Automatic detection for abnormal movement of passenger in elevator

A movement detection system for a passenger in the present invention includes: a first Bluetooth module (150) mounted in an elevator landing area; and a movement prediction unit (270) configured to predict, based on Bluetooth movement data, that a movement of a passenger in the elevator landing area is a normal movement or an abnormal movement. The movement detection system and a movement detection method in the present invention can automatically detect an abnormal movement of a passenger, and are especially applicable to an elevator system that completes an elevator call operation without an input operation.

TECHNICAL FIELD

The present invention belongs to the technical field of intelligent Elevator control, and relates to a movement detection system and method for a passenger, and an elevator system using the movement detection system.

BACKGROUND ART

As elevator technologies develop, various automatic elevator call technologies in which a passenger does not need to perform an input operation have emerged. For example, an elevator system may automatically send an elevator call request command to the elevator system according to a movement of the passenger. However, because of the uncertainties of movements of the passenger with respect to an elevator car, an invalid elevator call request command is easily generated. For example, a passenger passes an elevator landing area but does not intend to enter an elevator car to take an elevator. Such a movement easily leads to the generation of an invalid elevator call request command.

SUMMARY OF THE INVENTION

According to a first aspect of the present invention, a movement detection system for a passenger is provided, including: a first Bluetooth module mounted in an elevator landing area and configured to broadcast a first Bluetooth signal to the elevator landing area, wherein

the movement detection system receives the first Bluetooth signal by a personal mobile terminal carried by the passenger, and generates Bluetooth movement data corresponding to a movement of the passenger in the elevator landing area; and

the movement detection system further includes:

a movement prediction unit configured to predict, based on the Bluetooth movement data, that the movement of the passenger in the elevator landing area is a normal movement or an abnormal movement.

In the movement detection system according to an embodiment of the present invention, the movement prediction unit is further configured to predict, based on the Bluetooth movement data and historical Bluetooth data, that the movement of the passenger in the elevator landing area is a normal movement or an abnormal movement, wherein the historical Bluetooth movement data includes historical Bluetooth movement data corresponding to the normal movement and/or abnormal movement.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the historical Bluetooth data is historical Bluetooth data corresponding to the passenger.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection system further includes:

a personal movement historical database, disposed corresponding to the personal mobile terminal, and storing historical Bluetooth movement data corresponding to the passenger.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection system tracks the corresponding movement of the passenger in the elevator landing area based on Bluetooth interaction between the personal mobile terminal and the first Bluetooth module, so as to generate the Bluetooth movement data corresponding to the movement.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection system further includes: a machine learning unit configured to learn and acquire a normal movement mode from historical Bluetooth movement data corresponding to the normal movement, and/or configured to learn and acquire an abnormal movement mode from historical Bluetooth movement data corresponding to the abnormal movement.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection system further includes: a machine learning unit configured to learn and acquire a normal movement mode of the passenger from historical Bluetooth movement data corresponding to the normal movement of the passenger, and/or configured to learn and acquire an abnormal movement mode of the passenger from historical Bluetooth movement data corresponding to the abnormal movement of the passenger.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement prediction unit is further configured to predict, based on the generated Bluetooth movement data and the normal movement mode and/or abnormal movement mode, that the movement of the passenger in the elevator landing area is a normal movement or an abnormal movement.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection system further includes a signal strength determination module and a movement tracking module that are disposed in the personal mobile terminal, wherein

the signal strength determination module is configured to determine the signal strength of the first Bluetooth signal received by the personal mobile terminal; and

the movement tracking module is configured to track the movement of the passenger in the elevator landing area by means of changes in the determined signal strength of the first Bluetooth signal, and generate the Bluetooth movement data corresponding to the movement.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement tracking module is further configured to analyze a change direction of the signal strength of the first Bluetooth signal, and track a movement direction of the passenger with respect to the first Bluetooth module in the elevator landing area based on the change direction.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement tracking module is further configured to analyze a change magnitude of the signal strength of the first Bluetooth signal, and track a movement distance of the passenger with respect to the first Bluetooth module in the elevator landing area based on the change magnitude.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection system further includes a second Bluetooth module mounted in an elevator car and configured to broadcast a second Bluetooth signal to the interior of the elevator car, wherein

the movement detection system further includes a movement judgment module disposed in the personal mobile terminal, the movement judgment module being configured to judge, according to whether the personal mobile terminal successfully receives the second Bluetooth signal, whether the tracked movement is a normal movement or an abnormal movement.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement judgment module is further configured to:

judge that the tracked movement is a normal movement if the personal mobile terminal successfully receives the second Bluetooth signal whose signal strength is greater than or equal to a predetermined value; and/or

judge that the tracked movement is an abnormal movement if the personal mobile terminal does not receive the second Bluetooth signal within a predetermined time period after sending an elevator call request command or does not receive the second Bluetooth signal whose signal strength is greater than or equal to a predetermined value.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the Bluetooth movement data corresponding to the normal movement or the abnormal movement of the passenger is stored respectively in a normal movement historical database or an abnormal movement historical database of the personal movement historical database.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the second Bluetooth module and/or an elevator controller of an elevator system is further configured to receive the judgment result for the tracked movement.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement prediction unit is further configured to transmit the result about the movement predicted by the movement prediction unit to at least one of the personal mobile terminal, the first Bluetooth module, and an elevator controller of an elevator system.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection system is further configured to: if the movement of the passenger in the elevator landing area is predicted to be an abnormal movement, skip automatically sending an elevator call request command or cancel an elevator call request command sent corresponding to the movement.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection system is further configured to provide the signal strength distribution diagram of the first Bluetooth signal of each elevator landing area to the personal mobile terminal.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, at least one of the personal movement historical database, the machine learning unit, and the movement prediction unit of the movement detection system is disposed in the personal mobile terminal.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection system further includes a server configured to implement one or more of the personal movement historical database, the machine learning unit, and the movement prediction unit of the movement detection system.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, one or more of the personal movement historical database, the machine learning unit, and the movement prediction unit of the movement detection system are implemented in a cloud.

In the movement detection system according to another embodiment of the present invention or any embodiment in the foregoing, the second Bluetooth module is a Bluetooth Low Energy (BLE) module, and the second Bluetooth signal is a BLE signal; and/or

the first Bluetooth module is a BLE module, and the first Bluetooth signal is a BLE signal.

According to a second aspect of the present invention, a movement detection method for a passenger is provided, including steps of:

receiving, by a personal mobile terminal carried by the passenger, a first Bluetooth signal broadcasted by a first Bluetooth module mounted in an elevator landing area;

generating Bluetooth movement data corresponding to a movement of the passenger in the elevator landing area; and

predicting, based on the Bluetooth movement data, that the movement of the passenger in the elevator landing area is a normal movement or an abnormal movement.

In the movement detection method according to an embodiment of the present invention, the step of predicting the movement includes: predicting, based on historical Bluetooth data of the generated Bluetooth movement data, that the movement of the passenger in the elevator landing area is a normal movement or an abnormal movement, wherein the historical Bluetooth movement data includes historical Bluetooth movement data corresponding to the normal movement and/or abnormal movement.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the historical Bluetooth data is historical Bluetooth data corresponding to the passenger.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the step of generating Bluetooth movement data includes: tracking the corresponding movement of the passenger in the elevator landing area based on Bluetooth interaction between the personal mobile terminal and the first Bluetooth module, thereby generating the Bluetooth movement data corresponding to the movement.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection method further includes a machine learning step: learning and acquiring a normal movement mode from historical Bluetooth movement data corresponding to the normal movement, and/or learning and acquiring an abnormal movement mode from historical Bluetooth movement data corresponding to the abnormal movement.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection method further includes a machine learning step: learning and acquiring a normal movement mode of the passenger from historical Bluetooth movement data corresponding to the normal movement of the passenger, and/or learning and acquiring an abnormal movement mode of the passenger from historical Bluetooth movement data corresponding to the abnormal movement of the passenger.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the step of predicting the movement includes: further predicting, based on the normal movement mode and/or abnormal movement mode corresponding to the passenger, that the movement is a normal movement or an abnormal movement.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection method further includes steps of:

determining the signal strength of the first Bluetooth signal received by the personal mobile terminal; and

tracking the movement of the passenger in the elevator landing area by means of changes in the determined signal strength of the first Bluetooth signal.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the step of tracking the movement of the passenger in the elevator landing area includes:

analyzing a change direction of the signal strength of the first Bluetooth signal, and tracking a movement direction of the passenger with respect to the first Bluetooth module in the elevator landing area based on the change direction.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the step of tracking the movement of the passenger in the elevator landing area includes:

analyzing a change magnitude of the signal strength of the first Bluetooth signal, and tracking a movement distance of the passenger with respect to the first Bluetooth module in the elevator landing area based on the change magnitude.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection method further includes steps:

receiving a second Bluetooth signal broadcasted by a second Bluetooth module mounted in an elevator car; and

judging, according to whether the personal mobile terminal successfully receives the second Bluetooth signal, whether the tracked movement is correspondingly a normal movement or an abnormal movement.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the step of judging the tracked movement includes:

judging that the tracked movement is a normal movement if the personal mobile terminal successfully receives the second Bluetooth signal whose signal strength is greater than or equal to a predetermined value; and/or

judging that the tracked movement is an abnormal movement if the personal mobile terminal does not receive the second Bluetooth signal within a predetermined time period after sending an elevator call request command or does not receive the second Bluetooth signal whose signal strength is greater than or equal to a predetermined value.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the Bluetooth movement data corresponding to the normal movement or the abnormal movement of the passenger is stored respectively in a normal movement historical database or an abnormal movement historical database of a personal movement historical database.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection method further includes a step of: receiving, by the second Bluetooth module and/or an elevator controller of an elevator system, the judgment result for the tracked movement.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection method further includes a step of: transmitting the prediction result about the movement to at least one of the personal mobile terminal, the first Bluetooth module, and an elevator controller of an elevator system.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the movement detection method further includes a step of: if the movement of the passenger in the elevator landing area is predicted to be an abnormal movement, skipping automatically sending an elevator call request command or cancelling an elevator call request command sent corresponding to the movement.

In the movement detection method according to another embodiment of the present invention or any embodiment in the foregoing, the signal strength distribution diagram of the first Bluetooth signal of each elevator landing area is provided to the personal mobile terminal.

According to a third aspect of the present invention, a personal mobile terminal is provided, including:

a Bluetooth interaction unit configured to enable a personal mobile terminal carried by a passenger who moves in an elevator landing area to receive a first Bluetooth signal broadcasted by a first Bluetooth module mounted in the elevator landing area, and generate corresponding Bluetooth movement data; and

a movement prediction unit configured to predict, based on the Bluetooth movement data, that a movement of the passenger in the elevator landing area is a normal movement or an abnormal movement.

In the personal mobile terminal according to an embodiment of the present invention, the movement prediction unit is further configured to predict, based on the Bluetooth movement data and historical Bluetooth movement data of the passenger, that the movement of the passenger in the elevator landing area is a normal movement or an abnormal movement, where the historical Bluetooth movement data includes historical Bluetooth movement data corresponding to the normal movement and/or abnormal movement of the passenger.

In the personal mobile terminal according to an embodiment of the present invention, a corresponding personal movement historical database is disposed in the personal mobile terminal, and stores the historical Bluetooth movement data corresponding to the passenger.

In the personal mobile terminal according to an embodiment of the present invention, the movement prediction unit is further configured to track the corresponding movement of the passenger in the elevator landing area based on Bluetooth interaction between the personal mobile terminal and the first Bluetooth module, so as to generate the Bluetooth movement data corresponding to the movement.

In the personal mobile terminal according to an embodiment of the present invention, the personal mobile terminal further includes: a machine learning unit configured to learn and acquire a corresponding normal movement mode of the passenger from historical Bluetooth movement data corresponding to the normal movement, and/or configured to learn and acquire a corresponding abnormal movement mode of the passenger from historical Bluetooth movement data corresponding to the abnormal movement.

In the personal mobile terminal according to an embodiment of the present invention, the movement prediction unit is further configured to predict, based on the generated Bluetooth movement data and the normal movement mode and/or abnormal movement mode of the passenger, that the movement of the passenger in the elevator landing area is a normal movement or an abnormal movement.

In the personal mobile terminal according to an embodiment of the present invention, the personal mobile terminal further includes:

a signal strength determination module configured to determine the signal strength of the first Bluetooth signal received by the personal mobile terminal; and

a movement tracking module configured to track the movement of the passenger in the elevator landing area based on changes in the determined signal strength of the first Bluetooth signal, and generate the Bluetooth movement data corresponding to the movement.

In the personal mobile terminal according to an embodiment of the present invention, the movement tracking module is further configured to analyze a change direction of the signal strength of the first Bluetooth signal, and track a movement direction of the passenger with respect to the first Bluetooth module in the elevator landing area based on the change direction.

In the personal mobile terminal according to an embodiment of the present invention, the movement tracking module is further configured to analyze a change magnitude of the signal strength of the first Bluetooth signal, and track a movement distance of the passenger with respect to the first Bluetooth module in the elevator landing area based on the change magnitude.

According to a fourth aspect of the present invention, an elevator system is provided, including an elevator car, an elevator controller, and any movement detection system in the foregoing, wherein

the first Bluetooth module is further configured to receive an elevator call request command sent from the personal mobile terminal.

In the elevator system according to an embodiment of the present invention, the elevator controller or the first Bluetooth module is configured to: if a movement of the passenger in the elevator landing area is predicted to be an abnormal movement, ignore or cancel the elevator call request command sent by the personal mobile terminal corresponding to the movement.

In the elevator system according to an embodiment of the present invention, the first Bluetooth module is further configured to receive the result about the movement predicted by the movement prediction unit.

According to a fifth aspect of the present invention, a personal mobile terminal is provided, including a memory, a processor, and a computer program stored in the memory and operable on the processor, wherein the processor, when executing the program, implements the steps in any method in the second aspect of the present invention.

According to a sixth aspect of the present invention, a computer readable storage medium storing a computer program is provided. The program can be executed by a processor to implement the steps in any method in the second aspect of the present invention.

The foregoing features and operations of the present invention will become more obvious according to the following descriptions and the accompanying drawings.

DETAILED DESCRIPTION

The present invention is described here more completely with reference to the accompanying drawings. Exemplary embodiments of the present invention are shown in the accompanying drawings. However, the present invention may be implemented in many different forms, and such forms should not be construed as being limited to the embodiments described here. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete and completely convey the concept of the present invention to those skilled in the art.

The features of the present invention are disclosed with reference to only one of several implementations/embodiments. However, provided that any given or recognizable function may be expected and/or beneficial, this feature may be combined with one or more other features in other implementations/embodiments

Some of the block diagrams shown in the accompanying drawings are functional entities, and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in the form of software. Alternatively, these functional entities are implemented in one or more hardware modules or integrated circuits. Alternatively, these functional entities are implemented in different processing apparatuses and/or microcontroller apparatuses.

Herein, a “normal movement” is at least one movement of a passenger with respect to an elevator car in order to take an elevator. In contrast, an “abnormal movement” is a movement of a passenger near an elevator car while the passenger does not intend to take an elevator. The “normal movement” and the “abnormal movement” may both include a movement process of approaching the elevator car. However, in the present application, a movement of approaching the elevator car does not necessarily means it is a “normal movement”.

FIG.1is a schematic diagram of an elevator system according to an embodiment of the present invention, and at the same time schematically shows a movement detection system for a passenger according to an embodiment.FIG.2is a schematic diagram of a modular structure when at least a part of the movement detection system shown inFIG.1is implemented by using a personal mobile terminal according to an embodiment. An elevator system10and the movement detection system in the embodiment of the present invention are described below with reference toFIG.1toFIG.3.

In the elevator system10shown inFIG.1, two elevator cars110-1and110-2are shown. It should be understood that the quantity of elevator cars110in the elevator system10is not limited. Each elevator car110can run vertically in a shaft in a building, so as to transport a passenger to a corresponding destination floor. It should be understood that the settings of the elevator cars110-1and110-2may be similarly applied to elevator cars of the elevator system10.

The movement detection system in an embodiment includes a second Bluetooth module130disposed in each elevator car110. For example, the second Bluetooth module130-1is disposed in the elevator car110-1, and the second Bluetooth module130-2is disposed in the elevator car110-2. Each second Bluetooth module130may be a Bluetooth beacon or a Bluetooth node, and can establish a communication connection with an elevator controller500in the elevator system10in which the elevator car110is located. In an embodiment, the second Bluetooth module130in the elevator car110may be, but not limited to, mounted on a destination floor registration control panel in the elevator car110or integrally disposed on the destination floor registration control panel. It should be understood that a mounting location of the second Bluetooth module130in the elevator car110is not limited thereto.

The second Bluetooth module130in each elevator car110can broadcast a second Bluetooth signal131that basically covers the interior of the elevator car110. In an embodiment, the second Bluetooth module130may continuously broadcast the second Bluetooth signal131to the interior of the elevator car110during the operation of the elevator car110. In another embodiment, the second Bluetooth module130may broadcast the second Bluetooth signal131to the interior of the elevator car110only when the elevator car110stops at a floor. The broadcasted second Bluetooth signal131may include current floor information, for example, a floor N, of the elevator car110. The broadcasted second Bluetooth signal131may further include universally unique identifier (UUID) information of the second Bluetooth module130.

The second Bluetooth module130can interact, by using the second Bluetooth signal131, with a personal mobile terminal200carried by a passenger90inside the elevator car110. During application, once the passenger90enters the elevator car110to take an elevator, the personal mobile terminal200first receives the second Bluetooth signal131, and may identify the second Bluetooth signal131according to the UUID of the second Bluetooth signal131. Moreover, the personal mobile terminal200may further determine, by identifying the second Bluetooth signal131, a floor from which the passenger90enters the elevator car110. Specifically, if a car door113is opened, the second Bluetooth module130may sequentially establish a second Bluetooth connection with a personal mobile terminal200of each passenger90who enters the elevator car110, and perform communication based on a preset Bluetooth communication protocol. Once it is determined that a personal mobile terminal200successfully receives the second Bluetooth signal131broadcasted by the second Bluetooth module130or determined that a personal mobile terminal200has successfully established a second Bluetooth connection with the second Bluetooth module130, the personal mobile terminal200or the second Bluetooth module130may determine that a passenger90corresponding to the personal mobile terminal200enters a corresponding elevator car110from an elevator landing area410.

As shown inFIG.1, the movement detection system in the elevator system10further includes a first Bluetooth module150. The first Bluetooth module150is mounted in an elevator landing area410, and may broadcast a first Bluetooth signal151to the elevator landing area410, so as to basically cover the elevator landing area410. In one case, the first Bluetooth signal151broadcasted by the first Bluetooth module150may further cover another adjacent area outside the elevator landing area410. A personal mobile terminal200of a passenger90in the elevator landing area410or the adjacent area may receive the first Bluetooth signal151. The first Bluetooth signal151may include floor information, for example, a floor N, of the elevator landing area410in which the first Bluetooth module150is located; and/or may include UUID information corresponding to the first Bluetooth module150. Therefore, when receiving the first Bluetooth signal151, the personal mobile terminal200can recognize the first Bluetooth signal and can determine a floor on which the first Bluetooth signal151is located.

The elevator landing area410may be, for example, a lobby. It should be noted that the shape and size of a specific area of the elevator landing area410may be determined according to the structure of a building, and its range may be not clearly defined as done by dotted lines shown inFIG.1. The dotted lines inFIG.1only schematically define the elevator landing area410. The boundary of the elevator landing area410may be relatively blurred. In the example inFIG.1, passageways411and412are provided in the example of the elevator landing area410. A passenger90may enter or leave the elevator landing area410through the passageways.

In an embodiment, some of the functions of the movement detection system in the elevator system10may be implemented by at least partially using the personal mobile terminal200carried by the passenger90, for example, may be partially implemented by using the personal mobile terminal200shown inFIG.2. A Bluetooth communication module210is disposed in the personal mobile terminal200carried by the passenger90, and is configured with a corresponding Bluetooth communication protocol. As such, the Bluetooth communication module210is suitable for receiving the second Bluetooth signal131or the first Bluetooth signal151and is suitable for establishing a second Bluetooth connection with the second Bluetooth module130or a first Bluetooth connection with the first Bluetooth module150.

The second Bluetooth module130or the first Bluetooth module150may be specifically a BLE module, and the second Bluetooth signal131broadcasted by the second Bluetooth module130or the first Bluetooth signal151broadcasted by the first Bluetooth module150is a correspondingly a BLE signal. The personal mobile terminal200is correspondingly a terminal that can adapt to BLE communication, for example, may be implemented by using a smart phone, a wearable smart device, a personal digital assistant (PAD) or the like (a Bluetooth communication module disposed in the terminal is a BLE module). As such, the Bluetooth communication interaction manner between the second Bluetooth module130or first Bluetooth module150and the personal mobile terminal200has low energy consumption.

It should be noted that specific signal forms of the second Bluetooth signal131and the first Bluetooth signal132are not limited. Generally, the second Bluetooth signal131and the first Bluetooth signal132have a characteristic that signal strengths of the signals attenuate as propagation distances of the signals increase. Therefore, especially for a personal mobile terminal200that receives the first Bluetooth signal, a distance between the personal mobile terminal200and the first Bluetooth module150may be approximately determined according to the signal strength of the first Bluetooth signal.

Correspondingly, during the interaction between each personal mobile terminal200and the second Bluetooth signal131or first Bluetooth signal151, each personal mobile terminal200can determine the signal strength of the second Bluetooth signal131or first Bluetooth signal151received by the personal mobile terminal200. In an embodiment, as shown inFIG.2, a signal strength determination module220in the personal mobile terminal200can determine, based on the first Bluetooth signal151, the signal strength of the first Bluetooth signal151received by the personal mobile terminal200, and certainly can also determine the signal strength of the second Bluetooth signal131received by the personal mobile terminal200. Specifically, the signal strength determination module220is implemented by using a received signal strength indicator (RSSI). The RSSI can determine the signal strength of the first Bluetooth signal151or any another Bluetooth signal received by the personal mobile terminal200.

In a movement process in which a passenger90approaches an elevator car130, a second Bluetooth signal131is generally received first. As a distance from the elevator car130decreases, a distance from a first Bluetooth module150also decreases approximately. Therefore, the signal strength of a received first Bluetooth signal151approximately grows gradually.

As shown inFIG.2, a movement tracking module230is further disposed in each personal mobile terminal200, and is configured to track a movement of the passenger90in the elevator landing area410by means of changes in the determined signal strength of the first Bluetooth signal151.

Referring toFIG.3,FIG.3exemplarily shows signal strength distribution of the first Bluetooth signal151broadcasted by the first Bluetooth module150in the elevator landing area410. The signal strength is represented by using grayscale. If the passenger90moves in the elevator landing area410, the signal strength at each movement point may be detected. According to signal strength data of all movement points, a movement path of a passenger90in the elevator landing area410may be approximately tracked. In an embodiment, the signal strength distribution diagram of the first Bluetooth signal151of the elevator landing area410may be stored in advance in the personal mobile terminal200. For example, the movement detection system is used to provide the signal strength distribution diagram to the personal mobile terminal200. A dotted-line movement path shown inFIG.3is used as an example. The passenger90first approaches the first Bluetooth module150and then leaves the first Bluetooth module150. The received signal strength of the personal mobile terminal200first approximately increases gradually, and then approximately decreases gradually. According to analysis of a change direction (for example, the signal strength increases or decreases) of the signal strength data, it may be tracked that the movement of the passenger90is correspondingly approaching the first Bluetooth module150first and then leaving the first Bluetooth module150. The foregoing analysis may include change direction analysis of the signal strength and may further include change magnitude analysis of the signal strength. The change direction may track whether the movement is approaching or leaving the first Bluetooth module150, i.e., track a movement direction of the passenger90with respect to the first Bluetooth module150in the elevator landing area410. A change magnitude (that is, a change amount) may represent a movement distance, so that a movement distance of the passenger90with respect to the first Bluetooth module150in the elevator landing area410is tracked.

The movement tracking module230may further generate corresponding Bluetooth movement data for each tracked movement. For example, the Bluetooth movement data may be data represented in the form of the Bluetooth signal strength, and may be generated in combination with the foregoing signal strength distribution diagram. It should be understood that the Bluetooth movement data is generated by a moving personal mobile terminal200that performs Bluetooth interaction with the first Bluetooth module150. Changes in the data may approximately represent changes in a movement process. Therefore, the movement may be represented by using the Bluetooth movement data to a certain degree.

As shown inFIG.2, a movement judgment module240is further disposed in a personal mobile terminal200, and is configured to judge, according to whether each personal mobile terminal200successfully receives the second Bluetooth signal131, whether the tracked movement is correspondingly a normal movement or an abnormal movement. As discussed above, when the car door113is opened, if a movement of a passenger90before entering the elevator car110is a normal movement, the passenger90will generally enter the elevator car110. During judgment, once the passenger90receives the second Bluetooth signal131, it may be basically determined that the passenger90will enter the elevator car90to take an elevator. Therefore, it may be determined that the movement tracked before is correspondingly a normal movement. Otherwise, it may be determined that the movement tracked before is correspondingly an abnormal movement. For example, the movement of the passenger90is a movement (a movement920-2shown inFIG.1) passing the elevator landing area410, or a movement (a movement920-1shown inFIG.1) of entering the elevator landing area410and then leaving the elevator landing area410.

To judge more accurately whether the passenger90enters the elevator car90, the movement judgment module240further determines that the tracked movement is correspondingly a normal movement only when the personal mobile terminal200successfully receives the second Bluetooth signal whose signal strength is greater than or equal to a predetermined value131, or otherwise judges that the tracked movement is an abnormal movement. The reason is that a passenger90who is near the opened car door113but does not enter the elevator car110may receive the second Bluetooth signal131(broadcasted from the elevator car110) whose signal strength is relatively weak. By setting a predetermined value and judging whether the signal strength of the received second Bluetooth signal131is greater than or equal to the predetermined value, the accuracy of judgment can be improved. The predetermined value may be correspondingly a minimum value of the signal strength of the second Bluetooth signal131received by the passenger90inside the elevator car110, and may be tested and determined in advance. The signal strength of the received second Bluetooth signal131is further judged. If the signal strength is less than the predetermined value, it is determined that the passenger90does not enter the elevator car110, so that the movement tracked before is determined to be an abnormal movement.

In an embodiment, the movement judgment module240determines that the tracked movement is an abnormal movement if the personal mobile terminal200does not receive the second Bluetooth signal151within a predetermined time period after sending an elevator call request command or does not receive the second Bluetooth signal151whose signal strength is greater than or equal to a predetermined value.

In another embodiment, the movement judgment module240may determine whether the tracked movement is an abnormal movement or a normal movement in another manner, for example, through a manual input of the passenger90.

The judgment result obtained by the movement judgment module240of the personal mobile terminal200may be transmitted to the second Bluetooth module130by using the second Bluetooth connection between the personal mobile terminal200and the second Bluetooth module130, or may further be transmitted to the elevator controller500by using the second Bluetooth module130.

The Bluetooth communication module210, the signal strength determination module220, the movement tracking module230, and the movement judgment module240in the foregoing embodiment approximately form a Bluetooth interaction unit (not shown in the figure) in the personal mobile terminal200in this embodiment of the present invention.

As shown inFIG.2, in an embodiment, a personal movement historical database250may be disposed in the personal mobile terminal200. It should be understood that a corresponding personal movement historical database may be disposed for a historical movement corresponding to each passenger90. As such, Bluetooth movement data generated by a movement behavior of each passenger90is recorded and stored in the personal movement historical database250, to form historical Bluetooth movement data. A normal movement historical database or an abnormal movement historical database or both may be established in the personal movement historical database250. Bluetooth movement data corresponding to a normal movement of each personal mobile terminal200is stored in the normal movement historical database of the personal movement historical database250, and Bluetooth movement data corresponding to an abnormal movement of each personal mobile terminal200is stored in the abnormal movement historical database of the personal movement historical database250. As such, in a data learning process in a historical database, analysis can be accurately performed to obtain a normal movement mode or an abnormal movement mode.

As shown inFIG.2, in an embodiment, a machine learning unit260may be disposed in the personal mobile terminal200. The machine learning unit260performs learning analysis on historical data in the personal movement historical database250, so as to acquire a normal movement mode and/or an abnormal movement mode of a passenger. Based on the normal movement determined in the movement judgment module240, the normal movement mode of the passenger is learned and acquired from the normal movement historical database in the personal movement historical database250. Based on the abnormal movement determined in the movement judgment module240, the abnormal movement mode of the passenger is learned and acquired from the abnormal movement historical database in the personal movement historical database250.

Specific learning methods used by the machine learning unit260may be various machine learning classification technologies that exist or will emerge in the future, and are not limited. It should be understood that as the amount of data stored in the personal movement historical database250keeps increasing, an increasingly large amount of data in the normal movement historical database or the abnormal movement historical database is used for learning. The learning or training of the normal movement mode or the abnormal movement mode will become more accurate. Bluetooth movement data corresponding to each movement of approaching the elevator car110of each passenger90will be stored in the personal movement historical database250. Therefore, learning results may be continuously improved.

As shown inFIG.2, a movement prediction unit270may further be disposed in the personal mobile terminal200. The movement prediction unit270predicts, based on the Bluetooth movement data, that a movement of a passenger90in the elevator landing area is a normal movement or an abnormal movement, so that it may be known as soon as possible or known in time whether a current movement of the passenger90is a normal movement or an abnormal movement. In an embodiment, the movement prediction unit270may predict, based on the currently generated Bluetooth movement data and historical Bluetooth movement data, that the movement of the passenger90in the elevator landing area is a normal movement or an abnormal movement. For example, the currently generated Bluetooth movement data is compared with the historical Bluetooth movement data corresponding to a normal movement or an abnormal movement and analyzed, so as to predict the movement of the passenger90. If the historical Bluetooth movement data corresponds to the historical Bluetooth movement data of the passenger90, the movement of the passenger90may be predicted more accurately. For example, a success rate of predicting that the movement of the passenger90is an abnormal movement is improved.

It should be noted that the historical Bluetooth movement data used by the movement prediction unit270may be from the foregoing personal movement historical database250. Certainly, when the personal movement historical database250does not have historical Bluetooth movement data (for example, is used for the first time), the historical Bluetooth movement data may be set in advance in another manner. For example, the historical Bluetooth movement data is acquired in a manner such as downloading. Furthermore, historical Bluetooth movement data of a corresponding passenger90is acquired. Existing Bluetooth movement data corresponding to a normal movement and/or an abnormal movement is edited or categorized to form corresponding historical Bluetooth movement data.

In another embodiment, the movement prediction unit270may use the learning result of the machine learning unit260to predict a currently tracked movement, so as to predict more accurately that a current movement of the passenger90is a normal movement or an abnormal movement. Specifically, the personal mobile terminal200predicts the tracked movement based on the Bluetooth movement data received from the movement tracking module230and the normal movement mode and/or abnormal movement mode obtained through learning for the passenger90, for example, predicts that the tracked movement is a normal movement or an abnormal movement. Even if each passenger90has a different movement or behavior of approaching the elevator car110, as a normal movement mode or an abnormal movement mode are obtained through learning based on personalized historical data, the accuracy of prediction is high. Therefore, the movement detection system in the foregoing embodiment can automatically make an accurate prediction about a movement of each passenger90, but does need to wait till it is judged whether the passenger90enters the elevator car90or does not need to wait till the movement of the passenger90in the elevator landing area completely ends. Moreover, an abnormal movement of the passenger90can be automatically recognized.

It should be understood that the foregoing learning process is not limited to learning of historical Bluetooth movement data of a normal movement or an abnormal movement corresponding to the passenger to obtain a normal movement mode and/or an abnormal movement mode, and for example, may further perform learning according to historical Bluetooth movement data of normal movements or abnormal movements of other passengers to obtain a normal movement mode and/or an abnormal movement mode of a corresponding landing area.

It should be noted that as an increasingly large amount of Bluetooth movement data is generated, historical Bluetooth movement data of determined or judged normal movements or abnormal movements keeps growing. Therefore, a normal movement mode and/or an abnormal movement mode obtained through learning may become more accurate, and the accuracy of prediction is improved.

It should be noted that because a movement of a passenger90is a continuous process, tracking of the movement is also a continuous process. The tracked movement is continuously updated, and Bluetooth movement data corresponding to the tracked movement is continuously updated. It should be understood that as a movement takes place, the tracked movement is more complete, an amount of Bluetooth movement data for prediction corresponding to the movement increases, and the accuracy of prediction becomes higher. Therefore, in an embodiment, the prediction is a continuous process. For example, when a tracked movement corresponds to an initial movement, an amount of correspondingly generated Bluetooth movement data is relatively small, and the accuracy of prediction is relatively low. As the tracked movement continues, the accuracy of prediction may be higher. During prediction, the movement prediction unit270approximately calculates the accuracy of prediction at the same time, and outputs the prediction result when the accuracy is greater than or equal to a predetermined value.

The prediction result obtained by the movement prediction unit270of the personal mobile terminal200may be transmitted to the first Bluetooth module150by using a first Bluetooth connection between the personal mobile terminal200and the first Bluetooth module150, or may further be transmitted to the elevator controller500by using the first Bluetooth module150.

The prediction of the movement detection system in the foregoing embodiment for the movement of the passenger90is very meaningful, especially for the elevator system10that automatically implements an elevator call operation based on a movement of approaching the elevator car110of the passenger90.

The elevator system10that implements an input-free automatic elevator call operation at least based on the personal mobile terminal200and the first Bluetooth module150is used as an example. As shown inFIG.1, in a movement process in which the passenger90approaches the elevator car110, the first Bluetooth module150mounted in each elevator landing area410may implement Bluetooth interaction with the personal mobile terminal200carried by the passenger90, so as to implement the function of an automatic elevator call operation. Specifically, the first Bluetooth module150may continuously transmit or broadcast the first Bluetooth signal151. In the movement process in which the passenger90approaches the elevator car110, the personal mobile terminal200also approaches the first Bluetooth module150. Once the passenger90enters the elevator landing area410, the personal mobile terminal200may automatically establish a first Bluetooth connection with the first Bluetooth module150, so that the personal mobile terminal200automatically sends an elevator call request command to the first Bluetooth module150. The second Bluetooth module150receives the elevator call request command and automatically sends the elevator call request command to the elevator controller500connected to the second Bluetooth module150.

In an embodiment, a distance between the personal mobile terminal200and the first Bluetooth module150may be determined according to the signal strength of the first Bluetooth signal received by the personal mobile terminal200. When the distance is less than or equal to a predetermined distance threshold, the personal mobile terminal200automatically establishes the first Bluetooth connection with the first Bluetooth module150.

Specifically, the elevator call request command may be preset in the personal mobile terminal200, and may be an elevator call request command that includes an elevator call direction and/or a destination floor. The first Bluetooth module150may establish a communication connection with the elevator controller500of the elevator system, and automatically send the elevator call request command to the elevator controller500. The elevator controller500is configured to control the operation of a plurality of elevator cars110in the elevator system10. For example, the elevator controller500performs scheduling control based on the elevator call request command, and appoints one of the elevator cars110to stop at a floor or a landing of the passenger90and transport the passenger90to a corresponding destination floor. The appointed elevator car110also registers the destination floor of the passenger90in advance, for example, automatically registers a destination floor in the destination floor registration control panel. As such, the passenger90may completely implement an automatic elevator call operation, and may implement an elevator call operation without performing a manual operation or without providing an input.

However, when a movement of approaching the elevator car110of a passenger90cannot represent an actual elevator-taking intention of the passenger90, an invalid elevator call operation may be caused, which severely affects the operation efficiency of the elevator system10. To avoid an invalid elevator call operation, in an embodiment, the elevator system10or the movement detection system used by the elevator system10may cancel an elevator call request command sent corresponding to the movement when a tracked movement is predicted to be an abnormal movement. Further, the elevator controller500may not schedule the elevator car for the passenger90, or the elevator system10may further cancel previous scheduling arranged for the passenger90. In another embodiment, when the tracked movement is predicted to be an abnormal movement, the elevator controller500or the first Bluetooth module150is used to ignore or cancel the elevator call request command sent by the personal mobile terminal200corresponding to the movement. As such, the operation efficiency of the elevator system10can be improved.

In an example of a passenger movement, as shown inFIG.1, a passenger90first moves towards the elevator landing area410and enters the elevator landing area410through the passageway411. When the passenger90enters the elevator landing area410, a personal mobile terminal200can automatically establish a first Bluetooth connection with the first Bluetooth module150and send an elevator call request command. The passenger90subsequently leaves from the elevator landing area410(for example, because the passenger90changes an elevator-taking intention). A movement920-1schematically shown by a dotted line arrow inFIG.1occurs correspondingly. The signal strength of a first Bluetooth signal151received by the personal mobile terminal200approximately increases gradually from 0, and then approximately decreases to 0 gradually. Based on the changes (for example, including a change direction and a change magnitude) of the signal strength, the movement920-1may be tracked. Further, the movement prediction unit270analyzes Bluetooth movement data corresponding to the movement920-1. Specifically, for example, the movement prediction unit270compares and analyzes the Bluetooth movement data corresponding to the movement920-1with an abnormal movement mode generated according to historical Bluetooth movement data. As such, the movement prediction unit270may predict that the currently tracked movement920-1is an abnormal movement. Moreover, because the passenger90does not enter any elevator car110within a predetermined time (for example, 5 minutes) after the elevator call request command is sent, it may further be determined that the movement920-1is an abnormal movement, and Bluetooth movement data corresponding to the movement920-1is stored in the abnormal movement historical database of the personal movement historical database250, so as to facilitate more accurate subsequent prediction of this type of movement.

In another example of a passenger movement, as shown inFIG.1, a passenger90first moves towards the elevator landing area410and enters the elevator landing area410through the passageway411. When the passenger90enters the elevator landing area410, the personal mobile terminal200can automatically establish a first Bluetooth connection with the first Bluetooth module150and send an elevator call request command. When the elevator car110-1reaches the floor and the car door113-1is opened, the passenger90enters the elevator car110-1, and a movement910-1schematically shown by a dotted line arrow inFIG.1occurs correspondingly. The signal strength of the first Bluetooth signal151received by the personal mobile terminal200approximately increases from 0 gradually, and then suddenly drops to 0. Based on the changes (for example, including a change direction and a change magnitude) of the signal strength, the movement910-1may be tracked. Because the passenger90enters the elevator car110-1within a predetermined time (for example, 5 minutes) after the elevator call request command is sent, the personal mobile terminal200may receive the second Bluetooth signal131-1, so that it is determined that the movement910-1is a normal movement. Moreover, Bluetooth movement data corresponding to the movement910-1is stored in the normal movement historical database of the personal movement historical database250, so as to facilitate more accurate subsequent prediction of this type of movement. Certainly, the movement prediction unit270may analyze the Bluetooth movement data corresponding to the movement910-1and compare and analyze the Bluetooth movement data corresponding to the movement910-1with the normal movement mode generated according to historical data, so as to predict sooner that the currently tracked the movement910-1is a normal movement.

In still another example of a passenger movement, as shown inFIG.1, the passenger90first moves towards the elevator landing area410and enters the elevator landing area410through the passageway411. When the passenger90enters the elevator landing area410, the personal mobile terminal200can automatically establish a first Bluetooth connection with the first Bluetooth module150and send an elevator call request command. The passenger90subsequently leaves from another passageway412(for example, the passenger90passes through the elevator landing area410) of the elevator landing area410. A movement920-2schematically shown by a dotted line arrow inFIG.1occurs correspondingly. The signal strength of the first Bluetooth signal151received by the personal mobile terminal200approximately increases from 0 gradually, and then approximately decreases to 0 gradually. Based on the changes (for example, including a change direction and a change magnitude) of the signal strength, the movement920-2may be tracked. Further, the movement prediction unit270analyzes Bluetooth movement data corresponding to the movement920-2, and compares and analyzes Bluetooth movement data corresponding to the movement920-2with the abnormal movement mode generated according to historical data, so that it may be predicted that the currently tracked the movement920-2is an abnormal movement. Moreover, because the passenger90does not enter any elevator car110within a predetermined time (for example, 5 minutes) after the elevator call request command is sent, it may also be determined that the movement920-2is an abnormal movement, and the Bluetooth movement data corresponding to the movement920-2is stored in the abnormal movement historical database of the personal movement historical database250, so as to facilitate more accurate subsequent prediction of this type of movement.

In yet another example of a passenger movement, as shown inFIG.1, the passenger90first moves towards the elevator landing area410and enters the elevator landing area410through the passageway411. When the passenger90enters the elevator landing area410, the personal mobile terminal200can automatically establish a first Bluetooth connection with the first Bluetooth module150and send an elevator call request command. When the elevator car110-2reaches the floor and the car door113-2is opened, the passenger90enters the elevator car110-2. A movement910-2schematically shown by a dotted line arrow inFIG.1occurs correspondingly. The signal strength of a first Bluetooth signal151received by the personal mobile terminal200approximately increases from 0 gradually, then gradually decreases to a particular value, and then suddenly drops to 0. Based on the changes (for example, including a change direction and a change magnitude) of the signal strength, the movement910-2may be tracked. Because the passenger90enters the elevator car110-2within a predetermined time (for example, 5 minutes) after the elevator call request command is sent, the personal mobile terminal200may receive the second Bluetooth signal131-2, so that it is determined that the movement910-2is a normal movement, and the Bluetooth movement data corresponding to the movement910-2is stored in the normal movement historical database of the personal movement historical database250, so as to facilitate more accurate subsequent prediction of this type of movement. Certainly, the movement prediction unit270may analyze Bluetooth movement data corresponding to the movement910-1in advance and compare and analyze the Bluetooth movement data corresponding to the movement910-2with the normal movement mode generated according to historical data, so that it may be predicted or determined that the currently tracked the movement910-2is a normal movement.

The abnormal movements920-1and920-2may be predicted in advance. Therefore, the elevator system10cancels or ignores in time an elevator call request command caused by the movement, or changes in time a scheduling arrangement, thereby greatly improving the operation efficiency of an elevator.

FIG.4is a schematic flowchart of a movement detection method for a passenger according to an embodiment of the present invention. The movement detection method in this embodiment of the present invention is described below with reference toFIG.1,FIG.2, andFIG.4, and includes a process of movement prediction and a process of movement mode learning.

First, in a normal case, the second Bluetooth module130broadcasts the second Bluetooth signal131to the interior of the elevator car110, and the first Bluetooth module150broadcasts the first Bluetooth signal151to the elevator landing area410. The first Bluetooth module150may continuously broadcast the first Bluetooth signal151, and the second Bluetooth module130broadcasts the second Bluetooth signal131at least when stopping at a floor. The signal strengths of the first Bluetooth signal131and the first Bluetooth signal151may be determined in advance, and decrease as propagation distances of the signals increase. When each passenger90moves in the elevator landing area410, the following steps S420to S490are correspondingly performed.

Further, in step S420, a personal mobile terminal200of the passenger90who moves in the elevator landing area410receives the first Bluetooth signal151, and may recognize the first Bluetooth signal151, so as to determine a floor of the elevator landing area410in which a movement occurs. The movement in the elevator landing area410may include a movement of approaching the elevator car110of the passenger90, and certainly may include an abnormal movement, for example, a movement of leaving the elevator car110.

Further, in step S430, the signal strength of the received first Bluetooth signal151is determined, so that changes in the received first Bluetooth signal151that occur as the passenger90moves may be determined in real time. Step S430may be completed in the signal strength determination module220of the personal mobile terminal200.

Further, in step S440, the movement of the passenger90in the elevator landing area410is tracked, and corresponding Bluetooth movement data is generated. In this embodiment of the present invention, the movement is tracked by means of the determined changes in the signal strength of the first Bluetooth signal151. Step S440may be completed in the movement tracking module230of the personal mobile terminal200. For a specific tracking principle, refer to the foregoing exemplary description about the movement tracking module230.

Further, in step S450, it is judged whether the second Bluetooth signal is successfully received. In an embodiment, it is judged whether the second Bluetooth signal131is successfully received within a predetermined time after the personal mobile terminal200automatically sends an elevator call request command. In another embodiment, it is judged whether the second Bluetooth signal131whose signal strength is greater than or equal to the predetermined signal strength is successfully received.

If the second Bluetooth signal131whose signal strength is greater than or equal to the predetermined signal strength is successfully within the predetermined time, it indicates that the passenger90enters the elevator car110. The process turns to step S461to determine that the tracked movement is correspondingly a normal movement. Further, in step S471, Bluetooth movement data corresponding to a normal movement of each personal mobile terminal200is stored in the normal movement historical database of the personal movement historical database250, so as to update the normal movement historical database.

If the second Bluetooth signal131whose signal strength is greater than or equal to the predetermined signal strength is not successfully received within the predetermined time period, the judgment result is “no”, indicating that the passenger90does not enter the elevator car110. The process turns to step S462to determine that the tracked movement is correspondingly an abnormal movement. Further, in step S472, Bluetooth movement data corresponding to an abnormal movement of each personal mobile terminal200is stored in the abnormal movement historical database of the personal movement historical database250, so as to update the abnormal movement historical database.

The foregoing steps S450, S461, S462, S471, and S472may be completed in the movement judgment module240of the movement detection system. It should be noted that the personal movement historical database250and/or movement prediction unit270are not limited to being disposed in each personal mobile terminal200, and for example, may be disposed in a server of the elevator system10, or may further be implemented in a manner of cloud storage of the cloud. After each judgment, Bluetooth movement data may be transferred in real time to the personal movement historical database250. Alternatively, the Bluetooth movement data may be transferred to the personal movement historical database250according to a predetermined time interval or in batches according to a predetermined amount.

Further, the process turns to a machine learning stage, that is, step S481and/or step S482. In step S481, a normal movement mode of a passenger is learned and acquired from the normal movement historical database based on the determined normal movement. In step S482, an abnormal movement mode of a passenger is learned and acquired from the abnormal movement historical database based on the determined abnormal movement.

The foregoing step S481or step S482is completed in the machine learning unit260. It should be noted that the machine learning unit260is not limited to being disposed in each personal mobile terminal200, and, for example, may be disposed in a server of the elevator system10, or may further be implemented by using cloud computing of the cloud. Specifically, machine learning may be performed after each update of a historical database, or may be performed according to a predetermined time interval.

The foregoing steps S440to step S481or S482are correspondingly a process of implementing movement mode learning, and do not need to be performed in each process of movement detection. For example, the foregoing steps S440to step S481or S482may even be omitted after the normal movement mode or the abnormal movement mode is obtained.

After step S440, step S490may further be performed to predict that the tracked movement is a normal movement or an abnormal movement. That is, the type of the tracked movement is judge in advance before the step S461or S462, so that an abnormal movement can be detected in advance. The judgment may be performed by using a historical learning result generated in step S481or S482. For example, it is predicted, based on the Bluetooth movement data received from the movement tracking module230and the normal movement mode and/or abnormal movement mode of the passenger learned and acquired by the machine learning unit260, that the tracked movement is a normal movement or an abnormal movement.

Especially, when the tracked movement is predicted to be an abnormal movement, the movement tracking module230sends a corresponding message to the personal mobile terminal200, the first Bluetooth module150, and/or the elevator controller500. As such, an elevator call request command automatically generated corresponding to the abnormal movement can be cancelled in time, or a scheduling arrangement of the elevator call request command automatically generated corresponding to the abnormal movement can be cancelled in time.

FIG.5is a schematic diagram of an elevator system according to another embodiment of the present invention, and at the same time schematically shows a movement detection system for a passenger according to another embodiment.FIG.6is a schematic diagram of a modular structure when at least a part of the movement detection system shown inFIG.1is implemented by using a personal mobile terminal according to another embodiment.

Compared with the personal mobile terminal200in the embodiment shown inFIG.2, a main change in a personal mobile terminal200′ in the embodiment shown inFIG.6used in the movement detection system lies in that the personal movement historical database250and the machine learning unit260are not disposed in the personal mobile terminal200′. A Bluetooth communication module210, the signal strength determination module220, a movement tracking module230, a movement judgment module240, and a movement prediction unit270similar to those in the personal mobile terminal200inFIG.2are disposed in the personal mobile terminal200′. They are no longer elaborated herein. The movement judgment module240may submit Bluetooth movement data to an external personal movement historical database250in a manner of wireless communication. During working, the movement prediction unit270may retrieve the normal movement mode or the abnormal movement mode in the machine learning unit260in a manner of wireless communication.

Corresponding to the personal mobile terminal200′ in the embodiment shown inFIG.6, in the elevator system20in embodiment shown inFIG.5, the personal movement historical database250is disposed for each personal mobile terminal200′. For example, a plurality of personal movement historical databases250may be implemented in a server, or may be implemented by using cloud storage of the cloud. The machine learning unit260may be disposed corresponding to one or more personal movement historical databases250, and for example, may be implemented in a server, or may be implemented by using cloud computing of the cloud.

With reference to the descriptions of the foregoing examples, those skilled in the art should understand that at least one of the Bluetooth communication module210, the signal strength determination module220, the movement tracking module230, the movement judgment module240, and the movement prediction unit270used in the movement detection system may be disposed outside the personal mobile terminal200or200′ according to a specific requirement. For example, the movement judgment module240, the movement prediction unit270, and the like may be disposed outside the personal mobile terminal200or200′. Specifically, the movement prediction unit270and the machine learning unit260may be disposed together in a server. A result predicted by the movement prediction unit270may be delivered in time to a corresponding personal mobile terminal.

Because the movement detection system for a passenger is applied, in the elevator system10or20in the foregoing embodiment, an abnormal movement of a passenger can be automatically detected, so that the elevator system10can judge an invalid elevator call request command. As such, scheduling arrangements are more accurate and appropriate, thereby greatly improving the operation efficiency of the elevator system.

It should be understood that the movement detection system for a passenger in the foregoing embodiments of the present invention is not limited to being applied to the elevator system10in the foregoing embodiments, and may further be applied to elevator systems having an automatic elevator call function in other embodiments. For example, the first Bluetooth module150is replaced with a wireless node that broadcasts or transmits another radio signal and can wirelessly interact with a personal mobile terminal200. The first Bluetooth module150sends an elevator call request command regarding an elevator call direction.

It should be understood that the “Bluetooth connection” herein includes “Bluetooth communication”, for example, Bluetooth communication based on a Bluetooth protocol.

Those skilled in the art should understand that aspects of the present invention may be embodied as systems, methods or computer program products. Therefore, the aspects of the present invention may use the following forms: a complete hardware implementation, a complete software implementation (including firmware, resident software, microcode, and the like), or an implementation that is generally referred to as a “service”, “circuit”, “circuit system”, “module” and/or “processing system” herein and combines software and hardware aspects. In addition, the aspects of the present invention may be embodied in the form of a computer program product in one or more computer readable media on which computer readable program code is implemented.

Any combination of one or more computer readable media may be used. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared or semiconductor system, device or apparatus, or any suitable combination of the foregoing items. More specific examples (a non-exhaustive list) of the computer readable storage medium include the following items: an electrical connection having one or more wires, a portable computer magnetic disk, a hard disk, a random-access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or a flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage apparatus, a magnetic storage apparatus, or any suitable combination of the foregoing items. In the context of the document, the computer readable storage medium may be any tangible medium that may contain or store instructions used for execution by systems, devices or apparatuses or used in combination with systems, devices or apparatuses.

Program code and/or executable instructions embodied on a computer readable medium may be transmitted by using any suitable medium, including, but not limited to, a wireless medium, a wired medium, an optical fiber cable, and RF, or any suitable combination of the foregoing items.

Computer program code used to implement the operations of the aspects of the present invention may be compiled by using one programming language or any combination of programming languages including an object-oriented programming language such as Java, Smalltalk, and C++ and a conventional program programming language such as the “C” programming language or a similar programming language. The program code may be completely executed on a computer (apparatus) of a user, partially executed on the computer of the user, executed as an independent software package, partially executed on the computer of the user and partially executed on a remote computer, or completely executed on the remote computer or a server. In the latter cases, the remote computer may be connected to the computer of the user by using any type of network including a local area network (LAN) or a wide area network (WAN), or may be connected (for example, connected through the Internet by using an Internet service provider) to an external computer.

A computer program instruction may be provided to a processor of a general-purpose computer, a processor of a special-purpose computer, for example, a graphics processing unit or another programmable data processing device to produce a machine, so that the instruction executed by a processor of a computer or another programmable data processing device creates manners for implementing the functions/acts designated in one or more blocks in the flowcharts and/or block diagrams.

A computer program instruction may be loaded to a computer, another programmable data processing device or another apparatus, to perform a series of operation steps on the computer, another programmable device or another apparatus, so as to generate a computer-implemented process, so that the instruction executed on the computer or another programmable device provides a process used for implementing designated functions and acts herein.

It should further be noted that in some alternative implementations, the functions/operations noted in the blocks may occur out of the order noted in the flowcharts. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or these blocks may sometimes be executed in the reverse order, depending upon the functions/operations involved. Although specific step orders are shown, disclosed and required, it should be understood that the steps can be implemented, separated or combined in any order, and are still benefited by the present disclosure unless otherwise indicated

Examples are used in this specification to disclose the present invention, include optimal modes, and enable any of those skilled in the art to implement the present invention, including manufacturing and using any apparatus or system and performing any covered method. The patent scope of the present invention is defined by the claims, and may include other examples conceived of by those skilled in the art. If other examples of such types have structural elements that are not literally different from those in the claims, or if other examples of such types include equivalent structural elements that do not have substantial literal differences from those in the claims, the examples shall fall within the scope of the claims.