Smart mobile device

Abstract

This application discloses a smart mobile device, comprising: a device body, an iris recognition unit, and at least two fingerprint recognition units. A processor is disposed within the device body, and a screen is disposed on the target surface of the device body. The iris recognition unit is connected to the processor and is disposed on the target surface of the device body where the screen is formed. Each fingerprint recognition unit is connected to the processor and is located on a different target area. The target area includes the lower end of the target surface, the middle of the right side of the device body, the upper end of the left side of the device body, and the back of the target surface of the device body. Through this structure, this application increases the amount of identification information by collecting biometric features from multiple locations and of multiple types, significantly improving the device's security level and greatly reducing the false recognition rate.

Description

Technical Field

[0001] This application is applied to the field of liveness detection, and in particular to a smart mobile device. Background Technology

[0002] Smart mobile devices may be stolen or misused. As the functions of smart mobile devices become more diverse, such theft or misuse can have a significant impact on the owners of these devices.

[0003] Existing solutions often employ passwords or biometric identification methods to verify user identity in order to reduce the occurrence of theft or misuse of smart mobile devices.

[0004] However, passwords are easily leaked, and current traditional methods rely on a single biometric feature for identification, which is at risk of being forged. Utility Model Content

[0005] This application provides a smart mobile device to address the problem of potentially inaccurate identification of smart mobile devices.

[0006] To address the aforementioned technical problems, this application provides a smart mobile device, comprising: a device body, an iris recognition unit, and at least two fingerprint recognition units. A processor is disposed within the device body, and a screen is disposed on the target surface of the device body. The iris recognition unit is connected to the processor and is disposed on the target surface of the device body where the screen is located. Each fingerprint recognition unit is connected to the processor and is located in a different target area. The target area includes the lower end of the target surface, the middle of the right side of the device body, the upper end of the left side of the device body, and the back of the target surface of the device body.

[0007] The device includes at least two fingerprint recognition units, namely a first fingerprint recognition unit, a second fingerprint recognition unit, a third fingerprint recognition unit, and a fourth fingerprint recognition unit; the first fingerprint recognition unit is located at the lower end of the target surface; the second fingerprint recognition unit is located in the middle of the right side of the device body; the third fingerprint recognition unit is located at the upper left side of the device body; and the fourth fingerprint recognition unit is located on the back of the target surface of the device body.

[0008] The first fingerprint recognition unit includes a receiving electrode layer, a piezoelectric layer, a transmitting electrode layer, and a control circuit layer stacked in sequence. The first fingerprint recognition unit is located on the side of the target surface closer to the main body of the device, with the receiving electrode layer positioned close to the target surface, and the control circuit layer connected to the processor.

[0009] The piezoelectric layer includes multiple sub-piezoelectric layers arranged in an array; the receiving electrode layer includes multiple receiving electrodes arranged in an array, with each receiving electrode corresponding to one of the multiple sub-piezoelectric layers.

[0010] The second fingerprint recognition unit includes a first capacitive sensor and a first algorithm board that are connected to each other. The first algorithm board is connected to the processor. The length of the second fingerprint recognition unit ranges from 12 to 18 mm.

[0011] The second fingerprint recognition unit is integrated on the power button or in the sliding touch sensing area on the right side of the main body of the device.

[0012] The third fingerprint recognition unit includes a second capacitive sensor and a second algorithm board that are interconnected. The second algorithm board is connected to the processor. The length of the third fingerprint recognition unit ranges from 5 to 10 mm.

[0013] The fourth fingerprint recognition unit includes a fingerprint chip and a microlens array located on the side of the fingerprint chip away from the device body. The side of the fingerprint chip away from the device body is provided with photosensitive pixels, and the microlenses in the microlens array correspond one-to-one with the photosensitive pixels. The fingerprint chip is connected to the processor.

[0014] The iris recognition unit includes an infrared light source, an image acquisition lens, a supplementary light source, and a controller. The controller is connected to the image acquisition lens, the supplementary light source, and the processor, respectively, and the infrared light source is connected to the processor.

[0015] The iris recognition unit is integrated into the front-facing camera of the main body of the device, and the image acquisition lens includes the front-facing camera.

[0016] To address the aforementioned technical issues, the intelligent mobile device of this application includes a device body, an iris recognition unit, and at least two fingerprint recognition units. A processor is housed within the device body, and a screen is positioned on the target surface of the device body. The iris recognition unit is connected to the processor and is located on the target surface of the device body where the screen is formed. Each fingerprint recognition unit is connected to the processor and is located in a different target area. The target area includes the lower end of the target surface, the middle of the right side of the device body, the upper left side of the device body, and the back of the target surface of the device body. This multi-location, multi-type biometric data collection increases the amount of identification information, significantly improves the device's security level, and drastically reduces the false recognition rate. Furthermore, the multiple fingerprint recognition units can act as backups, ensuring basic verification functionality even if a single fingerprint recognition unit fails, thus improving device availability. Moreover, the collaborative analysis of the iris and at least two fingerprints effectively prevents biometric forgery attacks, enhances overall anti-counterfeiting capabilities, and improves the accuracy of user identification by the intelligent mobile device. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the framework of an embodiment of the smart mobile device provided in this application;

[0018] Figure 2 This is a structural schematic diagram of one implementation method for the target surface of a smart mobile device;

[0019] Figure 3 This is a schematic diagram of the structure of one embodiment of the target surface of a smart mobile device;

[0020] Figure 4 This is a schematic diagram of one embodiment of the first fingerprint recognition unit;

[0021] Figure 5 This is a schematic diagram of the framework of one embodiment of the second fingerprint recognition unit;

[0022] Figure 6 This is a schematic diagram of the framework of one embodiment of the third fingerprint recognition unit;

[0023] Figure 7 This is a schematic diagram of one embodiment of the fourth fingerprint recognition unit;

[0024] Figure 8 This is a schematic diagram of the framework of one embodiment of the iris recognition unit. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0027] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0028] Please refer to this together. Figure 1 , Figure 1 This is a schematic diagram of the framework of an embodiment of the smart mobile device provided in this application.

[0029] The smart mobile device 100 of this embodiment includes: a device body 110, an iris recognition unit 120, and at least two fingerprint recognition units 130. The smart mobile device 100 includes smart devices such as mobile phones and tablets. The device body 110 is the main functional structure of the smart mobile device 100. The iris recognition unit 120 is used to recognize the iris features of the user, while the at least two fingerprint recognition units 130 are used to recognize at least two different fingerprint features of the user, thereby improving the accuracy of user identification through the combination of multiple biometric features.

[0030] The device body 110 is equipped with a processor 111, and a screen 112 is provided on the target surface of the device body 110; wherein, the target surface is the side of the smart mobile device 100 that is facing the user when it is used normally, and the screen 112 is provided on it for the user to view.

[0031] The iris recognition unit 120 is connected to the processor 111, and the iris recognition unit 120 is disposed on the target surface of the device body 110 where the screen 112 is formed, so as to collect and recognize the iris features of the user.

[0032] Each fingerprint recognition unit 130 is connected to the processor 111, and each fingerprint recognition unit 130 is located on a different target area. The target area includes the lower end of the target surface, the middle of the right side of the device body 110, the upper end of the left side of the device body 110, and the back of the target surface of the device body 110. At most one fingerprint recognition unit 130 is provided in each target area. The locations of these target areas are the conventional positions where a user's finger contacts the smart mobile device 100 during normal use. At least two fingerprint recognition units 130 respectively recognize different fingerprints collected from different locations on the smart mobile device 100.

[0033] In a specific application scenario, when performing identity recognition, the smart mobile device 100 can adjust the verification method according to the usage scenario. For example, daily unlocking can require iris recognition combined with any fingerprint for dual verification; payment verification can require iris recognition plus any two fingerprints for triple verification; privacy access can require iris recognition plus three fingerprints for quadruple verification; and special modes can require iris recognition plus four fingerprints for quintuple verification, and so on, without specific limitations. When a fingerprint recognition unit 130 fails, the system can automatically switch to the remaining available recognition units for combination.

[0034] The aforementioned identification unit configuration significantly enhances the device's security level and drastically reduces the false recognition rate through multi-location and multi-type biometric data collection. Furthermore, the inclusion of multiple fingerprint recognition units 130 ensures basic verification functionality even when a single unit 130 malfunctions, improving device availability. Collaborative analysis of the iris and at least two fingerprints effectively prevents biometric forgery attacks, enhancing overall anti-counterfeiting capabilities.

[0035] With the above structure, the smart mobile device of this embodiment includes a device body, an iris recognition unit, and at least two fingerprint recognition units. A processor is disposed within the device body, and a screen is disposed on the target surface of the device body. The iris recognition unit is connected to the processor and is located on the target surface of the device body where the screen is formed. Each fingerprint recognition unit is connected to the processor and is located in a different target area. The target area includes the lower end of the target surface, the middle of the right side of the device body, the upper left side of the device body, and the back of the target surface of the device body. This multi-location, multi-type biometric feature collection increases the amount of recognition information, significantly improves the device's security level, and greatly reduces the false recognition rate. Furthermore, the multiple fingerprint recognition units can act as backups for each other, ensuring basic verification functionality even if a single fingerprint recognition unit fails, thus improving device availability. Moreover, the collaborative analysis of the iris and at least two fingerprints effectively prevents biometric forgery attacks, enhances overall anti-counterfeiting capabilities, and improves the accuracy of the smart mobile device in identifying the user's identity.

[0036] Please see Figure 2-3 , Figure 2 This is a structural diagram of one implementation method for the target surface of a smart mobile device. Figure 3 This is a schematic diagram of the structure of one embodiment of the target surface of a smart mobile device.

[0037] In one embodiment, at least two fingerprint recognition units 130 include a first fingerprint recognition unit 131, a second fingerprint recognition unit 132, a third fingerprint recognition unit 133, and a fourth fingerprint recognition unit 134. That is, the smart mobile device 100 is provided with a total of four fingerprint recognition units 130, which can separately recognize up to four different fingerprints of the user, thereby increasing the amount of information required for recognition, significantly improving the security protection level of the device, and greatly reducing the false recognition rate.

[0038] At least two fingerprint recognition units 130 contain fingerprint modules in four specific locations. The first fingerprint recognition unit 131 is located at the lower end of the target surface and can be used for fingerprint collection in a normal grip position. The second fingerprint recognition unit 132 is located in the middle of the right side of the device body 110, adapting to the natural touch area of ​​the index or middle finger. The third fingerprint recognition unit 133 is arranged at the upper left side of the device body 110, meeting the side recognition needs during one-handed operation. The fourth fingerprint recognition unit 134 is located on the back of the target surface, enabling identity verification in special scenarios through rear touch. Here, the left side, right side, and back are all relative to the target surface where the screen is located, i.e., Figure 2 The indicated orientation is used as a reference for determination.

[0039] The four fingerprint recognition units 130 form a backup structure through spatial redundancy design. When one fingerprint recognition unit 130 fails, it can automatically switch to another available fingerprint recognition unit 130.

[0040] By setting up four fingerprint recognition units 130 in different positions, it can adapt to various usage scenarios such as portrait and landscape modes, one-handed and two-handed operation, effectively solving the recognition failure problem of traditional solutions in special operation modes such as landscape games. The spatial redundancy design ensures that basic recognition function can still be maintained even if a single fingerprint recognition unit 130 fails, greatly improving device availability. The multi-recognition unit collaborative verification mechanism combined with iris recognition forms five layers of security protection, with a false recognition rate of less than 1*10. -6 This significantly improves device security. Among them, the innovative layout of the third fingerprint recognition unit 133 on the upper left side of the main body 110 solves the recognition blind spot of traditional solutions when holding the device in landscape mode, and achieves intelligent fusion verification of multimodal biometrics in conjunction with a dynamic weight allocation algorithm.

[0041] Please see Figure 4 , Figure 4 This is a schematic diagram of one embodiment of the first fingerprint recognition unit.

[0042] In one embodiment, the first fingerprint recognition unit 131 can be an ultrasonic fingerprint recognition unit. Specifically, the first fingerprint recognition unit 131 includes a receiving electrode layer 1312, a piezoelectric layer 1313, a transmitting electrode layer 1314, and a control circuit layer 1311 stacked in sequence. The first fingerprint recognition unit 131 is located on the side of the target surface closer to the device body 110, and the receiving electrode layer 1312 is disposed close to the target surface. The control circuit layer 1311 is connected to the processor 111.

[0043] The target surface is the finger contact side. The control circuit layer 1311 is used for drive control and signal preprocessing. The transmitting electrode layer 1314 is used to excite the piezoelectric layer 1313 to generate ultrasonic waves. The piezoelectric layer 1313 is the core of the acoustic-electric conversion and is used for bidirectional transmission and reception. The receiving electrode layer 1312 is used to collect the ultrasonic signals reflected from the fingerprint. When the first fingerprint recognition unit 131 is working, the control circuit layer 1311 drives the transmitting electrode layer 1314 to excite the piezoelectric layer 1313 to generate ultrasonic waves, and receives the reflected ultrasonic signals through the receiving electrode layer 1312. The control circuit layer 1311 then processes the reflected ultrasonic signals and transmits them to the processor 111.

[0044] The receiving electrode layer 1312 can be made of conductive metal or transparent conductive material, the piezoelectric layer 1313 can be a piezoelectric crystal material such as PZT or PMN-PT, and the emitting electrode layer 1314 can be a metal thin film or a conductive polymer.

[0045] In practical implementation, the receiving electrode layer 1312 can be designed as a mesh structure to improve sensitivity, or the pressure sensing range can be optimized by adjusting the thickness of the piezoelectric layer 1313. This structure achieves close contact between the electrodes and the piezoelectric layer 1313 through stacking, enabling pressure changes during fingerprint recognition to be accurately converted into electrical signals. At the same time, the design of the receiving electrode layer 1312 close to the target surface reduces signal attenuation. The processor 111 acquires and analyzes fingerprint features through the signals obtained by the receiving electrode layer 1312.

[0046] In one embodiment, the piezoelectric layer 1313 includes a plurality of sub-piezoelectric layers (not shown) arranged in an array; the receiving electrode layer 1312 includes a plurality of receiving electrodes (not shown) arranged in an array, with each of the plurality of receiving electrodes corresponding to one of the plurality of sub-piezoelectric layers.

[0047] The piezoelectric layer 1313 is composed of multiple sub-piezoelectric layers arranged in an array, and the receiving electrode layer 1312 contains multiple receiving electrodes, each of which interacts with a corresponding sub-piezoelectric layer. A piezoelectric thin film such as polyvinylidene fluoride can be used as the material substrate, and the arrayed sub-piezoelectric units can be formed using photolithography. The receiving electrodes can be fabricated using silver nanowires or graphene conductive layers through spraying or sputtering processes. Through the configuration of the arrayed piezoelectric layer 1313 and its corresponding electrodes, high-precision spatial resolution detection of touch pressure can be achieved, improving the detail capture capability of fingerprint recognition.

[0048] Please see Figure 5 , Figure 5 This is a schematic diagram of the framework of one embodiment of the second fingerprint recognition unit.

[0049] In one embodiment, the second fingerprint recognition unit 132 includes a first capacitive sensor 1321 and a first algorithm board 1322 connected to each other. The first algorithm board 1322 is connected to the processor 111. The length of the second fingerprint recognition unit 132 is in the range of 12-18mm, specifically 12mm, 13mm, 14mm, 15mm, 16mm, 17mm or 18mm, etc.

[0050] The second fingerprint recognition unit 132 achieves fingerprint acquisition and preliminary processing through the combination of the first capacitive sensor 1321 and the first algorithm board 1322. The first capacitive sensor 1321 adopts a metal electrode array structure, and completes image acquisition by detecting the capacitance changes caused by the fingerprint pattern. It can be a single-layer or multi-layer stacked design. The first algorithm board 1322 has a built-in fingerprint feature extraction chip, which supports noise filtering and local feature point matching. The overall length of this unit is controlled within the range of 12-18mm. It can be installed by bending using a flexible circuit board made of LCP material, or it can be arranged in a planar manner using a rigid PCB board.

[0051] The integrated design of the first capacitive sensor 1321 and the first algorithm board 1322 reduces signal transmission loss and improves fingerprint recognition response speed. The physical size design within a specific length range allows the module to adapt to various device forms.

[0052] In one embodiment, the second fingerprint recognition unit 132 is integrated on the power button or in the sliding touch sensing area in the middle of the right side of the device body 110.

[0053] The second fingerprint recognition unit 132 can be integrated inside the power button in the middle of the right side of the device, using capacitive sensing technology to collect fingerprints. Alternatively, it can be positioned at a specific location within the sliding touch sensing area, detecting fingerprint information through pressure or capacitance changes. This location design can be combined with the physical pressing function of the power button or the lateral movement function of the sliding touch; for example, the power button triggers fingerprint recognition when pressed, or the sliding touch area completes fingerprint verification during lateral movement. In specific implementations, a multi-touch sensor array or a miniature capacitive sensor array can be used to ensure high-precision fingerprint recognition within a limited space. Furthermore, this area can also create spatial redundancy with other fingerprint modules on the device; for example, when the top fingerprint module fails due to being held and obstructed, the side fingerprint module can supplement the verification.

[0054] By placing the second fingerprint recognition unit 132 in the power button or sliding touch area, the stability of fingerprint recognition when the device is held horizontally or operated with one hand can be improved, avoiding recognition failures caused by finger misalignment. This design integrates functions using existing physical buttons or operating areas of the device, saving space and enhancing adaptability to multiple scenarios. Simultaneously, the combination of the power button and fingerprint recognition simplifies the user's operation process; for example, fingerprint verification can be triggered by a short press of the power button, or fingerprint recognition can be completed simultaneously while adjusting the volume. When some fingerprint modules fail due to malfunction or obstruction, the fingerprint recognition unit in this location can serve as a backup, significantly improving the device's fault tolerance and overall security verification reliability.

[0055] Please see Figure 6 , Figure 6 This is a schematic diagram of the framework of one implementation of the third fingerprint recognition unit.

[0056] In one embodiment, the third fingerprint recognition unit 133 includes a second capacitive sensor 1331 and a second algorithm board 1332 connected to each other. The second algorithm board 1332 is connected to the processor 111. The length of the third fingerprint recognition unit 133 is in the range of 5-10mm, specifically 5mm, 6mm, 7mm, 8mm, 9mm or 10mm, etc.

[0057] The third fingerprint recognition unit 133 adopts a combined structure of a second capacitive sensor 1331 and a second algorithm board 1332. The second capacitive sensor 1331 collects biometric features by detecting changes in fingerprint capacitance, while the second algorithm board 1332 extracts features and performs preliminary verification on the collected data, transmitting the processing results to the processor 111 for final judgment. The unit's length is designed to be 5-10mm to adapt to the internal space layout requirements of the device. A flexible printed circuit board can be used to connect the second capacitive sensor 1331 and the second algorithm board 1332, or a modular design can be achieved through miniaturized chip integration. When the third fingerprint recognition unit 133 is positioned on the upper left side of the device, its length range ensures stable thumb contact during landscape grip scenarios. Cross-modal liveness detection technology effectively enhances anti-counterfeiting capabilities by simultaneously analyzing iris micro-vibration signals and fingerprint capacitance changes.

[0058] Please see Figure 7 , Figure 7 This is a schematic diagram of one embodiment of the fourth fingerprint recognition unit.

[0059] In one embodiment, the fourth fingerprint recognition unit 134 includes a fingerprint chip 1341 and a microlens array 1342 located on the side of the fingerprint chip 1341 away from the device body 110. Photosensitive pixels 1344 are attached to the side of the fingerprint chip 1341 away from the device body 110, and the microlenses in the microlens array 1342 correspond one-to-one with the photosensitive pixels 1344. The fingerprint chip 1341 is connected to the processor 111. The fourth fingerprint recognition unit 134 can be disposed under a transparent shell on the back of the device body 110 for protection.

[0060] The fourth fingerprint recognition unit 134 achieves high-precision biometric acquisition through the combination of a fingerprint chip 1341 and a microlens array 1342. An array of photosensitive pixels 1344 is attached to the surface of the fingerprint chip 1341, and the microlens array 1342 consists of multiple microlenses, each optically coupled to its corresponding photosensitive pixel 1344. This structure efficiently focuses the optical signals of the fingerprint ridges onto the pixel array, and the processor 111 extracts and compares the acquired data. The microlens array 1342 can be manufactured using photolithography, and its material can be PMMA or silicone; it can also be formed using 3D printing technology to create a curved microlens structure; or the microlens array 1342 can be designed with a non-uniform distribution to adapt to a specific fingerprint acquisition area.

[0061] By strategically configuring the microlens array 1342 and the photosensitive pixels 1344, the clarity and accuracy of fingerprint image acquisition are significantly improved, enabling the device to maintain stable biometric recognition capabilities even in complex environments. This structural design effectively enhances the environmental adaptability of the fingerprint recognition module, maintaining reliable performance under varying lighting conditions and finger moisture levels. Simultaneously, this technical solution reduces the power consumption of the fingerprint recognition module through optical path optimization, and, combined with the scene-level strategy of the dynamic security engine, achieves a balance between security and user experience. The redundant design of the microlens array 1342 also enhances the device's fault tolerance; even when some microlenses are damaged, basic recognition functions are still guaranteed, thereby improving the overall availability and security of the device.

[0062] Please see Figure 8 , Figure 8 This is a schematic diagram of the framework of one embodiment of the iris recognition unit.

[0063] In one embodiment, the iris recognition unit 120 includes an infrared light source 124, an image acquisition lens 123, a supplementary light source 121, and a controller 122. The controller 122 is connected to the image acquisition lens 123, the supplementary light source 121, and the processor 111, respectively.

[0064] The iris recognition unit 120 provides imaging conditions in low-light environments via an infrared light source 124. The image acquisition lens 123 captures iris texture features, and the supplementary light source 121 enhances image quality in low-brightness scenes. The controller 122 coordinates the control of each component and interacts with the processor 111. An infrared LED array can be used as the infrared light source 124, in conjunction with the image acquisition lens 123 using a near-infrared filter, and LED beads or miniature flashes can be used as the supplementary light source 121. The infrared light source 124 is connected to the processor 111.

[0065] In specific implementation, the controller 122 can be integrated into the main chipset of the device body 110, or connected to the image acquisition lens 123 as an independent control module, and the supplementary light source 121 can be linked with the ambient light sensor of the device to adjust the brightness.

[0066] The coordinated operation of the infrared light source 124 and the supplementary light source 121 enables iris recognition to maintain high accuracy under different lighting conditions, and the dynamic adjustment capability of the controller 122 effectively reduces the false recognition rate. The combined design of the image acquisition lens 123 and the supplementary light source 121 improves the quality of biometric acquisition in low-light environments, and the data interaction between the controller 122 and the processor 111 enables real-time response for multimodal verification.

[0067] In one embodiment, the iris recognition unit 120 may be integrated into the front-facing camera of the device body 110, and the image acquisition lens 123 includes the front-facing camera.

[0068] The iris recognition unit 120 is integrated with the front-facing camera module of the main body 110, enabling the image acquisition lens 123 to simultaneously perform regular shooting and iris recognition functions. A miniature optical sensor array can be embedded within the camera module, and iris imaging can be achieved through a beam splitter or filter. Embodiments may include sharing an infrared LED supplementary lighting module with the front-facing camera, or utilizing the camera's image processing chip for iris feature extraction. This integration method improves the accuracy of iris recognition by sharing optical paths and electronic components while leveraging the camera's existing imaging capabilities.

[0069] By integrating the iris recognition unit 120 into the front-facing camera, the adaptability of biometric recognition in various scenarios is effectively improved, maintaining a high recognition success rate even in low-light environments. This design allows the device to achieve multimodal biometric verification while maintaining a slim and lightweight body, forming a multi-layered security system in conjunction with the four fingerprint modules. When the user performs facial recognition, the front-facing camera can simultaneously acquire iris data, reducing the increased power consumption caused by additional hardware. This technology also supports cross-modal liveness detection, significantly reducing the risk of biometric forgery attacks through joint analysis of iris micro-vibration features and fingerprint capacitance changes, enabling the device to maintain stable recognition performance in complex usage scenarios.

[0070] The aforementioned solution can increase the amount of identification information by collecting biometric data from multiple locations and of multiple types, significantly improving the security level of the device and greatly reducing the false recognition rate. Furthermore, the setup of multiple fingerprint recognition units can serve as backups for each other, ensuring that basic verification functions are maintained even if a single fingerprint recognition unit fails, thus improving device availability. Moreover, through the collaborative analysis of iris scans and at least two fingerprints, it effectively prevents biometric forgery attacks, enhances overall anti-counterfeiting capabilities, and improves the accuracy of user identification by smart mobile devices.

[0071] The above are merely embodiments of this application and do not limit the scope of this patent application. Any equivalent structural or procedural changes made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of this application.

Claims

1. A smart mobile device, characterized by, include: The device body contains a processor, and a screen is mounted on the target surface of the device body. An iris recognition unit is connected to the processor and is disposed on a target surface on the main body of the device where a screen is formed. At least two fingerprint recognition units are provided, each of which is connected to the processor and is located in a different target area. The target area includes the lower end of the target surface, the middle of the right side of the device body, the upper end of the left side of the device body, and the back of the target surface of the device body.

2. The intelligent mobile device of claim 1, wherein, At least two fingerprint recognition units include a first fingerprint recognition unit, a second fingerprint recognition unit, a third fingerprint recognition unit, and a fourth fingerprint recognition unit; The first fingerprint recognition unit is located at the lower end of the target surface; the second fingerprint recognition unit is located in the middle of the right side of the device body; the third fingerprint recognition unit is located at the upper left side of the device body; and the fourth fingerprint recognition unit is located on the back of the target surface of the device body.

3. The intelligent mobile device of claim 2, wherein, The first fingerprint recognition unit includes a receiving electrode layer, a piezoelectric layer, a transmitting electrode layer, and a control circuit layer stacked sequentially; wherein, the first fingerprint recognition unit is located on the side of the target surface closer to the main body of the device, the receiving electrode layer is disposed close to the target surface, and the control circuit layer is connected to the processor.

4. The intelligent mobile device according to claim 3, characterized in that, The piezoelectric layer includes: a plurality of sub-piezoelectric layers arranged in an array; The receiving electrode layer includes: a plurality of receiving electrodes arranged in an array, wherein each of the plurality of receiving electrodes corresponds one-to-one with the plurality of sub-piezoelectric layers.

5. The intelligent mobile device of claim 2, wherein, The second fingerprint recognition unit includes a first capacitive sensor and a first algorithm board connected to each other, and the first algorithm board is connected to the processor; The length of the second fingerprint recognition unit ranges from 12 to 18 mm.

6. The intelligent mobile device of claim 5, wherein, The second fingerprint recognition unit is integrated on the power button or in the sliding touch sensing area in the middle of the right side of the main body of the device.

7. The intelligent mobile device of claim 2, wherein, The third fingerprint recognition unit includes a second capacitive sensor and a second algorithm board connected to each other, and the second algorithm board is connected to the processor. The length of the third fingerprint recognition unit ranges from 5 to 10 mm.

8. The intelligent mobile device of claim 2, wherein, The fourth fingerprint recognition unit includes a fingerprint chip and a microlens array located on the side of the fingerprint chip away from the device body. The side of the fingerprint chip away from the device body is provided with photosensitive pixels, and the microlenses in the microlens array correspond one-to-one with the photosensitive pixels. The fingerprint chip is connected to the processor.

9. The intelligent mobile device of claim 1, wherein, The iris recognition unit includes an infrared light source, an image acquisition lens, a supplementary light source, and a controller. The controller is connected to the image acquisition lens, the supplementary light source, and the processor, respectively. The infrared light source is connected to the processor.

10. The intelligent mobile device according to claim 9, characterized in that, The iris recognition unit is integrated into the front-facing camera of the main body of the device, and the image acquisition lens includes the front-facing camera.

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