Terminal display adjusting method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a terminal display adjusting method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining adjustment associated field data through a field sensor when a target user handles a business through a self-service terminal, and determining user preference posture data based on historical display posture data of the self-service terminal; based on the adjustment association field data and the user preference attitude data, predicting a user adaptive display attitude through a pre-trained display attitude prediction model; and adjusting a terminal display of the self-service terminal based on the user adaptive display posture. According to the embodiment of the invention, the service handling efficiency is improved and the user experience is improved when the service is handled through the self-service terminal.

Description

Technical Field

[0001] This invention relates to the field of self-service terminal technology, and in particular to a terminal display adjustment method, device, electronic device, and storage medium. Background Technology

[0002] Self-service terminals in banks are now widely available and have become a core tool for branch transformation. These terminals integrate hardware and software, supporting functions such as identity verification and remote video assistance, and incorporating new technologies like 5G and the Internet of Things. Currently, most self-service terminal displays have fixed height and tilt angles, unable to adjust to different user heights. Users must adjust their body position and posture to adapt to the terminal's height and tilt when conducting business, for example, requiring multiple adjustments during facial recognition. This leads to low efficiency and a poor user experience. Summary of the Invention

[0003] This invention provides a terminal display adjustment method, apparatus, electronic device, and storage medium, which can improve business processing efficiency and enhance user experience when conducting business through self-service terminals.

[0004] In a first aspect, embodiments of the present invention provide a terminal display adjustment method, comprising:

[0005] When a target user conducts business through a self-service terminal, on-site sensors acquire adjustment-related on-site data, which is on-site data associated with the terminal display of the self-service terminal.

[0006] User preference posture data is determined based on the historical display posture data of the self-service terminal;

[0007] Based on the aforementioned adjustment-related on-site data and the user preference posture data, a pre-trained display posture prediction model is used to predict the user's adapted display posture; and

[0008] The terminal display of the self-service terminal is adjusted based on the user's adapted display posture.

[0009] In a second aspect, embodiments of the present invention provide a terminal display adjustment device, comprising:

[0010] The on-site data acquisition module is used to acquire adjustment-related on-site data through on-site sensors when a target user conducts business through a self-service terminal. The adjustment-related on-site data is on-site data associated with the terminal display of the self-service terminal.

[0011] The preference data acquisition module is used to determine user preference posture data based on the historical display posture data of the self-service terminal;

[0012] The model prediction module is used to predict the user's adapted display posture based on the adjusted correlation field data and the user preference posture data, using a pre-trained display posture prediction model; and

[0013] An adjustment module is used to adjust the terminal display of the self-service terminal based on the user-adapted display posture.

[0014] Thirdly, embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the terminal display adjustment method as described in any of the embodiments of the present invention.

[0015] Fourthly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the terminal display adjustment method as described in any of the embodiments of the present invention.

[0016] This invention provides a terminal display adjustment method, apparatus, electronic device, and storage medium. It acquires adjustment-related on-site data and determines user-preferred posture data based on historical display posture data. Then, based on the adjustment-related on-site data and user-preferred posture data, it predicts the user-adapted display posture using a pre-trained display posture prediction model. Finally, it adjusts the self-service terminal's display based on the user-adapted display posture. This method accurately predicts the user-adapted display posture while considering both the adjustment-related on-site data and user-preferred posture data, and adjusts the self-service terminal's display accordingly. This ensures the display posture is precisely adapted to the target user, allowing them to successfully complete transactions through the self-service terminal without repeatedly adjusting their body posture, thus improving the convenience and efficiency of the transaction and enhancing the user experience. Attached Figure Description

[0017] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic flowchart of a terminal display adjustment method provided in an embodiment of the present invention;

[0019] Figure 2 This is another flowchart illustrating the terminal display adjustment method provided in this embodiment of the invention;

[0020] Figure 3 This is another flowchart illustrating the terminal display adjustment method provided in this embodiment of the invention;

[0021] Figure 4 This is a schematic diagram of the structure of a self-service terminal provided in an embodiment of the present invention;

[0022] Figure 5 This is another flowchart illustrating the terminal display adjustment method provided in this embodiment of the invention;

[0023] Figure 6 This is a schematic diagram of a terminal display adjustment device provided in an embodiment of the present invention.

[0024] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] Figure 1 This is a schematic flowchart illustrating a terminal display adjustment method provided in an embodiment of the present invention. This method can be executed by a terminal display adjustment device provided in this embodiment, which can be implemented using software and / or hardware. In a specific embodiment, the device can be integrated into an electronic device, such as a computer or server. The following embodiments will illustrate this using the integration of the device into an electronic device as an example. (Reference) Figure 1The method may specifically include the following steps:

[0028] Step 101: When the target user conducts business through the self-service terminal, adjustment-related on-site data is acquired through on-site sensors; the adjustment-related on-site data is the on-site data associated with the terminal display of the self-service terminal. This step enables the prediction of the user's adaptive display posture based on the adjustment-related on-site data, so as to accurately predict the user's adaptive display posture while taking into account the adjustment-related on-site data.

[0029] Optionally, the adjustment of the associated field data includes the target user's height and distance data, the target user's posture data, and / or ambient light intensity data.

[0030] Specifically, the aforementioned user height distance data includes the target user's height, eye level, and / or the distance between the user's eyes and the terminal display.

[0031] Specifically, the aforementioned user posture data can be understood as data used to analyze user postures, which may include standing postures, wheelchair postures, and single-leg support postures.

[0032] Optionally, the field sensors include 3D sensing cameras, pressure sensors, and / or ambient light sensors.

[0033] Specifically, the aforementioned field sensors may also include lidar.

[0034] Optionally, the process of acquiring and adjusting related on-site data through on-site sensors when the target user conducts business through the self-service terminal includes: acquiring user height and distance data through a three-dimensional perception camera.

[0035] Specifically, user height and distance data can also be obtained through LiDAR.

[0036] Specifically, the aforementioned 3D perception camera can be installed on the self-service terminal or on the wall next to the self-service terminal.

[0037] Optionally, the process of acquiring and adjusting related field data through field sensors when the target user conducts business through the self-service terminal includes: acquiring user posture data through pressure sensors.

[0038] Specifically, user posture data can be obtained through 3D sensing cameras or LiDAR.

[0039] Specifically, the aforementioned pressure sensor can be installed on the ground in front of the self-service terminal.

[0040] Specifically, it can acquire pressure distribution information sensed by pressure sensors when a user is conducting business, and analyze the user's posture based on the pressure distribution information.

[0041] Optionally, the process of acquiring and adjusting related field data through field sensors when the target user conducts business through the self-service terminal includes: acquiring ambient light intensity data through an ambient light sensor.

[0042] Specifically, in response to a business processing request initiated by a target user using a self-service terminal, step 101 can be initiated.

[0043] Specifically, step 101 can be initiated after receiving the business processing instruction sent by the host computer.

[0044] Step 102: Determine user preference posture data based on the historical display posture data of the self-service terminal. This step enables the prediction of the user's adapted display posture based on the user preference posture data, thus accurately predicting the user's adapted display posture while taking user preferences into account.

[0045] Specifically, the aforementioned historical display posture data can be understood as the posture data of the terminal display when different users conduct business through the self-service terminal. The posture data of the terminal display may include the height and tilt of the terminal display.

[0046] Specifically, the aforementioned user preference posture data may include the user's preferred monitor height and the user's preferred monitor tilt, or it may only include the user's preferred monitor height or the user's preferred monitor tilt.

[0047] Optionally, the process of determining user preference posture data based on the historical display posture data of the self-service terminal includes: obtaining target historical display posture data that is the same as or similar to the historical field data and the adjustment-related field data in the historical display posture data, and determining user preference posture data based on the target historical display posture data.

[0048] Step 103: Based on the conditioning-related field data and user preference posture data, predict the user's adapted display posture using a pre-trained display posture prediction model. This step can accurately predict the user's adapted display posture while taking into account the conditioning-related field data and user preference posture data.

[0049] Optionally, user-adapted monitor posture includes user-adapted monitor height and user-adapted monitor tilt.

[0050] Optionally, the display pose prediction model is a multi-output model based on the random forest algorithm.

[0051] Specifically, random forest is an ensemble learning method that effectively handles nonlinear relationships in multimodal data by constructing multiple decision trees and aggregating their predictions, making it well-suited for the complex input scenarios of this system. Compared to other algorithms, random forest has the following advantages: first, it is robust and can handle noise and missing values ​​in the data; second, it has high computational efficiency, making it suitable for real-time inference requirements; and third, it has good interpretability, facilitating debugging and optimization.

[0052] Specifically, the display pose prediction model can be configured with 100 trees and a maximum depth of 10.

[0053] Specifically, the prediction result of each decision tree can be represented as:

[0054]

[0055] Among them, R km c represents the m-th partition of the k-th decision tree; km This represents the output value of the m-th partition of the k-th tree.

[0056] Specifically, the final prediction result can be expressed as:

[0057]

[0058] Where K represents the total number of decision trees.

[0059] Optionally, the process described above, which predicts the user's adapted display posture using a pre-trained display posture prediction model based on adjusted correlation field data and user preference posture data, includes:

[0060] Feature extraction is performed on user height and distance data, user posture data, ambient light intensity data, and user preferred posture data to obtain corresponding height and distance features, posture features, ambient light intensity features, and user preferred posture features. Feature fusion is performed on the height and distance features, posture features, and / or ambient light intensity features to obtain fused features. The height and distance features, posture features, ambient light intensity features, user preferred posture features, and fused features are used as input features to the display posture prediction model. The display posture prediction model is then used to calculate and output the user-adapted display posture.

[0061] Specifically, the process of extracting features from user height distance data and ambient light intensity data to obtain user height distance features and ambient light intensity features may include: standardizing user height distance data and ambient light intensity data to obtain user height distance features and ambient light intensity features.

[0062] Specifically, the process of standardizing user height and distance data to obtain user height and distance features includes: standardizing the target user's height, eye height, and the distance between the user's eyes and the terminal display to obtain corresponding height features, eye height features, and eye distance features.

[0063] Specifically, the process of extracting features from user posture data to obtain posture features may include: determining the user posture type based on the posture data, and performing one-hot encoding on the posture type to obtain posture features.

[0064] Specifically, the process of extracting user preference posture features from user preference posture data can include: standardizing the user preference display height and user preference display tilt to obtain user preference height features and user preference tilt features respectively.

[0065] Specifically, the aforementioned fused features can be obtained by fusing user height and distance features with ambient lighting features to create a core feature.

[0066] Specifically, height and distance features, posture features, and ambient lighting features can be fused to obtain fused features.

[0067] Specifically, height features, eye height features, eye distance features, posture features, ambient lighting features, user preference height features, and user preference tilt features can also be used as input features for the display posture prediction model.

[0068] Specifically, the above input features can be represented as:

[0069] X = [h,e] h ,d,s,l,h pref ,θ pref ]

[0070] Where h represents height; e h d represents eye height; s represents eye distance; l represents pose; h represents ambient light. pref This indicates a high degree of user preference characteristics; θ pref This indicates the degree of user preference tilt.

[0071] Specifically, the fused features and user preference posture features can also be used as input features to the display posture prediction model.

[0072] Step 104: Adjust the terminal display of the self-service terminal based on the user's posture. Building upon steps 101 to 103, this step precisely adjusts the terminal display of the self-service terminal to match the user's posture. This ensures the display's posture is accurately adapted to the target user, allowing them to successfully complete transactions without repeatedly adjusting their body position. This makes transactions more convenient and efficient, improving the user experience.

[0073] Specifically, the aforementioned user-adapted display posture can be a single posture or a sequence of postures.

[0074] Optionally, the process of adjusting the terminal display of the self-service terminal based on the user-adapted display posture includes: adjusting the terminal display of the self-service terminal to the aforementioned user-adapted display posture.

[0075] Optionally, the process of adjusting the terminal display of the self-service terminal based on the user-adapted display posture includes: sequentially adjusting the posture of the self-service terminal display to each posture in the posture sequence according to the posture sequence of the user-adapted display posture.

[0076] The following further describes the terminal display adjustment method provided by the embodiments of the present invention, such as... Figure 2 As shown, that is Figure 1 Step 101 may include the following steps:

[0077] Step 1011: Obtain the target service response posture data from the historical display posture data based on the authentication information input by the target user. The target service response posture data is the display posture data corresponding to the response operation of the self-service terminal when the target user handles the business each time.

[0078] Specifically, the aforementioned identity verification information can be an ID card number, mobile phone number, or account number, etc.

[0079] Specifically, users can initiate business processing requests by entering provincial verification information such as ID card number, mobile phone number or account number. The system can obtain target business response data from the customer relationship management system or business processing history based on the corresponding identity verification information.

[0080] Specifically, the display posture data corresponding to the self-service terminal's response operations during each of the aforementioned target users' transactions may include the corresponding display height and display tilt.

[0081] Optionally, the response operations of the above self-service terminal include facial recognition operations.

[0082] Step 1012: Based on the time interval between the corresponding response time and the current time, determine the time decay weight of the target business response attitude data when the target user handles business in each instance.

[0083] Specifically, the process of determining the time decay weight of the target user's response attitude data during each transaction, based on the time interval between the corresponding response time and the current time, can be performed using the following formula:

[0084]

[0085] Where, ω t This represents the time decay weight; λ = 0.1 represents the decay coefficient, which is an empirical value; T t T represents the time (in hours) when the t-th transaction is processed; now : The current time.

[0086] Optionally, before step 1012, the recognition success rate and user satisfaction score of the facial recognition operation performed on the target user in each of the previous business transactions are obtained.

[0087] Optionally, the process of determining the time decay weight of the target user's response attitude data during each transaction based on the time interval between the corresponding response time and the current time includes:

[0088] The time decay weight of the target business response posture data is determined based on the time interval between the corresponding face recognition operation execution time and the current time, the corresponding recognition pass rate, and the corresponding user satisfaction score.

[0089] Step 1013: Determine user preference posture data based on the target user's target business response posture data and the corresponding time decay weights during each of the target user's previous business transactions.

[0090] Optionally, the process of determining user preference posture data based on the target user's response posture data during each transaction and the corresponding time decay weight can be based on the following formula:

[0091]

[0092] in, Indicates the user's preferred monitor height; Indicates the user's screen tilt angle; n indicates the user's nth transaction; h t θ represents the monitor height of the target user during the t-th transaction; t This represents the screen tilt angle when the target user conducts business for the tth time; β = 0.2 represents the trend factor, used to capture the direction of changes in the user's historical preferences.

[0093] Understandably, if the interval is too long, users' needs and preferences will inevitably change. To ensure the accuracy of determining user preference attitude data by referring to the target business response attitude data, it is necessary to consider the time interval between the corresponding response time and the current time, and determine user preference attitude data based on the target business response attitude data.

[0094] Furthermore, if the success rate of face recognition operation is low and the user satisfaction reflects the adaptability of the corresponding target business response posture data to the user and the reference value of the corresponding target business response posture data, specifically, if the success rate is low and the satisfaction is high, it indicates that the adaptability and reference value are high, and vice versa. Therefore, determining the time decay weight of the target business response posture data based on the corresponding recognition pass rate and the corresponding user satisfaction score can help to further determine more accurate user preference posture data.

[0095] The following further describes the terminal display adjustment method provided by the embodiments of the present invention, such as... Figure 3 As shown, the training steps of the display pose prediction model provided in this embodiment of the invention include:

[0096] Step 301: Obtain sample input features based on the adjusted correlation sample data and sample preference posture data.

[0097] Specifically, before step 301, the above-mentioned adjustment-related sample data can be obtained by acquiring on-site data of sample users when they conduct business through self-service terminals.

[0098] Specifically, the on-site data of the sample users when handling business through the self-service terminal may include the user's height and distance data, user posture data, and corresponding ambient light intensity data.

[0099] Specifically, before step 301, sample preference posture data can be determined by acquiring and analyzing the display posture data corresponding to the response operations of the self-service terminal when the sample user conducts business through the self-service terminal each time.

[0100] In practical applications, the dataset can be divided into training set (70%), validation set (15%), and test set (15%), which are used for model fitting, hyperparameter tuning, and performance evaluation, respectively.

[0101] Step 302: Based on the sample input features, the prediction results of the user-adapted display height and the user-adapted display tilt are calculated and output by the display pose prediction model to be trained.

[0102] Step 303: Determine the value of the training loss function based on the predicted results of the user-adapted display height and the user-adapted display tilt, as well as the actual data of the user-adapted display height and the user-adapted display tilt.

[0103] Specifically, the aforementioned real data on user-adapted monitor height and user-adapted monitor tilt can be understood as the monitor height and tilt angle of the self-service terminal when a sample user successfully completes a transaction. For example, when a user...

[0104] Specifically, the training loss function described above can be expressed as:

[0105]

[0106] Among them, H pred and θ pred The corresponding representations are the predicted height and tilt angle of the user-adapted monitor; H act and θ act The corresponding data represents the actual height and tilt of the user-adapted monitor; n represents the number of samples, and α and β are weighting coefficients.

[0107] Specifically, the design of this loss function fully considers the actual needs of display height and display tilt, and optimizes the model's performance by adjusting the weights, enabling it to learn the screen configuration prediction model that best meets user needs.

[0108] Step 304: Adjust the model parameters of the display pose prediction model based on the function value of the training loss function.

[0109] The embodiments of the present invention can train a display posture prediction model that can accurately predict the user's adapted display posture.

[0110] The following further describes the terminal display adjustment method provided by the embodiments of the present invention.

[0111] Optional, such as Figure 4 As shown, the self-service terminal includes an electric lifting platform 1, a tilt adjustment push rod 2, a push rod connecting shaft 3, and a lifting platform connecting shaft 4; the lower end of the terminal display 5 is connected to the electric lifting platform 1 through the lifting platform connecting shaft 4, and the terminal display 5 can rotate horizontally relative to the electric lifting platform 1; one end of the tilt adjustment push rod 2 is connected to the upper back of the terminal display through the push rod connecting shaft 3, and the other end passes through the electric lifting platform and is connected to the push rod push-pull mechanism, and the tilt adjustment push rod 2 can rotate horizontally relative to the terminal display 5.

[0112] Specifically, the end of the tilt adjustment push rod that is not connected to the terminal display can also be fixed on the electric lifting platform, and the tilt adjustment push rod can be a telescopic rod.

[0113] Optional, such as Figure 5 As shown, step 103 may include the following steps:

[0114] Step 1031: Adjust the height of the terminal display using an electric lifting platform based on the user-adapted display height.

[0115] Optionally, the process of adjusting the height of the terminal display based on the user-adapted display height via an electric lifting platform includes: raising or lowering the electric lifting platform so that the height of the terminal display connected to the electric lifting platform rope is the user-adapted display height.

[0116] Specifically, the tilt adjustment lever can be extended while raising the electric lifting platform to keep the tilt angle of the terminal display constant.

[0117] Specifically, the tilt adjustment lever can be pulled up and down while the electric lifting platform is lowered, so that the tilt angle of the terminal display remains unchanged.

[0118] Step 1032: Adjust the tilt of the terminal display by pushing and pulling the tilt angle adjustment lever through the push-pull mechanism based on the user-adapted display tilt angle.

[0119] Optionally, the process of adjusting the tilt angle of the terminal display by pushing and pulling the tilt angle adjustment lever through the push-pull mechanism based on the user-adapted display tilt angle includes: pushing out the tilt angle adjustment lever or pulling out the tilt angle adjustment lever so that the tilt angle of the terminal display is the user-adapted display tilt angle.

[0120] Specifically, the height of the terminal display can be adjusted to match the user's display height by raising or lowering the electric lifting platform, and the tilt angle of the terminal display can also be adjusted to match the user's display tilt angle.

[0121] The present invention adjusts the posture of the terminal display through a simple height adjustment structure and a tilt adjustment structure, which makes the adjustment process convenient and avoids the problems of high failure rate and high wear and tear that may exist in complex structures.

[0122] Figure 6 This is a structural diagram of a terminal display adjustment device provided in an embodiment of the present invention. This device is suitable for executing the terminal display adjustment method provided in an embodiment of the present invention. Figure 6 As shown, the device may specifically include:

[0123] The on-site data acquisition module 601 is used to acquire adjustment-related on-site data through on-site sensors when a target user conducts business through the self-service terminal. This adjustment-related on-site data is the on-site data associated with the terminal display of the self-service terminal. This step enables the prediction of the user's adaptive display posture based on the adjustment-related on-site data, allowing for accurate prediction of the user's adaptive display posture while taking into account the adjustment-related on-site data.

[0124] Optionally, the adjustment of the associated field data includes the target user's height and distance data, the target user's posture data, and / or ambient light intensity data.

[0125] Optionally, the field sensors include 3D sensing cameras, pressure sensors, and / or ambient light sensors.

[0126] Optionally, the above-mentioned field data acquisition module 601 can be specifically used to acquire user height and distance data through a three-dimensional perception camera; acquire user posture data through a pressure sensor; and acquire ambient light intensity data through an ambient light sensor.

[0127] The preference data acquisition module 602 is used to determine user preference posture data based on the historical display posture data of the self-service terminal. This module can help predict the user's adapted display posture based on the user preference posture data, so as to accurately predict the user's adapted display posture while taking user preferences into account.

[0128] Optionally, the aforementioned preference data acquisition module 602 can be specifically used to: acquire target service response posture data from historical display posture data based on the identity verification information input by the target user; the target service response posture data is the display posture data corresponding to the response operation of the self-service terminal when the target user handles business in previous instances; determine the time decay weight of the target service response posture data when the target user handles business in previous instances based on the time interval between the corresponding response time and the current time; and determine user preference posture data based on the target service response posture data when the target user handles business in previous instances and the corresponding time decay weight.

[0129] Optionally, the self-service terminal's response actions may include facial recognition.

[0130] Optionally, the terminal display adjustment device provided by the present invention can also be used to obtain the recognition pass rate and user satisfaction score of the target user's face recognition operation in each transaction before determining the time decay weight of the target user's response posture data in each transaction based on the time interval between the corresponding response time and the current time.

[0131] Optionally, the aforementioned preference data acquisition module 602 can be specifically used to determine the time decay weight of the target user's response posture data during each transaction based on the time interval between the corresponding face recognition operation execution time and the current time, the corresponding recognition pass rate, and the corresponding user satisfaction score.

[0132] The model prediction module 603 is used to predict the user-adapted display posture based on the conditioning-related field data and user preference posture data, using a pre-trained display posture prediction model. It can accurately predict the user-adapted display posture while taking into account both the conditioning-related field data and the user preference posture data.

[0133] Optionally, the aforementioned model prediction module 603 can be specifically used to extract features from user height and distance data, user posture data, ambient light intensity data, and user preferred posture data, respectively, to obtain height and distance features, posture features, ambient light features, and user preferred posture features; to perform feature fusion on the height and distance features, posture features, and / or ambient light features to obtain fused features; and to input the height and distance features, posture features, ambient light features, user preferred posture features, and fused features as input features to the display posture prediction model, and to output the user-adapted display posture through the display posture prediction model.

[0134] Optionally, the display pose prediction model is a multi-output model based on the random forest algorithm.

[0135] Adjustment module 604 is used to adjust the terminal display of the self-service terminal based on the user's posture. This module, in conjunction with modules 601 to 603, precisely adjusts the terminal display of the self-service terminal based on the user's posture, ensuring that the terminal display's posture is accurately adapted to the target user. This allows the target user to successfully complete transactions through the self-service terminal without repeatedly adjusting their body posture, thus making the transaction process convenient and efficient, and improving the user experience.

[0136] Optionally, user-adapted monitor posture includes user-adapted monitor height and user-adapted monitor tilt.

[0137] Optionally, the terminal display adjustment provided in this embodiment of the invention further includes a training module for training a display posture prediction model.

[0138] Optionally, the training module described above can be specifically used to: obtain sample input features based on the adjusted associated sample data and sample preference posture data; calculate and output the prediction results of the user-adapted display height and user-adapted display tilt based on the sample input features through the display posture prediction model to be trained; determine the function value of the training loss function based on the prediction results of the user-adapted display height and user-adapted display tilt and the real data of the user-adapted display height and user-adapted display tilt; and adjust the model parameters of the display posture prediction model according to the function value of the training loss function.

[0139] Optionally, the self-service terminal provided in this embodiment of the invention includes an electric lifting platform, a tilt adjustment push rod, a push rod connecting shaft, and a lifting platform connecting shaft; the lower end of the terminal display is connected to the electric lifting platform via the lifting platform connecting shaft, and the terminal display can rotate horizontally relative to the electric lifting platform; one end of the tilt adjustment push rod is connected to the upper back of the terminal display via the push rod connecting shaft, and the other end passes through the electric lifting platform and is connected to the push rod push-pull mechanism, and the tilt adjustment push rod can rotate horizontally relative to the terminal display.

[0140] Optionally, the aforementioned adjustment module 604 can be specifically used to adjust the height of the terminal display based on the height of the user-adaptive display via an electric lifting platform; and to adjust the tilt of the terminal display based on the tilt of the user-adaptive display via a push-pull mechanism to push and pull the tilt angle adjustment lever.

[0141] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is merely an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the functional modules described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0142] This invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the terminal display adjustment method provided in any of the above embodiments.

[0143] This invention also provides a computer-readable medium having a computer program stored thereon, which, when executed by a processor, implements the terminal display adjustment method provided in any of the above embodiments.

[0144] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the terminal display adjustment method as described in any of the embodiments of this invention.

[0145] The following is for reference. Figure 7 It shows a schematic diagram of the structure of a computer system 700 suitable for implementing an electronic device according to embodiments of the present invention. Figure 7 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0146] like Figure 7 As shown, the computer system 700 includes a central processing unit (CPU) 701, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 702 or programs loaded from storage section 708 into random access memory (RAM) 703. The RAM 703 also stores various programs and data required for the operation of the system 700. The CPU 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0147] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 710 as needed so that computer programs read from it can be installed into the storage section 708 as needed.

[0148] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 709, and / or installed from removable medium 711. When the computer program is executed by central processing unit (CPU) 701, it performs the functions defined above in the system of this invention.

[0149] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0150] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0151] The modules and / or units described in the embodiments of the present invention can be implemented in software or hardware. The described modules and / or units can also be housed in a processor; for example, a processor can be described as including a field data acquisition module, a preference data acquisition module, a model prediction module, and a regulation module. The names of these modules do not necessarily limit the module itself.

[0152] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs that, when executed by the device, cause the device to: acquire adjustment-related on-site data via on-site sensors when a target user conducts business through a self-service terminal, and determine user-preferred posture data based on historical display posture data of the self-service terminal; predict the user-adapted display posture using a pre-trained display posture prediction model based on the adjustment-related on-site data and the user-preferred posture data; and adjust the terminal display of the self-service terminal based on the user-adapted display posture.

[0153] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for adjusting a terminal display, characterized in that, include: When a target user conducts business through a self-service terminal, on-site sensors acquire adjustment-related on-site data, which is on-site data associated with the terminal display of the self-service terminal. User preference posture data is determined based on the historical display posture data of the self-service terminal; Based on the aforementioned adjustment-related field data and the aforementioned user preference posture data, the user's adapted display posture is predicted through a pre-trained display posture prediction model. as well as The terminal display of the self-service terminal is adjusted based on the user's adapted display posture.

2. The terminal display adjustment method according to claim 1, wherein the adjustment-related field data includes the target user's height-distance data, user posture data, and ambient light intensity data; The field sensors include a 3D sensing camera, a pressure sensor, and an ambient light sensor; The acquisition of adjustment-related field data through field sensors includes: The user's height and distance data are acquired through the three-dimensional sensing camera; The user's posture data is acquired via the pressure sensor; and The ambient light intensity data is obtained through the ambient light sensor.

3. The terminal display adjustment method according to claim 1, characterized in that, The process of determining user preference posture data based on the historical display posture data of the self-service terminal includes: Based on the identity verification information input by the target user, the target service response posture data is obtained from the historical display posture data. The target service response posture data is the display posture data corresponding to the response operation of the self-service terminal when the target user handles the business each time. Based on the time interval between the corresponding response time and the current time, determine the time decay weight of the target user's response attitude data for each transaction; and The user preference posture data is determined based on the target user's response posture data for each transaction and the corresponding time decay weight.

4. The terminal display adjustment method according to claim 2, wherein predicting the user's adapted display posture based on the adjustment-related on-site data and the user's preferred posture data using a pre-trained display posture prediction model includes: Feature extraction is performed on the user height and distance data, the user posture data, the ambient light intensity data, and the user preferred posture data respectively to obtain height and distance features, posture features, ambient light intensity features, and user preferred posture features. The height-distance feature, the attitude feature, and / or the ambient lighting feature are fused to obtain a fused feature; and The height distance feature, the posture feature, the ambient lighting feature, the user preferred posture feature, and the fusion feature are input to the display posture prediction model, and the user-adapted display posture is output through the display posture prediction model.

5. The terminal display adjustment method according to claim 3, characterized in that, The self-service terminal's response operations include facial recognition. Before determining the time decay weight of the target user's response attitude data for each transaction based on the time interval between the corresponding response time and the current time, the method further includes: Obtain the recognition success rate and user satisfaction score of the facial recognition operation performed on the target user in each transaction; The determination of the time decay weight of the target user's response attitude data during each transaction, based on the time interval between the corresponding response time and the current time, includes: The time decay weight of the target business response posture data during each transaction by the target user is determined based on the time interval between the corresponding face recognition operation execution time and the current time, the corresponding recognition pass rate, and the corresponding user satisfaction score.

6. The terminal display adjustment method according to claim 1, characterized in that, The user-adapted display posture includes the user-adapted display height and the user-adapted display tilt. The display pose prediction model is a multi-output model based on the random forest algorithm; The training process of the display pose prediction model includes: Sample input features are obtained based on the adjustment of correlated sample data and sample preference posture data; Based on the sample input features, the display pose prediction model to be trained outputs the prediction results of the user-adapted display height and the user-adapted display tilt. The value of the training loss function is determined based on the predicted results of the user-adapted display height and user-adapted display tilt, as well as the actual data of the user-adapted display height and user-adapted display tilt. The model parameters of the display pose prediction model are adjusted based on the function value of the training loss function.

7. The terminal display adjustment method according to claim 6, characterized in that, The self-service terminal includes an electric lifting platform, a tilt adjustment push rod, a push rod connecting shaft, and a lifting platform connecting shaft. The lower end of the terminal display is connected to the electric lifting platform via the lifting platform connecting shaft, and the terminal display can rotate horizontally relative to the electric lifting platform. One end of the tilt adjustment push rod is connected to the upper back of the terminal display via the push rod connecting shaft, and the other end passes through the electric lifting platform and is connected to the push rod push-pull mechanism. The tilt adjustment push rod can rotate horizontally relative to the terminal display. The method of adjusting the terminal display of the self-service terminal based on the user-adapted display posture includes: The height of the terminal display is adjusted via the electric lifting platform based on the user-adapted display height. as well as The tilt of the terminal display is adjusted by pushing and pulling the tilt adjustment lever based on the user-adapted display tilt angle.

8. A terminal display adjustment device, characterized in that, include: The on-site data acquisition module is used to acquire adjustment-related on-site data through on-site sensors when a target user conducts business through a self-service terminal. The adjustment-related on-site data is on-site data associated with the terminal display of the self-service terminal. The preference data acquisition module is used to determine user preference posture data based on the historical display posture data of the self-service terminal; The model prediction module is used to predict the user's adapted display posture based on the adjustment-related field data and the user's preferred posture data through a pre-trained display posture prediction model. as well as An adjustment module is used to adjust the terminal display of the self-service terminal based on the user-adapted display posture.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the terminal display adjustment method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the terminal display adjustment method as described in any one of claims 1 to 7.

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