CN113254742A - Display device based on 5G deep learning artificial intelligence - Google Patents
Display device based on 5G deep learning artificial intelligence Download PDFInfo
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Abstract
The invention provides a display device based on 5G deep learning artificial intelligence, which is characterized in that the display device processes an acquired data set by adopting a deep learning algorithm to obtain a data set after deep learning processing, and then the display device displays functions after deep learning on the basis of the data set after deep learning processing, so that scenes and functions displayed by the display device are iterated and sublimated, and the display device is more intelligent and improves user experience.
Description
Technical Field
The invention relates to the technical field of exhibition and display equipment, in particular to a display device based on 5G deep learning artificial intelligence.
Background
With the advancement of science and technology, exhibition display devices such as government program houses and real estate sand trays are greatly developed. The sand table is a model piled up by silt, military chess and other materials according to a certain proportion relation according to a topographic map, an aviation photograph or a field topography.
In the traditional real estate sand table, under the condition of electrification, information such as buildings, roads, landforms and the like can be simulated through flickering of lamplight and corresponding modeling on the sand table, so that a user can visually observe the information and know the relevant conditions of the buildings and the periphery of the buildings.
Although the real estate sand table in the prior art can show relevant visual information to a user to a certain extent, the real estate sand table is relatively deficient in artificial intelligence and interaction with the user, and accordingly the user experience is poor.
Disclosure of Invention
The present invention aims to solve at least one of the above technical problems to at least some extent or to at least provide a useful commercial choice. Therefore, the invention aims to provide a display device based on 5G deep learning artificial intelligence, the display device processes the acquired data set by adopting a deep learning algorithm to obtain a data set after deep learning processing, and then the display device displays the function after deep learning on the basis of the data set after deep learning processing, so that the scene and the function displayed by the display device are iterated and sublimed, the display device is more intelligent, and the user experience is improved.
According to the display device based on the 5G deep learning artificial intelligence, the intelligent device comprises an original data acquisition module, a display module and a display module, wherein the original data acquisition module is used for acquiring original sample data of a region corresponding to the display device; the characteristic extraction module is used for extracting the characteristics of the original sample data by adopting a characteristic extraction algorithm so as to obtain characteristic sample data; the classification processing module is used for classifying the characteristic sample data through a data classification processing method to obtain a plurality of classification processing data sets; a function presentation module for presenting a function corresponding to at least one of the sorted processing data sets on the basis of the at least one sorted processing data set; and the deep learning module is used for processing at least one classification processing data set by adopting a deep learning algorithm to obtain a deep learning processing data set, and the function display module is also used for displaying the function corresponding to the deep learning processing data set on the basis of the deep learning processing data set.
According to the display device based on the 5G deep learning artificial intelligence, the display device processes the acquired data set by adopting a deep learning algorithm to obtain the data set after deep learning processing, and then the display device displays the function after deep learning on the basis of the data set after deep learning processing, so that the scene and the function displayed by the display device are iterated and sublimated, the display device is more intelligent, and meanwhile, the user experience is improved.
In addition, the display device based on 5G deep learning artificial intelligence according to the present invention may further have the following additional technical features:
the display device further comprises a cloud server, and the original data acquisition module, the feature extraction module, the classification processing module, the function display module and the deep learning module are respectively connected with the cloud server.
The original data acquisition module, the feature extraction module, the classification processing module, the function display module and the deep learning module are respectively communicated with the cloud server through 5G.
The cloud server includes a processor, a memory, and a network interface.
The display device is an intelligent transportation system display device, and the original sample data comprises traffic flow, time length of traffic lights, number of buses and number of taxis.
The display device is a smart community display device, and the original sample data comprises the number of residents, the age condition of the residents, the education condition of the residents and the water and electricity consumption condition.
The feature extraction algorithm adopts at least one of a convolutional neural network, a deep confidence network and a multilayer feedback cyclic neural network.
The data classification processing method adopts at least one of a classification data processing method, a sequencing data processing method, a fixed-distance data processing method and a fixed-ratio data processing method.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a block diagram of a 5G deep learning artificial intelligence based presentation device according to an embodiment of the present invention;
FIG. 2 is a block diagram of a display device based on 5G deep learning artificial intelligence according to another embodiment of the present invention; and
fig. 3 is a block diagram of a cloud server according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The invention provides a display device based on 5G deep learning artificial intelligence, which is characterized in that the display device processes an acquired data set by adopting a deep learning algorithm to obtain a data set after deep learning processing, and then the display device displays functions after deep learning on the basis of the data set after deep learning processing, so that scenes and functions displayed by the display device are iterated and sublimated, and the display device is more intelligent and improves user experience.
FIG. 1 is a block diagram of a 5G deep learning artificial intelligence based presentation device according to an embodiment of the present invention; FIG. 2 is a block diagram of a display device based on 5G deep learning artificial intelligence according to another embodiment of the present invention; fig. 3 is a block diagram of a cloud server according to an embodiment of the present invention. Referring to fig. 1 to 3, the present invention provides a display device based on 5G deep learning artificial intelligence, which includes an original data acquisition module 10, a feature extraction module 20, a classification processing module 30, a function display module 40, and a deep learning module 50.
The original data obtaining module 10 is configured to obtain original sample data of an area corresponding to the display device. Specifically, the function display of the display device depends on original sample data of a certain area, and the display device displays corresponding functions by processing all the original sample data in the corresponding area on the basis of the original sample data; in this embodiment, the original data obtaining module 10 obtains all original sample data of the area corresponding to the display device, and summarizes the original sample data.
The feature extraction module 20 is connected to the original data acquisition module 10, and the feature extraction module 20 is configured to perform feature extraction on the original sample data by using a feature extraction algorithm to obtain feature sample data. Specifically, the original sample data acquired by the original data acquisition module 10 has a large quantity and contains more noise useless data, and the feature extraction module 20 performs filtering processing steps such as normalization and denoising on the original sample data acquired by the original data acquisition module 10 by using a feature extraction algorithm, so as to obtain more concentrated and clean feature sample data. Generally, the feature extraction module 20 may adopt one feature extraction algorithm or adopt several feature extraction algorithms in a fusion manner to perform feature extraction on the original sample data.
The classification processing module 30 is connected to the feature extraction module 20, and the classification processing module 30 is configured to perform classification processing on the feature sample data by using a data classification processing method to obtain a plurality of classification processing data sets. Specifically, after the feature extraction module 20 performs the feature extraction operation on the original sample data acquired by the original data acquisition module 10 to obtain the feature sample data, the feature sample data at this time is not classified, and the classification processing module 30 is configured to perform induction and classification processing on the feature sample data; generally, the classification processing module 30 may employ one or more data classification processing methods to classify and summarize the feature sample data, so as to obtain a plurality of classification processing data sets, wherein each classification processing data set is independent from other classification processing data sets.
A function presentation module 40 is connected to the classification processing module 30, and the function presentation module 40 is configured to present a function corresponding to at least one of the classification processing data sets based on the at least one of the classification processing data sets. Specifically, after the classification processing module 30 performs classification processing on the feature sample data to obtain a plurality of classification processing data sets, the function display module 40 constructs the function module of the display device of the present invention based on one or more classification processing data sets, and displays functions corresponding to the one or more classification processing data sets.
The deep learning module 50 is configured to process at least one of the classification processing data sets by using a deep learning algorithm to obtain a deep learning processing data set, and the function presentation module is further configured to present a function corresponding to the deep learning processing data set based on the deep learning processing data set. Specifically, the deep learning module 50 uses the classification processing data set as a research object, for example, the deep learning module 50 performs corresponding processing on one classification processing data set or a plurality of classification processing data sets to obtain a data set after deep learning processing, after the function display module 40 receives the data set after deep learning processing, the function display module 40 constructs a function of the display device corresponding to the data set after deep learning processing based on the data set after deep learning processing, and displays the function corresponding to the deep learning processing set, so that the scenes and functions displayed by the display device are iterated and sublimated, the scenes and functions displayed by the display device are more intelligent, and the user experience is improved.
According to the display device based on the 5G deep learning artificial intelligence, the display device processes the acquired data set by adopting a deep learning algorithm to obtain the data set after deep learning processing, and then the display device displays the function after deep learning on the basis of the data set after deep learning processing, so that the scene and the function displayed by the display device are iterated and sublimated, the display device is more intelligent, and meanwhile, the user experience is improved.
In specific implementation, referring to fig. 2, the display apparatus based on 5G deep learning artificial intelligence further includes a cloud server 60, and the raw data obtaining module 10, the feature extracting module 20, the classification processing module 30, the function displaying module 40, and the deep learning module 50 are respectively connected to the cloud server, that is, the raw data obtaining module 10, the feature extracting module 20, the classification processing module 30, the function displaying module 40, and the deep learning module 50 are all connected to the cloud server 60. The cloud server 60 is a simple, efficient, safe, reliable, and flexible computing service, and its management is simpler and more efficient than a physical server. In an embodiment of the present invention, referring to fig. 3, the cloud server 60 includes a processor 61, a memory 62, and a network interface 63.
In specific implementation, the raw data acquiring module 10, the feature extracting module 20, the classification processing module 30, the function exhibiting module 40 and the deep learning module 50 pass through 5G (5G)thGeneration Mobile Communication Technology; fifth-generation mobile communication technology) to communicate with the cloud server 60, respectively. According to the display based on the 5G deep learning artificial intelligence, the communication between each functional module and the cloud server 60 is realized by adopting 5G, so that the advantages of high speed, low time delay and large connection are realized, and the user experience is further improved.
In one embodiment, the display device is an intelligent transportation system display device, and the original sample data is the traffic flow, the traffic light duration, the number of buses and the number of taxis. Specifically, in this embodiment, the display device is an intelligent transportation system display device as an example, and the original sample data includes a transportation data set of an area covered by the intelligent transportation system, including but not limited to traffic flow, time length of traffic lights, number of buses, number of taxis, number of private cars, time period of congestion, time length of congestion, and the like. Specifically, in this embodiment, the intelligent transportation system display device can display the traffic jam condition of the city based on the traffic data set; and the deep learning module 50 of the intelligent traffic system display device can also process the traffic data set by utilizing a deep learning algorithm, so as to obtain the traffic data set after the deep learning processing, and further recalculate the urban traffic jam condition based on the traffic data set after the deep learning processing, and meanwhile, the function display module 40 of the intelligent traffic system display device can also display the urban traffic jam condition calculated based on the traffic data set after the deep learning processing, so as to display the traffic condition more intelligently, and improve the user experience.
In another embodiment, the display device is a smart community display device, and the original sample data includes the number of residents, the age condition of the residents, the education condition of the residents, and the water and electricity consumption condition. Specifically, in this embodiment, the display device is an intelligent community display device as an example; the original sample data comprises information of related personnel and energy consumption data in the smart community, including but not limited to population number of residents, age composition of the residents, sex composition of the residents, education condition of the residents, working condition of the residents, household water, electricity and gas consumption condition, public water and electricity consumption quantity of the community and the like. Specifically, in this embodiment, the display device of the smart community can display the energy consumption status of the smart community based on the personnel information and the energy consumption data set; and this wisdom community display device's deep learning module 50 can also utilize the deep learning algorithm to the above-mentioned personnel information, the energy consumption data set is handled, thereby obtain the personnel information after the deep learning is handled, the energy consumption data set, and then with the personnel information after this deep learning is handled, the energy consumption data set is the basis to recalculate the energy consumption situation, simultaneously wisdom community display device's function display module 40 can also show the personnel information after this deep learning is handled, the energy consumption data set is the energy consumption situation after the basis calculates, can directly perceivedly see out this wisdom community's energy consumption trend, the distribution of energy consumption family situation etc. thereby can for the family user recommends the concrete suggestion of the wrong peak energy of using intelligently, user experience is better.
In a specific implementation, the feature extraction algorithm adopts at least one of a convolutional neural network, a confidence network and a multi-layer feedback cyclic neural network. Specifically, a Convolutional Neural Network (CNN) is a type of feed-forward Neural network that includes convolution calculation and has a deep structure, and the Convolutional Neural network has a characterization learning capability and can perform stable classification on input information according to its hierarchical structure. The convolutional neural network is constructed by imitating a visual perception mechanism of a living being, and can be used for supervised learning and unsupervised learning, and the parameter sharing of convolution kernels in hidden layers and the sparsity of interlayer connection enable the convolutional neural network to learn lattice characteristics such as pixels and audio with small calculation amount, have stable effect and have no additional characteristic engineering requirement on data.
A Deep Belief Network (DBN) is a generative model, and training data can be generated by the whole neural Network according to the maximum probability by training the weights among neurons.
The multilayer feedback cyclic Neural Network (RNN) is an artificial Neural Network with nodes directionally connected into a ring, the internal state of the Network can show dynamic time sequence behaviors, and the internal memory of the Network can be used for processing input sequences with any time sequence, so that the input sequences such as non-segmented handwriting recognition, voice recognition and the like can be processed more easily.
In this embodiment, the feature extraction module 20 performs calculation processing on the original sample data by using a convolutional neural network, a confidence network, and a multi-layer feedback cyclic neural network at the same time, so as to obtain more accurate and efficient feature sample data.
In a specific implementation, the data classification processing method adopts at least one of a fixed class data processing method, a sequencing data processing method, a fixed distance data processing method and a fixed ratio data processing method. Specifically, the method for processing the classified data is the lowest layer of the data, the data is classified according to the class attributes, the classes are in an equal parallel relation, the data does not have quantity information, and the data cannot be sorted among the classes. The sequencing data processing method is an intermediate level of data, and sequencing data can not only divide the data into different categories, but also can compare the advantages and disadvantages among the categories through sequencing. In the distance data processing method, the distance data is an actual measurement value with a certain unit, so that the difference between two variables can be known, and the actual difference between the variables can be accurately calculated through addition and subtraction. In the fixed ratio data processing method, the fixed ratio data is the highest grade of the data, the data expression form of the fixed ratio data is the same as the fixed distance data and is the actual measurement value, and the fixed ratio data can be compared in size and subjected to addition and subtraction operation and multiplication and division operation.
In this embodiment, the classification processing module 30 of the presentation apparatus simultaneously adopts four processing methods, i.e., a classification data processing method, a sequencing data processing method, a fixed-distance data processing method, and a fixed-ratio data processing method, so that a plurality of more accurate and direct classification processing data sets can be obtained.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made in the above embodiments by those of ordinary skill in the art without departing from the principle and spirit of the present invention.
Claims (8)
1. The utility model provides a display device based on artificial intelligence of 5G degree of deep learning which characterized in that includes:
the original data acquisition module is used for acquiring original sample data of the area corresponding to the display device;
the characteristic extraction module is used for extracting the characteristics of the original sample data by adopting a characteristic extraction algorithm so as to obtain characteristic sample data;
the classification processing module is used for classifying the characteristic sample data through a data classification processing method to obtain a plurality of classification processing data sets;
a function presentation module for presenting a function corresponding to at least one of the sorted processing data sets on the basis of the at least one sorted processing data set; and
the deep learning module is used for processing at least one classification processing data set by adopting a deep learning algorithm to obtain a deep learning processing data set, and the function display module is also used for displaying the function corresponding to the deep learning processing data set on the basis of the deep learning processing data set.
2. The display device based on 5G deep learning artificial intelligence according to claim 1, further comprising a cloud server, wherein the raw data acquisition module, the feature extraction module, the classification processing module, the function display module and the deep learning module are respectively connected to the cloud server.
3. The display device based on 5G deep learning artificial intelligence according to claim 2, wherein the raw data acquisition module, the feature extraction module, the classification processing module, the function display module and the deep learning module are respectively in communication with the cloud server through 5G.
4. The 5G deep learning artificial intelligence-based presentation device of claim 2, wherein the cloud server comprises a processor, a memory and a network interface.
5. The display device based on 5G deep learning artificial intelligence of claim 1, wherein the display device is an intelligent transportation system display device, and the original sample data comprises traffic flow, length of time of traffic lights, number of buses and number of taxis.
6. The display device based on 5G deep learning artificial intelligence of claim 1, wherein the display device is a smart community display device, and the original sample data comprises the number of residents, the age condition of the residents, the education condition of the residents, and the water and electricity consumption condition.
7. The 5G deep learning artificial intelligence-based presentation device according to any one of claims 1-6, wherein the feature extraction algorithm employs at least one of a convolutional neural network, a deep confidence network, and a multi-layer feedback cyclic neural network.
8. The display device based on 5G deep learning artificial intelligence according to any one of claims 1-6, wherein the data classification processing method adopts at least one of a fixed class data processing method, a sequencing data processing method, a fixed distance data processing method and a fixed ratio data processing method.
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