A human voice interactive reading kiosk level lamp intensity indication automatic following system

Abstract

The application relates to the technical field of reading pavilion use systems, and discloses a human voice interactive reading pavilion level lamp intensity indication automatic following system which comprises the following operation steps: step one: scanning whether there is a person, a USB interface is externally installed on a processor, and the USB interface reads 3D point cloud data scanned by a laser radar; step two: identifying the number of people, the 3D point cloud data scanned by the laser radar is saved, and the 3D point cloud data contains a people number identification algorithm. The human voice interactive reading pavilion level lamp intensity indication automatic following system displays the human voice source state through the LED light bar only when a person is close to the reading pavilion, and does not display when there is no person, energy saving is achieved, and when a person walks near and far around the pavilion and sounds at the same volume, the LED light bar on the reading pavilion can also display stably, display fluctuation is reduced, and the state of the sound source can be truly displayed, that is, the stability of the LED light bar display can be increased.

Description

Technical Field

[0001] This invention relates to the technical field of reading booth systems, specifically to an automatic following system for the level light intensity indication of a human voice interactive reading booth. Background Technology

[0002] Currently, reading booths, as reading environments, are relatively static. When a person passes by the reading booth, the sound intensity is dynamically displayed by LED lights by collecting the sound volume around the booth. However, when a person speaks at the same volume and moves around the booth, the sound intensity indicator should remain unchanged or fluctuate very little to accurately show the volume of the voice. But existing solutions on the market affect the LED light intensity due to the distance between the sound source and the booth. Although there is an interactive effect, it cannot accurately reflect the true state of the sound source. Therefore, a human voice interactive reading booth level light intensity indicator automatic following system has been developed.

[0003] In the existing interactive reading booth level light intensity indicator automatic following system, the reading booth is constantly in working state during use. Maintaining the working state will cause current loss. At the same time, when no one is there, the outside of the reading booth will generate noise due to external wind and touch. Also, as long as there is sound inside the reading booth, the LED light will fluctuate and the LED light will be lit, which will cause some energy waste. Summary of the Invention

[0004] To address the shortcomings of existing automatic follow-up systems for level light intensity indication in interactive reading booths, this invention provides an automatic follow-up system for level light intensity indication in interactive reading booths. This system features laser radar scanning to detect passing crowds. Once the crowd has moved a certain distance, the system can monitor the distance and position of people and accurately calculate whether a person is using the reading booth. This increases the utilization rate of the reading booth and solves the problems mentioned in the background art.

[0005] This invention provides the following technical solution: an automatic following system for indicating the intensity of a level light in a human voice interactive reading booth, comprising the following operating steps:

[0006] Step 1: Scan to see if anyone is there.

[0007] The processor is externally equipped with a USB interface, which reads 3D point cloud data scanned by the LiDAR.

[0008] Step 2: Identify the number of people.

[0009] The 3D point cloud data scanned by the lidar is saved. The 3D point cloud data package contains a people recognition algorithm. The lidar scan detects the distance L1 and the included angle α between the person and the lidar.

[0010] Step 3: Calculate the distance.

[0011] Given L1, L2, L4 and the included angle α, use the Law of Cosines to calculate the distance.

[0012] L3=(L1^2+L2^2-2*L1*L2*COS(a))^0.5

[0013] L5=(L1^2+(L2+L4)^2-2*L1*(L2+L4)*COS(a))^0.5

[0014] The delay time for the sound from Mic1 to reach Mic2 is calculated as: T = (L3 - L5) / V;

[0015] Step 4: Beamforming algorithm,

[0016] To obtain the sound data of the target person from a specific direction closest to the reading booth and attenuate sound interference from other directions, the core idea of ​​the algorithm is to take the data M2[N] collected by Mic2, delay it by time T, and form a new array M2[N]. -T Mic2 and Mic1 collect data and perform calculations: M[N] = (M1[N] + M2[N]) -T ]) / 2;

[0017] Step 5: Sound compensation and correction.

[0018] Directional sound data M[N] is compensated for due to sound intensity attenuation caused by distance. Based on empirical data: "Sound Attenuation with Distance Table", the sound compensation value B corresponding to distance L1 is looked up to obtain the corrected sound data: M[N] = M[N] * B;

[0019] Step Six: Process data and control the lighting.

[0020] Calculate the maximum value M in the array M[N]. max The M value is obtained by performing an RC filtering algorithm (with a time constant set to 100ms). max-RC The CPU will M max-RC The value is converted to the LED light display intensity.

[0021] Preferably, the lidar scanner and the two microphones are kept on the same horizontal straight line. The two microphones are Mic1 and Mic2. The distance between Mic2 and the lidar is L2, the distance between Mic1 and Mic2 is L4, and the distances between the person and the microphones, Mic2 and Mic1 are L1, L3 and L5, respectively.

[0022] Preferably, in step 3, T can be a negative number, indicating that the sound arrives at Mic2 first; T can be a positive number, indicating that the sound arrives at Mic1 first.

[0023] Preferably, the microphone includes a pickup module, which has a signal amplification module installed inside. The signal amplification module is connected to an ADC module, which is connected to a CPU. The CPU is externally connected to a power module, a storage module, and a lidar module. The CPU is connected to a driver module, which controls the LED light strip.

[0024] Preferably, the power module includes an AC power interface, and the AC power interface is equipped with an AC power to DC 12V converter and a DC step-down module.

[0025] Preferably, in step 3, V is the speed of sound in the air.

[0026] Preferably, in step 2, if there are multiple people in the 3D point cloud data, only the 3D point cloud data of the person closest to the reading booth is retained.

[0027] Compared with the existing automatic following system for level light intensity indication in interactive reading booths, the present invention has the following advantages:

[0028] 1. The interactive voice reading booth features an automatic following system for LED light intensity indicators. This system displays the voice source status only when a person is near the reading booth, and does not display it when no one is around, thus saving energy. Furthermore, the LED light strip on the reading booth can maintain a stable display even when a person moves around the booth at a similar volume, reducing display fluctuations and truly displaying the voice source status, thereby increasing the stability of the LED light strip display. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the main operation process of the present invention;

[0030] Figure 2 This is a schematic diagram of the single-person radar and microphone signal reception of the present invention;

[0031] Figure 3 This is a schematic diagram of the multi-person spacing signal monitoring process of the present invention;

[0032] Figure 4 This is a schematic diagram of the system flow modules of the present invention;

[0033] Figure 5 This is a schematic diagram of the current conversion of the present invention;

[0034] Figure 6 This is a schematic representation of sound distance attenuation in this invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] Please see Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 and Figure 6 An automatic following system for the level light intensity indication in a human voice interactive reading booth includes the following operating steps:

[0037] Step 1: Scan to see if anyone is there.

[0038] The processor is externally equipped with a USB interface, which reads 3D point cloud data scanned by the LiDAR. The ejector is also externally equipped with a USB interface, which allows it to connect to the LiDAR. The LiDAR scans and detects external personnel and objects, detects the distance between the person and the processor, and generates and uploads 3D point cloud data.

[0039] Step 2: Identify the number of people.

[0040] The 3D point cloud data scanned by the lidar is saved. The 3D point cloud data package contains a people recognition algorithm. The lidar scan detects the distance L1 and the included angle α between the person and the lidar. The lidar saves the 3D metadata generated after scanning. The lidar scanning device can detect the number of people, and the lidar scan can calculate the distance L1 and α between the lidar and the person, which is convenient for the subsequent calculation of the distance between L3 and L5.

[0041] Step 3: Calculate the distance.

[0042] Given L1, L2, L4 and the included angle α, use the Law of Cosines to calculate the distance.

[0043] L3=(L1^2+L2^2-2*L1*L2*COS(a))^0.5

[0044] L5=(L1^2+(L2+L4)^2-2*L1*(L2+L4)*COS(a))^0.5

[0045] The delay time for the sound from Mic1 to reach Mic2 is calculated as: T = (L3 - L5) / V; by detecting L1, L2, L4 and the included angle α, the existing data can be used for investigation, and L3 and L5 are calculated using the formula;

[0046] L3=(L1^2+L2^2-2*L1*L2*COS(a))^0.5

[0047] L5=(L1^2+(L2+L4)^2-2*L1*(L2+L4)*COS(a))^0.5

[0048] After measuring and calculating the lengths of L3 and L5, the delay time for the sound from Mic1 to reach the microphone from Mic2 can be calculated, which serves to uniformly measure the position and distance between the person and the reading booth.

[0049] Step 4: Beamforming algorithm,

[0050] To obtain the sound data of the target person from a specific direction closest to the reading booth and attenuate sound interference from other directions, the core idea of ​​the algorithm is to take the data M2[N] collected by Mic2, delay it by time T, and form a new array M2[N]. -T Mic2 and Mic1 collect data and perform calculations: M[N] = (M1[N] + M2[N]) -T ]) / 2; By collecting data, we can calculate M[N]=(M1[N]+M2[N]) / 2; -T ]) / 2, which can reduce the impact of external noise on the speech of nearby personnel.

[0051] Step 5: Sound compensation and correction.

[0052] The directional sound data M[N] is compensated for by the sound intensity attenuation due to distance. Based on empirical data, "Sound Attenuation with Distance Table", the sound compensation value B corresponding to distance L1 is found in the table to obtain the corrected sound data: M[N] = M[N] * B. By checking the "Sound Attenuation with Distance Table" and finding the sound compensation value B corresponding to distance L1, the sound can be adjusted to avoid the influence of distance on sound propagation.

[0053] Step Six: Process data and control the lighting.

[0054] Calculate the maximum value M in the array M[N]. max The M value is obtained by performing an RC filtering algorithm (with a time constant set to 100ms). max-RC The CPU will M max-RC The value is converted to the LED light display intensity by using the maximum value M in the M[N] array. max The M value is obtained by performing an RC filtering algorithm (with a time constant set to 100ms). max-RC It can precisely control the distance of the sound, while also allowing the CPU to... max-RC The value is converted into the LED light display intensity, which increases the flexibility and precision of light intensity control.

[0055] refer to Figure 2 The lidar scanner and two microphones are kept on the same horizontal straight line. The two microphones are Mic1 and Mic2. The distance between Mic2 and the lidar is L2, and the distance between Mic1 and Mic2 is L4. The distances between the person and the microphones, Mic2 and Mic1 are L1, L3 and L5, respectively. Since the lengths of L2 and L4 are fixed, the lidar scanner can detect the length and angle between the person and the lidar scanner, thus monitoring the lengths of L3 and L5.

[0056] refer to Figure 1 In step 3, T can be negative, indicating that the sound arrives at Mic2 first, and T can be positive, indicating that the sound arrives at Mic1 first. By detecting the data of T in step 3, positive and negative values ​​of T can be calculated. T can be negative, indicating that the sound arrives at Mic2 first, and T can be positive, indicating that the sound arrives at Mic1 first. This allows us to measure the effect of people at different positions in front of the reading booth.

[0057] refer to Figure 4 The microphone includes a pickup module, which internally houses a signal amplification module. This signal amplification module is connected to an ADC module, which is connected to a CPU. The CPU is externally connected to a power supply module, a storage module, and a lidar module. The CPU is also connected to a driver module, which controls the LED strip. The microphone's pickup module, internally housing a signal amplification module connected to an ADC module and connected to the CPU, increases the microphone's sound reception efficiency. Simultaneously, the external power supply and storage modules of the CPU effectively power the device and store information about personnel.

[0058] refer to Figure 5 The power module includes an AC power interface, which is equipped with an AC power to DC 12V converter and a DC step-down module. A current conversion and step-down module is installed through the pilot interface, which can effectively convert AC power into power usable by the device. The internal sound of the reading booth is 12V, which can avoid the problem of electric shock damage to the user caused by excessive voltage.

[0059] refer to Figure 1 In step 3, V is the speed of sound in the air. By using V as the speed of sound in the air in step 3, the sound propagation time in step 3 can be monitored.

[0060] refer to Figure 3In step 2, if there are multiple people in the 3D point cloud data, only the 3D point cloud data of the person closest to the reading booth is retained. At the same time, if there are multiple people in the 3D point cloud data, the data of the people who are close to each other can be detected to avoid the problem of too many people in front of the reading booth causing noise and affecting the microphone's sound absorption effect.

[0061] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A voice-interactive reading booth level light intensity indication automatic following system, wherein the microphone includes a sound pickup module, and the sound pickup module has a signal amplification module installed inside, characterized in that: The signal amplification module is connected to an ADC module, which is connected to the CPU. The CPU is externally connected to a power module, a storage module, and a lidar module. The CPU is also connected to a driver module, which controls the LED light strip. The following steps are included: Step 1: Scan to see if anyone is there. The processor is externally equipped with a USB interface, which reads 3D point cloud data scanned by the LiDAR. Step 2: Identify the number of people. The 3D point cloud data scanned by the lidar is saved. The 3D point cloud data package contains a people recognition algorithm. The angle between the person and the lidar and between the lidar and the microphone is α. Step 3: Calculate the distance. Given L1, L2, L4 and the included angle α, use the Law of Cosines to calculate the distance. L3=(L1^2+L2^2-2 L1 L2 COS(a))^0.5 L5=(L1^2+(L2+L4)^2-2 L1 (L2+L4) COS(a))^0.5 The time difference between the distance from Mic1 to the person and the distance from Mic2 to the person is calculated as: T = (L3 - L5) / V; where V is the speed of sound in air. The lidar and two microphones are kept in the same horizontal straight line. The two microphones are Mic1 and Mic2. The distance between Mic2 and the lidar is L2. The distance between Mic1 and Mic2 is L4. The distances between the person and the lidar, Mic2 and Mic1 are L1, L3 and L5, respectively. Step 4: Beamforming algorithm, To obtain the sound data of the target person from a specific direction closest to the reading booth and attenuate sound interference from other directions, the core idea of ​​the algorithm is to take the data M2[N] collected by Mic2, delay it by time T, and form a new array M2[N]. -T The data M1[N] collected by Mic1 are used to form a new array M1[N]. -T Mic2 and Mic1 collect data and perform calculations: M[N] = (M1[N] + M2[N]) -T ]) / 2; Step 5: Sound compensation and correction. The directional sound data M[N] is compensated for by sound intensity attenuation due to distance. Based on empirical data and experiments, a "sound attenuation table with distance" is derived. Looking up the corresponding sound compensation value B in table L1, the corrected sound data is obtained: M[N] = M[N] B; Step Six: Process data and control the lights. Calculate the maximum value M in the array M[N]. max And perform RC filtering algorithm processing to obtain M max-RC The time constant is set to 100ms, and the CPU sends M... max-RC The value is converted to the LED light display intensity.

2. The automatic following system for level light intensity indication in a human voice interactive reading booth according to claim 1, characterized in that: In step three, if T is negative, it means that the sound reaches Mic2 first; if T is positive, the sound reaches Mic1 first.

3. The automatic following system for indicating the intensity of the level light in a human voice interactive reading booth according to claim 1, characterized in that: The power module includes an AC power interface, which is equipped with an AC power to DC 12V converter and a DC step-down module.

4. The automatic following system for level light intensity indication in a human voice interactive reading booth according to claim 1, characterized in that: In step two, since there are multiple people in the 3D point cloud data, only the 3D point cloud data of the person closest to the reading booth is retained.

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