Remote rental facility rental management system based on AI glasses

Abstract

The invention relates to the technical field of rental facility management, in particular to a rental facility remote rental management system based on AI glasses, which comprises a code scanning module, an imaging module, a gesture operation module, a charging server and a communication module. The code scanning module is used for identifying codes of leasing facilities, the imaging module is used for superposing leasing information through the AR technology, the gesture operation module is used for analyzing the intention of a user to complete leasing confirmation, the billing server generates bills and supports multi-mode payment, and the communication module is used for achieving data interaction and safety guarantee. The method can improve the lease management efficiency, optimizes the user experience, and achieves the real-time and convenient remote lease management.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of intelligent equipment and lease management, and specifically relates to a remote lease management system for rental facilities based on AI glasses.

[0002] With the rapid development of the sharing economy and the popularity of intelligent equipment, rental services play an increasingly important role in daily life. However, traditional rental management methods often have low information interaction efficiency and insufficient operational convenience when facing diversified rental facilities, which affects user experience and the overall efficiency of rental services. For example, in the case of rental facilities such as companion beds, shared wheelchairs, and power banks, users need to scan a two-dimensional code or manually input information to complete the operation during the rental process. This method may have a high learning cost or be less intuitive for some users. In addition, if the generation and payment of rental bills cannot be seamlessly connected, it will also reduce the willingness of users to use to some extent. Therefore, how to improve the intelligent level of rental management and optimize the human-computer interaction experience has become an important issue to be solved in the current rental service field.

[0003] The application relates to the technical field of rental facility management, and specifically relates to a remote lease management system for rental facilities based on AI glasses.

[0004] To solve the above technical problems, the application is implemented through the following technical scheme: a remote lease management system for rental facilities based on AI glasses, which comprises a code scanning module, an imaging module, a gesture operation module, a billing server and a communication module. The code scanning module is integrated on the side of the frame of the AI glasses and is used for scanning the two-dimensional code or bar code on the rental facility; the imaging module is embedded above the lens of the AI glasses and is used for capturing rental facility images in the user's field of view in real time; the gesture operation module is located on the inner side of the temple of the AI glasses and detects the fingertip action trajectory of the user through a capacitive sensor; the billing server is deployed in the cloud and interacts with the AI glasses through the communication module to generate rental bills and project them onto the display screen of the AI glasses.

[0005] The code scanning module cooperates with an infrared light source and a camera to identify the code information on the rental facility and sends the decoded rental facility identifier to the billing server. The imaging module is composed of a miniature camera and an image processing chip. The camera collects images in the user's field of view at a fixed frame rate, and the image processing chip performs edge detection and feature extraction on the images, locates the position of the rental facility and superimposes the relevant information on the display screen of the AI glasses. The gesture operation module collects the trajectory of the user's fingertip in the air, analyzes the user's intention in combination with a preset gesture library, and completes the rental confirmation and payment operation.

[0006] The communication module uses a low-power Bluetooth protocol to establish a connection with the billing server, uploads the data obtained by the code scanning module and the imaging module to the billing server, and receives the rental billing information returned by the billing server. The billing server queries the rental rules and fee standards of the rental facility according to its identifier, and generates a rental bill in combination with the rental duration. The rental bill is transmitted to the display screen of the AI glasses in the form of a virtual image through the communication module, and the user completes the payment operation through the gesture operation module.

[0007] Preferably, the code scanning module enhances the contrast of two-dimensional codes or barcodes through infrared light sources, and the camera is installed at a fixed angle on the side of the frame of the AI glasses, ensuring that the scanning range covers the 30° to 60° field of view area in front of the user. The decoding algorithm built-in the code scanning module supports multiple encoding formats, including QR code, DataMatrix and PDF417, and the decoding result is transmitted to the main control chip of the AI glasses in the form of a string through the UART interface.

[0008] The miniature camera of the imaging module adopts a wide-angle lens design with a field of view angle of 90° to adapt to the user's needs of observing rental facilities at different distances. The image processing chip performs semantic segmentation on the collected images based on a convolutional neural network model, extracts key feature points of the rental facility, and superimposes the rental information in the form of a floating window in the user's field of view through AR technology. The position and size of the floating window are dynamically adjusted according to the relative position of the rental facility in the field of view, ensuring that the user can intuitively obtain the rental information.

[0009] The capacitive sensors of the gesture operation module are distributed on the inner surface of the AI glasses' temples, and the sensor array is arranged in a grid pattern, with each sensor unit measuring 2mm x 2mm, covering the main area of the user's finger movement. The gesture operation module analyzes the motion trajectory of the user's fingertips through a sliding window algorithm, and determines the user's gesture type based on direction vectors and speed parameters. The gesture library has pre-set a variety of gesture commands, including single-finger click, double-finger slide and circle confirmation, corresponding to rental confirmation, bill viewing and payment operation, respectively.

[0010] The billing server is deployed on a distributed cloud platform and designed using a microservices architecture, including a rental rule management module, a fee calculation module, and a payment gateway module. The rental rule management module stores the rental duration limit and fee standards for each rental facility, the fee calculation module generates a rental bill based on the rental duration and fee standards, and the payment gateway module supports multiple payment methods, including credit cards, electronic wallets, and third-party payment platforms. The billing server interacts with the communication module of the AI glasses through an API interface to ensure real-time updating of rental bills and synchronous feedback of payment status.

[0011] Preferably, the communication module adopts Bluetooth 5.0 protocol with low power consumption, supports maximum transmission rate of 2Mbps, and communication distance of 10-30 meters. The communication module has a built-in data encryption unit, which uses AES-256 algorithm to encrypt the transmitted data, ensuring the security of the rental information and payment data. The communication module also supports the breakpoint resume function, which automatically caches the unfinished data packet in the case of signal interruption, and re-sends it after the network is restored.

[0012] The infrared light source of the code scanning module has a power of 5mW and a wavelength of 850nm. The pulse modulation technology is used to reduce power consumption and prolong the battery life of the AI glasses. The camera has a resolution of 1280x720 and a frame rate of 30fps. The lens surface is coated with an anti-reflection coating to reduce the impact of light refraction on image quality. The decoding algorithm uses a multi-thread parallel processing mechanism to ensure fast and accurate identification of two-dimensional codes or barcodes under complex lighting conditions.

[0013] The image processing chip of the imaging module uses ARM Cortex-M7 architecture with a main frequency of 216MHz and is equipped with 512KB SRAM and 4MB Flash memory. The convolutional neural network model is optimized by quantization, with model parameters compressed to within 1MB and inference time controlled within 50ms. AR technology uses SLAM algorithm to track user head pose in real time, ensuring that the floating window in the user's field of view is stable and does not shift with head movement.

[0014] The sliding window algorithm of the gesture operation module collects sensor data at a time interval of 10ms, with a window length of 100ms. The sensor data is denoised by a Kalman filter to improve the accuracy of gesture recognition. The gesture library supports custom extension, allowing users to add new gesture commands through the AI glasses' companion application and map them to specific operation functions.

[0015] The rental rules management module of the billing server uses a relational database to store the identifiers of rental facilities, rental duration limits and fee standards. The database table structure includes fields such as facility ID, rental duration interval, and fee coefficient. The fee calculation module is based on a time-based billing strategy, dividing the rental duration into multiple intervals, with independent setting of the fee coefficient for each interval to ensure flexibility and fairness of rental fees. The payment gateway module interacts with third-party payment platforms through HTTPS protocol, and payment requests and responses are encapsulated in JSON format.

[0016] The AI glasses-based remote rental management method for rental facilities includes the following steps:

[0017] Step one: rental information acquisition: the user wears AI glasses, scans the two-dimensional code or bar code on the rental facility through the code scanning module, the code scanning module sends the decoded rental facility identifier to the billing server, the billing server queries the rental rules and returns the rental information.

[0018] Step two: rental information display: the imaging module captures the rental facility image in the user's field of view in real time, the image processing chip extracts the key feature points of the rental facility, and the rental information is superimposed in the user's field of view in the form of a floating window through AR technology.

[0019] Step three: rental confirmation and payment: the user completes rental confirmation and payment operation through the gesture operation module, the gesture operation module analyzes the user's gesture trajectory and generates operation instructions, the operation instructions are sent to the billing server through the communication module, the billing server generates rental bills and returns the payment status.

[0020] Step four: rental bill review: the billing server transmits the rental bill in the form of a virtual image to the display screen of the AI glasses through the communication module, the user reviews the bill details and completes the payment operation through the gesture operation module.

[0021] Step five: rental status update: the billing server updates the usage status of the rental facility according to the payment status, and feeds back the update result to the AI glasses through the communication module, the AI glasses displays the latest status of the rental facility in real time through the imaging module.

[0022] Figure 1 The system architecture diagram of the present application shows the connection relationship between the code scanning module, the imaging module, the gesture operation module, the communication module and the billing server.

[0023] Figure 2 The structure diagram of the AI glasses, the specific position and layout of the code scanning module, the imaging module and the gesture operation module on the AI glasses are marked.

[0024] Figure 3 The working principle diagram of the code scanning module shows the process of infrared light source and camera cooperating to identify the rental facility code information.

[0025] Figure 4 The function implementation flow chart of the imaging module describes the steps of micro camera image acquisition, image processing chip feature extraction and rental information superposition through AR technology.

[0026] Figure 5 The gesture recognition flow chart of the gesture operation module shows the process of capacitive sensor collecting user fingertip trajectory and analyzing gesture instructions.

[0027] Figure 6The module structure diagram of the billing server presents the interactive logic of the lease rule management module, the fee calculation module, and the payment gateway module.

[0028] The reference signs are as follows: 1, a code scanning module; 2, an imaging module; 3, a gesture operation module; 4, a communication module; 5, a billing server; 6, an infrared light source; 7, a camera; 8, a miniature camera; 9, an image processing chip; and 10, a capacitive sensor. DETAILED DESCRIPTION

[0029] The AI glasses-based lease facility remote rental management system in the embodiment realizes the lease management function through the cooperative work of multiple modules, and the specific implementation manner is as follows: Figures 1 to 6 The system includes the code scanning module 1, the imaging module 2, the gesture operation module 3, the communication module 4, and the billing server 5. The connection relationship and the operation principle among the modules will be expanded one by one in the following.

[0030] As shown in Figure 1 The code scanning module 1 is integrated on the side of the AI glasses frame. The infrared light source 6 and the camera 7 constitute the core components. The infrared light source 6 has a power of 5 mW and a wavelength of 850 nm. The power consumption is reduced through the pulse modulation technology, and the equipment endurance time is prolonged. The camera 7 is installed at a fixed angle on the side of the AI glasses frame, ensuring that the scanning range covers the 30° to 60° field of view area in front of the user. The camera 7 has a resolution of 1280×720 and a frame rate of 30 fps. The lens surface is coated with an anti-reflection coating to reduce the influence of light refraction on image quality. When the infrared light source 6 and the camera 7 work cooperatively, the infrared light source 6 enhances the contrast of the two-dimensional code or the bar code. The camera 7 captures the code information on the lease facility and transmits the image data to the decoding unit. The decoding unit supports multiple encoding formats such as QR code, DataMatrix, and PDF417 through a multi-thread parallel processing mechanism. The decoding result is transmitted to the AI glasses main control chip in the form of a string through the UART interface. The main control chip sends the decoded lease facility identifier to the billing server 5. The billing server 5 queries the lease rules according to the identifier and returns related information such as the lease fee standard and the lease time limit.

[0031] The imaging module 2 is embedded above the AI glasses lens, and the miniature camera 8 and the image processing chip 9 are the core components. The miniature camera 8 adopts a wide-angle lens design with a field of view angle of 90° to adapt to the user's observation of the rental facilities at different distances. The miniature camera 8 collects images in the user's field of view and transmits image data to the image processing chip 9. The image processing chip 9 is based on the ARM Cortex-M7 architecture with a main frequency of 216 MHz, equipped with 512 KB SRAM and 4 MB Flash memory. The image processing chip 9 is built-in with a convolutional neural network model, which is quantized and optimized with parameters compressed to less than 1 MB, and the inference time is controlled within 50 ms. The image processing chip 9 performs semantic segmentation on the collected images, extracts key feature points of the rental facilities, and superimposes rental information in the form of a floating window in the user's field of view through AR technology. The position and size of the floating window are dynamically adjusted according to the relative position of the rental facilities in the field of view to ensure that the user can intuitively obtain rental information. The stability of the floating window is tracked in real time through the SLAM algorithm to avoid the floating window from shifting due to head movement. The imaging module 2 works in cooperation with the code scanning module 1. When the code scanning module 1 identifies the rental facilities, the imaging module 2 captures images of the rental facilities and extracts feature points through the image processing chip 9 to superimpose and display rental information in the user's field of view.

[0032] The gesture operation module 3 is located inside the AI glasses temple, and the capacitive sensor 10 is distributed on the inner surface of the temple. The sensor array is arranged in a grid form, and each sensor unit has a size of 2 mm x 2 mm, covering the main area of user finger movement. The capacitive sensor 10 collects user fingertip trajectory data at a time interval of 10 ms. The sliding window algorithm sets the window length to 100 ms, and the sensor data is denoised through the Kalman filter to improve the accuracy of gesture recognition. The gesture library predefines multiple gesture instructions, including single-finger click, double-finger slide, and circle confirmation, corresponding to rental confirmation, bill viewing, and payment operations, respectively. The gesture operation module 3 analyzes user gesture trajectories to generate operation instructions and sends them to the billing server 5 through the communication module 4. The billing server 5 generates rental bills according to the operation instructions and returns the payment status. The gesture operation module 3 also supports custom extension. Users can add new gesture instructions through the AI glasses supporting application and map them to specific operation functions.

[0033] The communication module 4 adopts a low-power Bluetooth 5.0 protocol to support a maximum transmission rate of 2 Mbps and a communication distance of 10-30 meters. The communication module 4 is internally provided with a data encryption unit that adopts an AES-256 algorithm to encrypt the transmission data, thereby ensuring the security of the rental information and payment data. The communication module 4 is responsible for uploading the data obtained by the code scanning module 1 and the imaging module 2 to the billing server 5 and receiving the rental billing information returned by the billing server 5. The communication module 4 also supports a breakpoint resume function to automatically cache the unfinished data packets in the case of signal interruption and resend them after the network is restored. The data interaction between the communication module 4 and the billing server 5 is realized through an API interface, thereby ensuring the real-time updating of the rental bill and the synchronous feedback of the payment status.

[0034] The billing server 5 is deployed on a distributed cloud platform and adopts a micro-service architecture design, including a rental rule management module, a fee calculation module, and a payment gateway module. The rental rule management module stores the rental facility identifiers, the rental time length limits, and the fee standards in a relational database. The database table structure includes facility ID, rental time length interval, fee coefficient, etc. The fee calculation module divides the rental time length into multiple intervals based on a time-based charging strategy, and the fee coefficient of each interval is independently set to ensure the flexibility and fairness of the rental fee. The payment gateway module supports multiple payment methods, including credit cards, electronic wallets, and third-party payment platforms. The payment gateway module interacts with the third-party payment platforms through the HTTPS protocol, and the payment request and response are packaged in JSON format. The billing server 5 interacts with the AI glasses through the communication module 4 to generate rental bills and return the payment status.

[0035] In actual application scenarios, the user wears the AI glasses and scans the two-dimensional code or barcode on the rental facility through the code scanning module 1. The code scanning module 1 sends the decoded rental facility identifier to the billing server 5, which queries the rental rules and returns the rental information. The imaging module 2 captures the rental facility images in the user's field of view in real time, and the image processing chip 9 extracts the key feature points of the rental facility and superimposes the rental information in the form of a floating window in the user's field of view through AR technology. The user completes the rental confirmation and payment operations through the gesture operation module 3. The gesture operation module 3 analyzes the user's gesture trajectory to generate operation instructions and sends them to the billing server 5 through the communication module 4. The billing server 5 generates rental bills and returns the payment status. The billing server 5 transmits the rental bills to the AI glasses display screen in the form of virtual images through the communication module 4. The user views the bill details and completes the payment operation through the gesture operation module 3. The billing server 5 updates the rental facility usage status according to the payment status and feeds back the update results to the AI glasses through the communication module 4. The AI glasses display the latest status of the rental facility in real time through the imaging module 2.

[0036] The modules in the above embodiments work cooperatively through hardware connection and software interaction. The code scanning module 1, the imaging module 2, the gesture operation module 3, the communication module 4 and the billing server 5 jointly constitute a complete remote rental management system of rental facilities. The code scanning module 1 is responsible for identifying the code information of the rental facility. The imaging module 2 is responsible for capturing the image of the rental facility and superimposing the rental information. The gesture operation module 3 is responsible for analyzing the user gesture instructions. The communication module 4 is responsible for data transmission. The billing server 5 is responsible for generating rental bills and payment status feedback. The clear connection relationship and data interaction logic between the modules ensure the stability and reliability of the system. In order to better enable relevant personnel in the technical field to fully understand and implement the present application, the specific implementation principles of the present application are further supplemented below in conjunction with a specific application scenario.

[0037] In actual application, the user wears AI glasses and enters the rental site, and scans the two-dimensional code or bar code on the rental facility through the code scanning module 1. The infrared light source 6 of the code scanning module 1 works at a wavelength of 850 nm and a power of 5 mW, uses pulse modulation technology to reduce power consumption and prolong the service life of the device. The infrared light source 6 enhances the contrast of the two-dimensional code or bar code, the camera 7 captures the image with a field of view range of 30° to 60°, and transmits the data to the decoding unit. The decoding unit supports recognition of multiple encoding formats such as QR code, DataMatrix and PDF417 through a multi-thread processing mechanism, and the decoding result is transmitted to the main control chip in the form of a string through the UART interface. The main control chip sends the decoded rental facility identifier to the billing server 5, and the billing server 5 queries the rental rules according to the identifier and returns related information such as rental fee standard and time limit.

[0038] Subsequently, the imaging module 2 starts to work, the miniature camera 8 collects the image of the rental facility in the user's field of view with a field of view angle of 90°, and transmits the image data to the image processing chip 9. The image processing chip 9 is based on ARM Cortex-M7 architecture, with a main frequency of 216 MHz, equipped with 512 KB SRAM and 4 MB Flash memory, and built-in convolutional neural network model, model parameters compressed to within 1 MB, inference time controlled within 50 ms. The image processing chip 9 performs semantic segmentation on the image, extracts the key feature points of the rental facility, and superimposes the rental information in the form of a floating window in the user's field of view through AR technology. The position and size of the floating window are dynamically adjusted according to the relative position of the rental facility in the field of view, ensuring that the user can intuitively obtain the rental information. The SLAM algorithm tracks the user's head pose in real time to avoid the floating window from shifting due to head movement.

[0039] When the user confirms the rental information, the gesture operation module 3 begins to collect the user's fingertip trajectory data. The capacitive sensor 10 is distributed on the inner surface of the glasses leg, and the sensor array is arranged in a grid form, with each sensor unit measuring 2mm x 2mm, covering the main area of user finger movement. The capacitive sensor 10 collects data at a time interval of 10ms, and the sliding window algorithm sets the window length to 100ms. The sensor data is denoised by a Kalman filter to improve the accuracy of gesture recognition. The gesture library presets multiple instructions, such as single-finger click for rental confirmation, double-finger swipe for bill viewing, and circle confirmation for payment operation. The gesture operation module 3 analyzes the user's gesture trajectory, generates operation instructions, and sends them to the billing server 5 through the communication module 4.

[0040] The communication module 4 uses the Bluetooth 5.0 protocol with a maximum transmission rate of 2Mbps and a communication distance of 10-30 meters. The communication module 4 has an AES-256 encryption unit built-in to ensure the security of rental information and payment data. The communication module 4 is responsible for uploading data obtained by the code scanning module 1 and the imaging module 2 to the billing server 5, and receiving rental bill information returned by the billing server 5. If the signal is interrupted, the communication module 4 automatically caches incomplete data packets and re-sends them after the network is restored, ensuring the integrity of data interaction.

[0041] The billing server 5 is deployed on a distributed cloud platform and uses a microservice architecture, including a rental rule management module, a fee calculation module, and a payment gateway module. The rental rule management module uses a relational database to store rental facility identifiers, rental duration limits, and fee standards. The database table structure includes facility ID, rental duration interval, and fee coefficient fields. The fee calculation module is based on a time-based billing strategy, dividing the rental duration into multiple intervals, with independent settings for the fee coefficient of each interval to ensure flexibility and fairness of rental fees. The payment gateway module supports multiple payment methods such as credit cards, electronic wallets, and third-party payment platforms, and interacts with third-party payment platforms through HTTPS protocol, with payment requests and responses encapsulated in JSON format. The billing server 5 generates rental bills based on operation instructions and feeds back payment status to AI glasses.

[0042] After the payment is completed, the billing server 5 updates the usage state of the rental facility, and feeds back the update result to the AI glasses through the communication module 4. The imaging module 2 displays the latest state of the rental facility in real time, ensuring that the user can timely understand the availability of the rental facility. The modules work cooperatively through hardware connection and software interaction. The code scanning module 1 is responsible for identifying the rental facility code information, the imaging module 2 is responsible for capturing the rental facility image and superimposing the rental information, the gesture operation module 3 is responsible for analyzing the user gesture instruction, the communication module 4 is responsible for data transmission, and the billing server 5 is responsible for generating the rental bill and payment state feedback. The clear connection relationship and data interaction logic between the modules ensure the stability and reliability of the system.

[0043] The above embodiments are only preferred solutions, and any modifications, equivalent replacements or improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A remote rental management system for rental facilities based on AI glasses, characterized in that, The system includes: The scanning module (1) is integrated into the side of the AI ​​glasses frame and is used to scan the QR code or barcode on the rental facility and send the decoded rental facility identifier to the billing server (5). The imaging module (2) is embedded above the lens of the AI ​​glasses. It is used to capture images of rental facilities in the user's field of vision in real time, and extract key feature points of rental facilities through the image processing chip (9) to overlay rental information in the user's field of vision in the form of a floating window. The gesture operation module (3) is located on the inside of the temple of the AI ​​glasses. It detects the user's fingertip movement trajectory through the capacitive sensor (10), parses the user's gesture command and generates operation command; The communication module (4) uses the Bluetooth Low Energy protocol to interact with the billing server (5) to upload the data obtained by the scanning module (1) and the imaging module (2) to the billing server (5) and receive the rental bill information returned by the billing server (5); The billing server (5) is deployed on a distributed cloud platform and includes a rental rule management module, a fee calculation module and a payment gateway module. It is used to query rental rules and fee standards based on the rental facility identifier, generate rental bills in combination with rental duration, and transmit rental bill information to the display screen of the AI ​​glasses.

2. The remote rental management system for rental facilities based on AI glasses according to claim 1, characterized in that: The scanning module (1) includes an infrared light source (6) and a camera (7). The infrared light source (6) has a power of 5mW and a wavelength of 850nm. Power consumption is reduced by pulse modulation technology. The camera (7) has a resolution of 1280×720 and a frame rate of 30fps. The lens surface is coated with an anti-reflective coating. The infrared light source (6) and the camera (7) work together to enhance the contrast of the QR code or barcode. The decoding algorithm supports QR code, DataMatrix and PDF417 encoding formats. The decoding result is transmitted to the AI ​​glasses main control chip in the form of a string through the UART interface.

3. The remote rental management system for rental facilities based on AI glasses according to claim 1, characterized in that: The imaging module (2) includes a miniature camera (8) and an image processing chip (9). The miniature camera (8) adopts a wide-angle lens design with a field of view of 90°. The image processing chip (9) is based on the ARM Cortex-M7 architecture with a main frequency of 216MHz. It is equipped with 512KB SRAM and 4MB Flash memory. The parameters of the convolutional neural network model are compressed to less than 1MB, and the inference time is controlled to less than 50ms. The image processing chip (9) performs semantic segmentation on the acquired images, extracts the key feature points of the rental facilities, and uses AR technology to overlay the rental information in the form of a floating window in the user's field of vision.

4. The remote rental management system for rental facilities based on AI glasses according to claim 1, characterized in that: The capacitive sensors (10) of the gesture operation module (3) are distributed on the inner surface of the temple of the AI ​​glasses. The sensor array is arranged in a grid pattern. Each sensor unit is 2mm×2mm in size. The sliding window algorithm collects sensor data at a time interval of 10ms. The window length is 100ms. The gesture library has a variety of preset gesture commands, including single-finger click, two-finger swipe and circle confirmation, which correspond to rental confirmation, bill viewing and payment operation, respectively.

5. The remote rental management system for rental facilities based on AI glasses according to claim 1, characterized in that: The communication module (4) adopts the Bluetooth 5.0 low-power protocol, supports a maximum transmission rate of 2Mbps, a communication distance of 10 to 30 meters, has a built-in data encryption unit, uses the AES-256 algorithm to encrypt the transmitted data, supports the function of resuming interrupted transmission, automatically caches incomplete data packets in the event of signal interruption and resends them after the network is restored.

6. The remote rental management system for rental facilities based on AI glasses according to claim 1, characterized in that: The billing server (5) uses a relational database to store the rental facility identifier, rental duration limit and fee standard. The database table structure includes facility ID, rental duration range and fee coefficient fields. The fee calculation module divides the rental duration into multiple ranges based on the time segment billing strategy. The fee coefficient of each range is set independently. The payment gateway module interacts with the third-party payment platform through the HTTPS protocol. The payment request and response are encapsulated in JSON format.

7. The remote rental management system for rental facilities based on AI glasses according to claim 1, characterized in that: The position and size of the floating window of the imaging module (2) are dynamically adjusted according to the relative position of the rental facility in the user's field of vision. The SLAM algorithm tracks the user's head posture in real time to ensure that the position of the floating window in the user's field of vision is stable and does not shift with head movement.

8. The remote rental management system for rental facilities based on AI glasses according to claim 1, characterized in that: The gesture operation module (3) uses a Kalman filter to denoise the sensor data, improving the accuracy of gesture recognition. It supports custom expansion, and users can add new gesture commands through the AI ​​glasses' accompanying application and map them to specific operation functions.

9. A method for remote rental management of rental facilities based on AI glasses, characterized in that, Includes the following steps: Step 1: Obtaining rental information: The user wears AI glasses and scans the QR code or barcode on the rental facility through the scanning module (1). The scanning module (1) sends the decoded rental facility identifier to the billing server (5). The billing server (5) queries the rental rules and returns the rental information. Step 2: Rental information display: The imaging module (2) captures images of rental facilities in the user's field of vision in real time, and the image processing chip (9) extracts key feature points of the rental facilities and overlays the rental information in the user's field of vision in the form of a floating window through AR technology; Step 3: Rental Confirmation and Payment: The user completes the rental confirmation and payment operation through the gesture operation module (3). The gesture operation module (3) analyzes the user's gesture trajectory and generates operation instructions. The operation instructions are sent to the billing server (5) through the communication module (4). The billing server (5) generates a rental bill and returns the payment status. Step 4: Viewing the rental bill: The billing server (5) transmits the rental bill as a virtual image to the display screen of the AI ​​glasses through the communication module (4). The user can view the bill details and complete the payment operation by using the gesture operation module (3). Step 5: Rental Status Update: The billing server (5) updates the usage status of the rental facility based on the payment status and feeds back the update result to the AI ​​glasses through the communication module (4). The AI ​​glasses display the latest status of the rental facility in real time through the imaging module (2).

10. The remote rental management method for rental facilities based on AI glasses according to claim 9, characterized in that: In step three, the sliding window algorithm of the gesture operation module (3) collects sensor data at a time interval of 10ms, the window length is 100ms, and the sensor data is denoised by a Kalman filter. The gesture library presets a variety of gesture commands, including single-finger click, two-finger swipe and circle confirmation, which correspond to rental confirmation, bill viewing and payment operation, respectively.

Images