Mobile communication terminal based on artificial intelligence

Abstract

The invention discloses a mobile communication terminal based on artificial intelligence. The mobile communication terminal comprises a data sensing module, a processing module, a power acquisition module, an artificial intelligence module, a filtering module and a communication module, the data sensing module is used for collecting data streams of the mobile communication terminal in real time and accurately capturing and integrating diversified network state information; and the processing module is used for carrying out real-time noise removal and error processing on the data stream, and converting the diversified data stream into a standard data format through data conversion so as to ensure the standardization of the data. The invention belongs to the technical field of mobile communication terminals, and aims at solving the problem that in the prior art, user data resources of different sizes are processed in a unified mode when being managed and output, and flexibility is poor. The method has the technical effects that the efficiency and the user experience are improved and the flexibility is higher by adopting a processing mode of splitting the differentiated data first and then merging the data.

Description

Technical Field

[0001] The present application relates to the technical field of mobile communication terminals, and in particular to a mobile communication terminal based on artificial intelligence. Background Art

[0002] Mobile communication terminals are highly portable computer-related devices and systems designed for mobile environments. They are closely connected to wireless communication networks and provide users with voice calls, data transmission, and the ability to run a variety of mobile applications anytime and anywhere. Mobile communication terminals not only meet people's basic communication needs, but also integrate a full range of functions such as multimedia playback, web browsing, navigation services, and social networks, greatly improving users' mobile life experience and bringing convenience to our lives.

[0003] Currently, most mobile communication terminals use a unified form of processing when managing and outputting user data resources of different sizes. Although this simplifies the development and maintenance process, it reduces efficiency and user experience and has poor flexibility. When the data volume is large or the network conditions are poor, the unified data processing method may lead to a decrease in processing efficiency and affect the user experience. Summary of the invention

[0004] To this end, the present application provides an artificial intelligence-based mobile communication terminal to solve the existing problem that a unified form is used for managing and outputting user data resources of different sizes. Although this simplifies the development and maintenance process, it reduces efficiency and user experience and has poor flexibility.

[0005] In order to achieve the above objectives, this application provides the following technical solutions:

[0006] An artificial intelligence-based mobile communication terminal, comprising a data sensing module, a processing module, a power acquisition module, an artificial intelligence module, a filtering module and a communication module;

[0007] The data sensing module is used to collect data streams from mobile communication terminals in real time, accurately capture and integrate diversified network status information;

[0008] The processing module is used to remove noise and process errors in real time on the data stream, and convert the diversified data stream into a standard data format through data conversion to ensure data standardization;

[0009] The power acquisition module is used to capture the key parameters of the amplitude and frequency of the transmission signal in the communication network environment from the transmission link, and transmit the key parameters of the transmission signal to the artificial intelligence module;

[0010] The artificial intelligence module is constructed by a deep learning neural network model and a data allocation module;

[0011] The artificial intelligence module can analyze the bandwidth requirements and actual usage of key parameters, and binary encode the standardized data according to the actual usage and split it into n data segments, including the header X 1+n and tail Y 1+n , where n = 1, 2, 3, ... n;

[0012] The filtering module is used to identify the merged and sorted data, effectively avoiding the propagation of erroneous data in the network;

[0013] The communication module is used for data transmission and communication with external devices or networks, so that the mobile communication terminal can transmit sorted data in various communication scenarios.

[0014] Furthermore, the data flow includes the size, transmission speed, transmission direction and communication network environment of the data.

[0015] Furthermore, the deep learning neural network can provide real-time mobile communication terminal data to the data perception module for tracking and prediction, predict the bandwidth resources occupied and consumed during the transmission process in the current time period and network environment, and analyze the data's demand for bandwidth and actual usage.

[0016] Furthermore, when the actual usage is less than the transmission power of the mobile communication terminal, the data allocation module directly allocates the data to the communication module, thereby achieving efficient utilization of bandwidth resources and load balancing.

[0017] Furthermore, when the actual usage is greater than the transmission power of the mobile communication terminal, the n split data segments are encapsulated through the transmission control protocol to avoid data loss during the transmission process, thereby ensuring reliable data transmission and the receiving end can correctly identify the corresponding data segment;

[0018] When n data segments are transmitted to the designated receiving end, the data is merged and the header X of the n+1th data segment is 1+n+1 and tail Y 1+n+1 The Y at the end of the nth data segment 1+n and the n+1th data segment header X 1+n+2 The data segments are connected to be merged and sorted to ensure the correct order and integrity of the data segments.

[0019] Furthermore, the data allocation module can allocate data to different modules according to the size of the data after standardization and the current bandwidth resource data, thereby realizing a parallel data processing mechanism, optimizing resource utilization efficiency, and ensuring that data processing tasks can be executed quickly and evenly under limited bandwidth conditions.

[0020] Furthermore, the data perception module includes a monitoring module and an interaction module.

[0021] Furthermore, the monitoring module is used to collect data streams of mobile communication terminals in real time, and the data streams include data size, transmission speed, transmission direction and communication network environment; the interaction module interacts with the communication network to collect and analyze network usage of mobile communication terminals to obtain more comprehensive network status information.

[0022] Compared with the prior art, this application has at least the following beneficial effects:

[0023] Through the coordinated work of the artificial intelligence module and the filtering module, the mobile communication terminal adopts a differentiated data split-then-merge processing method when managing and outputting user data resources of different sizes, and combines artificial intelligence to simplify the complexity of processing, which can improve efficiency and user experience and provide greater flexibility. In the case of large amounts of data or unsatisfactory network conditions, differentiated data processing methods can ensure processing efficiency, thereby optimizing user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more intuitively illustrate the prior art and the present application, exemplary drawings are given below. It should be understood that the specific shapes and structures shown in the drawings should not generally be regarded as limiting conditions for implementing the present application; for example, those skilled in the art are capable of easily making conventional adjustments or further optimizations to the addition / reduction / attribution division, specific shapes, positional relationships, connection methods, dimensional ratios, etc. of certain units (components) based on the technical concepts and exemplary drawings disclosed in the present application.

[0025] Figure 1 A schematic diagram of module connections of an artificial intelligence-based mobile communication terminal provided for one embodiment of the present application. DETAILED DESCRIPTION

[0026] The present application is further described below in detail through specific embodiments in conjunction with the accompanying drawings.

[0027] like Figure 1 As shown, an artificial intelligence-based mobile communication terminal in an embodiment of the first aspect of the present application includes a data perception module, a processing module, a power acquisition module, an artificial intelligence module, a filtering module, and a communication module, and each module is interconnected;

[0028] The data perception module includes a monitoring module and an interaction module. The monitoring module is used to collect the data flow of the mobile communication terminal in real time. The data flow includes the size, transmission speed, transmission direction and communication network environment of the data; the interaction module interacts with the communication network to collect and analyze the network usage of the mobile communication terminal, obtain more comprehensive network status information, and dynamically adjust its communication mode, seamlessly switch between various networks, and automatically select the optimal network connection mode to ensure the speed and stability of data transmission;

[0029] The processing module is used to remove noise and process errors in real time on the data stream, and convert the diverse data streams into a standard data format through data conversion to ensure data standardization.

[0030] The power acquisition module can capture the key parameters of the transmit signal amplitude and frequency in the communication network environment from the transmit link, and transmit the key parameters of the transmit signal to the artificial intelligence module. The deep learning neural network model is used to extract the key parameter features of the transmit power, and the actual transmit power is calculated based on the extracted features and specific algorithms, and real-time monitoring is performed.

[0031] The artificial intelligence module is constructed by a deep learning neural network model and a data allocation module. The deep learning neural network can provide the data perception module with real-time mobile communication terminal data tracking and prediction, predict the bandwidth resources occupied and consumed during the transmission process in the current period and network environment, and analyze the data's demand for bandwidth and actual usage;

[0032] The data allocation module can allocate data to different modules according to the size of the standardized data and the current bandwidth resource data, realizing the parallel processing mechanism of data, optimizing the resource utilization efficiency, and ensuring that data processing tasks can be executed quickly and evenly under limited bandwidth conditions, thereby improving the overall processing capacity and response speed of the system;

[0033] When the actual usage is less than the transmission power of the mobile communication terminal, the data distribution module directly distributes the data to the communication module to achieve efficient use of bandwidth resources and load balancing. The mobile communication terminal directly undertakes the task of data transmission and effectively sends the data to the receiving end to achieve the role of sharing data;

[0034] When the actual usage is greater than the transmission power of the mobile communication terminal, the artificial intelligence module will binary encode the data and split it into n data segments, including the header X n and tail Yn, where n = 1, 2, 3, ... n, to ensure logic and to avoid data loss during transmission through transmission control protocol encapsulation, thus ensuring reliable data transmission and the ability of the receiving end to correctly identify the corresponding data segment;

[0035] When n data segments are transmitted to the designated receiving end, the data is merged and the tail Y of the first data segment is 1 Respectively with the second data segment header X 2 Connect to merge and sort, the tail of the second data segment Y 2 Respectively with the third data segment header X 3 Connect, merge and sort until the tail Y of the n-1th data segment n-1 and the nth data segment header X n Connect, merge and sort to ensure the correct order and integrity of data segments, thereby simplifying the complexity of processing and ensuring processing efficiency when the data volume is large or the network conditions are not ideal;

[0036] The filtering module is used to identify the merged and sorted data. If the merged and sorted data is incorrect, the data will be discarded and the mobile communication terminal will be requested to send a retransmission, which effectively avoids the propagation of erroneous data in the network, reduces unnecessary data transmission, helps to reduce network congestion and improve data transmission efficiency.

[0037] The communication module is used for data transmission and communication with external devices or networks, so that the mobile communication terminal can transmit sorted data in various communication scenarios.

[0038] When managing and outputting user data resources of different sizes, mobile communication terminals adopt a differentiated data splitting and then merging processing method, and combine it with artificial intelligence to simplify the complexity of processing, which can improve efficiency and user experience and be more flexible. When the data volume is large or the network conditions are not ideal, the differentiated data processing method can ensure processing efficiency, thereby optimizing the user experience.

[0039] A specific application example is given below:

[0040] When the actual usage is greater than the transmission power of the mobile communication terminal, the 10 split data segments are encapsulated through the transmission control protocol to avoid data loss during transmission, ensure reliable data transmission and the receiving end can correctly identify the corresponding data segment;

[0041] When 10 data segments are transmitted to the designated receiving end, the data is merged and the tail Y of the first data segment is 1 Respectively with the second data segment header X 2 Connect to merge and sort, the tail of the second data segment Y 2 Respectively with the third data segment header X 3 Connect, merge and sort until the end of the 9th data segment Y 9 and the 10th data segment header X 10Connect to merge and sort.

[0042] The technical features of the above embodiments may be arbitrarily combined (as long as there is no contradiction in the combination of these technical features). To make the description concise, not all possible combinations of the technical features in the above embodiments are described; these embodiments that are not explicitly written should also be considered to be within the scope of this specification.

Claims

1. A mobile communication terminal based on artificial intelligence, characterized in that: include: Data sensing module, processing module, power acquisition module, artificial intelligence module, filtering module and communication module; The data sensing module is used to collect data streams from mobile communication terminals in real time, accurately capture and integrate diversified network status information; The processing module is used to remove noise and process errors in real time on the data stream, and convert the diversified data stream into a standard data format through data conversion to ensure data standardization; The power acquisition module is used to capture the key parameters of the amplitude and frequency of the transmission signal in the communication network environment from the transmission link, and transmit the key parameters of the transmission signal to the artificial intelligence module; The artificial intelligence module is constructed by a deep learning neural network model and a data allocation module; The artificial intelligence module can analyze the bandwidth requirements and actual usage of key parameters, and binary encode the standardized data according to the actual usage and split it into n data segments, including the header X n and tail Y n , where n = 1, 2, 3, ... n; The filtering module is used to identify the merged and sorted data, effectively avoiding the propagation of erroneous data in the network; The communication module is used for data transmission and communication with external devices or networks, so that the mobile communication terminal can transmit sorted data in various communication scenarios.

2. The mobile communication terminal based on artificial intelligence according to claim 1, characterized in that: The data flow includes the size, transmission speed, transmission direction and communication network environment of the data.

3. The mobile communication terminal based on artificial intelligence according to claim 1, characterized in that: The deep learning neural network can provide real-time mobile communication terminal data tracking and prediction to the data perception module, predict the bandwidth resources occupied and consumed during the transmission process in the current time period and network environment, and analyze the data's demand for bandwidth and actual usage.

4. The mobile communication terminal based on artificial intelligence according to claim 3, characterized in that: When the actual usage is less than the transmission power of the mobile communication terminal, the data allocation module directly allocates the data to the communication module, thereby achieving efficient utilization of bandwidth resources and load balancing.

5. The mobile communication terminal based on artificial intelligence according to claim 3, characterized in that: When the actual usage is greater than the transmission power of the mobile communication terminal, the n split data segments are encapsulated through the transmission control protocol to avoid data loss during the transmission process, thereby ensuring reliable data transmission and the receiving end can correctly identify the corresponding data segment; When n data segments are transmitted to the designated receiving end, the data is merged. The tail Y1 of the first data segment is connected to the head X2 of the second data segment for merging and sorting. The tail Y2 of the second data segment is connected to the head X3 of the third data segment for merging and sorting. This continues until the tail Y of the n-1th data segment is connected to the head X4 of the third data segment. n-1 and the nth data segment header X n The data segments are connected to be merged and sorted to ensure the correct order and integrity of the data segments.

6. The mobile communication terminal based on artificial intelligence according to claim 1, characterized in that: The data allocation module can allocate data to different modules according to the size of the data after standardization and the current bandwidth resource data, thereby realizing a parallel data processing mechanism, optimizing resource utilization efficiency, and ensuring that data processing tasks can be executed quickly and evenly under limited bandwidth conditions.

7. The mobile communication terminal based on artificial intelligence according to claim 1, characterized in that: The data perception module includes a monitoring module and an interaction module.

8. The mobile communication terminal based on artificial intelligence according to claim 7, characterized in that: The monitoring module is used to collect data streams from mobile communication terminals in real time, including data size, transmission speed, transmission direction, and communication network environment; the interaction module interacts with the communication network to collect and analyze network usage of mobile communication terminals to obtain more comprehensive network status information.

Images