Elevator target floor display method and system
By constructing a baseline scenario model and dynamic probability prediction, an adaptive elevator destination floor display interface is generated, which solves the problems of low operating efficiency and privacy protection in traditional elevators, and realizes an improvement in elevator operating efficiency that flexibly responds to passenger needs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HITACHI BUILDING TECH GUANGZHOU CO LTD
- Filing Date
- 2026-02-28
- Publication Date
- 2026-05-15
AI Technical Summary
Traditional elevator operation interfaces are prone to errors on high floors and during peak hours, and identity-based smart elevator solutions have privacy protection issues and cannot adapt to temporary travel needs.
By acquiring data from building management systems, meeting room reservation systems, and property management systems, a baseline scenario model is constructed. Dynamic probability prediction is then performed using time, space, environment, and event scenario vectors to generate an adaptive elevator destination floor display interface, dynamically prioritizing the display of the floor button with the highest probability.
It enables flexible responses to passenger travel intentions without the need for identity verification, improves operational efficiency, adapts to elevator usage needs in high-rise buildings and during peak hours, avoids the collection of privacy data, and provides a clear operation path.
Smart Images
Figure CN122035663A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of elevator dispatching technology, and in particular to a method and system for displaying the destination floor of an elevator. Background Technology
[0002] With the increasing prevalence of high-rise buildings and multi-functional buildings, elevators, as a core tool of vertical transportation, directly impact passenger experience through the user-friendliness and efficiency of their Car Operating Panel (COP). Traditional elevator COPs typically use fixed LCD panels or physical button arrays, listing all floors for passengers to select. In scenarios with a large number of floors, passengers need to find their target floor among numerous buttons, which is time-consuming and prone to errors, especially during peak hours or when multiple passengers are riding the elevator.
[0003] To improve operational efficiency, intelligent elevator solutions have emerged in existing technologies. The core idea is to dynamically display buttons for frequently used floors or floors within a passenger's authorized access range by recognizing their identity. This includes technologies such as identity recognition, access control mechanisms, and automatic registration. Identity recognition technologies include card swiping, fingerprint recognition, facial recognition, and mobile phone Bluetooth / NFC; access control mechanisms retrieve the passenger's preset floor permissions based on the identity recognition result and only display buttons for floors they are authorized to access; and automatic registration automatically registers the passenger's target floor without manual operation.
[0004] However, identity-based solutions heavily rely on the collection and identification of biometrics or identity information in practical applications, touching upon the boundaries of personal privacy protection. Under increasingly stringent personal information protection, this poses compliance risks and user resistance. Furthermore, fixed permissions cannot adapt to temporary intentions, only responding to fixed floors within a passenger's authorized area, failing to flexibly handle common temporary travel needs such as "going to a non-authorized floor for a meeting" or "temporarily visiting other departments." Passengers still need to complete registration through additional steps, such as visitor mode or administrator authorization, making the process cumbersome. For visitors or temporary visitors not registered in the system, effective guidance is not provided; their interface remains identical to traditional elevators, failing to solve the fundamental problem of difficulty in finding buttons.
[0005] Therefore, there is an urgent need for an intelligent elevator destination display solution that can improve elevator operation efficiency, eliminate the need for passenger identification, and flexibly respond to various real-time travel intentions, thereby achieving a truly universal, adaptive, and privacy-friendly elevator interface. Summary of the Invention
[0006] To address or partially address the problems existing in related technologies, this application provides an elevator destination floor display method and system, aiming to solve the technical problem that elevator smart button displays rely on passenger identification.
[0007] The first aspect of this application provides an elevator destination floor display method and system, including: Acquire data from building management systems, meeting room booking systems, property management systems, and elevator control systems, including calendar time, elevator location, floor data, passenger count data, and traffic flow data. The collected data is transformed into corresponding context vectors from four categories: time context vector, space context vector, environment context vector, and event context vector. Based on the time context vector and the spatial context vector, retrieve the baseline probability list from the pre-built baseline context model - floor probability matrix; The baseline probability list is dynamically weighted based on the environmental context vector and the event context vector to obtain the final probability list arranged in descending order of probability. The weighted probability values are normalized to generate a list of target layers sorted by probability. Based on the probability distribution characteristics of the destination floor list, an adaptive display interface is dynamically generated. The interface includes a dynamic priority area and a full function area. The N floor buttons with the highest probability are displayed in the dynamic priority area, and the value of N is adaptively adjusted according to the probability distribution and the number of passengers.
[0008] Optional, pre-built baseline scenario model - floor probability matrix, including: The baseline scenario model - floor probability matrix is a structured data model constructed through statistical analysis of historical elevator operation data in buildings. It consists of index dimensions and numerical dimensions. The row and column indexes of the index dimension correspond to the time context and spatial context respectively, covering all possible combinations of basic contexts; The numerical dimension is the matrix cell value, which stores the baseline probability data of each floor being selected by passengers in the corresponding scenario.
[0009] Optionally, a baseline probability list can be retrieved from a pre-built baseline scenario model-floor probability matrix: Using the time context vector and spatial context vector as a joint index, a set of floor probability data that matches the current context coordinates is retrieved from the baseline context model-floor probability matrix to obtain the baseline probability list.
[0010] Optionally, the baseline probability list can be dynamically weighted, including: Real-time offset compensation of the baseline probability list is performed using environmental context vectors and event context vectors: (1) In the formula, Represents the final probability. Represents the baseline probability. Indicates the event context weight, Represents the environmental context weight. This represents the floor offset corresponding to the event context vector. This represents the floor offset corresponding to the environmental context vector; If the event context vector contains a specific public event, then the offset of the corresponding floor. Increase, weighting coefficient It dynamically increases as the current time approaches the start time of the event; If the environmental context vector detects a real-time environmental change, set an environmental offset corresponding to the environmental change. Increase the probability weight of the target floor .
[0011] Optionally, the time context vector includes the current time and date type; the space context vector includes the elevator's current floor, the floor being called, and floor attributes; the environmental context vector includes the number of passengers and traffic flow; and the event context vector includes property management system data, building management system data, or public schedule data.
[0012] Optionally, dynamically generate an adaptive display interface, including: The dynamic priority zone displays the N floor buttons with the highest probability in the most prominent position on the elevator destination floor display screen. The value of N determines the rendering strategy based on the distribution characteristics of the final probability P2: Convergence determination: If the probability value of the first-ranked target floor is greater than the preset probability threshold, the intent is highly concentrated, a very small number of large-sized buttons are adaptively displayed, and the first-ranked target floor button is visually enhanced. If the probability distribution is relatively even or the number of passengers detected is greater than 1, indicating a diversified determination intention, the N value will be automatically increased and the data will be displayed in a multi-grid format to improve the coverage of the first screen. The full functionality area, located in a fixed area of the screen, always provides all floor buttons or numeric keypads, ensuring that visitors and passengers with temporary intentions to use the floors have a clear and direct operating path.
[0013] A second aspect of this application provides an elevator destination floor display system, comprising: External data source acquisition module, scenario data acquisition layer, dynamic probability prediction module, and adaptive UI generation module; The external data source acquisition module connects to the property management system, building management system, and meeting room reservation system to collect one or more of the following data from the elevator control system: calendar time, elevator location, floor data, passenger number data, traffic flow data, building management system data, meeting room reservation system data, and property management system data. The contextual data acquisition layer is used to transform the data collected by the external data source acquisition module into time context vectors, spatial context vectors, environmental context vectors, and event context vectors. The dynamic probability prediction module features multi-dimensional data fusion, a baseline probability model, a dynamic weighting engine, and a final probability list generator, used to generate a final probability list based on contextual data vectors. The adaptive UI generation module is used to dynamically generate a display interface that includes a dynamic priority area and a full functional area based on the final probability list.
[0014] Optional, dynamic probability prediction module, including: The baseline probability model is used to store the pre-designed baseline scenario model - floor probability matrix. The combination of time scenario vector and spatial scenario vector is used as a joint index to retrieve the baseline probability of matching the target floor in the baseline scenario model - floor probability matrix. The dynamic weighting engine is used to adjust the baseline probability in real time based on environmental context vector and event context vector data. The final probability list generator is used to normalize the weighted probability values and generate a list of target layers sorted by probability.
[0015] Optional adaptive UI generation modules include: The dynamic priority display module is used to display the N floor buttons with the highest probability in the most conspicuous position on the elevator destination floor display screen. The value of N is used to execute different rendering strategies based on the distribution characteristics of the final probability P2. If the probability value of the first destination floor is greater than the preset probability threshold, it is determined that the intent is highly concentrated, and a very small number of large-sized buttons are adaptively displayed, while the first destination floor button is visually enhanced. If the probability distribution is relatively even, or if more than 1 passenger is detected, it is determined that the intent is diversified, and the value of N is automatically increased and displayed in a multi-grid format to improve the coverage of the first screen. A fully functional display module provides all floor buttons or numeric keypads in a fixed area of the screen, ensuring that visitors and passengers with temporary intentions to use the floors have a clear and direct operating path.
[0016] The technical solution provided in this application may include the following beneficial effects: Based on non-personalized contextual data such as time, space, environment, and events, this system employs a baseline contextual probability model and a real-time dynamically weighted two-layer prediction mechanism. Building upon regular building traffic patterns, it responds in real-time to temporary public events and sudden environmental changes, predicting the probability of passengers' destination floors. This avoids the collection and processing of privacy data and solves the problems of rigid permissions and inability to adapt to flexible travel needs in traditional systems. The system dynamically adjusts the interface layout according to the predicted probability distribution of passengers' destination floors, shortening the average operation time for passengers and improving elevator operation efficiency. It is suitable for high-rise buildings with multiple elevators and during peak hours.
[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description
[0018] The above and other objects, features and advantages of this application will become more apparent from the more detailed description of exemplary embodiments thereof in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments thereof.
[0019] Figure 1 This is a flowchart illustrating the elevator destination floor display method according to an embodiment of this application; Figure 2 This is a schematic diagram of the elevator destination floor display system shown in an embodiment of this application. Detailed Implementation
[0020] Embodiments of this application will now be described in more detail with reference to the accompanying drawings. While embodiments of this application are shown in the drawings, it should be understood that this application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to make this application more thorough and complete, and to fully convey the scope of this application to those skilled in the art.
[0021] The technical solutions of the embodiments of this application are described in detail below with reference to the accompanying drawings.
[0022] Figure 1 This is a flowchart illustrating the elevator destination floor display method according to an embodiment of this application.
[0023] In some implementations, see Figure 1 A method for displaying the destination floor of an elevator, comprising: S101. Obtain data from the building management system, meeting room reservation system, property management system, and elevator control system, including calendar time, elevator location, floor data, passenger count data, and traffic flow data. Specifically, the elevator control system obtains calendar time, elevator location, floor data, passenger count data, and traffic flow data. Property management system data includes long-term, regular behavioral data of organizations and personnel within the building; for example, Company XX is located on the 10th floor and starts work at 8:30 in the morning. Building management system data includes real-time building operating status and space usage activity data; such as energy consumption of each floor at different times, air conditioning operating areas and times, etc. The meeting room booking system data includes explicit, short-term, group event intent data, such as a general meeting to be held in the 15th-floor conference hall at 9:00 AM.
[0024] S102. Convert the collected data into corresponding context vectors from the four categories: time context vector, spatial context vector, environmental context vector, and event context vector. Specifically, the time context vector includes the current time and date type; the date type includes weekdays, weekends, public holidays, etc.
[0025] The spatial context vector includes the elevator's current floor, the floor it is calling, and floor attributes; among which, floor attributes include: 1F = lobby, -1F = parking lot, 10F = office area, 20F = cafeteria.
[0026] The environmental context vector includes passenger numbers and traffic flow direction; passenger numbers are estimated using car gravity sensors, TOF sensors, or AI cameras; traffic flow direction is indicated by factors such as predominant behavior during the morning rush hour and predominant behavior during the evening rush hour.
[0027] Event context vectors include data from property management systems, building management systems, or public schedules. Property management system data includes data such as "Company XX on the 10th floor starts work at 8:30 am." Building management system data includes data such as energy consumption, air conditioning operation areas and times for different time periods on different floors. Public schedule data includes data such as meeting reservation events obtained through the building's meeting room reservation system.
[0028] S103. Based on the time context vector and the spatial context vector, retrieve the baseline probability list from the pre-constructed baseline context model - floor probability matrix; Specifically, the pre-built baseline scenario model – the floor probability matrix – includes: The baseline scenario model – the floor probability matrix – is a structured data model constructed through statistical analysis of historical elevator operation data. It consists of an index dimension and a numerical dimension. The row and column indices of the index dimension correspond to the time scenario and the spatial scenario, respectively, covering all possible combinations of basic scenarios. The numerical dimension consists of matrix cell values, which store the baseline probability data of each floor being selected by passengers under the corresponding scenario.
[0029] Using the time context vector and spatial context vector as a joint index, a set of floor probability data that matches the current context coordinates is retrieved from the baseline context model-floor probability matrix to obtain the baseline probability list.
[0030] S104. Dynamically weight the baseline probability list based on the environmental context vector and the event context vector to obtain the final probability list arranged in descending order of probability. Specifically, the probability values in the baseline probability list are offset in real time using environmental context vectors and event context vectors. The calculation formula is as follows: (1) In the formula, Represents the final probability. Represents the baseline probability. Indicates the event context weight, Represents the environmental context weight. This represents the floor offset corresponding to the event context vector. This represents the floor offset corresponding to the environmental context vector; If the event context vector contains a specific public event, then the offset of the corresponding floor. Increase, weighting coefficient The environment dynamically increases as the current time approaches the event start time; if the environment context vector detects a real-time environmental change, an environmental offset corresponding to the environmental change is set. Increase the probability weight of the target floor .
[0031] S105. Normalize the weighted probability values to generate a list of target layers sorted by probability. The target layer list is sorted by probability, such as {15F:45%, 10F:15%, 12F:10%,...}.
[0032] S106. Based on the probability distribution characteristics of the destination floor list, dynamically generate an adaptive display interface, which includes a dynamic priority area and a full function area; display the N floor buttons with the highest probability in the dynamic priority area, and the value of N is adaptively adjusted according to the probability distribution and the number of passengers.
[0033] Specifically, the dynamic priority zone is set in the most prominent position on the screen, displaying the N floor buttons with the highest probability. The value of N is adaptive: if the probability is highly concentrated, such as 15F having a probability >40%, then N can be very small, such as N=4, and the 15F button can be highlighted or enlarged. If the probability distribution is even, such as during morning rush hour when people are going to various office floors, N can be appropriately increased to improve coverage. If the number of passengers is greater than 1, N should also be appropriately increased.
[0034] The full functionality area, located in a fixed area of the screen, always provides all floor buttons or a numeric keypad. This area ensures that visitors and passengers with temporary intentions always have a clear and direct path to navigate.
[0035] In some embodiments, corresponding to the aforementioned application function implementation device embodiments, this application also provides an elevator destination floor display system and corresponding embodiments.
[0036] See Figure 2 An elevator destination floor display system, comprising: External data source acquisition module, scenario data acquisition layer, dynamic probability prediction module, and adaptive UI generation module; The external data source acquisition module connects to the property management system, building management system, and meeting room reservation system. This module collects one or more of the following data from the elevator control system: calendar time, elevator location, floor data, passenger count data, traffic flow data, building management system data, meeting room reservation system data, and property management system data.
[0037] The contextual data acquisition layer transforms data collected by external data source modules into time context vectors, spatial context vectors, environmental context vectors, and event context vectors. The time context vector includes the current time and date type; date types include weekdays, weekends, and public holidays. The spatial context vector includes the elevator's current floor, the floor being called, and floor attributes; floor attributes include: 1F = lobby, -1F = parking lot, 10F = office area, 20F = cafeteria. The environmental context vector includes passenger numbers and traffic flow; passenger numbers are estimated using car gravity sensors, TOF sensors, or AI cameras; traffic flow is indicated by factors such as peak hours above the morning rush hour and off-peak hours below the evening rush hour. The event context vector includes data from the property management system, building management system, or public schedule data; property management system data includes information such as "Company XX on the 10th floor starts work at 8:30 AM"; building management system data includes information such as energy consumption, air conditioning operation areas and times for different time periods on each floor; public schedule data includes meeting reservations obtained through the building's meeting room reservation system.
[0038] The dynamic probability prediction module features multi-dimensional data fusion, a baseline probability model, a dynamic weighting engine, and a final probability list generator, used to generate a final probability list based on contextual data vectors. Specifically, the dynamic probability prediction module includes: Baseline probability model, dynamic weighting engine, and final probability list generator; The baseline probability model stores a pre-designed baseline scenario model-floor probability matrix. Using a combination of time scenario vectors and spatial scenario vectors as a joint index, the baseline probability of matching the target floor is retrieved from the baseline scenario model-floor probability matrix.
[0039] The dynamic weighting engine is used to adjust the baseline probabilities in real time based on environmental context vectors and event context vectors; it also uses environmental context vectors and event context vectors to compensate for the real-time offset of probability values in the baseline probability list, calculated using the following formula: (1) If the event context vector contains a specific public event, then the offset of the corresponding floor. Increase, weighting coefficient The dynamic weighting engine dynamically increases as the current time approaches the event's start time; for example, if "9:00 15F Conference" is detected, the engine will significantly increase the offset of the 15th floor between 8:50 and 9:00. and probability weights .
[0040] If the environmental context vector detects a real-time environmental change, set an environmental offset corresponding to the environmental change. Increase the probability weight of the target floor If 12:00 is detected and the number of passengers is greater than 5, the dynamic weighted engine will increase the offset of the 20F-cafeteria and 1F-lobby. and probability weights .
[0041] The final probability list generator is used to normalize the weighted probability values and generate a list of target layers sorted by probability.
[0042] The adaptive UI generation module is used to dynamically generate a display interface that includes a dynamic priority area and a full functional area based on the final probability list.
[0043] Specifically, the adaptive UI generation module includes: The dynamic priority display module is used to display the N floor buttons with the highest probability in the most conspicuous position on the elevator destination floor display screen. The value of N is used to execute different rendering strategies based on the distribution characteristics of the final probability P2. If the probability value of the first destination floor is greater than the preset probability threshold, it is determined that the intent is highly concentrated, and a very small number of large-sized buttons are adaptively displayed, while the first destination floor button is visually enhanced. If the probability distribution is relatively even, or if more than 1 passenger is detected, it is determined that the intent is diversified, and the value of N is automatically increased and displayed in a multi-grid format to improve the coverage of the first screen. A fully functional display module provides all floor buttons or numeric keypads in a fixed area of the screen, ensuring that visitors and passengers with temporary intentions to use the floors have a clear and direct operating path.
[0044] The various embodiments of this application have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.
Claims
1. A method for displaying the destination floor of an elevator, characterized in that, include: Acquire data from building management systems, meeting room booking systems, property management systems, and elevator control systems, including calendar time, elevator location, floor data, passenger count data, and traffic flow data. The collected data is transformed into corresponding context vectors from four categories: time context vector, space context vector, environment context vector, and event context vector. Based on the time context vector and the spatial context vector, retrieve the baseline probability list from the pre-built baseline context model - floor probability matrix; The baseline probability list is dynamically weighted based on the environmental context vector and the event context vector to obtain the final probability list arranged in descending order of probability. The weighted probability values are normalized to generate a list of target layers sorted by probability. Based on the probability distribution characteristics of the destination floor list, an adaptive display interface is dynamically generated. The interface includes a dynamic priority area and a full function area. The N floor buttons with the highest probability are displayed in the dynamic priority area, and the value of N is adaptively adjusted according to the probability distribution and the number of passengers.
2. The elevator destination floor display method according to claim 1, characterized in that, The pre-built baseline scenario model - floor probability matrix includes: The baseline scenario model - floor probability matrix is a structured data model constructed through statistical analysis of historical elevator operation data in buildings. It consists of index dimensions and numerical dimensions. The row and column indexes of the index dimension correspond to the time context and spatial context respectively, covering all possible combinations of basic contexts; The numerical dimension is the matrix cell value, which stores the baseline probability data of each floor being selected by passengers in the corresponding scenario.
3. The elevator destination floor display method according to claim 1, characterized in that, The baseline probability list is retrieved from the pre-built baseline scenario model-floor probability matrix: Using the time context vector and spatial context vector as a joint index, a set of floor probability data that matches the current context coordinates is retrieved from the baseline context model-floor probability matrix to obtain the baseline probability list.
4. The elevator destination floor display method according to claim 1, characterized in that, The dynamic weighting of the baseline probability list includes: Real-time offset compensation of the baseline probability list is performed using environmental context vectors and event context vectors: （1） In the formula, Represents the final probability. Represents the baseline probability. Indicates the event context weight, Represents the context weights. This represents the floor offset corresponding to the event context vector. This represents the floor offset corresponding to the environmental context vector; If the event context vector contains a specific public event, then the offset of the corresponding floor. Increase, weighting coefficient It dynamically increases as the current time approaches the start time of the event; If the environmental context vector detects a real-time environmental change, set an environmental offset corresponding to the environmental change. Increase the probability weight of the target floor .
5. The elevator destination floor display method according to claim 1, characterized in that: The time context vector includes the current time and date type; The spatial context vector includes the elevator's current floor, the floor being called, and floor attributes; The context vector includes passenger numbers and traffic flow direction; Event context vectors include data from property management systems, building management systems, or public schedules.
6. The elevator destination floor display method according to claim 1, characterized in that, The dynamically generated adaptive display interface includes: The dynamic priority zone displays the N floor buttons with the highest probability in the most prominent position on the elevator destination floor display screen. The value of N determines the rendering strategy based on the distribution characteristics of the final probability P2: Convergence determination: If the probability value of the first-ranked target floor is greater than the preset probability threshold, the intent is highly concentrated, a very small number of large-sized buttons are adaptively displayed, and the first-ranked target floor button is visually enhanced. If the probability distribution is relatively even or the number of passengers detected is greater than 1, indicating a diversified determination intention, the N value will be automatically increased and the data will be displayed in a multi-grid format to improve the coverage of the first screen. The full functionality area, located in a fixed area of the screen, always provides all floor buttons or numeric keypads, ensuring that visitors and passengers with temporary intentions to use the floors have a clear and direct operating path.
7. An elevator destination floor display system, used to execute the elevator destination floor display method according to any one of claims 1-6, characterized in that, include: External data source acquisition module, scenario data acquisition layer, dynamic probability prediction module, and adaptive UI generation module; The external data source acquisition module is connected to the property management system, building management system and meeting room reservation system, and is used to collect one or more of the following data from the elevator control system: calendar time, elevator location, floor data, passenger number data, traffic flow data, building management system data, meeting room reservation system data and property management system data. The context data acquisition layer is used to transform the data collected by the external data source acquisition module into time context vectors, spatial context vectors, environmental context vectors, and event context vectors. The dynamic probability prediction module features multi-dimensional data fusion, a baseline probability model, a dynamic weighting engine, and a final probability list generator, used to generate a final probability list based on contextual data vectors. The adaptive UI generation module is used to dynamically generate a display interface that includes a dynamic priority area and a full functional area based on the final probability list.
8. The elevator destination floor display system according to claim 7, characterized in that, The dynamic probability prediction module includes: The baseline probability model is used to store the pre-designed baseline scenario model - floor probability matrix. The combination of time scenario vector and spatial scenario vector is used as a joint index to retrieve the baseline probability of matching the target floor in the baseline scenario model - floor probability matrix. The dynamic weighting engine is used to adjust the baseline probability in real time based on environmental context vector and event context vector data. The final probability list generator is used to normalize the weighted probability values and generate a list of target layers sorted by probability.
9. The elevator destination floor display system according to claim 7, characterized in that, The adaptive UI generation module includes: The dynamic priority display module is used to display the N floor buttons with the highest probability in the most conspicuous position on the elevator destination floor display screen. The value of N is used to execute different rendering strategies based on the distribution characteristics of the final probability P2. If the probability value of the first destination floor is greater than the preset probability threshold, it is determined that the intent is highly concentrated, and a very small number of large-sized buttons are adaptively displayed, while the first destination floor button is visually enhanced. If the probability distribution is relatively even, or if more than 1 passenger is detected, it is determined that the intent is diversified, and the value of N is automatically increased and displayed in a multi-grid format to improve the coverage of the first screen. A fully functional display module provides all floor buttons or numeric keypads in a fixed area of the screen, ensuring that visitors and passengers with temporary intentions to use the floors have a clear and direct operating path.