Efficient interaction elevator control management method and system based on elevator code scanning reservation

Abstract

The application provides an efficient interactive elevator control management method and system based on elevator code scanning reservation. Through code scanning reservation, cloud intelligent scheduling, voice interaction and other technical functions, the defects of the background technology are effectively solved, and efficient elevator control and high-quality user experience are realized. The system takes "reservation allocation and execution" as the main line, supports internal users (enterprise employees) to scan and reserve elevators, allocates elevators through intelligent algorithms, and realizes efficient elevator control. The system has good scalability (supports adding new elevators and users), security (identity verification and data encryption), user experience (real-time status display and voice interaction), and can be widely applied to office buildings, shopping malls and other scenarios.

Description

Technical Field

[0001] This invention relates to the field of elevator control management technology, and in particular to an efficient interactive elevator control management method based on elevator QR code reservation, as well as an efficient interactive elevator control management system, electronic equipment, and computer-readable storage medium based on elevator QR code reservation. Background Technology

[0002] Traditional elevator control and management systems primarily rely on IC card access control, in-car button calling, or hall button calling, with core functions focused on basic access verification and command execution. This type of system has significant shortcomings in application:

[0003] First, the interaction efficiency is low, as users have to wait for the elevator to respond on-site and cannot make reservations in advance.

[0004] Secondly, unreasonable resource allocation and lack of intelligent algorithm scheduling can easily lead to elevators running empty or becoming crowded.

[0005] Third, the user experience is poor, with no real-time status feedback and reminder mechanism;

[0006] Fourth, it lacks scalability and is difficult to be compatible with multiple brands of elevator motherboards and newly added functional modules. Summary of the Invention

[0007] To address the technical problems existing in the prior art, the present invention provides the following technical solution:

[0008] On the one hand, a highly efficient interactive elevator control management system based on elevator QR code reservation is provided, including:

[0009] The reservation terminal is used to receive elevator reservation requests from users and verify their identity.

[0010] The cloud-based dispatch center communicates with the reservation terminal and includes a dispatch algorithm service for allocating elevator tasks based on real-time elevator status data.

[0011] The elevator execution terminal, which communicates with the cloud-based dispatch center, includes an edge elevator control terminal and a sensor group, and is used to execute elevator control commands and collect elevator status data.

[0012] The system is configured to trigger the elevator scheduling process by scanning a QR code to make a reservation, and to optimize elevator allocation using a greedy algorithm.

[0013] Preferably, the reservation terminal is a smartphone APP or WeChat mini program, configured to support both QR code reservation and voice input reservation, and integrates Baidu Voice API for voice recognition.

[0014] Preferably, the elevator actuator terminal includes:

[0015] The edge elevator control terminal uses a microcontroller and runs the FreeRTOS real-time operating system.

[0016] The sensor group includes strain gauge load cells, photoelectric switch floor sensors, and magnetically controlled door status sensors;

[0017] The actuator, including a DC24V relay module, is used to control the opening and closing of the elevator doors and the direction of travel.

[0018] Preferably, the scheduling algorithm service of the cloud scheduling center adopts a greedy algorithm, and its optimization objective is to minimize the total waiting time TWT = Σ(t wait,i + t ride,i It is subject to elevator load limits, consistency of running direction, and task queue length constraints, where t wait,i User i's waiting time (time from reservation to elevator arrival); t ride,i User i's travel time (time from leaving the elevator to arriving at the target floor).

[0019] Preferably, the scheduling algorithm service also integrates an LSTM prediction model to predict the elevator running time t based on the elevator's current floor, target floor, and real-time load data. ride,i The prediction results are cached in Redis for use by the greedy algorithm.

[0020] On the other hand, an elevator control management method based on the above-described system is provided, including the following steps:

[0021] User reservation steps: Users submit an elevator reservation request through the reservation terminal, including the target floor and reservation time;

[0022] Cloud-based scheduling steps: The cloud-based scheduling center uses a greedy algorithm to allocate the optimal elevator based on real-time elevator status data;

[0023] Elevator operation steps: The elevator terminal receives and executes control commands to complete the elevator dispatching task;

[0024] Status feedback steps: The elevator actuator collects elevator status data in real time and transmits it back to the cloud.

[0025] Preferably, the user reservation step includes:

[0026] Users can submit reservation requests by scanning a QR code or using voice input.

[0027] The system verifies user identity through methods including employee ID verification, mobile phone verification code verification, or IC card verification.

[0028] The reservation request parameters include reservation type, target floor, and number of accompanying persons.

[0029] Preferably, the greedy algorithm used in the cloud scheduling step includes:

[0030] Input the user list and real-time elevator status data;

[0031] Calculate the cost increment for each user to be assigned to each elevator;

[0032] Select the elevator with the smallest cost increment for allocation;

[0033] Update the elevator task queue and total wait time.

[0034] Preferably, the calculation of the cost increment includes:

[0035] Predict the elevator travel time from its current location to the user's reserved floor using an LSTM model;

[0036] Predict the elevator travel time from the user's reserved floor to the target floor using an LSTM model;

[0037] The sum of user waiting time and travel time is calculated as the cost increment.

[0038] Preferably, the method further includes a fault handling step:

[0039] Real-time monitoring of elevator door status and load data via sensors;

[0040] When it is detected that the door is not closed properly or the load exceeds the limit, the execution relay will be immediately disconnected and an alarm message will be sent to the cloud.

[0041] The cloud system marks the elevator as unavailable and reassigns the task to another elevator.

[0042] On the other hand, an electronic device is provided, comprising: a processor; and a memory storing computer-readable instructions, wherein when the computer-readable instructions are executed by the processor, any one of the methods described above for efficient interactive elevator control management based on elevator QR code reservation is implemented.

[0043] On the other hand, a computer-readable storage medium is provided, wherein at least one instruction is stored in the storage medium, and the at least one instruction is loaded and executed by a processor to implement any of the above-described efficient interactive elevator control management methods based on elevator QR code reservation.

[0044] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0045] By incorporating technologies such as QR code reservation, cloud-based intelligent scheduling, and voice interaction, the system effectively addresses the shortcomings of the aforementioned technologies, achieving efficient elevator control and a superior user experience. The system operates on a "reservation, allocation, and execution" model, supporting internal users (company employees) to reserve elevators via QR code. Intelligent algorithms allocate elevators, enabling efficient elevator control. The system boasts excellent scalability (supporting the addition of new elevators and users), security (authentication and data encryption), and a superior user experience (real-time status display and voice interaction), making it widely applicable in office buildings, shopping malls, and other similar settings. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a block diagram of an efficient interactive elevator control management system based on elevator QR code reservation provided by an embodiment of the present invention;

[0048] Figure 2 This is a flowchart of an efficient interactive elevator control management method based on elevator QR code reservation provided by an embodiment of the present invention. Detailed Implementation

[0049] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0050] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0051] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0052] In this embodiment of the invention, sometimes a subscript such as W1 may be mistakenly written as a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0053] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0054] The application scheme of this system and method will be described in detail below.

[0055] 1. System Overall Architecture

[0056] This system is based on the principle of "reservation, allocation, and execution," allowing internal users (company employees) to reserve elevators by scanning a code. Elevators are allocated through intelligent algorithms to achieve efficient elevator control.

[0057] like Figure 1 As shown, the architecture is divided into three core layers: reservation terminal, cloud dispatch center, and elevator execution terminal. The hardware and software interaction link is as follows: the reservation terminal (hardware) transmits user commands (scanning code / voice) to the cloud dispatch center (software) via WiFi / BLE; the cloud sends the dispatch results to the edge controller (hardware) of the elevator execution terminal via the MQTT protocol; the edge controller controls the elevator motherboard (hardware) to perform actions via the Modbus RTU protocol and sends sensor data (floor / load) back to the cloud to update the status.

[0058] 2. Hardware Components

[0059] Reservation terminals: smartphones (supporting QR code scanning and voice input), and fixed QR code scanners next to elevators (supporting IC cards / QR codes);

[0060] Cloud-based dispatch center: Alibaba Cloud ECS instance (8 cores, 16GB memory, 200GB SSD storage), MySQL database (master-slave architecture), Redis cache;

[0061] Elevator actuator terminal: Specific hardware includes: Edge elevator control terminal: adopts STM32F407ZGT6 microcontroller (1MBFlash, 192KB RAM, supports FreeRTOS real-time operating system), integrates ESP8266 WiFi module (supports 8011b / g / n, realizes MQTT protocol communication with the cloud); Elevator controller interface: communicates with mainstream elevator motherboards such as Otis / Mitsubishi through RS485 interface using Modbus RTU protocol; 3. Sensor group: strain gauge load sensor (accuracy 0.5%, ADC sampling range 0-2000kg), photoelectric switch floor sensor (NPN output, detects the current floor of the elevator), magnetic control door status sensor (detects whether the door is fully closed); 4. Actuator: DC24V relay module (controls elevator door opening and closing, running direction).

[0062] 3. Software Components

[0063] 3.1 Reservation terminal software (APP / Mini Program)

[0064] Technical framework: Flutter (cross-platform development);

[0065] Core functional modules:

[0066] Permission recognition module: Supports recognizing user permissions (e.g., "XX company employee") via mobile verification code, employee ID, IC card, etc.

[0067] Reservation module: Select reservation time (e.g., "Immediate" or "10:00"), target floor (e.g., 15th floor), number of people (e.g., 2 people), and support voice input (e.g., "I want to reserve the elevator on the 15th floor for 2 people").

[0068] Reminder module: Receive service reminders pushed from the cloud (such as "Elevator has been assigned, number 01, estimated arrival time is 5 minutes").

[0069] 3.2 Cloud-based dispatch center software

[0070] Technical framework: Spring Cloud (microservice architecture);

[0071] Core microservices:

[0072] Reservation management service: Stores user reservation information (such as user ID, reservation time, target floor, number of people);

[0073] Scheduling algorithm service: Based on real-time status data collected by elevator execution terminal hardware (such as floor position and strain gauge load data uploaded by STM32 controller), a greedy algorithm is used to dynamically allocate elevators. The algorithm prioritizes elevators with the smallest difference between the current floor and the user's reserved floor and the largest load margin, and generates elevator control task instructions (such as "Elevator 01 descends from the 5th floor to the 1st floor to pick up the user"), which are then sent to the edge elevator control terminal through the ESP8266 WiFi module.

[0074] Task execution service: Generates elevator control tasks and sends them to the elevator execution terminal;

[0075] Voice interaction service: Integrates Baidu voice API to realize voice command recognition (such as converting "I want to reserve the elevator on the 15th floor" into a text command).

[0076] 3.3 Elevator Execution Terminal Software

[0077] (Edge elevator control terminal software): The technical framework is the FreeRTOS real-time operating system. Core modules include: 1. Protocol stack module: Built-in Modbus RTU protocol stack (for communication with the elevator mainboard) and MQTT protocol stack (for communication with the cloud); 2. Task scheduling module: Divided into three tasks: instruction parsing (high priority), communication (medium priority), and sensor acquisition (low priority), ensuring real-time response to cloud instructions; 3. Fault handling module: When faults such as doors not closing properly or overload are detected, the execution relay is immediately disconnected and an MQTT alarm is sent to the cloud; 4. Data synchronization module: The floor and load data collected by the sensors are periodically transmitted back to the cloud Redis cache via the ESP8266 WiFi module.

[0078] 4. System Interaction Principles and Application Steps

[0079] 4.1 Overview of Interaction Principles

[0080] like Figure 2 As shown, the system adopts a closed-loop process of "user reservation → cloud scheduling → elevator execution → service reminder", and optimizes elevator allocation through intelligent algorithms to reduce user waiting time.

[0081] 4.2 Detailed Application Steps

[0082] Step 1: User Reservation

[0083] Internal users open the app, click "Reserve Elevator," and select:

[0084] Reservation type: Immediate reservation / Scheduled reservation (e.g., "10:00");

[0085] Target floor: 15th floor;

[0086] Number of people: 2;

[0087] Permission verification: Enter employee ID (e.g., "123456"), and the cloud verification will pass (the employee ID exists and belongs to XX company).

[0088] Alternatively, you can input via voice: "I want to reserve the elevator on the 15th floor, for 2 people, now." The app will then call the voice recognition API to convert the command into a text message.

[0089] Step 2: Cloud Scheduling

[0090] After the cloud-based reservation management service reads user reservation information through MySQL, the scheduling algorithm service retrieves the real-time status uploaded by the elevator execution terminal from the Redis cache (e.g., elevator 01 is currently on the 3rd floor, load capacity is 200kg), and substitutes it into the greedy algorithm formula TWT= Calculate the total waiting time increment, select the elevator with the smallest increment (e.g., elevator 01) to assign the task, and write the task data to the MySQL master database and synchronize it to the slave database.

[0091] Step 3: Elevator Allocation

[0092] The goal of the greedy algorithm is to minimize the total user wait time, and the constraints include:

[0093] Elevator load limit (e.g., ≤1000kg).

[0094] Elevator direction of travel (if reservations are made in the same direction, the same elevator will be given priority).

[0095] Task queue length (e.g., task queue ≤ 5).

[0096] For example, User A (reservation for the 15th floor, 2 people, immediate) and User B (reservation for the 15th floor, 1 person, immediate) make reservations simultaneously. Currently, elevator 01 is on the 1st floor (load capacity 0kg, empty task queue), and elevator 02 is on the 5th floor (load capacity 300kg, 1 task in the task queue). The greedy algorithm selects elevator 01 and assigns tasks: first pick up User A to the 15th floor, then pick up User B to the 15th floor.

[0097] Step 4: Service Reminder

[0098] The cloud-based dispatch center pushes a service reminder to the user's app: "Elevator has been assigned, number 01, currently on the 1st floor, estimated arrival time is 2 minutes."

[0099] Step 5: Elevator Operation

[0100] The cloud-based task execution service sends the elevator control task { "elevator_id": "elevator_01", "tasks": [ { "command": "up", "target_floor": 15, "user_id": "user_01"}, { "command": "up", "target_floor": 15, "user_id": "user_02"} ]} to the ESP8266 WiFi module of elevator 01 via the MQTT protocol. The edge controller STM32F407 (running the FreeRTOS real-time operating system, with three priority tasks: instruction parsing, communication, and sensor acquisition) receives the task, parses the instruction via the Modbus RTU protocol stack, maps the "up" instruction to the closed signal of the up-moving relay K3 (driven by the DC24V relay module), and sends Modbus RTU instructions (such as 01 06 00 03 00 01 CRC) via the RS485 interface to control the elevator mainboard to move upwards; simultaneously, it activates the photoelectric switch floor sensor (NPN output, STM32). The elevator uses GPIO interrupt acquisition to detect the floor position in real time. The strain gauge load sensor (ADC sampling accuracy 12-bit, sampling frequency 10Hz) collects load data in real time and periodically (1 second / time) sends it back to the cloud Redis cache via MQTT protocol. If the load exceeds the standard (ADC sampling value exceeds the 1000kg threshold) or the door is not closed properly (magnetic switch is continuously low level), the fault handling process is immediately triggered: disconnect the execution relay, send an MQTT alarm to the cloud, and mark the elevator as unavailable.

[0101] Step 6: Completion Notification

[0102] After the elevator completes all its tasks, it sends a status update to the cloud: { "elevator_id": "elevator_01","status": "idle", "floor": 1}. The cloud then pushes a completion notification to the user's app: "The elevator has completed its service. Thank you for using it."

[0103] 5. Intelligent Algorithm Optimization – Multi-person Reservation Allocation Algorithm (Greedy Algorithm)

[0104] 5.1 Problem Description

[0105] When multiple users simultaneously reserve elevators, they need to be allocated reasonably to minimize the total waiting time. For example, if three users simultaneously reserve the 15th floor, and elevator 01 is located on the 1st floor (empty) and elevator 02 is located on the 3rd floor (empty), how should they be allocated?

[0106] 5.2 Algorithm Objective

[0107] Minimize the total waiting time (TWT) for all users:

[0108] ,

[0110] in The prediction is made by an LSTM model. The model input includes hardware acquisition parameters such as the current floor of the elevator (photoelectric switch data), the target floor, and the load (strain gauge data). The prediction results are cached in Redis for the algorithm to call.

[0111] in:

[0112] n: The total number of users currently awaiting allocation;

[0113] : User i's waiting time (time from reservation to elevator arrival);

[0114] User i's travel time (time from leaving the elevator to arriving at the target floor);

[0115] Operating mechanism: By accumulating the waiting time and riding time of each user, the overall service efficiency of the system is quantified, and the greedy algorithm selects the elevator allocation scheme that minimizes the increment of the sum each time.

[0116] Advantages of the solution: It directly focuses on the core user experience metric (waiting time), the algorithm has a clear objective and is easy to calculate, and it is suitable for the rapid decision-making needs of real-time elevator control scenarios.

[0117] 5.3 Algorithm Constraints

[0118] Elevator load limit: ,

[0119] The real-time data collected by the strain gauge load cell (converted by STM32 ADC and uploaded to Redis) is the weight (kg) that elevator j is currently carrying. The default value is the number of users who made reservations × 60kg, which is the estimated weight (kg) of user i and his / her companions / items. The rated load of the elevator (stored in the MySQL configuration table) is the maximum rated load (kg) of elevator j.

[0120] Operating mechanism: When allocating an elevator, first check whether the sum of the current load and the user's estimated weight exceeds the rated value. If it does, the elevator will be excluded.

[0121] Advantages of the solution: It ensures the safe operation of elevators, avoids malfunctions or safety hazards caused by overloading, and optimizes load utilization.

[0122] Elevator travel direction: Users traveling in the same direction are given priority to be assigned to the same elevator (e.g., users going up are assigned to an elevator that is going up).

[0123] Task queue length limit: ( For elevator j's task queue, (Maximum number of tasks, e.g., 5); Symbol definition:

[0124] : The length of the current unfinished task queue for elevator j;

[0125] : The maximum allowed task queue length for elevator j (e.g., 5);

[0126] Operating mechanism: If the task queue of elevator j has reached its limit, no new tasks will be assigned to avoid task backlog and response delay.

[0127] Advantages of the solution: It balances elevator load and response speed, ensuring that each task is processed in a timely manner and improving the user experience.

[0128] 5.4 Algorithm Flow

[0129] enter:

[0130] User list: ,in ( For user i's appointment time, For the target floor, (For user i's load).

[0131] Elevator list: ,in —— Data acquired from photoelectric switch floor sensor (STM32 GPIO interrupt acquisition). Source: Strain gauge load cell (STM32 ADC 12-bit sampling). Stored in the FreeRTOS task queue on the edge controller (queue length ≤ Consistent with the algorithm constraints, tasks are prioritized (urgent tasks > scheduled tasks) and synchronized to MySQL via MQTT;

[0132] Initialization: Total waiting time TWT = 0, allocation result A = {} (A[i] = j means user i is assigned to elevator j).

[0133] Iterate through users: Iterate through each user from morning to night according to their appointment time. .

[0134] Calculate the candidate allocation cost for each elevator: For each elevator Calculate allocation Give Subsequent costs (total waiting time increment):

[0135] Elevator J completes the current task queue Time:

[0136]

[0137] ,in;

[0138] The total time for elevator j to complete all tasks in its task queue, i.e., from the current floor. To user i's reserved floor (e.g., the time on the 1st floor) —f is an LSTM model deployed on the ECS cloud, with input parameters including the current floor of the elevator collected by the photoelectric switch. User-reserved floors Real-time load data collected by strain gauge load cells The model outputs predicted runtime values ​​and caches them in Redis for algorithm calls; The travel time for each task in the queue (the travel time from the departure floor to the destination floor).

[0139] User i's waiting time: (The total time for elevator j to complete the current task queue and reach the floor reserved by user i) Later than user i's appointment time If the waiting time is zero, then the waiting time is the difference between the two values; otherwise, the waiting time is zero.

[0140] User i's travel time: —f is the LSTM model, and the input parameters include the starting floor data collected by the photoelectric switch. Target floor User-reserved load The prediction results are synchronized to the scheduling algorithm service via the MQTT protocol;

[0141] Cost allocation: The cost is the sum of user i's waiting time and ride time, used to evaluate the priority of elevator allocation.

[0142] Choose the optimal elevator: Select the elevator with the lowest cost. ,Will Add to Task queue Update TWT+= Global total latency is optimized by minimizing the allocation cost per user.

[0143] Output: Allocation result A.

[0144] 5.5 Algorithm Application Examples

[0145] Assumption:

[0146] User list: U = {u1(Reservation time 10:00, target floor 15, load capacity 200kg), u2(Reservation time 10:01, target floor 15, load capacity 150kg), u3(Reservation time 10:02, target floor 15, load capacity 100kg)};

[0147] Elevator list: E = {e1(current floor 1, load 0, task queue empty), e2(current floor 3, load 0, task queue empty)};

[0148] The LSTM model predicted the following running times: f(1→15) = 20 seconds (based on the historical running times of floors 1 to 15 collected by the photoelectric switch and the strain gauge load data trained on the model), f(3→1) = 5 seconds (based on the historical floor switching data of floor 3 to 1), and f(3→15) = 18 seconds (based on the load and floor difference data of floors 3 to 15).

[0149] Step 1: Allocate u1

[0150] The cost of e1: =0, →i=f(1→1)=0 seconds, =0+010:00=0 seconds =20 seconds, coste1=0+20=20 seconds;

[0151] The cost of e2: =0, →i=f(3→1)=5 seconds, =0 + 510:00 = 5 seconds =20 seconds, coste2=5+20=25 seconds;

[0152] Select e1, assign u1 to e1, e1's task queue becomes [u1], TWT=20 seconds.

[0153] Step 2: Allocate u2

[0154] The current task queue [u1] of e1, and its completion time. =20 seconds (10:00:20);

[0155] The cost of e1: →i=f(15→1)=20 seconds, =20 + 2061 (10:01 = 61 seconds) = 21 seconds → 0 seconds =20 seconds, =0 + 20 = 20 seconds;

[0156] The cost of e2: =0, →i=f(3→1)=5 seconds, =0 + 561 = 56 seconds → 0 seconds =20 seconds, =0 + 20 = 20 seconds;

[0157] Choose e1 (or e2, either one), assign u2 to e1, and e1's task queue becomes [u1, u2], TWT=20+20=40 seconds.

[0158] Step 3: Allocate u3

[0159] The current task queue [u1, u2] of e1, with completion time =20+20=40 seconds (10:00:40).

[0160] The cost of e1: →i=f(15→1)=20 seconds, =40 + 2062 (10:02 = 62 seconds) = 2 seconds → 0 seconds =20 seconds, =0 + 20 = 20 seconds;

[0161] The cost of e2: =0, →i=f(3→1)=5 seconds, =0 + 562 = 57 seconds → 0 seconds =20 seconds, =0 + 20 = 20 seconds;

[0162] Select e2, assign u3 to e2, e2's task queue becomes [u3], TWT=40+20=60 seconds.

[0163] Final allocation results:

[0164] e1: [u1, u2] (connect u1 to the 15th floor first, then connect u2 to the 15th floor).

[0165] e2: [u3] (connect to u3 to the 15th floor);

[0166] Total wait time: 60 seconds.

[0167] 6. Voice interaction

[0168] 6.1 Technical Solution

[0169] Voice input: Users can record voice commands (such as "I want to reserve the elevator on the 15th floor for 2 people") via the voice input button in the APP.

[0170] Voice recognition: Users collect voice commands through the phone's microphone hardware. The APP calls Baidu Voice ASR's HTTPSRESTful API (to transmit PCM format audio data) to convert the voice into text (such as "I want to reserve the elevator on the 15th floor, for 2 people").

[0171] Intent parsing: The text is parsed using a regular expression rule engine to extract key parameters such as "reservation" (intent), "15th floor" (target floor dᵢ), and "2 people" (user load wᵢ=2×60kg), which are then used as input for the greedy algorithm;

[0172] Scheduled execution: The parsed information is converted into a schedule request and sent to the cloud scheduling center.

[0173] 6.2 Example Process

[0174] The user said, "I want to reserve the elevator on the 15th floor for two people."

[0175] The app records a voice message, calls the Baidu Voice API, and returns the text: "I want to reserve the elevator on the 15th floor, for 2 people."

[0176] Rule engine analysis:

[0177] Intent: To make an appointment;

[0178] Target floor: 15th floor;

[0179] Number of people: 2;

[0180] The app sends a reservation request { "intent": "reserve", "target_floor":15, "num_people": 2} to the Spring Cloud Gateway on Alibaba Cloud ECS via an HTTPS POST request. The gateway forwards the request to the reservation management service, which writes it to the MySQL master database. Simultaneously, it triggers the scheduling algorithm service to read the elevator's real-time status from Redis (e.g., ...). ) to allocate;

[0181] The cloud-based dispatch center processes requests, allocates elevators, and sends service reminders.

[0182] 7. System security

[0183] (1) Authentication

[0184] Visitor side: Optimized to support multi-factor authentication (mobile phone number / verification code, WeChat authorization login, or face recognition) after scanning QR code; users can only use the app after successful verification; added a face recognition module (calls Baidu's face API to collect facial features based on the phone's camera) to improve convenience and security;

[0185] Front-end terminal: Login using account and password (supports multi-factor authentication, such as SMS verification code);

[0186] Internal users: Employee ID + password or IC card authentication is used to ensure that only authorized users can book elevators.

[0187] (2) Data encryption

[0188] Communication encryption: Communication between the visitor terminal and the cloud, and between the cloud and the edge elevator control terminal, uses HTTPS / MQTT TLS encryption to prevent data tampering;

[0189] Storage encryption: User passwords are stored using BCrypt hash encryption, and elevator commands are stored using AES256 encryption.

[0190] (3) Troubleshooting

[0191] Elevator malfunction: The STM32F407 edge controller continuously monitors the door status via a reed switch magnetic control (model J3052Z, STM32 GPIO pin PA0 interrupt trigger detection). If the input pin level remains low for more than 2 seconds, it is determined that the door is not closed properly. Load data is collected via a strain gauge load sensor (model YZC131, STM32 ADC1 channel 12-bit sampling, sampling frequency 10Hz). When the converted ADC sample value exceeds the 1000kg threshold, it is determined that the load is overloaded. After the fault is triggered, the STM32 immediately communicates with the ESP8266. The WiFi module sends an MQTT alarm message (format: {"elevator_id":"e1","fault_type":"door_not_closed" / "overload","timestamp":1620000000}) to the cloud; the cloud scheduling algorithm service marks the elevator as unavailable and excludes it from subsequent allocations, and pushes a fault notification (such as "Elevator e1 door is not closed properly, please switch to another elevator") to the user's APP via the WebSocket protocol;

[0192] Network failure: The edge elevator control terminal supports offline operation (stores unexecuted tasks, which are synchronized to the cloud after the network is restored) to ensure the normal operation of the elevator.

[0193] This solution details the hardware and software components, interaction principles, and application steps of the two elevator control systems. It optimizes elevator running time prediction using an LSTM model and optimizes multi-user reservation allocation using a greedy algorithm, achieving efficient and intelligent elevator control management. The elevator execution terminal adopts a standardized hardware interface (RS485 / Modbus RTU compatible with mainstream elevator motherboards such as Otis and Mitsubishi) and pluggable software modules (FreeRTOS dynamic task loading, protocol stack expandable), supporting rapid access of new elevator terminals. The system features excellent scalability (supporting new elevators and users), security (authentication, data encryption), and user experience (real-time status display, voice interaction), and can be widely used in office buildings, shopping malls, and other scenarios.

[0194] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable system. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0195] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0196] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0197] It should be understood that, in various embodiments of the present invention, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0198] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0199] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, systems, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0200] In the embodiments provided by this invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0201] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0202] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0203] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0204] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A highly efficient interactive elevator control management system based on elevator QR code reservation, characterized in that, include: The reservation terminal is used to receive elevator reservation requests from users and verify their identity. The cloud-based dispatch center communicates with the reservation terminal and includes a dispatch algorithm service for allocating elevator tasks based on real-time elevator status data. The elevator execution terminal, which communicates with the cloud-based dispatch center, includes an edge elevator control terminal and a sensor group, and is used to execute elevator control commands and collect elevator status data. The system is configured to trigger the elevator scheduling process by scanning a QR code to make a reservation, and to optimize elevator allocation using a greedy algorithm.

2. The system according to claim 1, characterized in that, The reservation terminal is a smartphone APP or WeChat mini program, configured to support both QR code reservation and voice input reservation, and integrates Baidu Voice API for voice recognition.

3. The system according to claim 1, characterized in that, The elevator actuator terminal includes: The edge elevator control terminal uses a microcontroller and runs the FreeRTOS real-time operating system. The sensor group includes strain gauge load cells, photoelectric switch floor sensors, and magnetically controlled door status sensors; The actuator, including a DC24V relay module, is used to control the opening and closing of the elevator doors and the direction of travel.

4. The system according to claim 1, characterized in that, The scheduling algorithm service of the cloud scheduling center adopts a greedy algorithm, and its optimization objective is to minimize the total waiting time TWT = Σ(t wait,i + t ride,i It is subject to elevator load limits, consistency of running direction, and task queue length constraints, where t wait,i User i's waiting time (time from reservation to elevator arrival); t ride,i User i's travel time (time from leaving the elevator to arriving at the target floor).

5. The system according to claim 4, characterized in that, The scheduling algorithm service also integrates an LSTM prediction model to predict the elevator running time t based on the elevator's current floor, target floor, and real-time load data. ride,i The prediction results are cached in Redis for use by the greedy algorithm.

6. A ladder control management method based on the system described in any one of claims 1-5, characterized in that, Includes the following steps: user Reservation steps: Users submit elevator reservation requests through the reservation terminal, including the target floor and reservation time; Cloud-based scheduling steps: The cloud-based scheduling center uses a greedy algorithm to allocate the optimal elevator based on real-time elevator status data; Elevator operation steps: The elevator terminal receives and executes control commands to complete the elevator dispatching task; Status feedback steps: The elevator actuator collects elevator status data in real time and transmits it back to the cloud.

7. The method according to claim 6, characterized in that, The user reservation process includes: Users can submit reservation requests by scanning a QR code or using voice input. The system verifies user identity through methods including employee ID verification, mobile phone verification code verification, or IC card verification. The reservation request parameters include reservation type, target floor, and number of accompanying persons.

8. The method according to claim 6, characterized in that, The greedy algorithm used in the cloud scheduling step includes: Input the user list and real-time elevator status data; Calculate the cost increment for each user to be assigned to each elevator; Select the elevator with the smallest cost increment for allocation; Update the elevator task queue and total wait time.

9. The method according to claim 8, characterized in that, The calculation of the cost increment includes: Predict the elevator travel time from its current location to the user's reserved floor using an LSTM model; Predict the elevator travel time from the user's reserved floor to the target floor using an LSTM model; The sum of user waiting time and travel time is calculated as the cost increment.

10. The method according to claim 6, characterized in that, The method also includes fault handling steps: Real-time monitoring of elevator door status and load data via sensors; When it is detected that the door is not closed properly or the load exceeds the limit, the execution relay will be immediately disconnected and an alarm message will be sent to the cloud. The cloud system marks the elevator as unavailable and reassigns the task to another elevator.

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