Data collection method, device and system

Abstract

The present disclosure discloses a data acquisition method, device, and system. The method comprises: generating a sound signal watermark based on first audio data collected by a microphone, wherein the sound signal watermark is a signal in the audible frequency domain of the human ear and has lower energy than the signal in the audio data; sending the sound signal watermark to a speaker so that the speaker plays the sound signal watermark in the form of an analog signal; and receiving second audio data collected by the microphone, wherein the second audio data includes a superposition signal of the original ambient sound signal collected by the microphone and the sound signal watermark.

Description

Technical Field

[0001] The present disclosure relates to the field of data acquisition technology, and in particular to a data acquisition method, device, and system. Background Art

[0002] Existing data acquisition technology based on ultrasonic analog signal watermarking involves controlled addition of an ultrasonic analog signal to the environment during the acquisition process. This superimposes the ultrasonic signal watermark on the sound signal reflecting the target object. After digital-to-analog conversion and digital encoding, the audio data contains the relevant information embedded in the ultrasonic analog signal watermark. The authenticity of the audio data is subsequently verified by verifying whether the data contains the relevant information of the ultrasonic analog watermark.

[0003] Although this technology can prevent forgery attacks through reverse engineering to a certain extent, malicious actors can easily infer and forge ultrasonic analog signal watermarks by observing historical ultrasonic signals, making the collected audio data unreliable. Summary of the Invention

[0004] In view of this, the present disclosure provides a data collection method and apparatus to increase the reliability of collected audio data.

[0005] In a first aspect, a data acquisition method is provided, comprising: generating a sound signal watermark based on first audio data collected by a microphone, wherein the sound signal watermark is a signal in the frequency domain audible to the human ear, and the energy of the sound signal watermark is lower than the energy of the signal in the audio data; sending the sound signal watermark to a speaker so that the speaker plays the sound signal watermark in the form of an analog signal; and receiving second audio data collected by a microphone, wherein the second audio data includes a superimposed signal of an original ambient sound signal collected by the microphone and the sound signal watermark.

[0006] According to a second aspect, a data acquisition method is provided, including: a data acquisition device acquires first audio data; the data acquisition device generates a sound signal watermark based on the first audio data, wherein the sound signal watermark is a signal in the frequency domain audible to the human ear, and the energy of the sound signal watermark is lower than the energy of the signal in the audio data; the data acquisition device plays the sound signal watermark in the form of an analog signal; the data acquisition device acquires second audio data, and the second audio data includes a superimposed signal of the original environmental sound signal and the sound signal watermark; the data acquisition device sends the sound signal watermark and the second audio data to the blockchain, so that the blockchain can store the sound signal watermark and the second audio data; the server obtains the sound signal watermark and the second audio data from the blockchain, and verifies whether the second audio data contains the sound signal watermark.

[0007] According to a third aspect, a data acquisition device is provided, comprising: a generating module for generating a sound signal watermark based on first audio data collected by a microphone, wherein the sound signal watermark is a signal in the frequency domain audible to the human ear, and the energy of the sound signal watermark is lower than the energy of the signal in the audio data; a sending module for sending the sound signal watermark to a speaker so that the speaker plays the sound signal watermark in the form of an analog signal; and a receiving module for receiving second audio data collected by a microphone, wherein the second audio data includes a superimposed signal of the original ambient sound signal collected by the microphone and the sound signal watermark.

[0008] In a fourth aspect, a data acquisition device is provided, comprising: a sound sensor for collecting sensing information; a transmitting device for transmitting an analog signal; a memory for storing a code for generating a sound signal watermark; and a processor for executing the code stored in the memory to utilize the sound sensor and the transmitting device to perform the method described in the first aspect.

[0009] In a fifth aspect, a data acquisition system is provided, including: a data acquisition device for collecting first audio data; generating a sound signal watermark based on the first audio data, wherein the sound signal watermark is a signal in the frequency domain audible to the human ear, and the energy of the sound signal watermark is lower than the energy of the signal in the audio data; playing the sound signal watermark in the form of an analog signal; collecting second audio data, the second audio data including a superimposed signal of the original environmental sound signal and the sound signal watermark; sending the sound signal watermark and the second audio data to a blockchain so that the blockchain can store the sound signal watermark and the second audio data; a server, for obtaining the sound signal watermark and the second audio data from the blockchain, and verifying whether the second audio data contains the sound signal watermark.

[0010] In a sixth aspect, a computer-readable storage medium is provided, on which executable code is stored. When the executable code is executed, the method described in the first aspect or the second aspect can be implemented.

[0011] In a seventh aspect, a computer program product is provided, comprising an executable code, which, when executed, can implement the method described in the first aspect or the second aspect.

[0012] The ultrasonic watermarks used in existing ultrasonic analog watermarking technologies are easily inferred or reverse engineered because they belong to different frequency domains than the original sound signal. This disclosure utilizes a sound signal watermark in the human-audible frequency domain, superimposing it on the original ambient sound signal. This allows for a more thorough blending of the sound signal watermark and the original ambient sound signal, thereby increasing the difficulty of forgery attacks. Furthermore, this disclosure sets the energy of the sound signal watermark to be lower than the energy of the signal in the audio data. This is done to exploit the acoustic masking effect, allowing the high-energy signal in the audio data to mask the low-energy sound signal watermark. This prevents the sound signal watermark in the audio data from being heard by the human ear and, therefore, does not affect the quality of the original ambient sound signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 Shown is an example diagram of the system framework of an embodiment of the present disclosure.

[0014] Figure 2 FIG2 is a schematic diagram for explaining the sound masking effect provided by an embodiment of the present disclosure.

[0015] Figure 3 The figure is a flow chart of a data collection method provided in one embodiment of the present disclosure.

[0016] Figure 4 Shown Figure 3 Flow chart of the implementation method of step S310.

[0017] Figure 5 Shown is a flow chart of a data acquisition method provided by another embodiment of the present disclosure.

[0018] Figure 6 Shown is a structural diagram of a data acquisition device provided by an embodiment of the present disclosure.

[0019] Figure 7 Shown is a structural schematic diagram of a data acquisition device provided by another embodiment of the present disclosure.

[0020] Figure 8 Shown is a schematic structural diagram of a data acquisition system provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0021] The technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments.

[0022] Off-chain descriptions of people, objects, and places are typically based on data collection from offline IoT devices. This data, collected through video and photo capture, audio capture, and sensors like Radio Frequency Identification (RFID), Bluetooth, and Ultra Wide Band (UWB), is uploaded to the blockchain to create a comprehensive portrait, providing proof of the existence of the abstract model on the chain. While blockchain's on-chain trusted transfer technology is relatively mature, there are still many challenges in the process of transferring information from the off-chain physical world to its actual reflection on the chain.

[0023] Currently, some anti-counterfeiting technologies, such as digital watermarking and blockchain consensus, can further verify data collected by terminal devices, but they are not yet effective at the earlier sensor acquisition stage. Physical anti-counterfeiting technologies require a high degree of process and technical customization, resulting in high physical integration and implementation costs. Identity authentication technologies focus on people and devices rather than data. Sensor hardware fingerprinting can, to a certain extent, verify the authenticity of data collected from devices after the fact, but its accuracy is low and it is susceptible to forgery attacks through reverse engineering.

[0024] As can be seen from the above description, in the process of data collection, how to ensure the authenticity and credibility of the collected objects and the collection process is an issue that is both interesting and of practical value.

[0025] Currently, there are some trusted data collection technologies, such as using terminals to reliably collect data, mini-programs (for example, Alipay mini-programs) or other applications (APPs) jumping to trusted data collection APPs for evidence collection. After the trusted data collection APP collects data, it uploads it to the blockchain trusted evidence storage, and then sends the evidence code to the mini-program or other APP. The mini-program or other APP can verify the authenticity of the collected data afterwards through the evidence code.

[0026] Similar technologies can also be used to collect data from edge devices other than terminals (such as sound sensors). For example, during the data collection process, a trusted data collection app receives the output of the sound sensor and uploads it to the blockchain for trusted storage.

[0027] However, simply using a trusted data collection app to collect data and store evidence, and then ensuring data authenticity through post-verification, does not meet the data trust requirement. Malicious actors can come from outside the system (illegal users of Ant Chain) or from within the system (legitimate users of Ant Chain). The former can commit malicious acts by stealing devices and attacking them and their software without their knowledge, while the latter can commit malicious acts by directly attacking devices and software and forging collection objects and contexts.

[0028] Analog signal watermarking technology ensures secure and reliable data collection during the acquisition phase, increasing the cost of malicious actors. This technology involves controlled addition of an analog signal watermark to the environment during the data acquisition process. This watermark is then superimposed on the sound signal reflecting the target object. After digital-to-analog conversion and digital encoding, the audio data contains the relevant information embedded in the watermark. A malicious actor must distinguish the watermark from the original audio data to forge the watermark. Furthermore, the authenticity of the audio data can be further verified by post-verification of the presence of the watermark information in the data.

[0029] In order to facilitate understanding of the data collection method provided by the embodiment of the present disclosure, Figure 1 , taking trusted data collection as an example, the system framework in which the embodiments of the present disclosure may be applied is first illustrated.

[0030] like Figure 1 As shown, the system 100 includes: a microphone 110, a trusted data collection APP 120, a speaker 130, and a blockchain 140.

[0031] The microphone 110 may be configured to receive analog signals and decode the analog signals into digital signals. The received analog signals may be, for example, original ambient sound signals from the environment, analog signals transmitted to the environment by the speaker 130, or a sound signal resulting from the superposition of the original ambient sound signals and the analog signals transmitted to the environment by the speaker 130.

[0032] The trusted data collection app 120 can be used to receive the output information of the microphone 110. Furthermore, the trusted data collection app 120 can also be used to generate and send a sound signal watermark to the speaker 130. The output information of the microphone 110 received by the trusted data collection app 120 is a digital signal, and the sound signal watermark generated is also a digital signal. In some implementations, the trusted data collection app 120 can be a trusted app running on the terminal device.

[0033] Furthermore, the trusted data collection APP 120 is also used to send sound signal watermarks and audio data evidence to the blockchain 140 so as to verify the sound signal watermarks and audio data on the blockchain 140.

[0034] The speaker 130 may be configured to receive a digital signal sent by the trusted data collection APP 120 , encode the digital signal into an analog signal, and transmit the analog signal into an environment.

[0035] Blockchain 140 can be used to store the sound signal watermarks generated by the trusted data collection app 120, as well as the audio data obtained through data collection. Furthermore, blockchain 140 can be used to verify the sound signal watermarks in the cloud to determine the authenticity of the audio data.

[0036] As an example, during the data collection process, microphone 110 receives the original ambient sound signal and decodes it into a digital signal. Trusted data collection app 120 receives the digital signal output by microphone 110, generates a sound signal watermark, and sends it to speaker 130. Simultaneously, trusted data collection app 120 sends the sound signal watermark to blockchain 140 for storage. Speaker 130 encodes the digital sound signal watermark provided by trusted data collection app 120 into an analog sound signal watermark and transmits the analog sound signal watermark into the environment, where it is superimposed with the original ambient sound signal. Microphone 110 receives the superimposed sound signal, decodes it into a digital signal, and outputs it to trusted data collection app 120. Trusted data collection app 120 sends the digitally encoded audio data containing the analog sound signal watermark to blockchain 140 for storage. A cloud-based verification program on blockchain 140 verifies whether the audio data contains the previously stored sound signal watermark to determine the data's authenticity.

[0037] Traditional analog signal watermarking technology superimposes ultrasonic analog signal watermarks. Although ultrasonic analog signal watermarking technology can prevent forgery attacks by reverse engineering to a certain extent, malicious actors can infer and forge the generation of ultrasonic analog signal watermarks by observing historical ultrasonic signals.

[0038] An analysis of traditional technologies reveals that trusted data acquisition based on ultrasonic analog signal watermarking, which superimposes an ultrasonic analog signal on the original ambient sound signal, can, to a certain extent, prevent reverse engineering attacks without affecting the quality of the original ambient sound signal. However, because the watermark is an ultrasonic signal watermark, which operates in the ultrasonic frequency domain, different from the frequency domain of the original ambient signal, it is easy for attackers to distinguish the ultrasonic signal from the real audio signal containing the ultrasonic signal watermark. By observing historical ultrasonic signals, they can infer and forge the generation of the ultrasonic analog signal watermark.

[0039] Based on the above analysis, this paper uses a sound signal in the human audible frequency range of 20Hz to 20,000Hz as a sound signal watermark, superimposing this sound signal watermark onto the original ambient sound signal. By taking advantage of the fact that the frequency domain of the original ambient sound signal and the sound signal watermark are the same, the superposition of the two allows for a more thorough blending of the watermark and the original audio, making forgery attacks more difficult.

[0040] However, the human ear's sensitivity to one sound will decrease with the addition of another sound, and the closer the frequencies of the two sounds, the more easily the original sound is affected, and even the original sound is difficult to hear. Therefore, superimposing a sound watermark signal in the human ear's audible frequency domain on the original ambient sound signal can easily affect the expression quality of the original ambient sound watermark signal because the frequency domain of the sound watermark signal is the same as the frequency domain of the original ambient sound signal.

[0041] As can be seen from the above description, generating a watermark signal that does not affect the quality of the original audio and is not easily distinguishable from the original audio is a current difficulty.

[0042] The human auditory system (HAS) is known to experience a sound masking effect. While the human ear can detect subtle sounds in silence, these subtle sounds are drowned out by the noise in a noisy environment. This phenomenon, where the hearing threshold of a second sound is raised due to the presence of the first, is called the masking effect. Masking effects can be categorized into frequency domain masking and time domain masking. Time domain masking occurs when a high-energy sound over a short period of time masks a low-energy sound, resulting in humans only being able to hear the high-energy portion.

[0043] like Figure 2 As shown in the figure, in the time domain, sound masking effects can be categorized as advanced masking, simultaneous masking, and delayed masking, depending on the different situations in which the high and low energy components appear. Advanced masking occurs when the energy of the latter component is higher than the former, resulting in only the latter component being audible. Simultaneous masking occurs when the energy of the preceding and following components is higher than the current component, resulting in the current component being inaudible and masked by the preceding and following components. Delayed masking occurs when the energy of the preceding component is higher than the following component, resulting in only the preceding component being audible.

[0044] By utilizing the sound masking effect, a low-energy sound signal watermark is obtained, so that the high-energy original environmental sound signal masks the low-energy sound signal watermark. It is necessary to first obtain the original environmental sound signal, and then generate a sound signal watermark that meets the masking effect based on the original environmental sound signal.

[0045] Therefore, the disclosed embodiments utilize the delayed masking effect of sound to generate a sound signal watermark. The high-energy original ambient sound signal of the previous moment masks the low-energy sound signal of the next moment. This ensures that only the high-energy original ambient sound signal is heard by the human ear, thus preserving the quality of the original sound watermark signal. Furthermore, the generated sound signal watermark and the original ambient sound signal belong to the same frequency domain, resulting in a more thorough mixing and making forgery attacks more difficult.

[0046] The following is combined with Figure 3 , a data collection method provided by an embodiment of the present disclosure is described in detail. Figure 3As shown, the data collection method provided by an embodiment of the present disclosure includes steps S310 to S330.

[0047] Step S310: Generate a sound signal watermark based on the first audio data collected by the microphone, wherein the sound signal watermark is a signal in the frequency domain audible to human ears, and the energy of the sound signal watermark is lower than the energy of the signal in the audio data.

[0048] The low-energy sound signal watermark is generated based on the sound hysteresis masking effect.

[0049] Optionally, in some embodiments, the trusted data collection APP 120 receives a collection of output information from the microphone 110 and generates a low-energy sound signal watermark based on the received output information by using a sound hysteresis masking effect.

[0050] It's understandable that the frequency and intensity of the sound watermark are constrained by the original ambient sound signal; the two cannot differ significantly, nor can they be very close. If the frequency of the sound watermark differs significantly from the original ambient sound signal, while the audio data quality won't be affected by the watermark, it will be easily discernible to malicious actors, and the risk of counterfeiting remains high. If the frequency of the sound watermark is close to the original ambient sound signal, the audio data quality will be affected by the watermark.

[0051] Alternatively, as Figure 4 As shown, step S310 may include steps S312 to S318.

[0052] Step S312: Perform Discrete Wavelet Transform (DWT) on the first audio data.

[0053] Step S314: Detect the energy of the high frequency part of the first audio data after the DWT.

[0054] Step S316: determine whether the decrease in the energy of the high-frequency part is greater than a first preset threshold.

[0055] Step S318a: If it is detected that the energy drop of the high-frequency part is greater than a first preset threshold, the sound signal watermark is generated.

[0056] Step S318b: If the condition is not met, the sound signal watermark is not generated.

[0057] Alternatively, step S318a may be replaced by: if it is detected that the energy drop of the high-frequency portion is greater than a first preset threshold, and the energy of the high-frequency portion is greater than a second preset threshold, generating the sound watermark signal. Generating a sound signal watermark that satisfies the sound hysteresis masking effect at the moment of high-frequency drop does not affect the expression of audio quality and is not easily forged.

[0058] As a specific implementation method, generating the above-mentioned sound signal watermark can be achieved through the following steps.

[0059] If no sound watermark was emitted during the [Tk, T] time interval, the following steps are executed. First, the output from microphone 110 during the [Tk, T] time interval is digitally converted to form an audio segment X. Next, a DWT is performed on audio segment X, and its energy is calculated. Next, a determination is made as to whether the energy is greater than a threshold m and whether the high-frequency drop around time T is greater than a threshold n. If these conditions are met, the frequency, intensity, and duration of the sound watermark are calculated. If these conditions are not met, the watermark is not output.

[0060] Optionally, the above k may be a fixed time length, for example, may be tens of milliseconds.

[0061] Since the sound masking effect is formed in a short period of time, Figure 2 As shown, the high-frequency drop near time T refers to the high-frequency drop part in a very short time near time T, and its time span is shorter than the above-mentioned fixed time length k.

[0062] There are many ways to calculate the sound signal watermark, which is not specifically limited in the embodiments of this disclosure.

[0063] Alternatively, as an implementation method, the frequency and intensity of the sound watermark can be calculated by calculating the mean of the complex cepstrum analysis (CCEPS) and multiplying it by a fixed coefficient. CCEPS is a Fourier transform spectrum of a signal that is subjected to a logarithmic operation and then an inverse Fourier transform.

[0064] Step S320: Send the sound signal watermark to the speaker 130, so that the speaker 130 plays the sound signal watermark in the form of an analog signal.

[0065] Optionally, in some embodiments, the trusted data collection APP 120 encrypts the sound watermark and sends it to the speaker 130. After receiving and decrypting the watermark, the speaker 130 transmits the sound watermark into the environment in the form of an analog signal.

[0066] Step S330 : receiving second audio data collected by the microphone 110 , where the second audio data includes a superimposed signal of the original ambient sound signal collected by the microphone 110 and the sound signal watermark.

[0067] Optionally, the microphone 110 receives a sound signal obtained by superimposing the original environmental sound signal and the watermark sound signal, and outputs the received information to the trusted data collection APP 120 .

[0068] Optionally, the trusted data collection APP 120 may continuously receive output information from the microphone 110 and generate a plurality of sound signal watermarks according to the received output information.

[0069] In some embodiments, the first audio data is audio data collected by the microphone 110 at the t-th sampling time, and the second audio data is audio data collected by the microphone 110 at the t+1-th sampling time.

[0070] As an example, at time T, the trusted data collection app 120 generates a watermark using function F. The input to F is the aggregated output from microphone 110 up to time T, and the output of F is the watermark at time T+1. The trusted data collection app 120 encrypts the sound watermark and sends it to speaker 130. Speaker 130 receives and decrypts the watermark, then transmits it into the environment as an analog signal. Microphone 110 receives the sound signal, a superposition of the original ambient sound signal and the watermarked sound signal, and outputs this information to the trusted data collection app 120 as its input at time T+1.

[0071] In order to further ensure the authenticity of the audio data before being uploaded to the chain, the data collection method provided by the embodiment of the present disclosure also includes: step S340, sending the sound signal watermark and the second audio data to the blockchain, so that the blockchain can store the sound signal watermark and the second audio data.

[0072] Optionally, the duration, starting position, amplitude, frequency, etc. of the sound signal watermark are archived into a file, each file corresponds to a unique hash value, and the hash value is stored on the blockchain to verify the authenticity of the audio data outside the device.

[0073] For example, during the data collection process, the trusted data collection APP 120 sends the relevant information of the sound watermark to the blockchain 140 for evidence storage; when the collection process is completed, the trusted data collection APP 120 sends the audio data to the blockchain 140 for evidence storage, so as to use the cloud verification program to verify whether the audio data contains the previously stored sound signal watermark and determine the authenticity of the audio data.

[0074] It should be noted that in the above steps, the communication between the microphone 110, the speaker 130 and other sound sensors and the trusted collection APP 120, and the communication content between the blockchain 140 and the trusted collection APP 120 are transmitted through public and private key encryption and decryption.

[0075] Figure 5 This is a flow chart of a data collection method provided by another embodiment of the present disclosure. Figure 5 The method shown includes steps S510 to S560.

[0076] In step S510 , the data acquisition device acquires first audio data.

[0077] In step S520, the data acquisition device generates a sound signal watermark based on the first audio data, wherein the sound signal watermark is a signal in the frequency domain audible to human ears, and the energy of the sound signal watermark is lower than the energy of the signal in the audio data.

[0078] Step S530: the data acquisition device plays the sound signal watermark in the form of an analog signal.

[0079] In step S540 , the data acquisition device acquires second audio data, where the second audio data includes a superimposed signal of an original ambient sound signal and the sound signal watermark.

[0080] In step S550, the data acquisition device sends the sound signal watermark and the second audio data to the blockchain so that the blockchain can store the sound signal watermark and the second audio data.

[0081] In step S560, the server obtains the sound signal watermark and the second audio data from the blockchain, and verifies whether the second audio data contains the sound signal watermark.

[0082] Optionally, relevant information of the sound signal watermark is obtained from blockchain 140. The relevant information includes at least one of a time starting position of the sound signal watermark in the second audio data, a frequency of the sound signal watermark, and an intensity of the sound signal watermark.

[0083] Optionally, the server verifies whether the second audio data contains the sound signal watermark based on relevant information of the sound signal watermark.

[0084] As an implementation method, taking cloud-based verification of audio data as an example, the audio segment Y where each sound watermark is located can be extracted based on the time starting position of each watermark; a DWT transformation can be performed on each audio segment; and it can be verified whether each audio segment contains sound information of the frequency and intensity corresponding to the preset watermark. The verification results of each audio segment are combined, and when the verification success ratio is greater than the preset threshold, the verification passes, otherwise the verification fails.

[0085] Among them, the time starting position of each watermark corresponds to the starting position in the previously stored evidence file.

[0086] The verification of each audio segment has a confidence level, which is used to measure the credibility of the similarity between the watermark in the collected audio segment and the preset watermark.

[0087] Optionally, when the verification confidence between the watermark in a certain audio segment collected and the preset watermark is greater than a preset threshold, the audio segment passes the verification; otherwise, the verification fails.

[0088] Optionally, the verification confidence of each audio clip can be combined and the average value can be taken to obtain the overall confidence. When the overall confidence is greater than a preset threshold, the verification is passed, otherwise the verification fails.

[0089] Combined with the above Figures 1 to 5 , describes the method embodiment of the present disclosure in detail, and the following is combined with 6 to Figure 8 The device embodiment of the present disclosure is described in detail. It should be understood that the description of the method embodiment corresponds to the description of the device embodiment, so for parts not described in detail, reference can be made to the previous method embodiment.

[0090] Figure 6 It is a schematic structural diagram of a data acquisition device provided in one embodiment of the present disclosure. Figure 6 The data acquisition device 600 includes a generating module 610 , a sending module 620 and a receiving module 630 .

[0091] The generating module 610 may be configured to generate a sound signal watermark based on the first audio data collected by the microphone 110, wherein the sound signal watermark is a signal in the frequency domain audible to the human ear and has lower energy than the signal in the audio data.

[0092] The sending module 620 may be configured to send the sound signal watermark to the speaker 130 , so that the speaker 130 plays the sound signal watermark in the form of an analog signal.

[0093] The receiving module 630 may be configured to receive second audio data collected by the microphone 110 , where the second audio data includes a superimposed signal of the original ambient sound signal collected by the microphone 110 and the sound signal watermark.

[0094] The sending module 620 can also be used to send the sound signal watermark and the second audio data to the blockchain 140, so that the blockchain 140 can store the sound signal watermark and the second audio data.

[0095] Optionally, in some embodiments, the generation module 610 can be used to perform a discrete wavelet transform on the first audio data; detect the energy of the high-frequency part of the first audio data after the discrete wavelet transform; if it is detected that the decrease in the energy of the high-frequency part is greater than a first preset threshold, generate the sound signal watermark.

[0096] For example, the generating module 610 may be configured to generate the sound watermark signal if it is detected that the energy drop of the high frequency part is greater than a first preset threshold and the energy of the high frequency part is greater than a second preset threshold.

[0097] Optionally, the first audio data in the generating module 610 is the audio data collected by the microphone 110 at the t-th sampling time, and the second audio data in the receiving module is the audio data collected by the microphone 110 at the t+1-th sampling time.

[0098] Figure 7 It is a schematic structural diagram of a data acquisition device provided in another embodiment of the present disclosure. Figure 7 The data acquisition device 700 includes a sound sensor 710 , a transmitting device 720 , a memory 730 and a processor 740 .

[0099] The sound sensor 710 can be used to collect sensing information and can be a microphone.

[0100] The transmitting device 720 can be used to transmit analog signals and can be a speaker.

[0101] The memory 730 may be used to store a code for generating a sound signal watermark.

[0102] The processor 740 may be configured to execute the code stored in the memory to utilize the sound sensor and the transmitting device to perform the steps in the various methods described above.

[0103] Figure 8 It is a schematic structural diagram of the data acquisition system provided by an embodiment of the present disclosure. Figure 8 The data acquisition system 800 includes a data acquisition device 810 and a server 820 .

[0104] The data acquisition device 810 can be any of the data acquisition devices described above, such as Figure 7The data acquisition device 700 in FIG. 1 and the server 820 can be a cloud server. Both the data acquisition device 810 and the server 820 can communicate and exchange data with the blockchain 140.

[0105] The data acquisition device 810 can be used to collect first audio data; generate a sound signal watermark based on the first audio data, wherein the sound signal watermark is a signal in the audible frequency domain of the human ear and the energy of the sound signal watermark is lower than the energy of the signal in the audio data; play the sound signal watermark in the form of an analog signal; collect second audio data, wherein the second audio data includes a superimposed signal of the original environmental sound signal and the sound signal watermark; and send the sound signal watermark and the second audio data to the blockchain 140 so that the blockchain 140 can store the sound signal watermark and the second audio data.

[0106] The server 820 may be configured to obtain the sound signal watermark and the second audio data from the blockchain 140 and verify whether the second audio data contains the sound signal watermark.

[0107] In addition, the communication content between the data acquisition device 810 and the server 820 is transmitted through public and private key encryption and decryption.

[0108] In the above embodiments, all or part of the embodiments can be implemented using software, hardware, firmware, or any other combination. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in accordance with the embodiments of the present disclosure are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0109] Those skilled in the art will appreciate that the units and algorithm steps of the various examples described in conjunction with the embodiments of the present disclosure can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0110] It should be understood that the terminal devices in the embodiments of the present disclosure may also be referred to as user equipment (UE), mobile terminal (MT), remote terminal, mobile device, user terminal, terminal, or user device. The terminal devices in the embodiments of the present disclosure may be mobile phones, tablet computers, laptop computers, PDAs, wearable devices, etc.

[0111] In the several embodiments provided in the present disclosure, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0112] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0113] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0114] The above description is merely a specific embodiment of the present disclosure, but the scope of protection of the present disclosure is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this disclosure should be included in the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure should be based on the scope of protection of the claims.

Claims

1. A data collection method, comprising: generating a sound signal watermark based on first audio data collected by a microphone, wherein the sound signal watermark is a signal in a frequency domain audible to human ears, the sound signal watermark and the first audio data are located in the same frequency domain, and the energy of the sound signal watermark is lower than the energy of the signal in the first audio data; Sending the sound signal watermark to a speaker so that the speaker plays the sound signal watermark in the form of an analog signal; receiving second audio data collected by a microphone, wherein the second audio data comprises a superimposed signal of an original ambient sound signal collected by the microphone and the sound signal watermark; The step of generating a sound signal watermark based on the first audio data collected by the microphone includes: Performing discrete wavelet transform on the first audio data, where the first audio data is an audio segment within a time interval of [Tk, T], and no sound signal watermark has been emitted within the time interval of [Tk, T]; detecting energy of a high-frequency portion of the first audio data after discrete wavelet transformation; If it is detected that the energy drop of the high-frequency part near time T is greater than the first preset threshold, and the energy of the high-frequency part is greater than the second preset threshold, the sound signal watermark is generated. The energy drop of the high-frequency part near time T refers to the energy drop of the high-frequency part in a very short time near time T, and the very short time is less than k.

2. The method according to claim 1, further comprising: The sound signal watermark and the second audio data are sent to the blockchain so that the blockchain can store the sound signal watermark and the second audio data. 3 . The method according to claim 1 , wherein the first audio data is audio data collected by the microphone at the tth sampling time, and the second audio data is audio data collected by the microphone at the t+1th sampling time.

4. A data collection method comprising: The data acquisition device acquires first audio data; The data acquisition device generates a sound signal watermark based on the first audio data, wherein the sound signal watermark is a signal in a frequency domain audible to human ears, the sound signal watermark and the first audio data are located in the same frequency domain, and the energy of the sound signal watermark is lower than the energy of the signal in the first audio data; The data acquisition device plays the sound signal watermark in the form of an analog signal; The data acquisition device acquires second audio data, wherein the second audio data includes a superimposed signal of an original ambient sound signal and the sound signal watermark; The data acquisition device sends the sound signal watermark and the second audio data to the blockchain, so that the blockchain can store the sound signal watermark and the second audio data; The server obtains the sound signal watermark and the second audio data from the blockchain, and verifies whether the second audio data contains the sound signal watermark; The data acquisition device generates a sound signal watermark according to the first audio data, including: The data acquisition device performs discrete wavelet transform on the first audio data, the first audio data is an audio segment within a time interval of [Tk, T], and no sound signal watermark is emitted within the time interval of [Tk, T]; The data acquisition device detects the energy of the high frequency part of the first audio data after discrete wavelet transformation; If it is detected that the energy drop of the high-frequency part near time T is greater than a first preset threshold, and the energy of the high-frequency part is greater than a second preset threshold, the data acquisition device generates the sound signal watermark. The energy drop of the high-frequency part near time T refers to the energy drop of the high-frequency part in a very short time near time T, and the very short time is less than k.

5. The method according to claim 4, wherein the blockchain further stores relevant information of the sound signal watermark, wherein the relevant information includes at least one of a time starting position of the sound signal watermark in the second audio data, a frequency of the sound signal watermark, and an intensity of the sound signal watermark. The server verifies whether the second audio data contains the sound signal watermark, including: The server verifies whether the second audio data contains the sound signal watermark according to the relevant information of the sound signal watermark.

6. A data acquisition device comprising: a generating module, configured to generate a sound signal watermark based on first audio data collected by a microphone, wherein the sound signal watermark is a signal in a frequency domain audible to the human ear, the sound signal watermark and the first audio data are located in the same frequency domain, and the energy of the sound signal watermark is lower than the energy of the signal in the first audio data; A sending module, configured to send the sound signal watermark to a speaker, so that the speaker plays the sound signal watermark in the form of an analog signal; A receiving module, configured to receive second audio data collected by a microphone, wherein the second audio data comprises a superimposed signal of an original ambient sound signal collected by the microphone and the sound signal watermark; Among them, the generation module is specifically used to: perform discrete wavelet transform on the first audio data, the first audio data is an audio segment within the time interval [Tk, T], and no sound signal watermark has been emitted within the time interval [Tk, T]; detect the energy of the high-frequency part of the first audio data after the discrete wavelet transform; if it is detected that the energy drop of the high-frequency part near the T moment is greater than the first preset threshold, and the energy of the high-frequency part is greater than the second preset threshold, generate the sound signal watermark, the energy drop of the high-frequency part near the T moment refers to the energy drop of the high-frequency part in a very short time near the T moment, and the very short time is less than k.

7. According to the device according to claim 6, the sending module is further used to send the sound signal watermark and the second audio data to the blockchain, so that the blockchain can store the sound signal watermark and the second audio data.

8. The device according to claim 6 or 7, wherein the first audio data in the generating module is the audio data collected by the microphone at the t-th sampling time, and the second audio data in the receiving module is the audio data collected by the microphone at the t+1-th sampling time.

9. A data acquisition device comprising: Sound sensor, used to collect sensing information; Transmitting equipment, used to transmit analog signals; A memory for storing a code for generating a sound signal watermark; A processor, configured to execute the code stored in the memory, so as to use the sound sensor and the transmitting device to perform the method according to any one of claims 1 to 3.

10. A data acquisition system comprising: A data acquisition device, configured to acquire first audio data; Generate a sound signal watermark based on the first audio data, wherein the sound signal watermark is a signal in the frequency domain audible to the human ear, the sound signal watermark and the first audio data are located in the same frequency domain, and the energy of the sound signal watermark is lower than the energy of the signal in the first audio data; play the sound signal watermark in the form of an analog signal; collect second audio data, where the second audio data includes a superposition signal of an original ambient sound signal and the sound signal watermark; and send the sound signal watermark and the second audio data to a blockchain so that the blockchain can store the sound signal watermark and the second audio data as evidence. A server, configured to obtain the sound signal watermark and the second audio data from the blockchain, and verify whether the second audio data contains the sound signal watermark; Among them, generating a sound signal watermark based on the first audio data includes: performing a discrete wavelet transform on the first audio data, the first audio data is an audio segment within the time interval [Tk, T], and no sound signal watermark has been emitted within the time interval [Tk, T]; detecting the energy of the high-frequency part of the first audio data after the discrete wavelet transform; if it is detected that the energy drop of the high-frequency part near the time T is greater than a first preset threshold, and the energy of the high-frequency part is greater than a second preset threshold, generating the sound signal watermark, the energy drop of the high-frequency part near the time T refers to the energy drop of the high-frequency part in a very short time near the time T, and the very short time is less than k.

11. According to the system of claim 10, the blockchain also stores relevant information of the sound signal watermark, wherein the relevant information includes at least one of a time starting position of the sound signal watermark in the second audio data, a frequency of the sound signal watermark, and an intensity of the sound signal watermark, and the server is configured to verify whether the second audio data contains the sound signal watermark based on the relevant information of the sound signal watermark.

Images