmitted via a second sensor, that when the elevator car stops at a landing and its doors open, the passengers are still outside the elevator car. as well as The controller determines, at its location, a reduced capacity limit for the elevator car as a function of the capacity parameter based on the first sensor data and the second sensor data, including: As the elevator car approaches its design capacity limit or a predetermined reduced capacity limit, data related to passengers entering the elevator car in response to a lobby call is accumulated. The reduced capacity limit is set to be related to a predetermined probability of boarding, and the tolerance range is set around the reduced capacity limit; Determine whether the probability of taking the ride is within an acceptable limit over time; and When it is determined that the probability of taking a ride is outside an acceptable limit over time, one or both of the tolerance range and the reduced capacity limit are modified.

12. The method according to claim 11, wherein: The controller, the first sensor, and the second sensor communicate with each other via a wireless network.

13. The method according to claim 11, wherein: Determining the reduced capacity limit involves applying a pre-determined multiplier to the capacity parameter.

14. The method of claim 11, wherein: The capacity parameters also include time of day, season, geographical location, occupancy type, and one or more of the building's utilization; and The occupancy type is one or more of cargo, passengers, and robots.

15. The method of claim 11, further comprising: When the elevator car is at or above the reduced capacity limit, the controller controls the elevator car to ignore service calls.

16. The method of claim 11, wherein: The first sensor is located on the elevator car; The method includes: The controller communicates directly with the first sensor or via a cloud service, and The data from the first sensor is processed, in whole or in part, at one or more of the first sensor, the cloud service, and the controller.

17. The method of claim 16, further comprising: Based on the data from the first sensor, one or more of the following can be determined: passenger count, volume of available space, and volume of occupied space.

18. The method of claim 16, wherein: The second sensor is located on the elevator car or at the landing. as well as The method further includes: The second sensor communicates directly with the controller or via the cloud service, and The second sensor data is processed, in whole or in part, at one or more of the second sensor, the cloud service, and the controller.

19. The method of claim 18, wherein: The second sensor includes a motion sensor or a depth sensor located on the layer station.

20. The method of claim 11, wherein: When determining the reduced capacity limit, the method includes the controller: Determine whether a passenger responds to a lobby call and enters the elevator car; as well as When it is determined that a passenger has entered the elevator car in response to a lobby call, the reduced capacity limit is increased by half the range of the upper capacity tolerance; otherwise, the reduced capacity limit is decreased by half the range of the lower capacity tolerance.

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