Multimodal triboelectric self-powered smart floor system

Abstract

The present invention provides a self-powered intelligent floor system based on the principle of triboelectric power generation, comprising a solid wood floor body, a superelastic triboelectric pressure sensor, a material identification electrode, a group positioning interconnection design, a data readout module, a data acquisition module, an energy acquisition module, a BLE Bluetooth module, and a mobile phone / PC supporting APP. The solid wood floor body, the superelastic triboelectric pressure sensor, and the material identification electrode are stacked up and down in a certain order and quantity to form a single multimodal intelligent floor unit. After multiple intelligent floor units are interconnected, an array is obtained. When the human body interacts with the intelligent floor unit through gait, the generated material identification signal and pressure signal will be collected by the data reading module, a part of which will enter the data acquisition module for positioning and identification; the other part will enter the energy acquisition module to realize the self-powered function.

Description

Technical Field

[0001] The present invention belongs to the field of triboelectric smart home, and specifically relates to a multi-modal triboelectric self-powered smart floor system. Background Art

[0002] Promote technological innovation in sensors, network slicing, and high-precision positioning, coordinate the development of cloud and edge computing services, and foster the Internet of Vehicles, the Internet of Medical Things, and the Internet of Home Things. With the advent of the 5G era, the interconnected Internet of Things (IoT) and the digital twin of virtual and real interaction have become the trend of the times. The multimodal triboelectric self-powered smart floor system can achieve more convenient home monitoring and interaction, providing multimodal sensor big data for building an interconnected smart home digital twin platform. It also empowers other smart sensors through energy harvesting, playing an important role in supporting the smart city strategies of the United States, the European Union, Singapore, South Korea, and other countries, and is therefore of great significance.

[0003] Existing floor sensors have problems such as high cost over large areas, difficulty in laying, single function, high complexity of large arrays, and the failure to integrate sensing and energy harvesting. They are still mainly in the research stage and have not been widely commercialized.

[0004] Nowadays, scalable, multifunctional smart floor systems are a future trend. Therefore, a multimodal triboelectric self-powered smart floor system has been proposed. Based on triboelectric self-powered sensing and energy harvesting technology as its core innovation, it uses deep learning-assisted data analysis to implement smart home monitoring and interactive applications such as home positioning, trajectory tracking, motion monitoring, gait monitoring, home security, and gaming / personalized interaction. Its goal is to achieve maximum automation and multifunctionality in smart home interconnection and monitoring, while reducing overall system energy consumption. It is also applicable to most triboelectric monitoring scenarios and has high versatility. Summary of the Invention

[0005] Technical Issues: Existing triboelectric floor sensors are primarily based on a single-mode monitoring principle. This results in a single sensor signal source, preventing the acquisition of rich information and resulting in low data recognition accuracy. Current floor sensors are either used solely for triboelectric sensing or solely for energy harvesting, failing to fully utilize the entire system. Large-scale floor arrays suffer from the large number of electrodes and complex wiring. Given current trends, a multimodal intelligent floor system is needed that integrates sensing and energy harvesting with a minimized electrode design.

[0006] Technical solution: To solve the above problems, the present invention proposes a multi-modal triboelectric self-powered intelligent floor system, including multiple sets of intelligent floors, data readout modules, data acquisition modules and energy acquisition modules,

[0007] The smart floor group is used to convert pressure information into a voltage signal output; each smart floor group is connected to a data readout module respectively, which is used to collect the voltage signal of each smart floor group and process the voltage signal. The data readout module processes the collected voltage signal, including boosting the voltage signal, and then using an operational amplifier to achieve voltage isolation. Finally, a first-order RC network is used for low-pass filtering to remove noise. The processed voltage signal enters the data acquisition module to obtain more stable data transmission; the output of the smart floor group is also connected to the energy acquisition module. The energy collected by the energy acquisition module is used to self-power the above-mentioned data readout module and data acquisition module.

[0008] The low-noise operational amplifier RS822XK used in the data readout module is used for voltage isolation.

[0009] The data acquisition module adopts the AD7606 multi-channel AD data acquisition module, which is suitable for stable data transmission.

[0010] The energy collection module includes an LTC3588 nanopower buck regulator, which is used to stably supply energy to other modules. Furthermore, the multimodal triboelectric self-powered intelligent floor system of the present invention also includes a BLE Bluetooth module and a mobile APP; the data collection module is wirelessly transmitted to the mobile APP through the BLE Bluetooth module for integration calculation; the energy collection module is connected to the BLE Bluetooth module to supply energy to the BLE Bluetooth module; the Bluetooth module includes a Bluetooth chip nRF52832 and its supporting circuits, and its internal processor can complete the processing of protocol and application tasks in a short time, and can enter sleep mode in a shorter time to save power, which is suitable for large-scale use

[0011] The data readout module, data acquisition module, BLE Bluetooth module, and energy acquisition module all use mature commercial chips, which are cheap, stable, and reliable, and are suitable for application in smart floor systems.

[0012] Furthermore, the smart flooring assembly includes multiple smart flooring units; each unit comprises a base, a superelastic triboelectric pressure sensor, an insulating layer, and a solid wood panel stacked in sequence from bottom to top. The smart flooring unit contains nine superelastic triboelectric pressure sensors arranged in a 3x3 array. Five of these sensors, located at the four corners and the center, are used for pressure sensing. The outputs of these five superelastic triboelectric pressure sensors, connected in series, are connected to the other smart flooring units to form the smart flooring unit assembly. The outputs of the remaining four superelastic triboelectric pressure sensors, used for energy harvesting, are then connected to the energy harvesting unit. The solid wood flooring is constructed from lightweight, non-deformable pinewood panels. The superelastic triboelectric pressure sensors are made of Ecoflex 00_30 silicone rubber, cured in a custom mold created using 3D printing.

[0013] The base is used to support the entire smart floor unit and separate it from the ground; the insulating layer is used to prevent crosstalk between the signals generated by the super-elastic triboelectric pressure sensor and the material identification electrode; the presence of the solid wood board ensures that the nine super-elastic triboelectric pressure sensors are evenly stressed.

[0014] Furthermore, the smart floor unit also includes material recognition electrodes. Located on the top surface of the solid wood board, these electrodes are used to identify the material in contact with them. These electrodes consist of interdigitated aluminum electrodes and an insulating recognition material, such as PI or PET, attached to the electrodes. The insulating recognition material is repeated in a fixed sequence, ensuring that a recognizable signal is generated regardless of user contact from different locations and directions. Four known insulating recognition materials are pre-applied to the interdigitated electrode surface, arranged in a fixed, repeated sequence.

[0015] When a person interacts with the smart floor through gait, the hyperelastic triboelectric pressure sensor collects pressure information from the user and simultaneously harvests energy; the material recognition electrode collects information about the material and contact area. The multimodal implementation and integrated sensing and energy harvesting design ensure the versatility of the entire system.

[0016] Furthermore, the smart floor units are interconnected through groups. Each group of smart floor units, also called a smart unit group, includes four smart floor units. In order to ensure that continuous stepping will not cause signal coupling problems, each smart unit is in a different group from all the surrounding adjacent smart floor units. The simultaneous reading of position information and pressure information reduces the number of electrodes and reduces the complexity of the design.

[0017] Furthermore, the smart floor units in the smart floor group are connected in series in sequence, and resistors are connected in series between adjacent smart floor units. The smart floor units located at the head and tail ends of the series circuit in the smart floor group respectively draw out electrode output voltage signals, and the positioning is performed through the ratio of the voltage signals at the head and tail ends to determine the position of the smart floor unit where the signal is generated, and the size of the charge is used to determine the pressure.

[0018] The mobile terminal can be a mobile phone or PC. The app on the mobile phone or PC receives the processed voltage signal data transmitted by the Bluetooth module, identifies the data based on factors such as the voltage signal's waveform, relative amplitude, and peak-to-valley sequence, integrates the charge, and visualizes the positioning information, pressure information, material identification information, and personal identity information in the signal through intuitive animation within the app interface. The machine learning training algorithm embedded in the app improves the accuracy of data recognition and also enables human-computer interaction. Based on open source code, the mobile app can be modified to meet different interaction requirements in different scenarios.

[0019] The machine learning training algorithm is written in Python, and the Bluetooth module transmits the collected information to the mobile terminal. After program processing, it can perform high-accuracy identity recognition, home positioning, trajectory tracking, movement monitoring, movement quality monitoring, and gait monitoring on the user.

[0020] Beneficial effects: Compared with existing floor sensors, the multi-modal triboelectric self-powered intelligent floor system of the present invention has the following advantages:

[0021] 1. Large-scale use. The intelligent floor array is composed of single floor units connected together, with strong scalability, simple configuration, low cost, and is suitable for various monitoring application scenarios;

[0022] 2. Rich multimodal sensing information. The simultaneous application of planar material recognition electrodes and microstructured superelastic triboelectric pressure sensors can simultaneously collect multiple sensing information;

[0023] 3. Realize self-powered sensing and low system energy consumption. Integrating triboelectric sensing and energy harvesting effectively reduces energy consumption issues caused by large-scale deployment.

[0024] 4. Minimize electrode design and simplify circuit modules. Through reasonable grouping, interconnection, and decoupling of sensing information, the number of electrodes is greatly reduced, thus reducing design costs.

[0025] 5. Smooth operation. The nRF52832 Bluetooth chip's onboard 64MHz ARM Cortex-M4F processor can complete protocol and application processing in a short time, making the acquisition process smooth and smooth;

[0026] 6. High accuracy. The multi-modal triboelectric self-powered intelligent floor system of the present invention has been trained through machine learning, and the data processing has high accuracy.

[0027] 7. Smooth operation. The nRF52832 Bluetooth chip's onboard 64MHz ARM Cortex-M4F processor can complete protocol and application processing in a short time, making the acquisition process smooth and smooth;

[0028] 8. Human-computer interaction. The present invention uses mobile APP visualization processing to improve the interactivity between the smart floor system and people, making monitoring easier to implement. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is the overall composition diagram of the multimodal triboelectric self-powered intelligent floor system.

[0030] Figure 2 This is the schematic diagram of the multimodal triboelectric self-powered smart floor system.

[0031] Figure 3 This is a data verification diagram of the positioning function of the multimodal triboelectric self-powered intelligent floor system.

[0032] Figure 4 It is the distribution diagram of the hyperelastic triboelectric pressure sensor in the smart floor unit.

[0033] The figure includes: 1. Solid wood board; 2. Material identification electrode; 3. Superelastic triboelectric pressure sensor; 4. Smart floor unit; 5. Insulation layer; 6. Base; 7. Data readout module; 8. Data acquisition module; 9. BLE Bluetooth module; 10. Mobile APP; 11. Energy collection module. DETAILED DESCRIPTION

[0034] The technical solution of the multi-modal triboelectric self-powered intelligent floor system of the present invention is further described in detail below with reference to the accompanying drawings and embodiments.

[0035] like Figure 1 As shown, the present invention proposes a multimodal triboelectric self-powered intelligent floor system, including multiple sets of intelligent floors, a data readout module 7, a data acquisition module 8, an energy acquisition module, a BLE Bluetooth module 9 and a mobile terminal APP 10;

[0036] like Figure 2 As shown, the smart floor group includes multiple smart floor units 4; the smart floor unit 4 includes a base 6, a super-elastic triboelectric pressure sensor 3, an insulating layer 5, a solid wood board 1 and a material identification electrode 2 stacked in sequence from bottom to top; wherein, there are nine super-elastic triboelectric pressure sensors 3 in the smart floor unit 4, as shown in FIG. Figure 4As shown, the five superelastic triboelectric pressure sensors 3 are arranged in a 3*3 array and located at the four corners and the center for pressure sensing. The five superelastic triboelectric pressure sensors 3 are arranged as shown in FIG. Figure 4 The other four superelastic friction electric pressure sensors 3 are also connected in series according to Figure 4 The material identification electrode 2 includes a forked electrode and an insulating identification material on the electrode, such as PI, PET, etc. The forked electrode is an aluminum electrode, and the insulating identification material is pasted on the aluminum electrode. The material identification electrode only exists at the entrance of the array. The corresponding electrode is connected according to the number of identification materials. The subsequent processing method is the same as the pressure signal processing method mentioned above. The superelastic triboelectric pressure sensor (three-dimensional structure sensor) and the material identification electrode (planar sensor) perform triboelectric sensing at the same time, that is, multimodal sensing.

[0037] The superelastic triboelectric pressure sensor is made of silicone rubber cured in a special mold and has a unique mixed microstructure of large and small sizes. In addition, materials with different Young's moduli and electronegativity such as the Ecoflex series (such as Ecoflex00_10, Ecoflex 00_30), PDMS, and AB glue can be flexibly selected according to the usage scenario and measurement pressure range.

[0038] The grouped positioning interconnection design includes resistor interconnection and dual-electrode readout to minimize electrode design. Multiple smart floor units 4 are combined into a smart floor array through grouped positioning and interconnection design. The grouped positioning design means that each group of smart floor units 4 includes four smart floor units 4, and each smart unit is in a different group from all adjacent smart floor units 4. The interconnection design of smart floor units 4 means that each smart floor group includes four smart floor units 4, and the smart floor units 4 in each smart floor group are connected in series in sequence, with resistors connected in series between adjacent smart floor units 4. The smart floor units 4 at the head and tail of the series circuit in the smart floor group respectively draw out electrode output voltage signals. The ratio of the voltage signals at the head and tail is used for positioning, determining the position of the smart floor unit 4 generating the signal, and the magnitude of the charge is used to determine the magnitude of the pressure.

[0039] The smart floor array's electrodes are connected to a data readout module 7 and an energy harvesting module 11. The data readout module 7 is then connected to a data acquisition module 8 and a Bluetooth Low Energy (BLE) module 9 for preliminary data processing, acquisition, and wireless transmission. The energy harvesting module 11 supplies energy to these modules, enabling the system to self-power itself. After receiving data transmitted by the Bluetooth Low Energy (BLE) module 9, the mobile app 10 further processes and identifies the data, using machine learning training algorithms to improve accuracy. The data readout module 7, data acquisition module 8, Bluetooth Low Energy (BLE) module 9, and energy harvesting module 11 all utilize mature commercial chips, which are inexpensive, stable, and reliable, making them suitable for use in smart floor systems.

[0040] The multimodal triboelectric self-powered intelligent floor system is arranged in the home. When a family member steps into the array entrance, the material identification electrode 2 on the surface comes into contact with the user's shoes, socks or soles of the feet, generating a triboelectric signal. At the same time, the superelastic triboelectric pressure sensor 3 located below will generate a voltage signal under the action of the user's weight, part of which will enter the data readout module 7 together with the signal generated by the material identification electrode 2, and the other part of the signal will enter the energy collection module 11; the signal entering the data readout module 7 is collected by the data collection module 8 after boosting, voltage isolation and low-pass filtering, and transmitted to the mobile terminal APP 10 by the BLE Bluetooth module 9 for further processing; the signal entering the energy collection module 11 will be converted and used to read the data readout module 7, the data collection module 8, and the BLUE Bluetooth module 9. E Bluetooth module 9 is used for power supply; after receiving the signal, the mobile terminal APP 10 will identify the user by identifying the difference in signals generated by different users stepping on it, analyze the signal generated by the material identification electrode 2 to obtain the properties of the material in contact with it, and thus determine whether the user is barefoot, wearing socks or shoes, and the type of contact material, integrate the signal generated by the superelastic friction electric pressure sensor 3 and determine the user's weight by the size of the charge value, and finally give exercise suggestions on the interactive interface based on the above information and pre-stored user information. Due to the assistance of the machine learning training algorithm, the above data processing has a very high accuracy; after that, the user enters the array body and moves between the grouped interconnected smart floor units 4. After the same data reading and processing process, the ratio of the signals collected by the two electrodes in each group is used to obtain the user's position, such as Figure 3 As shown, the positioning and trajectory tracking functions are realized, and the occurrence of accidents such as falls can be monitored.

[0041] The advantages of the present invention are that it has strong scalability and the number of smart floor units 4 included in the system is not fixed, which makes its application scenarios very flexible; the subsequent data preliminary processing, collection and transmission, and energy collection modules use existing commercial modules, which are low in cost and stable in process; the addition of the energy collection module 11 greatly reduces the energy consumption of the system; the mobile APP 10 is used to improve the ability of human-computer interaction, increase visualization and reminder functions, and use machine learning training algorithms to assist, so that data recognition accuracy is high; the overall equipment is cheap and stable, can be used in most smart home scenarios, has a wide range of applications, and can be promoted.

Claims

1. A multi-modal triboelectric self-powered intelligent floor system, characterized in that: It includes multiple sets of intelligent floors, data readout modules, data acquisition modules and energy acquisition modules; The intelligent floor group is used to convert pressure information into voltage signal output; Each smart floor group is connected to a data readout module. The data readout module is used to collect the voltage signal of each smart floor group and process the voltage signal. The processed voltage signal enters the data acquisition module. The output of the smart floor group is also connected to the energy collection module. The energy collected by the energy collection module is used to self-power the above-mentioned data readout module and data collection module; The smart floor group includes a plurality of smart floor units; The smart floor unit consists of a substrate, a hyperelastic triboelectric pressure sensor, an insulating layer, and a solid wood board stacked sequentially from bottom to top; The intelligent floor unit contains nine hyperelastic triboelectric pressure sensors arranged in a 3x3 array. Four sensors at the four corners of the 3x3 array and one at the center are used for pressure sensing. These five sensors are connected in series and output voltage signals. The remaining four superelastic triboelectric pressure sensors are used for energy collection, and the output ends of the four superelastic triboelectric pressure sensors are connected to the energy collection unit.

2. A multi-modal triboelectric self-powered intelligent floor system according to claim 1, characterized in that: The intelligent floor unit also includes a material identification electrode, which is located on the upper surface of the solid wood board and is used to contact different materials and perform material identification after subsequent data processing. The material identification electrode has a cross-finger structure.

3. The multimodal triboelectric self-powered intelligent floor system according to claim 1, characterized in that: Each group of intelligent floor units, also called an intelligent unit group, includes four intelligent floor units, and each intelligent unit is in a different group from all the surrounding adjacent intelligent floor units.

4. The multimodal triboelectric self-powered intelligent floor system according to claim 1, characterized in that: The smart floor units in the smart floor group are connected in series in sequence, and resistors are connected in series between adjacent smart floor units. The smart floor units at the head and tail ends of the series circuit in the smart floor group respectively draw out electrode output voltage signals, and the positioning is determined by the ratio of the voltage signals at the head and tail ends to determine the position of the smart floor unit where the signal is generated, and the size of the charge is used to determine the pressure.

5. The multimodal triboelectric self-powered intelligent floor system according to claim 1, characterized in that: The data readout module processes the collected voltage signal by boosting it, isolating it through an operational amplifier, and finally performing a low-pass filter through a first-order RC network to remove noise.

6. The multimodal triboelectric self-powered intelligent floor system according to claim 1, characterized in that: It also includes a BLE Bluetooth module and a mobile APP; The data acquisition module transmits the data wirelessly to the mobile APP through the BLE Bluetooth module for integration calculation; The energy harvesting module is connected to the BLE Bluetooth module to supply energy to the BLE Bluetooth module.

7. The multimodal triboelectric self-powered intelligent floor system according to claim 6, characterized in that: The Bluetooth module includes the Bluetooth chip nRF52832 and its supporting circuits.

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