Floor positioning method and device, computer equipment and storage medium

Abstract

The invention discloses a floor positioning method and device, computer equipment and a storage medium, and the method comprises the steps: collecting atmospheric pressure data at two preset reference floors at the same time, carrying out the calibration through combining with the temperature, and building the floor reference data; during the running period of the elevator, atmospheric pressure and temperature sensor data are collected in real time, the sensor data are processed, and stable fusion data are output; based on the fused data, the running state of the elevator is judged, and the data sampling frequency and filtering parameters are adjusted according to the running state; calculating an expected atmospheric pressure value of a target floor according to the floor reference data and the current atmospheric pressure data; and comparing the atmospheric pressure value compensated by the real-time fusion data with the calculated expected atmospheric pressure value of the target floor, and if the difference value is within a preset tolerance range, judging that the target floor is reached. According to the invention, accurate and stable real-time positioning information can be provided in a complex elevator operation environment.

Description

Technical Field

[0001] The present invention relates to the technical field of floor positioning, and in particular to a floor positioning method, device, computer equipment and storage medium. Background Art

[0002] Currently, elevator floor positioning systems primarily rely on visual displays, LED indicators, and touch buttons to inform users of their current floor. This meets basic needs for average users. However, for people with visual impairments, traditional visual and touch interaction methods have significant limitations, making it difficult for them to accurately obtain floor information while riding, thus impacting travel safety and convenience.

[0003] Some existing systems attempt to calculate floor height using a single air pressure sensor. However, due to the complex internal environment of an elevator, affected by factors such as acceleration and deceleration, and local air pressure fluctuations, data from a single sensor often exhibits instability and errors, making accurate and real-time floor determination impossible. Furthermore, traditional data processing algorithms lack adaptability, making it difficult to quickly adjust parameters as the elevator's operating state changes, further exacerbating positioning errors. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to propose a floor positioning method, a floor positioning device, a computer device and a storage medium to solve the technical problem that visually impaired people cannot accurately obtain floor information.

[0005] In order to solve the above technical problems, the embodiment of the present application provides a floor positioning method, which adopts the following technical solutions:

[0006] A floor positioning method comprises the following steps:

[0007] Atmospheric pressure data is collected simultaneously on two predetermined reference floors, and calibrated with temperature to establish floor reference data;

[0008] During elevator operation, atmospheric pressure and temperature sensor data are collected in real time, and the sensor data is processed and output as stable fusion data;

[0009] Based on the fused data, determine the operating status of the elevator, and adjust the data sampling frequency and filtering parameters according to the operating status;

[0010] Calculating the expected atmospheric pressure value of the target floor based on the floor reference data and the current atmospheric pressure data;

[0011] The atmospheric pressure value after real-time fusion data compensation is compared with the calculated expected atmospheric pressure value of the target floor. If the difference between the two is within the preset tolerance range, it is determined that the target floor has been reached.

[0012] In a possible implementation, the step of calculating the expected atmospheric pressure value of the target floor based on the floor reference data and the current atmospheric pressure data specifically includes:

[0013] Atmospheric pressure values ​​PA and PB and their corresponding height difference H are collected on two predetermined floors, and the pressure change rate per unit height K = (PB – PA) / H is calculated;

[0014] The real-time atmospheric pressure P0 is collected at the elevator starting floor, and temperature compensation is performed using a linear temperature compensation model;

[0015] According to the floor difference ΔN and the single-floor height set by the user, the target height difference h = ΔN × the single-floor height is determined;

[0016] Calculate the target pressure change ΔP using the pressure change rate K and the target height difference h target =K×h;

[0017] Calculate the expected atmospheric pressure value at the target floor based on the elevator's running direction:

[0018] Up: P obj_lin =P0–ΔP target ,

[0019] Downward: P obj_lin =P0+ΔP target ;

[0020] Output the expected atmospheric pressure value P of the target floor obj_lin .

[0021] In a possible implementation, the step of collecting the real-time atmospheric pressure P0 at the elevator starting floor and performing temperature compensation using a linear temperature compensation model specifically includes:

[0022] Before the elevator starts, make sure the elevator is stationary at the starting floor and start collecting the current atmospheric pressure data at a sampling frequency of 10 Hz, which is recorded as P raw ;

[0023] Collect temperature data T and humidity data;

[0024] The collected atmospheric pressure data is temperature compensated, and the temperature compensation model is used as P comp =P raw +a×T+b×T 2 , where a and b are compensation coefficients, P comp is the compensated atmospheric pressure data;

[0025] The atmospheric pressure data after compensation P comp Perform real-time filtering and output a stable starting atmospheric pressure P0.

[0026] In a possible implementation, the output target floor's expected atmospheric pressure value P obj After the steps, it also includes:

[0027] During the operation of the elevator, the atmospheric pressure data P is continuously collected and temperature compensated in real time at a sampling frequency of 10 Hz. measured ;

[0028] Continue to P measured With the expected atmospheric pressure value P obj Make comparisons;

[0029] When |P measured -P obj_lin When |<∈, it is determined that the target floor has been reached, where ∈ is the preset tolerance.

[0030] In a possible implementation manner, when |P measured -P obj_lin When |<∈, it is determined that the target floor has been reached, where ∈ is a preset tolerance. After that, the following steps are also included:

[0031] Using the current temperature-compensated data and the current temperature T, the target pressure value P is calculated using the isothermal atmospheric model. obj_iso , Where g is the acceleration due to gravity, M is the molar mass of air, R is the universal gas constant, and h is the target height difference;

[0032] Calculate the difference between the isothermal atmospheric model and the linear temperature compensation model, δ = |P obj_lin -P obj_iso |;

[0033] If δ is less than ∈, the calculation result of the linear temperature compensation model is considered stable and reliable, and the output P obj =P obj_lin ;

[0034] If δ is greater than or equal to ∈, it is considered that the linear temperature compensation model has a large prediction deviation, and it automatically switches to the isothermal atmospheric model and outputs P obj =P obj_iso .

[0035] In one possible implementation, in the step of determining the operating state of the elevator based on the fused data and adjusting the data sampling frequency and filtering parameters according to the operating state, when the acceleration modulus is close to the acceleration due to gravity and has little fluctuation, and the angular velocity is almost zero, it is determined that the elevator is in a stationary state;

[0036] If a rapid change in the acceleration modulus or a sudden increase in the angular velocity is detected, it is determined that the elevator is in the acceleration or deceleration stage;

[0037] When the elevator is in a non-stationary state, but the acceleration and angular velocity remain within a small and stable range, it is determined that the elevator is in a uniform speed operation state.

[0038] In a possible implementation, after comparing the atmospheric pressure value compensated by the real-time fusion data with the calculated expected atmospheric pressure value of the target floor, and if the difference between the atmospheric pressure value and the atmospheric pressure value is within a preset tolerance range, determining that the target floor has been reached, the step further includes:

[0039] After determining that the target floor has been reached, the floor information is fed back to the user in the form of voice announcements and vibration prompts.

[0040] In order to solve the above technical problems, the embodiment of the present application further provides a floor positioning device, which adopts the following technical solution:

[0041] A floor positioning device, comprising:

[0042] The acquisition module is used to simultaneously collect atmospheric pressure data on two predetermined reference floors, calibrate it in combination with temperature, and establish floor reference data;

[0043] The processing module is used to collect atmospheric pressure and temperature sensor data in real time during elevator operation, process the sensor data and output stable fusion data;

[0044] A judgment module, configured to judge the operating status of the elevator based on the fused data, and adjust the data sampling frequency and filtering parameters according to the operating status;

[0045] a calculation module, configured to calculate an expected atmospheric pressure value of a target floor based on the floor reference data and current atmospheric pressure data;

[0046] The comparison module is used to compare the atmospheric pressure value after real-time fusion data compensation with the calculated expected atmospheric pressure value of the target floor. If the difference between the two is within the preset tolerance range, it is determined that the target floor has been reached.

[0047] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0048] A computer device includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the floor positioning method described above when executing the computer-readable instructions.

[0049] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0050] A computer-readable storage medium stores computer-readable instructions, which implement the steps of the floor positioning method described above when executed by a processor.

[0051] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0052] The floor positioning method disclosed in the present application establishes floor reference data by simultaneously collecting atmospheric pressure data on two predetermined reference floors and calibrating it in combination with temperature, humidity and inertial data; during elevator operation, atmospheric pressure, temperature, humidity and inertial sensor data are collected in real time, each sensor data is processed and stable fusion data is output; based on the fusion data, the operating status of the elevator is judged, and the data sampling frequency and filtering parameters are adjusted according to the operating status; based on the floor reference data and the current atmospheric pressure data, the expected atmospheric pressure value of the target floor is calculated; the atmospheric pressure value after the real-time fusion data compensation is compared with the calculated expected atmospheric pressure value of the target floor, and if the difference between the two is within the preset tolerance range, it is determined that the target floor has been reached. The present application realizes closed-loop control of the entire process of elevator floor positioning through multi-sensor data collection, fusion and temperature compensation, and can provide accurate and stable real-time positioning information in complex elevator operating environments. It is particularly suitable for providing reliable non-visual floor prompts for people with visual impairments. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the solutions in this application, a brief introduction will be given below to the drawings required for use in the description of the embodiments of this application. Obviously, the drawings described below are some embodiments of this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0054] Figure 1 is a flow chart of an embodiment of a floor positioning method according to the present application;

[0055] Figure 2 is a structural schematic diagram of an embodiment of a floor positioning device according to the present application;

[0056] Figure 3 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solutions and advantages of this application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0058] refer to Figure 1 , shows a flow chart of an embodiment of a floor positioning method according to the present application. The floor positioning method comprises the following steps:

[0059] Step S101 : Atmospheric pressure data is collected simultaneously on two predetermined reference floors, and calibrated in combination with temperature to establish floor reference data.

[0060] In this embodiment, the electronic device on which the floor positioning method is executed can send or receive data via a wired connection or a wireless connection. It should be noted that the wireless connection method may include but is not limited to 3G / 4G / 5G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultrawideband) connection, and other wireless connection methods currently known or to be developed in the future.

[0061] In this embodiment, atmospheric pressure data is first collected simultaneously on two predetermined reference floors, and calibrated in combination with temperature, humidity and inertial data to establish floor reference data. This process utilizes the basic physical principle that atmospheric pressure changes with altitude - that is, as the altitude increases, the atmospheric pressure will show a linear or approximately linear decrease. By collecting data from, for example, Building A and Building B, the rate of change of air pressure per unit height can be calculated, and the atmospheric pressure value can be corrected using temperature and humidity data to eliminate the impact of environmental conditions on the sampled data; and the data from inertial sensors (such as accelerometers and gyroscopes) is used to calibrate the state of the elevator when it is stationary, providing a stable benchmark for subsequent real-time calculations. This step is applicable to scenarios where precise measurement of floor height differences is required within a building, laying the foundation for the subsequent calculation of the expected air pressure value of the target floor.

[0062] Step S102: During the operation of the elevator, atmospheric pressure and temperature sensor data are collected in real time, the sensor data are processed and stable fusion data is output.

[0063] In this embodiment, during elevator operation, the system collects atmospheric pressure, temperature, humidity, and inertial sensor data in real time. This data undergoes preprocessing, such as zero-point correction and low-pass filtering, to eliminate high-frequency noise and environmental interference. By employing a data fusion algorithm (such as Kalman filtering or mean filtering), the sensor data is integrated into a stable set of fused data. This not only improves the reliability of individual sensor data but also enables the elevator to output smooth and accurate environmental parameters in various states, such as acceleration, deceleration, and uniform motion. This step is critical during elevator operation, as elevator motion is often accompanied by rapid changes and transient interference. The fused data helps provide continuous and stable input for subsequent positioning calculations.

[0064] Step S103: Based on the fused data, the operating status of the elevator is determined, and the data sampling frequency and filtering parameters are adjusted according to the operating status.

[0065] In this embodiment, based on the above-mentioned fused data, the system further determines the operating status of the elevator. This step determines whether the elevator is currently at rest, accelerating / decelerating, or in constant motion by extracting the inertial components (such as acceleration and angular velocity) from the fused data. The judgment result is crucial for the dynamic adjustment of subsequent data sampling frequency and filtering parameters. For example, in a stationary state, the system can reduce the sampling frequency and extend the filter window to achieve higher data smoothness; while in the acceleration or deceleration stage, it is necessary to increase the sampling frequency and shorten the filter window to quickly respond to data changes. This dynamic adjustment ensures that no matter what operating state the elevator is in, the collected data can meet the positioning accuracy requirements. Especially for people with visual impairments, it is crucial to ensure the timeliness and accuracy of floor prompts.

[0066] Step S104: Calculate the expected atmospheric pressure value of the target floor according to the floor reference data and the current atmospheric pressure data.

[0067] In this embodiment, the system calculates the expected atmospheric pressure at the target floor based on established floor reference data and the current temperature-compensated atmospheric pressure data. The atmospheric pressure change rate between the reference floors, combined with the user-defined target floor difference and the floor height, is used to calculate the atmospheric pressure change from the starting floor to the target floor. The expected atmospheric pressure at the target floor is then determined through addition and subtraction operations based on the elevator's ascending or descending direction. This calculation process relies on the fundamental physical relationship between atmospheric pressure and altitude, and incorporates actual measured data for temperature and humidity compensation, ensuring high accuracy across diverse environmental conditions.

[0068] Step S105 : Compare the atmospheric pressure value after real-time fusion data compensation with the calculated expected atmospheric pressure value of the target floor. If the difference between the two is within a preset tolerance range, it is determined that the target floor has been reached.

[0069] In this embodiment, the system compares the temperature-compensated atmospheric pressure value in the real-time fusion data with the calculated expected atmospheric pressure value of the target floor. When the difference between the two is within a preset tolerance range (for example, 12 Pa corresponds to a height error of approximately 1 meter), the system determines that the target floor has been reached. This judgment not only relies on the continuous comparison of environmental data, but can also be combined with the static state information provided by the inertial sensor to ensure that the final judgment result is output only after the elevator has completely stopped. This step is ultimately fed back to the user through voice, vibration, or wireless signals, meeting the non-visual interaction needs of visually impaired users for floor positioning and ensuring that they can know in a timely and accurate manner that the elevator has reached the target floor.

[0070] This application realizes closed-loop control of the entire process of elevator floor positioning through multi-sensor data collection, fusion and temperature compensation. It can provide accurate and stable real-time positioning information in complex elevator operating environments, and is particularly suitable for providing reliable non-visual floor prompts for people with visual impairments.

[0071] In some optional implementations of this embodiment, the step of calculating the expected atmospheric pressure value of the target floor based on the floor reference data and the current atmospheric pressure data specifically includes:

[0072] Atmospheric pressure values ​​PA and PB and their corresponding height difference H are collected on two predetermined floors, and the pressure change rate per unit height K = (PB – PA) / H is calculated;

[0073] The real-time atmospheric pressure P0 is collected at the elevator starting floor, and temperature compensation is performed using a linear temperature compensation model;

[0074] According to the floor difference ΔN and the single-floor height set by the user, the target height difference h = ΔN × the single-floor height is determined;

[0075] Calculate the target pressure change ΔP using the pressure change rate K and the target height difference h target =K×h;

[0076] Calculate the expected atmospheric pressure value at the target floor based on the elevator's running direction:

[0077] Up: P obj_lin =P0–ΔP target ,

[0078] Downward: P obj_lin =P0+ΔP target ;

[0079] Output the expected atmospheric pressure value P of the target floor obj_lin .

[0080] In this embodiment, first, the atmospheric pressure values PA and PB at two predetermined reference floors are collected, and the actual height difference H between the two floors is recorded at the same time. Using these two data, the atmospheric pressure change rate K per unit height can be calculated, that is, K = (PB - PA) / H, which is based on the basic physical law that atmospheric pressure changes with altitude. Inside the building, due to the relatively small floor height, it is generally considered that the atmospheric pressure changes linearly. By obtaining the K value, the system can understand the atmospheric pressure change corresponding to each 1-meter rise or fall, which provides a key parameter for subsequent target floor calculation. Next, the current atmospheric pressure data P0 at the starting floor of the elevator is collected in real time, and combined with the temperature sensor data, a linear temperature compensation model is used to correct P0. The role of temperature compensation is to eliminate the influence of environmental temperature change on the atmospheric pressure measurement result, and to ensure that the current data is more accurate. Temperature compensation usually uses a simple linear formula, for example, P0' = P0 + k1 · T + k2 · T2, where k1 and k2 are compensation coefficients determined by experiment, and T is the temperature value. The P0' obtained after compensation is used as the actual starting atmospheric pressure. Then, according to the user-set floor difference ΔN (positive value indicating up, negative value indicating down) and the single-layer height (for example, 3 meters per floor), the target height difference h is calculated, that is, h = ΔN × single-layer height, so that the height distance that the elevator crosses from the starting floor to the target floor is determined, which provides a basis for calculating the pressure change. Then, using the unit height atmospheric pressure change rate K calculated before and the target height difference h, the target pressure change amount ΔP target = K × h can be obtained, which represents the theoretical pressure change amount between the target floor and the starting floor. Due to the different directions of the elevator, the actual calculation needs to be adjusted according to the direction. If the elevator is going up (the target floor is higher than the starting floor), the atmospheric pressure decreases with the height, so the target pressure should be lower than the starting pressure; conversely, when going down, the target pressure should be higher than the starting pressure. Therefore, the expected atmospheric pressure value P obj_lin of the target floor is finally determined according to the direction of the elevator:

[0081] When going up: P obj_lin = P0 - ΔP target ;

[0082] When going down: P obj_lin = P0 + ΔP target ;

[0083] Finally, the system outputs this expected atmospheric pressure value P obj_lin , which is used for comparison with the compensated atmospheric pressure value collected in the subsequent real-time monitoring process to determine whether the elevator has reached the target floor.

[0084] Overall, this step leverages the principle that atmospheric pressure varies linearly with altitude, combined with temperature compensation, to accurately calculate the expected atmospheric pressure at the target floor. This provides a scientific basis for elevator positioning and is particularly suitable for providing non-visual floor information for people with visual impairments in elevator environments. This method enables the system to obtain relatively accurate floor location information in dynamic environments, and subsequent comparisons allow for accurate floor determination, ensuring timely and reliable positioning feedback.

[0085] This application calculates the expected atmospheric pressure value of the target floor by using floor reference data and real-time atmospheric pressure data. This step converts the abstract floor difference set by the user into a specific air pressure change, providing a scientific and quantitative basis for subsequent floor arrival judgment, thereby improving the accuracy and reliability of positioning.

[0086] In some optional implementations of this embodiment, the step of collecting the real-time atmospheric pressure P0 at the elevator starting floor and performing temperature compensation using a linear temperature compensation model specifically includes:

[0087] Before the elevator starts, make sure the elevator is stationary at the starting floor and start collecting the current atmospheric pressure data at a sampling frequency of 10 Hz, which is recorded as P raw ;

[0088] Collect temperature data T and humidity data;

[0089] The collected atmospheric pressure data is temperature compensated, and the temperature compensation model is used as P comp =P raw +a×T+b×T 2 , where a and b are compensation coefficients, P comp is the compensated atmospheric pressure data;

[0090] The atmospheric pressure data after compensation P comp Perform real-time filtering and output a stable starting atmospheric pressure P0.

[0091] In this embodiment, before the elevator starts, in order to ensure the accuracy of the measurement data, it is necessary to first ensure that the elevator is in a stationary state. At this time, the environment inside and outside the elevator is relatively stable, avoiding the instantaneous fluctuation of air pressure caused by the movement of the elevator. Subsequently, the system collects the current atmospheric pressure data at a sampling frequency of 10Hz, which is recorded as P raw. A higher sampling frequency can capture subtle changes and provide sufficient data for subsequent filtering to extract stable values ​​from data fluctuations. The principle of this step is based on the working principle of the atmospheric pressure sensor to ensure that the data can represent the actual environmental conditions. At the same time, the system synchronously collects temperature data T and humidity data. Temperature and humidity have an impact on the output of the atmospheric pressure sensor because the sensor may drift or respond nonlinearly under different temperature conditions. The purpose of collecting this data is to provide the necessary parameters for subsequent temperature compensation, to ensure that the measured atmospheric pressure data is closer to the actual environmental value, and to avoid errors introduced by environmental factors. Next, the collected raw atmospheric pressure data P raw Perform temperature compensation. The linear temperature compensation model used is: P comp =P raw +a×T+b×T 2 , where a and b are compensation coefficients obtained through experimental calibration. This formula uses the linear and quadratic terms of temperature data to correct the sensor output. Its principle is to compensate for the sensor error caused by temperature changes. Through this temperature compensation, P comp It can more accurately reflect the actual atmospheric pressure value, thereby improving the accuracy of floor positioning. The compensation process is particularly important in elevator environments because air conditioning and heat sources in elevators may cause temperature fluctuations, thereby affecting sensor readings. Finally, the compensated atmospheric pressure data P comp Perform real-time filtering. This filtering method can use moving average or digital low-pass filtering to remove random noise and transient interference, outputting a stable starting atmospheric pressure value, P0. Real-time filtering smoothes the data, providing a reliable basis for subsequent calculations of expected floor pressure values. This step ensures a stable, calibrated pressure reading at elevator startup, resulting in greater accuracy in subsequent target floor calculations.

[0092] This application uses a linear temperature compensation model to correct the air pressure data collected in real time on the starting floor, which not only eliminates the errors caused by fluctuations in ambient temperature and humidity, but also ensures stable data output through high-frequency sampling and filtering, providing an accurate starting reference for the entire positioning system and enhancing the robustness of the positioning system.

[0093] In some optional implementations of this embodiment, the expected atmospheric pressure value P of the output target floor is obj After the steps, it also includes:

[0094] During the operation of the elevator, the atmospheric pressure data P is continuously collected and temperature compensated in real time at a sampling frequency of 10 Hz. measured ;

[0095] Continue to P measured With the expected atmospheric pressure value P obj Make comparisons;

[0096] When |P measured -P obj_lin When |<∈, it is determined that the target floor has been reached, where ∈ is the preset tolerance.

[0097] In this embodiment, the atmospheric pressure data collected in real time is compared with the theoretical expected value to determine whether the elevator has reached the target floor. The principle that atmospheric pressure changes linearly with altitude ensures that when the elevator moves to the predetermined height, the actually measured air pressure should be close to the calculated expected value. Continuous comparison enables the system to monitor data changes in real time during elevator movement and dynamically determine the arrival time of the floor. The introduction of a preset tolerance ∈ can tolerate certain measurement errors and environmental interference, avoiding misjudgments due to instantaneous fluctuations. Environmental interference and dynamic changes are relatively common during elevator operation. Real-time data collection and temperature compensation can ensure data stability. For visually impaired users, the system can automatically determine whether the elevator has reached the target floor, thereby triggering subsequent prompts, thereby improving safety and reliability.

[0098] This application continuously compares the atmospheric pressure data collected in real time and temperature compensated with the expected target pressure value, and uses the preset tolerance as the judgment standard. This step realizes the functions of dynamic detection and automatic judgment of whether the elevator has reached the target floor, providing users with timely and accurate floor positioning feedback.

[0099] In some optional implementations of this embodiment, when |P measured -P obj_lin When |<∈, it is determined that the target floor has been reached, where ∈ is a preset tolerance. After that, the following steps are also included:

[0100] Using the current temperature-compensated data and the current temperature T, the target pressure value P is calculated using the isothermal atmospheric model. obj_iso , Where g is the acceleration due to gravity, M is the molar mass of air, R is the universal gas constant, and h is the target height difference;

[0101] Calculate the difference between the isothermal atmospheric model and the linear temperature compensation model, δ = |P obj_lin -P obj_iso |;

[0102] If δ is less than ∈, the calculation result of the linear temperature compensation model is considered stable and reliable, and the output P obj =P obj_lin ;

[0103] If δ is greater than or equal to ∈, it is considered that the linear temperature compensation model has a large prediction deviation, and it automatically switches to the isothermal atmospheric model and outputs P obj =P obj_iso .

[0104] In this embodiment, the physical principles of two air pressure models are used: the linear model is simple and efficient, but deviations may occur under certain environmental conditions (such as when the temperature fluctuates drastically); the isothermal model takes into account the nonlinear effect of temperature changes on air pressure. By comparing the differences in the predicted values ​​of the two models, a more accurate prediction method can be dynamically selected. Through adaptive model switching, the system can automatically correct the prediction error according to the actual situation in the elevator environment, thereby ensuring the accuracy of the target air pressure value. This is crucial to the accuracy of floor positioning, because a slight error may cause positioning failure or delayed feedback. In different buildings or elevator internal environments, the temperature and humidity may vary greatly. For visually impaired users, accurate floor prompts are very important. This step ensures that no matter how the environment changes, the system can select the optimal calculation model for positioning, thereby improving the robustness and safety of the overall positioning.

[0105] This application effectively solves the prediction error problem caused by ambient temperature changes and nonlinear factors by introducing a comparison and adaptive switching mechanism between the isothermal atmospheric model and the linear model, thereby automatically selecting a more accurate calculation model and further improving the accuracy of floor positioning and system adaptability.

[0106] In some optional implementations of this embodiment, in the step of determining the operating state of the elevator based on the fused data and adjusting the data sampling frequency and filtering parameters according to the operating state, when the acceleration modulus is close to the acceleration due to gravity and has little fluctuation, and the angular velocity is almost zero, it is determined that the elevator is in a stationary state;

[0107] If a rapid change in the acceleration modulus or a sudden increase in the angular velocity is detected, it is determined that the elevator is in the acceleration or deceleration stage;

[0108] When the elevator is in a non-stationary state, but the acceleration and angular velocity remain within a small and stable range, it is determined that the elevator is in a uniform speed operation state.

[0109] In this embodiment, acceleration and angular velocity are used to reflect the elevator's motion state based on inertial sensor data. When stationary, sensor data is stable, with acceleration primarily due to gravity. During acceleration, deceleration, or vibration, the data fluctuates significantly. During uniform motion, while the data is non-zero, the fluctuations are minimal and stable. The sampling frequency and filtering parameters are adjusted based on the different motion states, enabling the system to capture dynamic data at a higher sampling rate during rapid changes and to use a longer filtering window for smoother data during periods of stationary or uniform motion. This dynamic adjustment ensures both rapid response and stability in data processing. During operation, an elevator undergoes various phases: starting, accelerating, maintaining a constant speed, decelerating, and coming to a complete stop. Each phase requires different data accuracy and response speed. For visually impaired users, accurately determining the elevator's state can improve the real-time and reliability of positioning feedback, ensuring that users are promptly notified when the elevator reaches the correct floor.

[0110] This application determines the elevator operating status based on fused data and dynamically adjusts the data sampling frequency and filtering parameters, so that the system can maintain the optimal balance of data processing under different motion states, ensuring both rapid response to the elevator startup and acceleration stages, and data smoothness in the stationary and uniform speed stages, providing more reliable support for the positioning process.

[0111] In some optional implementations of this embodiment, after comparing the atmospheric pressure value compensated by the real-time fusion data with the calculated expected atmospheric pressure value of the target floor, and if the difference between the atmospheric pressure value and the real-time fusion data is within a preset tolerance range, determining that the target floor has been reached further includes:

[0112] After determining that the target floor has been reached, the floor information is fed back to the user in the form of voice announcements and vibration prompts.

[0113] In this embodiment, when the atmospheric pressure value measured in real time matches the expected value within the set tolerance, it means that the elevator has reached the target height. At this time, the system automatically triggers feedback to convey the positioning information to the user. Voice and vibration are both non-visual feedback methods and are suitable for people with visual impairments. This step not only realizes the automatic determination of floor arrival, but also ensures that the user can accurately know that the elevator has reached the target floor through multimodal feedback (voice, vibration, etc.). The diversity of feedback methods increases the applicability of the system and improves user experience and safety. For visually impaired users, non-visual feedback mechanisms are particularly critical. Voice broadcasts can clearly inform users of floor information, while vibration prompts provide users with intuitive tactile signals. This combination ensures that users can perceive that the elevator has reached the expected floor even in a noisy environment, reducing confusion or accidents caused by untimely information transmission.

[0114] This application provides users with intuitive and timely information through multimodal feedback methods such as voice broadcast and vibration prompts after the floor arrival determination. It is particularly suitable for visually impaired users, significantly improves the safety of use and user experience, and ensures that users can receive clear prompts when the elevator reaches the target floor.

[0115] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0116] Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0117] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware via computer-readable instructions. The computer-readable instructions can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes in the above-described method embodiments. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0118] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0119] Further references Figure 2 , as a response to the above Figure 1 The present application provides an embodiment of a floor positioning device for realizing the method shown in FIG. Figure 1Corresponding to the method embodiment shown, the system can be specifically applied to various electronic devices.

[0120] like Figure 2 As shown, the floor positioning device 200 described in this embodiment includes: a collection module 201, a processing module 202, a judgment module 203, a calculation module 204 and a comparison module 205.

[0121] in:

[0122] The acquisition module 201 is used to simultaneously acquire atmospheric pressure data on two predetermined reference floors, calibrate it in combination with temperature, and establish floor reference data;

[0123] The processing module 202 is used to collect atmospheric pressure and temperature sensor data in real time during elevator operation, process the sensor data and output stable fusion data;

[0124] A judgment module 203 is used to judge the operating status of the elevator based on the fused data, and adjust the data sampling frequency and filtering parameters according to the operating status;

[0125] A calculation module 204 is configured to calculate an expected atmospheric pressure value of a target floor based on the floor reference data and the current atmospheric pressure data;

[0126] The comparison module 205 is used to compare the atmospheric pressure value after the real-time fusion data is compensated with the calculated expected atmospheric pressure value of the target floor. If the difference between the two is within a preset tolerance range, it is determined that the target floor has been reached.

[0127] The floor positioning device provided in the embodiment of the present invention can implement all the processes of the floor positioning method of the above embodiment. The functions of each module in the device and the technical effects achieved are respectively the same as the functions and technical effects achieved by the floor positioning method of the above embodiment, and will not be repeated here.

[0128] To solve the above technical problems, the present application also provides a computer device. Figure 3 , Figure 3 This is a basic structural block diagram of the computer device in this embodiment.

[0129] The computer device 3 includes a memory 31, a processor 32, and a network interface 33 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 3 with components 31-33, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0130] The computer device may be a desktop computer, notebook computer, PDA, cloud server, etc. The computer device may interact with the user via a keyboard, mouse, remote control, touchpad, or voice control device.

[0131] The memory 31 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 31 can be an internal storage unit of the computer device 3, such as the hard disk or memory of the computer device 3. In other embodiments, the memory 31 can also be an external storage device of the computer device 3, such as a plug-in hard disk equipped on the computer device 3, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Of course, the memory 31 can also include both the internal storage unit of the computer device 3 and its external storage device. In this embodiment, the memory 31 is generally used to store the operating system and various application software installed on the computer device 3, such as computer-readable instructions for the floor positioning method. In addition, the memory 31 can also be used to temporarily store various types of data that have been output or are to be output.

[0132] In some embodiments, the processor 32 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 32 is generally used to control the overall operation of the computer device 3. In this embodiment, the processor 32 is used to execute computer-readable instructions or process data stored in the memory 31, such as computer-readable instructions for executing the floor location method.

[0133] The network interface 33 may include a wireless network interface or a wired network interface. The network interface 33 is generally used to establish a communication connection between the computer device 3 and other electronic devices.

[0134] The computer equipment provided in this application realizes closed-loop control of the entire process of elevator floor positioning through multi-sensor data acquisition, fusion and temperature compensation. It can provide accurate and stable real-time positioning information in complex elevator operating environments, and is particularly suitable for providing reliable non-visual floor prompts for people with visual impairments.

[0135] The present application also provides another embodiment, namely, providing a computer-readable storage medium, which stores computer-readable instructions. The computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the floor positioning method as described above.

[0136] The computer-readable storage medium provided in this application realizes closed-loop control of the entire process of elevator floor positioning through multi-sensor data acquisition, fusion and temperature compensation. It can provide accurate and stable real-time positioning information in complex elevator operating environments, and is particularly suitable for providing reliable non-visual floor prompts for people with visual impairments.

[0137] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0138] The above are only preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A floor positioning method, characterized in that: The steps include: Atmospheric pressure data is collected simultaneously on two predetermined reference floors, and calibrated with temperature to establish floor reference data; During elevator operation, atmospheric pressure and temperature sensor data are collected in real time, and the sensor data is processed and output as stable fusion data; Based on the fused data, determine the operating status of the elevator, and adjust the data sampling frequency and filtering parameters according to the operating status; Calculating the expected atmospheric pressure value of the target floor based on the floor reference data and the current atmospheric pressure data; The atmospheric pressure value after real-time fusion data compensation is compared with the calculated expected atmospheric pressure value of the target floor. If the difference between the two is within the preset tolerance range, it is determined that the target floor has been reached.

2. The floor positioning method according to claim 1, characterized in that: The step of calculating the expected atmospheric pressure value of the target floor based on the floor reference data and the current atmospheric pressure data specifically includes: Atmospheric pressure values ​​PA and PB and their corresponding height difference H are collected on two predetermined floors, and the pressure change rate per unit height K = (PB – PA) / H is calculated; The real-time atmospheric pressure P0 is collected at the elevator starting floor, and temperature compensation is performed using a linear temperature compensation model; According to the floor difference ΔN and the single-floor height set by the user, the target height difference h = ΔN × the single-floor height is determined; Calculate the target pressure change ΔP using the pressure change rate K and the target height difference h. target =K×h; Calculate the expected atmospheric pressure value at the target floor based on the elevator's running direction: Up: P obj_lin =P0–ΔP target , Downward: P obj_lin =P0+ΔP target ; Output the expected atmospheric pressure value P of the target floor obj_lin .

3. The floor positioning method according to claim 2, characterized in that: The step of collecting the real-time atmospheric pressure P0 at the elevator starting floor and performing temperature compensation using a linear temperature compensation model specifically includes: Before the elevator starts, make sure the elevator is stationary at the starting floor and start collecting the current atmospheric pressure data at a sampling frequency of 10 Hz, which is recorded as P raw ; Collect temperature data T and humidity data; The collected atmospheric pressure data is temperature compensated, and the temperature compensation model is used as P comp =P raw +a×T+b×T 2 , where a and b are compensation coefficients, P comp is the compensated atmospheric pressure data; The atmospheric pressure data after compensation P comp Perform real-time filtering and output a stable starting atmospheric pressure P0.

4. The floor positioning method according to claim 2, characterized in that: The expected atmospheric pressure value P of the output target floor obj After the steps, it also includes: During the operation of the elevator, the atmospheric pressure data P is continuously collected and temperature compensated in real time at a sampling frequency of 10 Hz. measured ; Continue to P measured With the expected atmospheric pressure value P obj Make comparisons; When |P measured -P obj_lin When |<∈, it is determined that the target floor has been reached, where ∈ is the preset tolerance.

5. The floor positioning method according to claim 4, characterized in that: When the |P measured -P obj_lin When |<∈, it is determined that the target floor has been reached, where ∈ is a preset tolerance. After that, the following steps are also included: Using the current temperature-compensated data and the current temperature T, the target pressure value P is calculated using the isothermal atmospheric model. obj_iso , Where g is the acceleration due to gravity, M is the molar mass of air, R is the universal gas constant, and h is the target height difference; Calculate the difference between the isothermal atmospheric model and the linear temperature compensation model, δ = |P obj_lin -P obj_iso |; If δ is less than ∈, the calculation result of the linear temperature compensation model is considered stable and reliable, and the output P obj =P obj_lin ; If δ is greater than or equal to ∈, it is considered that the linear temperature compensation model has a large prediction deviation, and it automatically switches to the isothermal atmospheric model and outputs P obj =P obj_iso .

6. The floor positioning method according to claim 1, characterized in that: In the step of determining the operating state of the elevator based on the fused data and adjusting the data sampling frequency and filtering parameters according to the operating state, when the acceleration modulus is close to the acceleration due to gravity and has a small fluctuation, and the angular velocity is almost zero, it is determined that the elevator is in a stationary state; If a rapid change in the acceleration modulus or a sudden increase in the angular velocity is detected, it is determined that the elevator is in the acceleration or deceleration stage; When the elevator is in a non-stationary state, but the acceleration and angular velocity remain within a small and stable range, it is determined that the elevator is in a uniform speed operation state.

7. The floor positioning method according to claim 1, characterized in that: After comparing the atmospheric pressure value compensated by the real-time fusion data with the calculated expected atmospheric pressure value of the target floor, and determining that the target floor has been reached if the difference between the atmospheric pressure value and the calculated atmospheric pressure value is within a preset tolerance range, the step further includes: After determining that the target floor has been reached, the floor information is fed back to the user in the form of voice announcements and vibration prompts.

8. A floor positioning device, characterized in that: include: The acquisition module is used to simultaneously collect atmospheric pressure data on two predetermined reference floors, calibrate it in combination with temperature, and establish floor reference data; The processing module is used to collect atmospheric pressure and temperature sensor data in real time during elevator operation, process the sensor data and output stable fusion data; A judgment module, configured to judge the operating status of the elevator based on the fused data, and adjust the data sampling frequency and filtering parameters according to the operating status; a calculation module, configured to calculate an expected atmospheric pressure value of a target floor based on the floor reference data and current atmospheric pressure data; The comparison module is used to compare the atmospheric pressure value after real-time fusion data compensation with the calculated expected atmospheric pressure value of the target floor. If the difference between the two is within the preset tolerance range, it is determined that the target floor has been reached.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the floor positioning method according to any one of claims 1 to 7 when executing the computer-readable instructions.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the floor positioning method according to any one of claims 1 to 7.

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