Equipment information changing method based on Bluetooth technology

Abstract

The invention relates to the technical field of equipment information change, and particularly discloses an equipment information change method based on a Bluetooth technology, which comprises the following steps: acquiring a Bluetooth name list of to-be-connected terminal equipment; selecting a Bluetooth name of a terminal device needing to be connected from the Bluetooth name list, and clicking a connection button; after connection succeeds, an automatic address allocation button is clicked, and an address is allocated to the terminal equipment needing to be connected; after the process of address allocation is completed, equipment information of the terminal equipment needing to be connected is automatically read, and the equipment information is displayed on a screen; performing content configuration on the equipment information to obtain updated equipment information; and performing intelligent content verification on the updated equipment information to obtain an intelligent content verification result. Thus, through wireless communication connection, a user can easily interact with the equipment without complex wiring.

Description

Technical Field

[0001] The present application relates to the technical field of device information modification, and more specifically, to a method for modifying device information based on Bluetooth technology. Background Art

[0002] In modern society, fast update and flexible configuration of information are crucial for users. With the rapid development of technology and the acceleration of social pace, people are increasingly dependent on instant communication and real-time data updates. The popularity of smartphones, social media and IoT devices has made it easier than ever to obtain and share information. Therefore, users have higher requirements for the speed and flexibility of information updates.

[0003] However, the traditional way of changing information may be cumbersome and requires wired connection or complicated operation steps. This method is not only time-consuming and labor-intensive, but also limits the mobility and convenience of users. For example, wired connection requires users to operate the device within the physical contact range, which increases the inconvenience of operation. In addition, complicated operation steps often require users to have certain technical knowledge, which increases the difficulty and error-proneness of use. In actual applications, users may need to frequently plug and unplug cables, causing wear and tear on the interface or even damage to the device.

[0004] Therefore, an optimized device information changing method is desired. Summary of the invention

[0005] The present application provides a method for changing device information based on Bluetooth technology, which is connected via wireless communication and allows users to easily interact with the device without complicated wiring.

[0006] In the first aspect, a method for changing device information based on Bluetooth technology is provided, comprising: obtaining a list of Bluetooth names of terminal devices to be connected; selecting the Bluetooth name of the terminal device to be connected from the Bluetooth name list, and clicking a connect button; after the connection is successful, clicking an automatic address assignment button to assign an address to the terminal device to be connected; after completing the address assignment process, automatically reading the device information of the terminal device to be connected, and displaying the device information on the screen; performing content configuration on the device information to obtain updated device information; performing content intelligent verification on the updated device information to obtain a content intelligent verification result; in response to the content intelligent verification result being normal, clicking a send to device button to send the updated device information to the terminal device to be connected.

[0007] In the second aspect, a device information changing system based on Bluetooth technology is provided, including: a Bluetooth name list acquisition module, used to obtain a Bluetooth name list of terminal devices to be connected; a terminal device connection module, used to select the Bluetooth name of the terminal device to be connected from the Bluetooth name list, and click a connection button; an address allocation module, used to click an automatic address allocation button to allocate an address to the terminal device to be connected after the connection is successful; a device information automatic reading module, used to automatically read the device information of the terminal device to be connected after completing the address allocation process, and display the device information on the screen; a device information content configuration module, used to perform content configuration on the device information to obtain updated device information; a content intelligent verification module, used to perform content intelligent verification on the updated device information to obtain a content intelligent verification result; an updated device information sending module, used to respond to the content intelligent verification result being normal, click a send to device button, and send the updated device information to the terminal device to be connected.

[0008] The present application provides a method for changing device information based on Bluetooth technology, which includes: obtaining a Bluetooth name list of terminal devices to be connected; selecting the Bluetooth name of the terminal device to be connected from the Bluetooth name list, and clicking the connect button; after the connection is successful, clicking the automatic address allocation button to allocate an address for the terminal device to be connected; after completing the address allocation process, automatically reading the device information of the terminal device to be connected, and displaying the device information on the screen; performing content configuration on the device information to obtain updated device information; performing content intelligent verification on the updated device information to obtain content intelligent verification results; in response to the content intelligent verification result being normal, clicking the send to device button to send the updated device information to the terminal device to be connected. In this way, connecting through wireless communication allows users to easily interact with the device without complicated wiring. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solution of the embodiment of the present application, the drawings of the embodiment of the present application are briefly introduced below.

[0010] Figure 1 This is a schematic flowchart of a method for changing device information based on Bluetooth technology according to an embodiment of the present application.

[0011] Figure 2 This is a schematic flowchart of performing content intelligent verification on the updated device information to obtain a content intelligent verification result in the device information modification method based on Bluetooth technology in an embodiment of the present application.

[0012] Figure 3This is a data flow diagram of a method for changing device information based on Bluetooth technology according to an embodiment of the present application, in which content intelligent verification is performed on the updated device information to obtain a content intelligent verification result.

[0013] Figure 4 This is a schematic block diagram of a device information modification system based on Bluetooth technology according to an embodiment of the present application.

[0014] Figure 5 This is a product block diagram of an embodiment of the present application.

[0015] Figure 6 This is a schematic diagram of the app interface of an embodiment of the present application. DETAILED DESCRIPTION

[0016] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work also fall within the scope of protection of the present application.

[0017] Based on this, this application proposes a device information modification method based on Bluetooth technology. Figure 1This is a schematic flow chart of a device information changing method based on Bluetooth technology according to an embodiment of the present application. The device information changing method based on Bluetooth technology comprises: S1, obtaining a Bluetooth name list of terminal devices to be connected; S2, selecting the Bluetooth name of the terminal device to be connected from the Bluetooth name list, and clicking the connect button; S3, after the connection is successful, clicking the automatic address assignment button to assign an address to the terminal device to be connected; S4, after completing the address assignment process, automatically reading the device information of the terminal device to be connected, and displaying the device information on the screen; S5, performing content configuration on the device information to obtain updated device information; S6, performing content intelligent verification on the updated device information to obtain content intelligent verification results; S7, in response to the content intelligent verification result being normal, clicking the send to device button to send the updated device information to the terminal device to be connected. In this way, connecting through wireless communication allows users to easily interact with the device without complicated wiring. It should be understood that content verification of updated device information is crucial during the device information change process. It can ensure that the information sent to the device is accurate and prevent erroneous or malicious data from causing system failures or security issues. In addition, content verification can verify the integrity and correctness of the data, ensuring that device performance will not be affected by information errors during the update process. It also provides an additional layer of security protection for the update and enhances the stability and reliability of the system. However, traditional methods often rely on manual verification based on fixed rules or templates. When faced with a large amount of device information, manual verification is not only time-consuming and labor-intensive, but may also fail to accurately determine the expression errors in the information. For example, for some non-standard format information, traditional methods may not be able to accurately identify it.

[0018] In the above-mentioned method for changing device information based on Bluetooth technology, the step S1 obtains a list of Bluetooth names of the terminal devices to be connected. It should be understood that in step S1, the system scans and collects information of available Bluetooth devices around, especially their Bluetooth names, to form a list. This list contains the Bluetooth names of all the terminal devices that can be connected, allowing users to select the target device they want to connect to.

[0019] In the above-mentioned device information changing method based on Bluetooth technology, S2, selects the Bluetooth name of the terminal device to be connected from the Bluetooth name list, and clicks the connect button. It should be understood that in step S2, when the user obtains the Bluetooth name list of all the connectable terminal devices around, the next thing to do is to select the Bluetooth name of the specific terminal device that you want to connect from this list. This process is usually implemented on the user interface. The user can visually check the listed Bluetooth names to find the name of the device they want to connect to, and start the pairing or connection process with the selected device by clicking or selecting the connect button next to the name. This step simplifies user operations, avoids the physical contact and complicated steps required for traditional wired connections, and improves user experience and operating efficiency.

[0020] In the above-mentioned device information changing method based on Bluetooth technology, in S3, after the connection is successful, click the automatic address assignment button to assign an address to the terminal device that needs to be connected. It should be understood that in step S3, once the user successfully establishes a Bluetooth connection with the required terminal device, the system will prompt the user to trigger an automated address assignment process by clicking a specified button. This process is usually used to assign a unique address identifier to the newly connected terminal device so that the device can be uniquely identified in subsequent communications. Doing so can ensure the uniqueness of the device in the network, avoid address conflicts, and help maintain the orderliness and security of communications between devices. In this way, users can quickly and easily complete the configuration of the device address without manually entering or memorizing complex address information, thereby simplifying the device management process.

[0021] In the above-mentioned device information changing method based on Bluetooth technology, S4, after completing the address allocation process, automatically reads the device information of the terminal device to be connected, and displays the device information on the screen. It should be understood that in step S4, once the address is successfully assigned to the terminal device, the system will automatically execute the operation of reading the device information and display this information to the user. This means that the user interface will display key information related to the connected device, such as the model, version number, status, etc. of the device. This automated reading and display process allows users to quickly view the current status and configuration details of the device, which facilitates subsequent updates or other operations on the device information. At the same time, this also saves the user the step of manually searching and entering device information, thereby improving the convenience and efficiency of operation.

[0022] In the above-mentioned method for changing device information based on Bluetooth technology, the S5 performs content configuration on the device information to obtain updated device information. It should be understood that in step S5, after the user has connected to the terminal device via Bluetooth and obtained the current information of the device, the next step is to make necessary modifications or adjustments to the information to meet new requirements or correct existing problems. After the configuration is completed, the modified information will become the updated device information, ready to replace the old information record.

[0023] In the above-mentioned device information change method based on Bluetooth technology, the S6 performs intelligent content verification on the updated device information to obtain the content intelligent verification result. It should be understood that in step S6, after the user configures the content of the device information, the system will perform intelligent verification on the updated information. Intelligent verification is an automated process that uses artificial intelligence technology to process the updated device information to determine whether the information is correct. If the information passes the verification, it means that the information content is valid and can be sent to the device; if it fails, the error needs to be corrected and then re-verified. This process replaces the traditional manual item-by-item verification method with intelligent means, which not only improves the efficiency of verification, but also reduces errors caused by manual operation. Intelligent verification can capture potential problems in non-standard format information, and can more accurately understand the meaning of each word and its role in the context, so as to more accurately judge the expression errors in the information and improve the accuracy and automation level of the verification work.

[0024] In the above-mentioned device information changing method based on Bluetooth technology, in S7, in response to the content intelligent verification result being normal, click the Send to Device button to send the updated device information to the terminal device that needs to be connected. It should be understood that in step S7, when the content intelligent verification confirms that the updated information is correct, this indicates that the updated information is ready to be transmitted to the terminal device to update the configuration or status of the device. At this time, the user only needs to simply confirm that the verification result is normal and click the button to start the transmission process of the updated information. This method greatly simplifies the interaction process between the user and the device, allowing the user to easily complete the change of device information without complicated wiring or operation. This not only improves operational efficiency, but also reduces the risk of errors that may be introduced due to manual operation, thereby enhancing the stability and reliability of the system.

[0025] Accordingly, in performing intelligent content verification on the update device information to obtain the intelligent content verification result, the technical concept of the present application is to perform word segmentation and semantic embedding on the update device information by using information analysis and processing technology based on artificial intelligence, so as to intelligently judge whether there are expression errors in these different update device information words according to the semantic query representation between the semantic embedding features of different update device information words and the semantic embedding features of the entire update device information words. In this way, through word segmentation processing and semantic query analysis, the meaning of each word and its role in the context can be understood more accurately, so as to more accurately judge the expression errors in the information, thereby reducing the workload of manual item-by-item verification, improving the degree of automation of the verification process, and making the verification work more efficient.

[0026] Optionally, in one embodiment of the present application, Figure 2 This is a schematic flowchart of performing content intelligent verification on the updated device information to obtain a content intelligent verification result in the device information modification method based on Bluetooth technology in an embodiment of the present application. Figure 3 This is a data flow diagram of a method for changing device information based on Bluetooth technology in an embodiment of the present application, in which content intelligent verification is performed on the updated device information to obtain a content intelligent verification result. Figure 2 and Figure 3 As shown, the content intelligent verification is performed on the update device information to obtain the content intelligent verification result, including: S61, performing word segmentation processing on the update device information to obtain a sequence of update device information words; S62, performing semantic embedding coding on each update device information word in the sequence of update device information words to obtain a sequence of update device information word semantic embedding coding vectors; S63, using the update device information word semantic embedding coding vector corresponding to the ith update device information word in the sequence of update device information words as a query feature vector, using the sequence of the update device information word semantic embedding coding vectors as a sequence of key feature vectors, performing local neighborhood-based query coding on the query feature vector and the sequence of the key feature vectors to obtain the semantic query coding representation of the ith update device information word; S64, obtaining a recognition result based on the semantic query coding representation of the ith update device information word.

[0027] In the above-mentioned device information changing method based on Bluetooth technology, the S61 performs word segmentation processing on the updated device information to obtain a sequence of updated device information words. It should be understood that, considering that the updated device information contains a large number of words, such as Bluetooth version, device model, etc., each semantic meaning of these words plays an important role in the correct judgment of semantic expression. Based on this, the updated device information is segmented to obtain a sequence of updated device information words, that is, after the updated device information is divided into words or phrases, semantic analysis can be performed according to the meaning of each word, so that it is easier to find possible expression errors.

[0028] In the above-mentioned device information changing method based on Bluetooth technology, the S62 performs semantic embedding coding on each updated device information word in the sequence of updated device information words to obtain a sequence of updated device information word semantic embedding coding vectors. It should be understood that in order to further capture and refine the main semantic meanings and information expressed in each updated device information word in the sequence of updated device information words, in the technical solution of the present application, a semantic embedding matrix is ​​used to perform semantic embedding coding on each updated device information word in the sequence of updated device information words to obtain a sequence of updated device information word semantic embedding coding vectors.

[0029] Optionally, in one embodiment of the present application, semantic embedding encoding is performed on each update device information word in the sequence of update device information words to obtain a sequence of semantic embedding encoding vectors of update device information words, including: using a semantic embedding matrix to semantically embedding encoding each update device information word in the sequence of update device information words to obtain a sequence of semantic embedding encoding vectors of update device information words.

[0030] In the above-mentioned device information changing method based on Bluetooth technology, the S63 uses the semantic embedding coding vector of the updated device information word corresponding to the i-th updated device information word in the sequence of the updated device information words as the query feature vector, and uses the sequence of the semantic embedding coding vectors of the updated device information words as the sequence of key feature vectors, and performs query coding based on the local neighborhood on the query feature vector and the sequence of the key feature vectors to obtain the semantic query coding representation of the i-th updated device information word. It should be understood that considering that the semantic embedding coding vector of the updated device information word corresponding to the i-th updated device information word refers to a vector representation obtained after semantic embedding coding of a specific word (i.e., the i-th word) in the sequence of the updated device information words, the semantic features of the word are captured. The sequence of the semantic embedding coding vectors of the updated device information words contains the semantic embedding coding vectors of all words in the sequence of the updated device information words, representing the semantic features of the entire sequence of updated device information words. Therefore, in order to more accurately and meticulously evaluate the importance and relevance of the i-th word in the entire context, so as to better understand and identify the verification device information, in the technical solution of the present application, the semantic embedding coding vector of the updated device information word corresponding to the i-th updated device information word in the sequence of updated device information words is used as the query feature vector, and the sequence of the semantic embedding coding vectors of the updated device information words is used as the sequence of key feature vectors. The query feature vector and the sequence of the key feature vectors are query encoded based on the local neighborhood to obtain the global context semantic query coding representation vector of the i-th updated device information word as the semantic query coding representation of the i-th updated device information word.

[0031] Optionally, in one embodiment of the present application, the semantic embedding coding vector of the update device information word corresponding to the i-th update device information word in the sequence of the update device information words is used as the query feature vector, and the sequence of the semantic embedding coding vectors of the update device information words is used as the sequence of key feature vectors, and the query feature vector and the sequence of the key feature vectors are subjected to local neighborhood-based query coding to obtain the semantic query coding representation of the i-th update device information word, including: performing value embedding processing on the semantic embedding coding vector of the update device information word corresponding to the i-th update device information word to obtain the semantic value feature vector of the update device information word; using the semantic embedding coding vector of the update device information word corresponding to the i-th update device information word as the query vector, the semantic value feature vector of the update device information word as the value vector and the sequence of the semantic embedding coding vectors of the update device information word as the sequence of key vectors, and performing attention-gating-based invisible optimization on the sequence of the query vector, the value vector and the key vector to obtain the semantic query coding representation of the i-th update device information word.

[0032] Optionally, in one embodiment of the present application, the update device information word semantic embedding coding vector corresponding to the i-th update device information word is value embedded to obtain an update device information word semantic value feature vector, including: using a value embedding coding matrix to process the update device information word semantic embedding coding vector corresponding to the i-th update device information word to obtain the update device information word semantic value feature vector.

[0033] Optionally, in one embodiment of the present application, the semantic embedding coding vector of the updated device information word corresponding to the i-th updated device information word is used as the query vector, the semantic value feature vector of the updated device information word is used as the value vector, and the sequence of the semantic embedding coding vectors of the updated device information word is used as the sequence of key vectors, and the query vector, the value vector and the sequence of the key vector are subjected to invisible optimization based on attention gating to obtain the i-th updated device information word semantic query coding representation, including: performing one-dimensional convolution coding on the sequence of the semantic embedding coding vectors of the updated device information word to obtain a sequence of local neighborhood semantic association feature vectors of the updated device information word; the semantic embedding coding vector of the updated device information word corresponding to the i-th updated device information word is used as the query vector, the semantic value feature vector of the updated device information word is used as the value vector, and the sequence of the semantic embedding coding vectors of the updated device information word is used as the sequence of key vectors, and the sequence of the query vector, the value vector and the key vector is input into the first multi-head attention query module based on the converter structure to obtain the semantic granularity query matching implicit representation of the updated device information word. A sequence of vectors; using the semantic embedding coding vector of the updated device information word corresponding to the i-th updated device information word as the query vector, the semantic value feature vector of the updated device information word as the value vector and the sequence of the local neighborhood semantic association feature vectors of the updated device information word as the sequence of key vectors, inputting the sequence of the query vector, the value vector and the key vector into a second multi-head attention query module based on a converter structure to obtain a sequence of semantic neighborhood granularity query matching implicit vectors for the updated device information word; calculating the positional mean vector of the sequence of semantic granularity query matching implicit vectors for the updated device information word and the sequence of semantic neighborhood granularity query matching implicit vectors for the updated device information word to obtain the semantic granularity query matching feature vector for the updated device information word and the semantic neighborhood granularity query matching feature vector for the updated device information word; fusing the semantic granularity query matching feature vector for the updated device information word and the semantic neighborhood granularity query matching feature vector for the updated device information word to obtain the global context semantic query encoding representation vector of the i-th updated device information word as the semantic query encoding representation of the i-th updated device information word.

[0034] Optionally, in one embodiment of the present application, the scale of the one-dimensional convolutional coding is equal to an integer multiple of the length of the semantic embedding coding vector of the updated device information word.

[0035] Optionally, in one embodiment of the present application, the update device information word semantic embedding coding vector corresponding to the i-th update device information word is used as the query vector, the update device information word semantic value feature vector is used as the value vector, and the sequence of the update device information word semantic embedding coding vectors is used as the sequence of key vectors, and the query vector, the value vector and the sequence of the key vectors are input into a first multi-head attention query module based on a converter structure to obtain a sequence of update device information word semantic granularity query matching implicit vectors, including: calculating the product between the update device information word semantic embedding coding vector corresponding to the i-th update device information word and the transposed vector of the update device information word semantic embedding coding vector, dividing the obtained update device information word semantic association matrix by the square root of the length of the update device information word semantic embedding coding vector by position to obtain an update device information word semantic association modulation matrix; inputting the update device information word semantic association modulation matrix into a softmax function to obtain an update device information word semantic association activation matrix; multiplying the update device information word semantic association activation matrix by the update device information word semantic value feature vector to obtain the update device information word semantic granularity query matching implicit vector.

[0036] Optionally, in one embodiment of the present application, the semantic granularity query matching feature vector of the updated device information word and the semantic neighborhood granularity query matching feature vector of the updated device information word are merged to obtain the global context semantic query encoding representation vector of the i-th updated device information word, including: respectively calculating the positional subtraction, positional dot multiplication and positional addition between the semantic granularity query matching feature vector of the updated device information word and the semantic neighborhood granularity query matching feature vector of the updated device information word to obtain the semantic granularity-neighborhood granularity difference vector of the updated device information word, the semantic granularity-neighborhood granularity dot product vector of the updated device information word and the updated device information word. The updated device information word semantic granularity-neighborhood granularity sum vector is cascaded to obtain the updated device information word semantic granularity-neighborhood granularity cascade vector; after one-dimensional convolution encoding is performed on the updated device information word semantic granularity-neighborhood granularity cascade vector, the obtained updated device information word semantic granularity-neighborhood granularity convolution encoding vector is subjected to local window-based maximum pooling processing to obtain the global context semantic query encoding representation vector of the i-th updated device information word.

[0037] In summary, in the embodiment of the present application, the semantic embedding coding vector of the updated device information word corresponding to the i-th updated device information word in the sequence of the updated device information words is used as the query feature vector, and the sequence of the semantic embedding coding vectors of the updated device information words is used as the sequence of key feature vectors. The query encoding based on the local neighborhood is performed on the sequence of the query feature vector and the key feature vector, which can be expressed as follows:

[0038] v v =v q W q +b q

[0039] K={k1,k2,...,k s , ..., k n}

[0040] K′=Conv 1×l ({k1, k2, ..., k s , ..., k n})

[0041] K′={k1′,k2′,...,k s ′, ..., k m ′}

[0042]

[0043]

[0044]

[0045]

[0046]

[0047] Among them, v q is the semantic embedding encoding vector of the updated device information word corresponding to the i-th updated device information word, W q is the value embedding encoding matrix, b q is the value bias vector, v v is the semantic value feature vector of the updated device information word, K represents the sequence of semantic embedding encoding vectors of the updated device information word, k1, k2, ..., k s , ..., k n is the 1st, 2nd, ..., sth, ..., nth updated device information word semantic embedding coding vector in the sequence of the updated device information word semantic embedding coding vector, Conv 1×l(·) is a one-dimensional convolutional code, l is an integer multiple of the length of the semantic embedding coding vector of the updated device information word, K′ is a sequence of local neighborhood semantic association feature vectors of the updated device information word, k1′, k2′, ..., k s ′, ..., k m ′ is the first, second, ..., sth, ..., mth updated device information word local neighborhood semantic association feature vector in the sequence of the updated device information word local neighborhood semantic association feature vector, k s T and k s ′ are k s and k s ′, d1 and d2 are the lengths of the semantic embedding encoding vector of the updated device information word and the local neighborhood semantic association feature vector of the updated device information word, respectively, softmax(·) is the softmax function, v ks is the sth updated device information word semantic granularity query matching implicit vector in the sequence of updated device information word semantic granularity query matching implicit vectors, n is the number of feature vectors in the sequence of updated device information word semantic granularity query matching implicit vectors, v ns is the sth updated device information word semantic neighborhood granularity query matching implicit vector in the sequence of updated device information word semantic neighborhood granularity query matching implicit vector, m is the number of feature vectors in the sequence of updated device information word semantic neighborhood granularity query matching implicit vector, v k is the semantic granularity query matching feature vector of the updated device information word, v n is the semantic neighborhood granularity query matching feature vector of the updated device information word, ⊙ and are position-wise subtraction, position-wise multiplication, and position-wise addition, respectively. [·,·,·] is a cascade process. conv1D(·) is a one-dimensional convolutional encoding operation. MaxPool(·) is a maximum pooling operation. p is the global context semantic query encoding representation vector of the i-th updated device information word.

[0048] Specifically, first, the semantic embedding coding vector of the updated device information word corresponding to the i-th updated device information word is embedded to better capture the semantic information of the vocabulary, understand the meaning in the context, and obtain the semantic value feature vector of the updated device information word. Then, the sequence of the semantic embedding coding vectors of the updated device information word is processed by one-dimensional convolution coding to capture the local neighborhood semantic information in the entire embedding sequence to obtain a sequence of local neighborhood semantic association feature vectors of the updated device information word. In particular, the size of the convolution kernel of the one-dimensional convolution coding here is an integer multiple of the length of the semantic embedding coding vector of the updated device information word in order to ensure that the contextual information within a certain range can be fully obtained, thereby more effectively capturing the semantic connection within the local neighborhood, which is conducive to more accurate query matching in subsequent stages. Furthermore, the sequence of the semantic embedding coding vectors of the updated device information words and the sequence of the local neighborhood semantic association feature vectors of the updated device information words are respectively used as the sequence of key vectors, and the sequence of the semantic embedding coding vectors (query vectors) of the updated device information words corresponding to the i-th updated device information words, the semantic value feature vectors (value vectors) of the updated device information words and the key vectors are input into the first and second multi-head attention query modules based on the converter structure to focus on the semantic relationship between the query vector and the key vector and optimize the expression between the semantics from different perspectives, and obtain the sequence of the implicit vectors of the semantic granularity query matching of the updated device information words and the sequence of the implicit vectors of the semantic neighborhood granularity query matching of the updated device information words. It should be understood that by using the multi-head attention mechanism, the attention weights can be estimated in multiple representation subspaces in parallel to identify the interdependencies in the input data. That is, the first multi-head attention query module focuses on analyzing the essential characteristics of the key vector; while the second multi-head attention query module pays more attention to the characteristics of the key vector and its surrounding environment, so that the accuracy of the query matching can be improved on the basis of comprehensive consideration of local details and overall context. Then, the mean vector of the sequence of implicit vectors of semantic granularity query matching of updated device information words and the sequence of implicit vectors of semantic neighborhood granularity query matching of updated device information words is calculated to integrate updated device information of different semantic granularities, and obtain the semantic granularity query matching feature vector of updated device information words and the semantic neighborhood granularity query matching feature vector of updated device information words. Finally, the semantic information between the different granularities of the two is fused to obtain the encoding representation vector of the global context semantic query of the i-th updated device information word.

[0049] In the above-mentioned device information change method based on Bluetooth technology, the S64 obtains a recognition result based on the semantic query encoding representation of the i-th updated device information word. Optionally, in one embodiment of the present application, obtaining a recognition result based on the semantic query encoding representation of the i-th updated device information word includes: inputting the global context semantic query encoding representation vector of the i-th updated device information word into a content identifier based on a classifier to obtain the recognition result, and the recognition result is used to indicate whether the i-th updated device information word has an expression error. That is, the i-th updated device information word semantic query encoding representation obtained by query encoding between the updated device information word semantic embedding encoding vector corresponding to the i-th updated device information word and the sequence of the updated device information word semantic embedding encoding vector is used for classification processing, so as to intelligently judge whether the i-th updated device information word has an expression error. In this way, through word segmentation processing and semantic query analysis, the meaning of each word and its role in the context can be understood more accurately, so as to more accurately judge the expression errors in the information, thereby reducing the workload of manual item-by-item verification, improving the degree of automation of the verification process, and making the verification work more efficient.

[0050] In a preferred example, passing the i-th update device information word global context semantic query encoding representation vector through a classifier-based content identifier to obtain an identification result includes:

[0051] Calculate the sum of the absolute values ​​of each eigenvalue of the i-th updated device information word global context semantic query encoding representation vector to obtain a first updated device information word global context semantic query encoding and modulation value, and calculate the square root of the sum of the squares of each eigenvalue of the i-th updated device information word global context semantic query encoding representation vector to obtain a second updated device information word global context semantic query encoding and modulation value;

[0052] After performing dot-wise subtraction on the i-th updated device information word global context semantic query coding representation vector and the second updated device information word global context semantic query coding and modulation value, perform dot-wise multiplication on the number of eigenvalues ​​of the i-th updated device information word global context semantic query coding representation vector and the reciprocal of the first updated device information word global context semantic query coding and modulation value, and take the reciprocal of each eigenvalue to obtain the first updated device information word global context semantic query coding phase conversion vector;

[0053] After performing dot-wise subtraction on the i-th updated device information word global context semantic query coding representation vector and the first updated device information word global context semantic query coding and modulation value, perform dot-wise multiplication on the square root of the number of eigenvalues ​​of the i-th updated device information word global context semantic query coding representation vector and the reciprocal of the second updated device information word global context semantic query coding and modulation value, and take the reciprocal of each eigenvalue to obtain the second updated device information word global context semantic query coding phase conversion vector;

[0054] Subtract the dot product vector of the second updated device information word global context semantic query encoding phase conversion vector from the first updated device information word global context semantic query encoding phase conversion vector and the weighted hyperparameter to obtain an optimized i-th updated device information word global context semantic query encoding representation vector;

[0055] The optimized i-th updated device information word global context semantic query encoding representation vector is passed through a classifier-based content identifier to obtain a recognition result.

[0056] Here, the optimized representation of the i-th updated device information word global context semantic query encoding representation vector, denoted as V, is:

[0057]

[0058]

[0059]

[0060]

[0061]

[0062] v k ∈V∈R n

[0063] Where V is the global context semantic query encoding representation vector of the i-th updated device information word, R represents a real number set, and v k represents the feature value of the kth position of the i-th updated device information word global context semantic query encoding representation vector, n represents the number of feature values ​​of the i-th updated device information word global context semantic query encoding representation vector, α represents the first updated device information word global context semantic query encoding and modulation value, β represents the second updated device information word global context semantic query encoding and modulation value, ⊙ represents the positional point multiplication, Indicates positional subtraction, [·] ⊙-1is the inverse of each eigenvalue in the vector, V1 represents the first updated device information word global context semantic query encoding phase transition vector, V2 represents the second updated device information word global context semantic query encoding phase transition vector, ω represents the weighted hyperparameter, and V′ represents the optimized i-th updated device information word global context semantic query encoding representation vector.

[0064] Here, in the technical solution of the present application, the semantic embedding coding vector of the updated device information word corresponding to the i-th updated device information word in the sequence of the updated device information words is used as the query feature vector and the sequence of the semantic embedding coding vectors of the updated device information words is used as the sequence of the imitation key feature vectors, and when the query feature vector and the sequence of the imitation key feature vectors are subjected to query encoding based on the local neighborhood, it is considered that the sequence of the query feature vector and the sequence of the imitation key feature vector are both derived from the sequence of the semantic embedding coding vector of the updated device information word, and there is a relatively significant semantic association space span correlation between each imitation key feature vector in the sequence of the imitation key feature vector. Therefore, when performing attention gated query encoding, the query matching results based on the local semantic association space span difference and the feature set distribution redundancy will also have cross-domain dynamic matching differences. Therefore, it is expected to improve the detail semantic aggregation expression effect of the global context semantic query encoding representation vector of the i-th updated device information word based on the cross-dynamic attention gate encoding difference.

[0065] Therefore, in the preferred example, the difference in the difference and modulation representation of the feature value of the global context semantic query encoding representation vector of the i-th updated device information word relative to the feature set of the vector as a whole of the i-th updated device information word global context semantic query encoding representation vector is used as the semantic change intensity information, and a phase-like transformation corresponding to the position-based intensity modulation is performed through different and modulation representation forms, so that the aggregation enhancement of the semantic change phase perception can enhance the axial aggregation receptive field along the feature aggregation direction by performing a spatial translation operation based on alternating stacking under the scale equalization of the vector set of the i-th updated device information word global context semantic query encoding representation vector, thereby improving the perception effect of the aggregated semantics of the i-th updated device information word global context semantic query encoding representation vector on the detailed semantic changes, so as to improve the expression effect of the i-th updated device information word global context semantic query encoding representation vector, and improve the accuracy of the recognition result obtained by passing it through a classifier-based content identifier. In this way, through word segmentation processing and semantic query analysis, we can more accurately understand the meaning of each word and its role in the context, so as to more accurately judge the expression errors in the information, thereby reducing the workload of manual checking item by item, improving the degree of automation of the verification process, and making the verification work more efficient.

[0066] In one embodiment of the present application, a method for simplifying the information update process using Bluetooth / Wi-Fi technology is also proposed. In today's society, instant update and flexible configuration of information are key parts of the user experience. Traditional methods usually require cumbersome wired connections or complex operating steps, while through wireless communication technology, users can easily interact with devices without complex wiring. When the user opens the mobile app, he can quickly see the Bluetooth name list, select the Bluetooth device to be connected, and click Connect to establish communication. Subsequently, click the Automatic Address Assignment button to assign an address to the screen. This process ensures that the device can accurately identify and receive information. After each address assignment process is completed, the device information is automatically re-read and displayed in the app interface, so that the user can understand the status of the device in real time. When the user has configured the content to be displayed, just click Send to Device. The progress bar that appears at this time allows the user to intuitively see the progress of information transmission. When the progress bar is full, the screen configuration is complete and the information is changed successfully. In this way, users can use Bluetooth connection to change the information of the device anytime and anywhere, greatly improving the convenience and efficiency of information change, and meeting people's needs for convenience and flexibility in fast-paced life.

[0067] The communication scheme in this embodiment adopts an asynchronous serial communication protocol, and the physical layer uses the 485 communication standard. In addition, a method for communicating with an embedded device using a mobile phone application based on 2.4G wireless communication technology is provided, and a new data communication protocol is defined. This method is actually applied to products, and the specific architecture is as follows Figure 5 As shown, it includes multiple communication cabinets, each of which is equipped with a host and several slaves, and each slave can be connected to multiple screens. Users can communicate with embedded devices via Bluetooth or Wi-Fi. The Bluetooth name of the host will be printed on a label and pasted on the surface of the host shell. The host supports assigning addresses to the slaves in the order of slave wiring, and transmits the number of slaves back to the mobile app. In addition, the mobile app supports the connection of Bluetooth version and Wi-Fi version (local area network), and provides batch modification function.

[0068] In the above embodiment, the app interface is as follows Figure 6As shown, it includes: a loading interface that displays the manufacturer's logo at startup; a main interface that supports renaming the cabinet name (for example, "Cabinet No. 1" followed by the Bluetooth address); clicking "Screen No. 1" to change its content; after selecting the screen, the product name is displayed if it has been edited; after expanding "Cabinet No. 1", a drop-down menu "Screen No. 1" is visible; a search device interface; a device address allocation interface; a data transmission interface; and a batch data modification interface, the latter of which adds the function of searching for terms, allowing users to modify only the searched terms. In addition, there is a detailed data display modification interface. The app also supports modifying only a single display area without affecting other parts (such as modifying only the logo without changing the price, etc.), and supports scanning the screen QR code to change the content. The application allows users to customize templates.

[0069] The operating logic of the method provided in this application for realizing simple information change through Bluetooth / Wi-Fi technology is as follows: After opening the mobile phone app, you can see a list of Bluetooth names (such as 0000001, 0000002, 0000003, and the corresponding Bluetooth host or Wi-Fi device will have a corresponding name label). The user can select the Bluetooth name to be connected and click to connect (multiple selections are supported, that is, connecting to multiple hosts at the same time). After the connection is completed, the app will automatically read the device information (there will be a progress bar prompt during this process). After clicking the "Automatically assign address" button, the system will assign an address to the screen. Each time the address allocation process is completed, the device information will be automatically re-read and displayed in the app interface. When the user has configured the content to be displayed, click "Send to Device". At this time, the progress bar shows the transmission progress until the screen configuration is completed.

[0070] In the communication scheme in the above embodiment, there are three information interaction modes between the application and the Bluetooth host, all of which adopt the inquiry-response mechanism.

[0071] 1. Reading device information

[0072] app sends to the Bluetooth host

[0073]

[0074] The Bluetooth host returns to the app

[0075]

[0076] 2. The price tag screen automatically assigns the address to the app and sends it to the Bluetooth host

[0077]

[0078] The Bluetooth host returns to the app

[0079]

[0080] 3. Send the price tag screen data to the device

[0081]

[0082] Continued from the table

[0083]

[0084] Continued from the table

[0085]

[0086] Continued from the table

[0087] check check Secondary separator *

[0088] 5.4 Ask the host if it is ready

[0089] Protocol Header Command code Data length Register Address Check(High) check First level separator 0XFFFA 0X03 0x02

[0090]

[0091] The communication protocol between the Bluetooth host and the slave in the above embodiment is as follows: 1. Address allocation protocol

[0092] 1. Addressing protocol

[0093] Protocol Header Command code Data length Register Address Address Number check check First level separator 0XFF FA 0X06 09 01 01 DC DA /

[0094]

[0095] 2. Addressing completed

[0096]

[0097] Among them, crc only calculates the first seven digits

[0098] 2. Sending pictures protocol

[0099] Continued from the table

[0100]

[0101] 3. Receiving the completion agreement

[0102]

[0103]

[0104] The above embodiment includes the following key points: 1. The communication between the mobile phone APP and the device adopts Bluetooth or WiFi communication. 2. The protocol specifies the communication protocol between the app and the host, including device information reading, automatic address allocation of the price tag screen, sending of price tag screen data to the device, host idle query, and communication protocol between the device and the next location, protecting the communication protocol for information interaction between the above host and the app, such as the meaning represented by a certain part of the protocol. 3. The order of the above data is specified in the protocol, but it should not be limited to the order between each data. 4. The protocol specifies that the transmitted data is hexadecimal, but it should not be limited to hexadecimal, and also protects the transmission of other base data such as decimal and octal.

[0105] In summary, the device information modification method based on Bluetooth technology according to the embodiment of the present application is explained, which uses artificial intelligence-based information analysis and processing technology to perform word segmentation and semantic embedding on the updated device information, so as to intelligently judge whether there are expression errors in these different updated device information words according to the semantic query representation between the semantic embedding features of different updated device information words and the semantic embedding features of the entire updated device information words. In this way, through word segmentation processing and semantic query analysis, the meaning of each word and its role in the context can be understood more accurately, so as to more accurately judge the expression errors in the information, thereby reducing the workload of manual item-by-item verification, improving the degree of automation of the verification process, and making the verification work more efficient.

[0106] Figure 5 Schematic block diagram of a device information modification system based on Bluetooth technology according to an embodiment of the present application. Figure 5 As shown, the device information change system 100 based on Bluetooth technology includes: a Bluetooth name list acquisition module 110, which is used to obtain a Bluetooth name list of terminal devices to be connected; a terminal device connection module 120, which is used to select the Bluetooth name of the terminal device to be connected from the Bluetooth name list and click the connection button; an address allocation module 130, which is used to click the automatic address allocation button after the connection is successful to allocate an address for the terminal device to be connected; a device information automatic reading module 140, which is used to automatically read the device information of the terminal device to be connected after completing the address allocation process, and display the device information on the screen; a device information content configuration module 150, which is used to perform content configuration on the device information to obtain updated device information; a content intelligent verification module 160, which is used to perform content intelligent verification on the updated device information to obtain a content intelligent verification result; an updated device information sending module 170, which is used to respond to the content intelligent verification result being normal, click the send to device button, and send the updated device information to the terminal device to be connected.

[0107] The basic principle of the present invention is described above in conjunction with specific embodiments. However, it should be pointed out that the advantages, strengths, effects, etc. mentioned in the present invention are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. must be possessed by each embodiment of the present invention. In addition, the specific details of the above embodiments are only for the purpose of illustration and facilitation of understanding, rather than limitation, and the above details do not limit the present invention to being implemented by adopting the above specific details.

Claims

1. A method for changing device information based on Bluetooth technology, characterized in that: include: Get the Bluetooth name list of the terminal devices to be connected; Select the Bluetooth name of the terminal device to be connected from the Bluetooth name list, and click the Connect button; After the connection is successful, click the automatic address allocation button to allocate an address for the terminal device that needs to be connected; After completing the address allocation process, the device information of the terminal device to be connected is automatically read and the device information is displayed on the screen; Performing content configuration on the device information to obtain updated device information; Performing content intelligent verification on the updated device information to obtain a content intelligent verification result; In response to the intelligent verification result of the content being normal, click the Send to Device button to send the updated device information to the terminal device that needs to be connected.

2. The device information changing method based on Bluetooth technology according to claim 1, characterized in that: Performing content intelligent verification on the update device information to obtain a content intelligent verification result, including: Performing word segmentation processing on the updated device information to obtain a sequence of updated device information words; Performing semantic embedding coding on each updated device information word in the sequence of updated device information words to obtain a sequence of updated device information word semantic embedding coding vectors; Taking the semantic embedding coding vector of the updated device information word corresponding to the ith updated device information word in the sequence of the updated device information words as the query feature vector, taking the sequence of the semantic embedding coding vectors of the updated device information words as the sequence of key feature vectors, performing query coding based on local neighborhood on the sequence of the query feature vector and the key feature vector to obtain the semantic query coding representation of the ith updated device information word, including: performing value embedding processing on the semantic embedding coding vector of the updated device information word corresponding to the ith updated device information word to obtain the semantic value feature vector of the updated device information word; taking the semantic embedding coding vector of the updated device information word corresponding to the ith updated device information word as the query vector, the semantic value feature vector of the updated device information word as the value vector and the sequence of the semantic embedding coding vector of the updated device information word as the sequence of key vectors, performing invisible optimization based on attention gating on the sequence of the query vector, the value vector and the key vector to obtain the semantic query coding representation of the ith updated device information word; Based on the semantic query encoding representation of the i-th updated device information word, a recognition result is obtained.

3. The device information changing method based on Bluetooth technology according to claim 2, characterized in that: Performing semantic embedding coding on each update device information word in the sequence of update device information words to obtain a sequence of semantic embedding coding vectors of update device information words, including: performing semantic embedding coding on each update device information word in the sequence of update device information words using a semantic embedding matrix to obtain a sequence of semantic embedding coding vectors of update device information words.

4. The device information changing method based on Bluetooth technology according to claim 3, characterized in that: The update device information word semantic embedding coding vector corresponding to the i-th update device information word is subjected to value embedding processing to obtain the update device information word semantic value feature vector, including: using the value embedding coding matrix to process the update device information word semantic embedding coding vector corresponding to the i-th update device information word to obtain the update device information word semantic value feature vector.

5. The method for changing device information based on Bluetooth technology according to claim 4, characterized in that: Taking the semantic embedding coding vector of the updated device information word corresponding to the i-th updated device information word as the query vector, the semantic value feature vector of the updated device information word as the value vector, and the sequence of the semantic embedding coding vectors of the updated device information word as the sequence of key vectors, performing invisible optimization based on attention gating on the sequence of the query vector, the value vector, and the key vector to obtain the semantic query coding representation of the i-th updated device information word, including: Performing one-dimensional convolution coding on the sequence of semantic embedding coding vectors of the updated device information words to obtain a sequence of local neighborhood semantic association feature vectors of the updated device information words; Taking the updated device information word semantic embedding coding vector corresponding to the i-th updated device information word as the query vector, the updated device information word semantic value feature vector as the value vector and the sequence of the updated device information word semantic embedding coding vectors as the sequence of key vectors, inputting the query vector, the value vector and the sequence of key vectors into a first multi-head attention query module based on a converter structure to obtain a sequence of updated device information word semantic granularity query matching implicit vectors; Taking the semantic embedding coding vector of the updated device information word corresponding to the i-th updated device information word as the query vector, the semantic value feature vector of the updated device information word as the value vector and the sequence of the local neighborhood semantic association feature vectors of the updated device information word as the sequence of key vectors, the query vector, the value vector and the sequence of the key vectors are input into a second multi-head attention query module based on a converter structure to obtain a sequence of implicit vectors for semantic neighborhood granularity query matching of the updated device information word; Calculating the position mean vector of the sequence of the updated device information word semantic granularity query matching implicit vectors and the sequence of the updated device information word semantic neighborhood granularity query matching implicit vectors to obtain the updated device information word semantic granularity query matching feature vector and the updated device information word semantic neighborhood granularity query matching feature vector; The updated device information word semantic granularity query matching feature vector and the updated device information word semantic neighborhood granularity query matching feature vector are fused to obtain the i-th updated device information word global context semantic query encoding representation vector as the i-th updated device information word semantic query encoding representation.

6. The method for changing device information based on Bluetooth technology according to claim 5, characterized in that: The scale of the one-dimensional convolutional coding is equal to an integer multiple of the length of the semantic embedding coding vector of the updated device information word.

7. The device information modification method based on Bluetooth technology according to claim 6, characterized in that: Taking the semantic embedding coding vector of the updated device information word corresponding to the i-th updated device information word as the query vector, the semantic value feature vector of the updated device information word as the value vector and the sequence of the semantic embedding coding vectors of the updated device information word as the sequence of key vectors, inputting the sequence of the query vector, the value vector and the key vector into a first multi-head attention query module based on a converter structure to obtain a sequence of semantic granularity query matching implicit vectors of the updated device information word, including: Calculate the product of the update device information word semantic embedding coding vector corresponding to the i-th update device information word and the transposed vector of the update device information word semantic embedding coding vector, and divide the obtained update device information word semantic association matrix by the square root of the length of the update device information word semantic embedding coding vector by position to obtain the update device information word semantic association modulation matrix; Inputting the updated device information word semantic association modulation matrix into a softmax function to obtain an updated device information word semantic association activation matrix; The semantic association activation matrix of the updated device information word is multiplied by the semantic value feature vector of the updated device information word to obtain the semantic granularity query matching implicit vector of the updated device information word.

8. The method for changing device information based on Bluetooth technology according to claim 7, characterized in that: The semantic granularity query matching feature vector of the updated device information word and the semantic neighborhood granularity query matching feature vector of the updated device information word are merged to obtain the global context semantic query encoding representation vector of the i-th updated device information word, including: Respectively calculating the positional subtraction, positional dot product and positional addition between the semantic granularity query matching feature vector of the updated device information word and the semantic neighborhood granularity query matching feature vector of the updated device information word to obtain an updated device information word semantic granularity-neighborhood granularity difference vector, an updated device information word semantic granularity-neighborhood granularity dot product vector and an updated device information word semantic granularity-neighborhood granularity sum vector; Cascading the semantic granularity-neighborhood granularity difference vector of the updated device information word, the semantic granularity-neighborhood granularity dot product vector of the updated device information word, and the semantic granularity-neighborhood granularity sum vector of the updated device information word to obtain a cascade vector of the semantic granularity-neighborhood granularity of the updated device information word; After performing one-dimensional convolution encoding on the semantic granularity-neighborhood granularity cascade vector of the updated device information word, the obtained semantic granularity-neighborhood granularity convolution encoding vector of the updated device information word is subjected to local window-based maximum pooling processing to obtain the global context semantic query encoding representation vector of the i-th updated device information word.

9. The method for changing device information based on Bluetooth technology according to claim 8, characterized in that: Based on the semantic query encoding representation of the i-th update device information word, a recognition result is obtained, including: inputting the global context semantic query encoding representation vector of the i-th update device information word into a classifier-based content identifier to obtain the recognition result, and the recognition result is used to indicate whether there is an expression error in the i-th update device information word.

10. A device information changing system based on Bluetooth technology, characterized in that: include: A Bluetooth name list acquisition module is used to obtain a Bluetooth name list of terminal devices to be connected; The terminal device connection module is used to select the Bluetooth name of the terminal device to be connected from the Bluetooth name list and click a connection button; An address allocation module is used to click an automatic address allocation button to allocate an address to the terminal device to be connected after the connection is successful; The device information automatic reading module is used to automatically read the device information of the terminal device to be connected after completing the address allocation process, and display the device information on the screen; A device information content configuration module, used to perform content configuration on the device information to obtain updated device information; A content intelligent verification module, used to perform content intelligent verification on the update device information to obtain a content intelligent verification result; The updated device information sending module is used to respond to the intelligent verification result of the content being normal by clicking the send to device button to send the updated device information to the terminal device that needs to be connected.

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