Ring communication method and device based on historical records

Abstract

The present invention discloses a ring communication method and device based on historical records, the method comprising: obtaining multiple historical communication data and corresponding scene information of multiple users of a target ring in a historical time period; training a communication prediction model of the target ring according to the multiple historical communication data and corresponding scene information; obtaining real-time scene information of the target ring, inputting the real-time scene information into the communication prediction model to obtain communication prediction parameters of the target ring; and controlling the target ring to package communication data in advance and controlling the corresponding communication server to make communication connection in advance according to the communication prediction parameters. It can be seen that the present invention can improve the intelligence level of smart ring communication, improve communication efficiency and accuracy, provide users with a better user experience, and reduce communication errors.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a finger ring communication method and device based on historical records. Background Art

[0002] Smart rings are wearable electronic devices that are generally equipped with mobile components such as sensors and NFC chips. They can be used in various applications, mainly for tracking daily activities and as peripheral tools to support mobile devices. Most existing smart rings can only communicate through pre-set communication paths or protocols, so their intelligence level is low, communication efficiency is poor, and user experience is difficult to be satisfactory. It can be seen that the existing technology has defects that need to be solved urgently. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a finger ring communication method and device based on historical records, which can improve the intelligence level of smart finger ring communication, improve communication efficiency and accuracy, provide users with better use experience, and reduce communication errors.

[0004] In order to solve the above technical problems, the first aspect of the present invention discloses a finger ring communication method based on historical records, the method comprising:

[0005] Acquire multiple historical communication data and corresponding scene information of multiple users of the target ring in a historical time period;

[0006] According to the plurality of historical communication data and corresponding scene information, a communication prediction model of the target ring is obtained by training;

[0007] Acquire real-time scene information of the target ring, and input the real-time scene information into the communication prediction model to obtain communication prediction parameters of the target ring;

[0008] According to the communication prediction parameters, the target ring is controlled to package the communication data in advance and the corresponding communication server is controlled to establish a communication connection in advance.

[0009] As an optional embodiment, in the first aspect of the present invention, the historical communication data or the communication prediction parameters include communication purpose, communication server, communication transmission data, communication transmission protocol and communication expected time.

[0010] As an optional embodiment, in the first aspect of the present invention, the corresponding scene information or the real-time scene information includes ring position, ring power, ring speed, ring acceleration, ring posture and physiological data acquired by the ring; the physiological data includes at least one of blood pressure, pulse, electrocardiogram, blood sugar, blood oxygen and body temperature.

[0011] As an optional implementation, in the first aspect of the present invention, the communication prediction model is a neural network prediction model based on a CNN structure.

[0012] As an optional implementation, in the first aspect of the present invention, the training of the communication prediction model of the target ring according to the plurality of historical communication data and the corresponding scene information includes:

[0013] Taking each of the historical communication data and the scene information corresponding to the time period as a training data pair to obtain a training data set;

[0014] 30% of the training data set is used as a test set, and 70% is used as a training set;

[0015] Each training data pair in the training set is input into a pre-set CNN neural network model for iterative training, and the model parameters of the CNN neural network model are optimized using a gradient descent algorithm and an L2 loss function. The CNN neural network model is tested using the test set until the training is completed, thereby obtaining a communication prediction model of the target ring.

[0016] As an optional implementation, in the first aspect of the present invention, the step of inputting the real-time scene information into the communication prediction model to obtain the communication prediction parameters of the target ring includes:

[0017] Inputting the real-time scene information into a grouping algorithm model to obtain multiple scene information sets;

[0018] Inputting each of the scene information sets into the communication prediction model to obtain a set communication prediction parameter corresponding to each of the scene information sets;

[0019] The intersection of the set communication prediction parameters corresponding to all the scene information sets is calculated to obtain the communication prediction parameters of the target ring.

[0020] As an optional implementation, in the first aspect of the present invention, the inputting the real-time scene information into a grouping algorithm model to obtain multiple scene information sets includes:

[0021] For any two pieces of scene information in the real-time scene information, the two pieces of scene information are input into a trained information relevance prediction neural network to obtain relevance parameters corresponding to the two pieces of scene information; the information relevance prediction neural network is trained by a training data set including a plurality of training scene information pairs and corresponding relevance annotations;

[0022] According to the correlation parameter, all scene information in the real-time scene information is grouped to obtain multiple scene information sets; wherein the correlation parameter corresponding to any two scene information in each of the scene information sets is greater than a preset parameter threshold.

[0023] As an optional implementation, in the first aspect of the present invention, controlling the target ring to package communication data in advance and controlling the corresponding communication server to establish a communication connection in advance according to the communication prediction parameter includes:

[0024] Determine, according to the communication server and the communication transmission protocol in the communication prediction parameters, a plurality of candidate communication servers that can satisfy the communication server and the communication transmission protocol;

[0025] Calculate the time difference between the predicted transmission time corresponding to the transmission distance between each candidate communication server and the target ring and the expected communication time;

[0026] Calculating a first similarity between a historical communication destination of each candidate communication server and the communication destination;

[0027] Calculating a second similarity between the historical communication data of each candidate communication server and the communication transmission data;

[0028] Calculate a weighted sum of the time difference, the first similarity and the second similarity of each candidate communication server to obtain a priority parameter of each candidate communication server;

[0029] Determine the candidate communication server with the highest priority parameter as the target prediction server;

[0030] Controlling the target ring to package the communication transmission data in advance;

[0031] The target ring is controlled to establish a communication connection with the target prediction server based on the communication transmission protocol in advance.

[0032] A second aspect of an embodiment of the present invention discloses a finger ring communication device based on historical records, the device comprising:

[0033] An acquisition module, used to acquire multiple historical communication data and corresponding scene information of multiple users of the target ring in a historical time period;

[0034] A training module, used for training a communication prediction model of the target ring according to the plurality of historical communication data and corresponding scene information;

[0035] A prediction module, used for acquiring real-time scene information of the target ring, and inputting the real-time scene information into the communication prediction model to obtain communication prediction parameters of the target ring;

[0036] The control module is used to control the target ring to package the communication data in advance and control the corresponding communication server to make a communication connection in advance according to the communication prediction parameters.

[0037] As an optional embodiment, in the second aspect of the present invention, the historical communication data or the communication prediction parameters include communication purpose, communication server, communication transmission data, communication transmission protocol and communication expected time.

[0038] As an optional embodiment, in the second aspect of the present invention, the corresponding scene information or the real-time scene information includes ring position, ring power, ring speed, ring acceleration, ring posture and physiological data acquired by the ring; the physiological data includes at least one of blood pressure, pulse, electrocardiogram, blood sugar, blood oxygen and body temperature.

[0039] As an optional implementation, in the second aspect of the present invention, the communication prediction model is a neural network prediction model based on a CNN structure.

[0040] As an optional implementation, in the second aspect of the present invention, the specific manner in which the training module trains the communication prediction model of the target ring according to the plurality of historical communication data and the corresponding scenario information includes:

[0041] Taking each of the historical communication data and the scene information corresponding to the time period as a training data pair to obtain a training data set;

[0042] 30% of the training data set is used as a test set, and 70% is used as a training set;

[0043] Each training data pair in the training set is input into a pre-set CNN neural network model for iterative training, and the model parameters of the CNN neural network model are optimized using a gradient descent algorithm and an L2 loss function. The CNN neural network model is tested using the test set until the training is completed, thereby obtaining a communication prediction model of the target ring.

[0044] As an optional implementation, in the second aspect of the present invention, the prediction module inputs the real-time scene information into the communication prediction model to obtain the communication prediction parameters of the target ring in a specific manner, including:

[0045] Inputting the real-time scene information into a grouping algorithm model to obtain multiple scene information sets;

[0046] Inputting each of the scene information sets into the communication prediction model to obtain a set communication prediction parameter corresponding to each of the scene information sets;

[0047] The intersection of the set communication prediction parameters corresponding to all the scene information sets is calculated to obtain the communication prediction parameters of the target ring.

[0048] As an optional implementation, in the second aspect of the present invention, the prediction module inputs the real-time scene information into the grouping algorithm model to obtain a specific manner of multiple scene information sets, including:

[0049] For any two pieces of scene information in the real-time scene information, the two pieces of scene information are input into a trained information relevance prediction neural network to obtain relevance parameters corresponding to the two pieces of scene information; the information relevance prediction neural network is trained by a training data set including a plurality of training scene information pairs and corresponding relevance annotations;

[0050] According to the correlation parameter, all scene information in the real-time scene information is grouped to obtain multiple scene information sets; wherein the correlation parameter corresponding to any two scene information in each of the scene information sets is greater than a preset parameter threshold.

[0051] As an optional implementation, in the second aspect of the present invention, the control module controls the target ring to package the communication data in advance and controls the corresponding communication server to make a communication connection in advance according to the communication prediction parameter, including:

[0052] Determine, according to the communication server and the communication transmission protocol in the communication prediction parameters, a plurality of candidate communication servers that can satisfy the communication server and the communication transmission protocol;

[0053] Calculate the time difference between the predicted transmission time corresponding to the transmission distance between each candidate communication server and the target ring and the expected communication time;

[0054] Calculating a first similarity between a historical communication destination of each candidate communication server and the communication destination;

[0055] Calculating a second similarity between the historical communication data of each candidate communication server and the communication transmission data;

[0056] Calculate a weighted sum of the time difference, the first similarity and the second similarity of each candidate communication server to obtain a priority parameter of each candidate communication server;

[0057] Determine the candidate communication server with the highest priority parameter as the target prediction server;

[0058] Controlling the target ring to package the communication transmission data in advance;

[0059] The target ring is controlled to establish a communication connection with the target prediction server based on the communication transmission protocol in advance.

[0060] The third aspect of the present invention discloses another finger ring communication device based on historical records, the device comprising:

[0061] A memory storing executable program code;

[0062] a processor coupled to the memory;

[0063] The processor calls the executable program code stored in the memory to execute part or all of the steps in the finger-ring communication method based on historical records disclosed in the first aspect of the present invention.

[0064] The fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute part or all of the steps in the history record-based finger-ring communication method disclosed in the first aspect of the present invention.

[0065] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0066] The present invention can obtain a prediction model based on historical communication data and corresponding scene information training, and then use it to predict real-time communication prediction parameters, so as to control the target ring to package communication data in advance and control the corresponding communication server to make a communication connection in advance according to the communication prediction parameters, thereby improving the intelligence level of smart ring communication, improving communication efficiency and accuracy, giving users a better user experience, and reducing communication errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0068] Figure 1 The present invention discloses a method for ring communication based on historical records.

[0069] Figure 2 It is a structural schematic diagram of a finger ring communication device based on historical records disclosed in an embodiment of the present invention.

[0070] Figure 3 It is a schematic diagram of the structure of another finger ring communication device based on historical records disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0071] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0072] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or equipment that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or equipment.

[0073] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0074] The present invention discloses a finger ring communication method and device based on historical records, which can train a prediction model based on historical communication data and corresponding scene information, and then use it to predict real-time communication prediction parameters, so as to control the target finger ring to package communication data in advance and control the corresponding communication server to make communication connection in advance according to the communication prediction parameters, thereby improving the intelligence level of smart finger ring communication, improving communication efficiency and accuracy, giving users a better use experience, and reducing communication errors. The following are detailed descriptions.

[0075] Embodiment 1

[0076] See also Figure 1 , Figure 1 1 is a flow chart of a ring communication method based on historical records disclosed in an embodiment of the present invention. Figure 1The described history-based finger-ring communication method can be applied to a data processing device / data processing equipment / data processing server (wherein the server includes a local processing server or a cloud processing server). Figure 1 As shown, the finger-ring communication method based on history records may include the following operations:

[0077] 101. Acquire multiple historical communication data and corresponding scene information of multiple users of a target ring in a historical time period.

[0078] 102. According to a plurality of historical communication data and corresponding scene information, a communication prediction model of the target ring is trained.

[0079] 103. Acquire real-time scene information of the target ring, and input the real-time scene information into a communication prediction model to obtain communication prediction parameters of the target ring.

[0080] 104. According to the communication prediction parameters, control the target ring to package the communication data in advance and control the corresponding communication server to establish a communication connection in advance.

[0081] It can be seen that the above-mentioned embodiments of the invention can obtain a prediction model based on historical communication data and corresponding scenario information training, and then use it to predict real-time communication prediction parameters, so as to control the target ring to package the communication data in advance and control the corresponding communication server to make a communication connection in advance according to the communication prediction parameters, thereby improving the intelligence level of the smart ring communication, improving communication efficiency and accuracy, giving users a better user experience, and reducing communication errors.

[0082] As an optional embodiment, in the above steps, the historical communication data or communication prediction parameters include communication purpose, communication server, communication transmission data, communication transmission protocol and communication expected time.

[0083] It can be seen that through the above optional embodiments, the content of communication data or communication parameters is clarified, thereby helping to improve the intelligence level of smart ring communication, improve communication efficiency and accuracy, provide users with a better user experience, and reduce communication errors.

[0084] As an optional embodiment, in the above steps, the corresponding scene information or real-time scene information includes ring position, ring power, ring speed, ring acceleration, ring posture and physiological data acquired by the ring; the physiological data includes at least one of blood pressure, pulse, electrocardiogram, blood sugar, blood oxygen and body temperature.

[0085] It can be seen that through the above optional embodiments, the content of the scene information is clarified, thereby helping to improve the intelligence level of smart ring communication, improve communication efficiency and accuracy, provide users with a better user experience, and reduce communication errors.

[0086] As an optional embodiment, in the above steps, the communication prediction model is a neural network prediction model based on a CNN structure.

[0087] It can be seen that through the above optional embodiments, the model architecture of the communication prediction model is clarified, thereby helping to improve the intelligence level of smart ring communication, improve communication efficiency and accuracy, provide users with a better user experience, and reduce communication errors.

[0088] As an optional embodiment, in the above step, training a communication prediction model of the target ring according to a plurality of historical communication data and corresponding scene information includes:

[0089] Each historical communication data and the scene information corresponding to the time period in which it is located are taken as a training data pair to obtain a training data set;

[0090] Use 30% of the training data set as the test set and 70% as the training set;

[0091] Each training data pair in the training set is input into the pre-set CNN neural network model for iterative training, and the model parameters of the CNN neural network model are optimized using the gradient descent algorithm and L2 loss function. The CNN neural network model is tested using the test set until the training is completed, and the communication prediction model of the target ring is obtained.

[0092] It can be seen that through the above optional embodiments, the CNN neural network model can be trained through the composition of the training data set to obtain a communication prediction model with better prediction effect, thereby assisting in improving the intelligence level of smart ring communication, improving communication efficiency and accuracy, giving users a better user experience, and reducing communication errors.

[0093] As an optional embodiment, in the above step, inputting the real-time scene information into the communication prediction model to obtain the communication prediction parameters of the target ring includes:

[0094] Inputting the real-time scene information into the grouping algorithm model to obtain multiple scene information sets;

[0095] Inputting each scene information set into the communication prediction model to obtain a set communication prediction parameter corresponding to each scene information set;

[0096] The intersection of the collective communication prediction parameters corresponding to all scene information sets is calculated to obtain the communication prediction parameters of the target ring.

[0097] It can be seen that through the above optional embodiments, real-time scene information can be grouped through a grouping algorithm model to obtain multiple scene information sets, and then multiple predictions can be performed through the prediction results of multiple sets to more accurately determine communication prediction parameters, thereby improving the intelligence level of smart ring communication, improving communication efficiency and accuracy, providing users with a better user experience, and reducing communication errors.

[0098] As an optional embodiment, in the above steps, the real-time scene information is input into the grouping algorithm model to obtain multiple scene information sets, including:

[0099] For any two scene information in the real-time scene information, the two scene information are input into a trained information relevance prediction neural network to obtain relevance parameters corresponding to the two scene information; optionally, the information relevance prediction neural network is trained by a training data set including a plurality of training scene information pairs and corresponding relevance annotations;

[0100] According to the correlation parameter, all scene information in the real-time scene information is grouped to obtain multiple scene information sets; wherein the correlation parameter corresponding to any two scene information in each scene information set is greater than a preset parameter threshold.

[0101] It can be seen that through the above optional embodiments, the correlation of scene information can be predicted through the information correlation prediction neural network, and then multiple scene information sets can be grouped based on this, which is convenient for the subsequent more accurate determination of communication prediction parameters according to the scene information sets that are more correlated with each other, thereby improving the intelligence level of smart ring communication, improving communication efficiency and accuracy, giving users a better user experience, and reducing communication errors.

[0102] As an optional embodiment, in the above steps, according to the communication prediction parameters, controlling the target ring to package the communication data in advance and controlling the corresponding communication server to establish a communication connection in advance includes:

[0103] Determine, based on the communication server and the communication transmission protocol in the communication prediction parameters, a plurality of candidate communication servers that can satisfy the communication server and the communication transmission protocol;

[0104] Calculate the time difference between the predicted transmission time and the expected communication time corresponding to the transmission distance between each candidate communication server and the target ring;

[0105] Calculating a first similarity between a historical communication purpose and a communication purpose of each candidate communication server;

[0106] calculating a second similarity between the historical communication data and the communication transmission data of each candidate communication server;

[0107] Calculate the weighted sum of the time difference, the first similarity and the second similarity of each candidate communication server to obtain a priority parameter of each candidate communication server;

[0108] Determine the candidate communication server with the highest priority parameter as the target prediction server;

[0109] Control the target ring to package communication transmission data in advance;

[0110] The target ring is controlled to communicate with the target prediction server in advance based on the communication transmission protocol.

[0111] It can be seen that through the above optional embodiments, multiple candidate servers can be determined through communication prediction parameters, and then the target server can be determined based on the transmission time difference and similarity algorithm and corresponding communication preparations can be performed, thereby improving the intelligence level of smart ring communication, improving communication efficiency and accuracy, providing users with a better user experience, and reducing communication errors.

[0112] Embodiment 2

[0113] See also Figure 2 , Figure 2 : is a schematic diagram of a structure of a finger ring communication device based on historical records disclosed in an embodiment of the present invention. Figure 2 The described history-based finger-ring communication device can be applied to a data processing device / data processing equipment / data processing server (wherein the server includes a local processing server or a cloud processing server). Figure 2 As shown, the history-based finger-ring communication device may include:

[0114] The acquisition module 201 is used to acquire multiple historical communication data of multiple users of the target ring in a historical time period and corresponding scene information.

[0115] The training module 202 is used to train a communication prediction model of a target ring according to a plurality of historical communication data and corresponding scene information.

[0116] The prediction module 203 is used to obtain the real-time scene information of the target ring and input the real-time scene information into the communication prediction model to obtain the communication prediction parameters of the target ring.

[0117] The control module 204 is used to control the target ring to package the communication data in advance and control the corresponding communication server to establish a communication connection in advance according to the communication prediction parameters.

[0118] It can be seen that the above-mentioned embodiments of the invention can obtain a prediction model based on historical communication data and corresponding scenario information training, and then use it to predict real-time communication prediction parameters, so as to control the target ring to package the communication data in advance and control the corresponding communication server to make a communication connection in advance according to the communication prediction parameters, thereby improving the intelligence level of the smart ring communication, improving communication efficiency and accuracy, giving users a better user experience, and reducing communication errors.

[0119] As an optional embodiment, the historical communication data or communication prediction parameters include communication purpose, communication server, communication transmission data, communication transmission protocol and communication expected time.

[0120] It can be seen that through the above optional embodiments, the content of communication data or communication parameters is clarified, thereby helping to improve the intelligence level of smart ring communication, improve communication efficiency and accuracy, provide users with a better user experience, and reduce communication errors.

[0121] As an optional embodiment, the corresponding scene information or real-time scene information includes ring position, ring power, ring speed, ring acceleration, ring posture and physiological data acquired by the ring; the physiological data includes at least one of blood pressure, pulse, electrocardiogram, blood sugar, blood oxygen and body temperature.

[0122] It can be seen that through the above optional embodiments, the content of the scene information is clarified, thereby helping to improve the intelligence level of smart ring communication, improve communication efficiency and accuracy, provide users with a better user experience, and reduce communication errors.

[0123] As an optional embodiment, the communication prediction model is a neural network prediction model based on a CNN structure.

[0124] It can be seen that through the above optional embodiments, the model architecture of the communication prediction model is clarified, thereby helping to improve the intelligence level of smart ring communication, improve communication efficiency and accuracy, provide users with a better user experience, and reduce communication errors.

[0125] As an optional embodiment, the training module trains the communication prediction model of the target ring according to the multiple historical communication data and the corresponding scene information, including:

[0126] Each historical communication data and the scene information corresponding to the time period in which it is located are taken as a training data pair to obtain a training data set;

[0127] Use 30% of the training data set as the test set and 70% as the training set;

[0128] Each training data pair in the training set is input into the pre-set CNN neural network model for iterative training, and the model parameters of the CNN neural network model are optimized using the gradient descent algorithm and L2 loss function. The CNN neural network model is tested using the test set until the training is completed, and the communication prediction model of the target ring is obtained.

[0129] It can be seen that through the above optional embodiments, the CNN neural network model can be trained through the composition of the training data set to obtain a communication prediction model with better prediction effect, thereby assisting in improving the intelligence level of smart ring communication, improving communication efficiency and accuracy, giving users a better user experience, and reducing communication errors.

[0130] As an optional embodiment, the prediction module inputs the real-time scene information into the communication prediction model to obtain the communication prediction parameters of the target ring in a specific manner, including:

[0131] Inputting the real-time scene information into the grouping algorithm model to obtain multiple scene information sets;

[0132] Inputting each scene information set into the communication prediction model to obtain a set communication prediction parameter corresponding to each scene information set;

[0133] The intersection of the collective communication prediction parameters corresponding to all scene information sets is calculated to obtain the communication prediction parameters of the target ring.

[0134] It can be seen that through the above optional embodiments, real-time scene information can be grouped through a grouping algorithm model to obtain multiple scene information sets, and then multiple predictions can be performed through the prediction results of multiple sets to more accurately determine communication prediction parameters, thereby improving the intelligence level of smart ring communication, improving communication efficiency and accuracy, providing users with a better user experience, and reducing communication errors.

[0135] As an optional embodiment, the prediction module inputs the real-time scene information into the grouping algorithm model to obtain a specific method of multiple scene information sets, including:

[0136] For any two scene information in the real-time scene information, the two scene information are input into a trained information relevance prediction neural network to obtain relevance parameters corresponding to the two scene information; optionally, the information relevance prediction neural network is trained by a training data set including a plurality of training scene information pairs and corresponding relevance annotations;

[0137] According to the correlation parameter, all scene information in the real-time scene information is grouped to obtain multiple scene information sets; wherein the correlation parameter corresponding to any two scene information in each scene information set is greater than a preset parameter threshold.

[0138] It can be seen that through the above optional embodiments, the correlation of scene information can be predicted through the information correlation prediction neural network, and then multiple scene information sets can be grouped based on this, which is convenient for the subsequent more accurate determination of communication prediction parameters according to the scene information sets that are more correlated with each other, thereby improving the intelligence level of smart ring communication, improving communication efficiency and accuracy, giving users a better user experience, and reducing communication errors.

[0139] As an optional embodiment, the control module controls the target ring to package the communication data in advance and controls the corresponding communication server to establish a communication connection in advance according to the communication prediction parameter, including:

[0140] Determine, based on the communication server and the communication transmission protocol in the communication prediction parameters, a plurality of candidate communication servers that can satisfy the communication server and the communication transmission protocol;

[0141] Calculate the time difference between the predicted transmission time and the expected communication time corresponding to the transmission distance between each candidate communication server and the target ring;

[0142] Calculating a first similarity between a historical communication purpose and a communication purpose of each candidate communication server;

[0143] calculating a second similarity between the historical communication data and the communication transmission data of each candidate communication server;

[0144] Calculate the weighted sum of the time difference, the first similarity and the second similarity of each candidate communication server to obtain a priority parameter of each candidate communication server;

[0145] Determine the candidate communication server with the highest priority parameter as the target prediction server;

[0146] Control the target ring to package communication transmission data in advance;

[0147] The target ring is controlled to communicate with the target prediction server in advance based on the communication transmission protocol.

[0148] It can be seen that through the above optional embodiments, multiple candidate servers can be determined through communication prediction parameters, and then the target server can be determined based on the transmission time difference and similarity algorithm and corresponding communication preparations can be performed, thereby improving the intelligence level of smart ring communication, improving communication efficiency and accuracy, providing users with a better user experience, and reducing communication errors.

[0149] Embodiment 3

[0150] See also Figure 3 , Figure 3It is another finger ring communication device based on historical records disclosed in an embodiment of the present invention. Figure 3 The described history-based finger-ring communication device is applied to a data processing device / data processing equipment / data processing server (wherein the server includes a local processing server or a cloud processing server). Figure 3 As shown, the history-based finger-ring communication device may include:

[0151] A memory 301 storing executable program codes;

[0152] a processor 302 coupled to the memory 301;

[0153] The processor 302 calls the executable program code stored in the memory 301 to execute the steps of the finger-ring communication method based on historical records described in the first embodiment.

[0154] Embodiment 4

[0155] The embodiment of the present invention discloses a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program enables a computer to execute the steps of the finger-ring communication method based on historical records described in the first embodiment.

[0156] Embodiment 5

[0157] The embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps of the history record-based finger-ring communication method described in the first embodiment.

[0158] The above describes specific embodiments of the present specification, and other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily have to be performed in the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0159] The devices, means, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0160] For the convenience of description, the above device is described by dividing it into various units according to its functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0161] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, devices, or computer program products. Therefore, the embodiments of this specification may take the form of complete hardware embodiments, complete software embodiments, or embodiments combining software and hardware. Moreover, the embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0162] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (apparatus), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0163] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0164] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0165] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0166] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0167] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0168] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0169] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0170] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0171] Finally, it should be noted that the historical record-based finger ring communication method and device disclosed in the embodiments of the present invention only disclose the preferred embodiments of the present invention, which are only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features therein can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A ring communication method based on historical records, characterized in that: The method comprises: Acquire multiple historical communication data and corresponding scene information of multiple users of the target ring in a historical time period; According to the plurality of historical communication data and corresponding scene information, a communication prediction model of the target ring is obtained by training; Acquire real-time scene information of the target ring, and input the real-time scene information into the communication prediction model to obtain communication prediction parameters of the target ring; the communication prediction parameters include communication purpose, communication server, communication transmission data, communication transmission protocol and communication expected time; According to the communication prediction parameter, controlling the target ring to package the communication data in advance and controlling the corresponding communication server to establish a communication connection in advance includes: Determine, according to the communication server and the communication transmission protocol in the communication prediction parameters, a plurality of candidate communication servers that can satisfy the communication server and the communication transmission protocol; Calculate the time difference between the predicted transmission time corresponding to the transmission distance between each candidate communication server and the target ring and the expected communication time; Calculating a first similarity between a historical communication destination of each candidate communication server and the communication destination; Calculating a second similarity between the historical communication data of each candidate communication server and the communication transmission data; Calculate a weighted sum of the time difference, the first similarity and the second similarity of each candidate communication server to obtain a priority parameter of each candidate communication server; Determine the candidate communication server with the highest priority parameter as the target prediction server; Controlling the target ring to package the communication transmission data in advance; The target ring is controlled to establish a communication connection with the target prediction server based on the communication transmission protocol in advance.

2. The finger ring communication method based on historical records according to claim 1, characterized in that: The corresponding scene information or the real-time scene information includes ring position, ring power, ring speed, ring acceleration, ring posture and physiological data acquired by the ring; the physiological data includes at least one of blood pressure, pulse, electrocardiogram, blood sugar, blood oxygen and body temperature.

3. The finger ring communication method based on historical records according to claim 1, characterized in that: The communication prediction model is a neural network prediction model based on a CNN structure.

4. The finger ring communication method based on historical records according to claim 3, characterized in that: The training of obtaining a communication prediction model of the target ring according to the plurality of historical communication data and corresponding scene information includes: Taking each of the historical communication data and the scene information corresponding to the time period as a training data pair to obtain a training data set; 30% of the training data set is used as a test set, and 70% is used as a training set; Each training data pair in the training set is input into a pre-set CNN neural network model for iterative training, and the model parameters of the CNN neural network model are optimized using a gradient descent algorithm and an L2 loss function. The CNN neural network model is tested using the test set until the training is completed, thereby obtaining a communication prediction model of the target ring.

5. The finger ring communication method based on historical records according to claim 2, characterized in that: The step of inputting the real-time scene information into the communication prediction model to obtain the communication prediction parameters of the target ring includes: Inputting the real-time scene information into a grouping algorithm model to obtain multiple scene information sets; Inputting each of the scene information sets into the communication prediction model to obtain a set communication prediction parameter corresponding to each of the scene information sets; The intersection of the set communication prediction parameters corresponding to all the scene information sets is calculated to obtain the communication prediction parameters of the target ring.

6. The finger ring communication method based on historical records according to claim 5, characterized in that: The real-time scene information is input into a grouping algorithm model to obtain a plurality of scene information sets, including: For any two pieces of scene information in the real-time scene information, the two pieces of scene information are input into a trained information relevance prediction neural network to obtain relevance parameters corresponding to the two pieces of scene information; the information relevance prediction neural network is trained by a training data set including a plurality of training scene information pairs and corresponding relevance annotations; According to the correlation parameter, all scene information in the real-time scene information is grouped to obtain multiple scene information sets; wherein the correlation parameter corresponding to any two scene information in each of the scene information sets is greater than a preset parameter threshold.

7. A finger ring communication device based on historical records, characterized in that: The device comprises: An acquisition module, used to acquire multiple historical communication data and corresponding scene information of multiple users of the target ring in a historical time period; A training module, used for training a communication prediction model of the target ring according to the plurality of historical communication data and corresponding scene information; A prediction module, used to obtain real-time scene information of the target ring, and input the real-time scene information into the communication prediction model to obtain communication prediction parameters of the target ring; the communication prediction parameters include communication purpose, communication server, communication transmission data, communication transmission protocol and communication expected time; A control module, used for controlling the target ring to package communication data in advance and controlling the corresponding communication server to establish communication connection in advance according to the communication prediction parameter, comprises: Determine, according to the communication server and the communication transmission protocol in the communication prediction parameters, a plurality of candidate communication servers that can satisfy the communication server and the communication transmission protocol; Calculate the time difference between the predicted transmission time corresponding to the transmission distance between each candidate communication server and the target ring and the expected communication time; Calculating a first similarity between a historical communication destination of each candidate communication server and the communication destination; Calculating a second similarity between the historical communication data of each candidate communication server and the communication transmission data; Calculate a weighted sum of the time difference, the first similarity and the second similarity of each candidate communication server to obtain a priority parameter of each candidate communication server; Determine the candidate communication server with the highest priority parameter as the target prediction server; Controlling the target ring to package the communication transmission data in advance; The target ring is controlled to establish a communication connection with the target prediction server based on the communication transmission protocol in advance.

8. A finger ring communication device based on historical records, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the historical record-based finger-ring communication method according to any one of claims 1 to 6.

Images