DE102021213207A1 - Data transmission device, data transmission arrangement and method for data transmission, computer program and storage medium - Google Patents

Abstract

Data transmission device 2, wherein the data transmission device 2 is provided with an input signal 4, with an analysis module 7, wherein the analysis module 7 is designed to determine analysis data 8 based on an analysis of the input signal 4, the analysis data 8 forming a time series (19), with a Transfer module 12 and an aggregation module 9 for determining aggregation data 11, with the aggregation module 9 being provided with the analysis data 8 and the aggregation module 9 being designed to aggregate analysis data 8 as the aggregation data 11 until a target size is reached and to aggregate the aggregation data 11 when the target size is reached Provide transfer module 12, with a rating module 10, the rating module 10 being designed to determine a relevance for the analysis data 8, the rating module 10 being designed to prematurely send the analysis data 8 and/or aggregation data 11 for analysis data 8 having a threshold value relevance the transfer module 12 to cause.

Description

State of the art

The invention relates to a data transmission device, wherein the data transmission device is provided with an input signal and the data transmission device has an analysis module, a transfer module and an aggregation module.

The efficient transmission of data often uses coding methods and algorithms. In this case, original data is compressed either without loss or with the acceptance of a loss. For example, compression methods are known in which a first method step compresses data by mapping to an existing domain. The differences resulting from this, in particular called residual differences, are encoded and/or compressed separately. A decoder can reconstruct the original input data by transmitting the domain-specifically compressed data and the residual data, which in particular are compressed separately.

In particular, such methods and/or algorithms are used in the transmission of multimedia data, e.g. for the transmission of video and/or image data.

For example, the reference describes DE 10 2018 208 058 A1 a method for detecting an anomaly in a signal, two mapping matrices being determined which describe a normal and an abnormal course of the signal. A third mapping matrix is determined from the two matrices, and a combined coefficient vector of the signal is reconstructed based on the third mapping matrix.

Disclosure of Invention

A data transmission device with the features of claim 1 is proposed. Furthermore, a data transmission arrangement, a method for data transmission, a computer program and a storage medium with the computer program are proposed. Preferred and/or advantageous embodiments result from the dependent claims, the description and the accompanying figures.

A data transmission device is proposed. The data transmission device is preferably a hardware device; alternatively, the data transmission device is embodied as a software device and/or a software module. The data transmission device is designed in particular to transmit metadata, in particular metadata based on an input signal. The data transmission device is used for the compressed, encoded and/or encrypted transmission of data. In particular, the data transmission device can be integrated into a sensor unit, for example into a camera. Alternatively, the data transmission device can form a camera or a sensor device.

An input signal is provided to the data transmission device. In particular, the data transmission device itself can be designed to receive and/or provide the input signal. For example, the data transmission device forms a camera for recording images and/or a video, with the images and/or the video forming the input signal. In particular, the input signal is provided to the data transmission device continuously and/or discontinuously, for example cyclically and/or with a frame rate or sampling rate. For example, the input signal is obtained by sampling a measured variable. The input signal preferably comprises and/or forms image data, in particular a video. Alternatively, the input signal can include or form an audio signal, a physical quantity, mechanical quantity, chemical quantity. In particular, the input signal includes or forms a data stream of different data.

The data transmission device includes an analysis module. The analysis module can be designed as a hardware or as a software module. For example, the analysis module includes and/or forms a computer module and/or a processor module. In particular, the input signal is made available to the analysis module. The analysis module is designed to evaluate and/or analyze the input signal. The analysis module determines analysis data based on the analysis and/or the evaluation of the input signal. In particular, the analysis data is determined continuously, regularly and/or at fixed time intervals by the analysis module. For example, the input signal is provided regularly and/or continuously, with the input signal provided being processed into analysis data in each case. For example, the analysis module includes analysis applications and/or an analysis application. In particular, the analysis applications can be exchanged, installed, selected, supplemented and/or parameterized. For example, the analytics applications are available, obtainable, and/or downloadable from an app store.

The analysis applications are used, for example, by the analysis module to carry out the analysis of the input signal and/or to provide it of the analysis data and/or applied to the input signal. The analysis data preferably form and/or describe a time series. For example, analysis data and/or an analysis date is determined at regular intervals, for example in milliseconds or microseconds, based on the current input signal, so that analysis data that varies over time can also be expected with an input signal that varies over time. A time series of the analysis data is understood to mean, for example, a change in the analysis data and/or the content of the analysis data over time. The analysis data can form and/or include a time profile of a signal, for example a signal value at any point in time. In particular, the analysis data form and/or describe a function and/or a dependency of a location or a physical variable. Alternatively and/or additionally, the analysis data are metadata and/or data that include a feature vector or a feature matrix.

The data transmission device comprises a transfer module and an aggregation module, with the two modules forming hardware modules or software modules. In particular, the transfer module is connected to the aggregation module in terms of data technology, with the aggregation module being connected to the analysis module in terms of data technology.

The analysis data is provided to the aggregation module. In particular, the analysis data are made available to the aggregation module immediately after their determination. In particular, the time series of the analysis data is made available to the aggregation module. The aggregation module is designed to determine aggregation data. The aggregation data includes the analysis data, in particular part of the analysis data. In particular, the aggregation data have a target size, for example a data size and/or a format as the target size. Specifically, the aggregation data includes a header.

The aggregation module is designed to aggregate the analysis data and/or combine them as a data package, with analysis data being aggregated and/or combined into a package and/or as aggregation data until the target size is reached. In other words, the aggregation module adds analysis data to a data package, the aggregation data, until the data package has reached the target size and/or target quantity, with the aggregation module generating, starting and/or determining a new data package as aggregate data when the target size is reached. Furthermore, the aggregation module is designed to make the data packet available to the transfer module as the aggregation data when the target size is reached. In particular, the aggregation module can be understood as a kind of buffer between the analysis module and the transfer module, which packs the analysis data into defined and/or standardized aggregation data and makes this, or the analysis data contained therein, available to the transfer module.

The transfer module is designed and/or set up to provide the provided aggregation data to a recipient and/or to send it to the recipient. In particular, the aggregation data are transmitted and/or made available to the recipient wirelessly, for example by radio. In particular, the transfer module is designed to provide the aggregation data to the recipient and/or to send them to the recipient when they are provided by the aggregation module.

The data transmission device includes a rating module, it being possible for the rating module to be in the form of a hardware or software module. The analysis data is provided to the rating module. In particular, it can be provided that the rating module is provided with the input signal. The rating module is designed to evaluate the analysis data and/or to determine a relevance for the analysis data. The relevance can in particular represent a measure. For example, the relevance describes an importance of the analysis data in the total amount of analysis data and/or a time interval of the analysis data. For example, the relevance describes how the respective, currently available analysis date fits into and/or deviates from the time series of the analysis data. The relevance can in particular represent a continuous variable, alternatively the relevance describes a discontinuous variable, for example a digital variable, in particular “0” for not relevant and “1” for relevant.

The rating module is designed to provide analysis data that have a relevance equal to or greater than a threshold relevance for early and/or immediate provision and/or sending to the recipient. The threshold relevance is in particular also called minimum relevance, the threshold relevance describing, for example, a relevance and/or a rating of the analysis data, in particular in relation to and/or relative to other analysis data and/or the time series. The threshold value relevance is in particular selected and/or arranged in such a way that analysis data with an increased deviation and/or analysis data required for evaluation and/or reconstruction have a relevance greater than or equal to the threshold value relevance. The threshold value relevance can in particular be user-defined. For example, the rating module is designed to cause and/or trigger that the analysis data having at least the threshold value relevance are sent by the transfer module to the recipient or are provided to the recipient. Alternatively and/or additionally, the transfer module is designed to cause the aggregation data, including the analysis data with the relevance of the threshold value, to be sent or provided prematurely, i.e. before the target value is reached, for example to cause the aggregation module to prematurely end the aggregation of the analysis data into the aggregation data and provides the aggregation data to the transfer module.

The invention is based on the consideration that data having a certain size and/or a certain format can be encoded and/or compressed more efficiently since, for example, the size and format is tailored and/or optimized for the compressed algorithm. By providing a rating module according to the invention, which evaluates how relevant analysis data that is to be added to the aggregation data, it can be avoided that very important and/or relevant data is transmitted with a delay, since it is not necessary to wait for such data until the target size of the aggregation data is reached.

The transfer module is particularly preferably designed and/or set up to compress and/or encode the aggregation data. In particular, the transfer module is designed to provide the compressed and/or encoded aggregation data to the recipient and/or to send it to the recipient. In particular, the transfer module is designed to send and/or provide the aggregation data in encrypted and/or cryptographic form to the recipient, for example based on keys and/or certificates exchanged between the transfer module and recipient.

One embodiment of the invention provides that the aggregation module is designed and/or set up to only provide the aggregation data to the transfer module for analysis data that has a relevance unequal to or less than the threshold value once the target size and/or target quantity has been reached. In particular, the aggregation module is designed and/or set up to add analysis data that has a relevance equal to or greater than the threshold relevance to the aggregation data and immediately, in particular without adding further analysis data, the aggregation data, in particular before the target size and/or the target quantity is reached provide the transfer module. This configuration is based on the consideration that the usual analysis data has an average relevance or a relevance lower than the threshold relevance and it is sufficient to send this analysis data regularly with the aggregation data and/or to make it available externally, so that it can be waited until the desired size and/or format of the aggregation data is reached. For analysis data that seems particularly relevant, in particular that exceeds and/or has the threshold value relevance, the aggregation data is provided to the transfer module immediately and before the target size is reached and is sent and/or provided externally. Based on the relevance of the respective analysis data and the relevance of the threshold value, a decision can be made as to whether the aggregation data should be provided before the target size is reached and thus at the expense of less efficiency in compression or coding, or whether one can wait until the target size is reached becomes. In particular, the relevance is designed as an aggregated relevance, e.g. if several data items are recognized with a medium but higher than average relevance, so that the decision cannot only be dependent on a single relevance, but can also be based on the sum of the relevance in can refer to the aggregation data.

In particular, it is provided that the rating module is designed to determine the relevance based on an anomaly analysis. In particular, the anomaly analysis is applied to the analysis data. In this case, an anomaly in the analysis data, in particular in the time series of the analysis data, is determined. For example, an anomaly can be understood as a deviation from an expected course of the analysis data and/or the time series. The anomaly can be determined in particular on the basis of analysis data recorded previously. For example, the rating module includes a neural network for determining the anomaly and/or for carrying out the anomaly analysis.

It is particularly preferred that the rating module has a prediction module. The prediction module is designed and/or set up to determine and/or carry out an analysis data prediction for the analysis data and/or specifically for the time series of the analysis data. For example, the analysis data prediction describes an expected course of the analysis data based on the preceding analysis data. For example, for analysis data, a statistical distribution around a mean is expected, so that the analysis data prediction describes and/or includes, for example, a mean and standard deviation. In particular, the analysis data prediction is based on a model and/or a simulation, in particular a physical model, a mechanical model, a sociological model and/or any model for describing the time series of the analysis data and/or the analysis data. In particular, the analysis data prediction is based on a neural network and the application of the neural network to the analysis data and/or the time series of the analysis data. The rating module is designed to determine a deviation of the analysis data and/or the time series of the analysis data from the analysis data prediction, with the relevance being ascertained and/or determined on the basis of the deviation. For example, analysis data that exhibit a deviation greater than a usual and/or expected deviation from the analysis data prediction is determined as analysis data having a relevance greater than or equal to the threshold value relevance.

It is optionally provided that the input signal includes image data and/or a video. The analysis module is designed, for example, to determine object tracking, a path and/or a trajectory of one or more objects based on the image data and/or the video as analysis data. For example, the analysis data prediction describes an expected trajectory and/or movement of the tracked object based on the previously collected and/or recorded analysis data. If the movement, trajectory and/or tracking of the analysis data based on the current analysis data deviates from the analysis data predictions, this analysis data is determined and/or selected as analysis data having the threshold value relevance.

One embodiment of the invention provides that the data transmission device has and/or includes a selection module. The selection module is designed and/or set up to select a preselection of analysis data for aggregation. In particular, the preselection forms a subset of analysis data. Based on the pre-selection made, the prediction module determines a certainty statement. As a statement of certainty, it is determined and/or determined, for example, how precisely and/or reproducibly the time series of the analysis data can be reconstructed and/or described based on the preselection made. The determined statement of certainty for the pre-selection made is made available to the selection module. The selection module is designed and/or set up to adjust, refine and/or coarsen the preselection based on the certainty statement. For example, the selection module adds further analysis data to the preselection or removes analysis data that has already been added from the preselection. For example, the selection module selected too few analysis data as a preselection, so that based on this preselection, the time series of the analysis data can only be reconstructed with great errors, so that the selection module adds further analysis data to the preselection, so that the time series of the analysis data can be reconstructed better. On the other hand, a large number of analysis data can have been preselected by the selection module, for example, so that the time series of the analysis data can be reconstructed almost exactly based on this preselection, so that if a certain error is accepted, even analysis data can be deleted from the preselection.

The selection module preferably has an adjustable resolution. The resolution describes, for example, whether an error in the reconstruction of the time series of the analysis data is accepted and/or the maximum size of this error, for example what deviation is accepted in the statement of certainty. The selection module is designed and/or set up to carry out and/or adapt the preselection of the analysis data based on the adjustable resolution. For example, the adjustable resolution can be increased by a user or an application, so that analysis data can be deleted from the preselection.

In particular, it is provided that the rating module is designed and/or set up to determine a reconstructed time series of the analysis data based on the preselection and/or the preselection made. In other words, the rating module is designed and/or set up to reconstruct the course of the analysis data and/or the time series of the analysis data by means of the preselection. Furthermore, in this refinement, the rating module is designed to determine a deviation between the reconstructed time series of the analysis data and the time series of the analysis data. Based on this determined and/or determined deviation, the selection module is designed to refine and/or adapt the preselection of the analysis data, for example to add further analysis data to the preselection and/or to remove analysis data from the preselection, in particular until a desired deviation and/or accuracy is achieved. For example, if the deviation is greater than a maximum deviation, further analysis data are added to the preselection, and if the reconstruction accuracy falls below a minimum, analysis data are removed from the preselection. In particular, it is provided that when adding and/or removing analysis data for the pre-selection, the pre-selection obtained from this is again made available to the rating module, which, based on this, determines the reconstructed time series and also the Deviation between this obtained reconstructed time series and the time series of the analysis data is determined. In particular, the rating module and the selection module are connected for iteration and/or as a control loop.

A further object of the invention is a data transmission arrangement. The data transmission arrangement comprises the data transmission device and at least one receiving unit as receiver. The receiving unit has an evaluation unit, which can be designed as a hardware or software module. The recipient is provided with the aggregation data, in particular provided by the transfer module. The evaluation unit is designed to store, further process, decompress and/or decode the aggregation data. In particular, the evaluation unit is designed to provide the aggregation data to additional modules and/or to store the analysis data comprised by the aggregation data and/or to provide additional modules.

The data transmission arrangement includes a client module. The client module forms a sensor module, for example, in particular a surveillance camera. The client module includes the analysis module, the rating module, the selection module and/or the transfer module. In particular, the evaluation unit of the receiving module includes a compression module, the compression module being designed to compress and/or encode the aggregation data provided.

For example, in this embodiment, the transfer module in the client module is designed to provide and/or send the aggregation data uncompressed and/or uncoded, with the compression and coding taking place in the client module for the purpose of storage. This refinement is based on the consideration that client modules with little computing power can be used in this way, since the computationally intensive compression and coding are carried out in the receiver unit, for example a cloud.

It is particularly preferred that the client module includes the selection module or a further selection module. The selection module of the client module is designed to select analysis data as a compression selection based on the aggregation data provided. The selection module is designed to add further analysis data to the compression selection or to remove analysis data from the compression selection until the time series of the analysis data can be reconstructed based on the preselection, in particular the preselection of the prediction module.

A further subject matter of the invention is a method for data transmission. An analysis is applied to a provided and/or recorded input signal, as a result of which analysis data are determined and/or obtained. The analysis data describe and/or form a time series. The obtained and/or determined analysis data is aggregated, put together and/or packed into aggregation data. The aggregation data includes a plurality of the analysis data. In particular, the aggregation data include a target size and/or should have a target size. In particular, as much analysis data is added to the aggregation data and/or as much is aggregated until the target size is reached. When the target size is reached, the aggregation data is provided to a recipient and/or sent to the recipient. The analysis data are also evaluated and/or analyzed to determine a relevance, a distinction being made in particular between a relevance that is less than a threshold value relevance and a relevance that has or exceeds the threshold value relevance. Analysis data that are relevant to the threshold value are provided and/or sent to the recipient before the target size of the aggregation data is reached, with the aggregation of the analysis data to form the aggregation data being canceled and/or terminated before the target size is reached, and the analysis data accredited up to that point as aggregation data provided to and/or sent to the recipient.

A further subject matter of the invention is a computer program comprising instructions which cause the data transmission device and/or the data transmission arrangement to carry out the method steps of the method for data transmission.

Furthermore, the invention relates to a computer-readable medium on which the computer program is stored.

• 1 schematische Ansicht eines Ausführungsbeispiels einer Datenübertragungsanordnung;
• 2 Beispiel einer Zeitreihe von Analysedaten;
• 3 Ausführungsbeispiel einer Datenübertragungsanordnung mit einem Vorhersagemodul;
• 4 Ausführungsbeispiel einer Datenübertragungsanordnung mit einem Auswahlmodul;
• 5 Ausführungsbeispiel einer Datenübertragungsanordnung mit Kompression im Empfangsmodul;

Further advantages, effects and configurations result from the accompanying figures and their description. show:

• 1 schematic view of an embodiment of a data transmission arrangement;
• 2 Example of a time series of analysis data;
• 3 Embodiment of a data transmission arrangement with a prediction module;
• 4 Embodiment of a data transmission arrangement with a selection module;
• 5 Embodiment of a data transmission arrangement with compression in the receiving module;

1 shows an embodiment of a data transmission arrangement 1 with a data transmission device 2 and a receiving module 3 as a receiver. The data transmission device 2 is provided with an input signal 4, for example a video. The input signal 4 has, in particular, a change over time. In particular, applications 5 can be obtained from a third party, for example an app store, which include application modules 6 a to 6 c and are designed for storage and/or execution on the data transmission device 2 or the data transmission arrangement 1 .

The data transmission device 2 has an analysis module 7 . For example, an application module 6c is run as a software component on the analysis module 7 for the analysis. The input signal 4 is provided to the analysis module 7 and is evaluated and/or analyzed by it in an analysis, with analysis data 8 being ascertained and/or determined based on the analysis, in particular continuously. For example, the analysis is carried out for data points of the input signal 4, for example for each image of the video, and analysis data 8 is provided, so that a stream of analysis data 8 is obtained and determined.

The data transmission device 2 comprises an aggregation module 9 and a rating module 10. The analysis data 8 are provided to the aggregation module 9 and the rating module 10. The aggregation module 9 is designed to determine aggregation data 11, the aggregation data 11 comprising a collection of analysis data 8 and/or analysis data of a specific time interval. In particular, the aggregation module 9 is designed to determine aggregation data 11 in a specific format and/or specific size, for example the target size, with this being coordinated with the transmission and/or compression of the aggregation data, for example, in order to be able to carry this out particularly efficiently. The aggregation module 9 adds as much analysis data 8 to the aggregation data 11 until the target size is reached. If the target size is reached, this aggregation data 11 is made available to a transfer module 12 . The aggregation module 9 then begins to determine new aggregation data 11, in particular until the target size is reached again.

The rating module 10 is designed to evaluate the analysis data 8 and to determine a relevance. The relevance describes, for example, how important the available analysis data is in comparison to previous and/or other analysis data 8, for example how they fit into the time profile of the analysis data 8. If the rating module 10 determines for analysis data 8 that these have a relevance greater than or equal to a threshold relevance, the rating module 10 causes the early transmission of the aggregation data by the transfer module by triggering 13 . For example, the triggering 13 takes place in the form that the aggregation module 9 makes the aggregation data 11 available to the transfer module 12 ahead of time and starts determining new aggregation data 11, in particular before the target size of the aggregation data 11 is reached. In particular, the transfer module 12 is designed to compress the aggregation data 11 and make it available to the receiving module 3 as a compressed data stream 14 .

The receiving module 3 includes an evaluation unit 15 , the evaluation unit 15 having a memory module 16 , a compression module 17 and a processing module 18 . Storage module 16 is designed to store the received compressed aggregation data, in particular data stream 14, with compression module 17 being designed to decompress and/or decode compressed aggregation data 11, with the decompressed and/or decoded aggregation data being sent to processing module 18 be made available for further use and/or evaluation.

In particular, it is provided that the applications 5 that can be obtained for the application module 6 c as analysis software have a decompression module as the application module 6 a. In particular, the applications 5 include an application module 6b as a rating module which, for example, carries out ratings and/or assessments based on the analysis data 8 .

2 shows an exemplary embodiment of a time series 19 of analysis data 8 with analysis data points 20 drawn in. The analysis data 8 describe here, for example, the position of a falling feather over the ground, which was determined based on the input signal 4 including a video. The height above the ground h is plotted against the time t. An analysis data forecast 21 is also drawn in, which describes the expected height over time. This is determined based on a simulation and/or a physical model, for example. The rating module 10 is designed to determine for the analysis data 8 or the analysis data points 20 a and 20 b whether these are rated as abnormal and deviate too much from the usual data 20 or the analysis data prediction 21 . This analysis data 8, belonging to the analysis data points 20 a and 20 b have a relevance greater than or equal to the threshold relevance and are transmitted early.

3 shows an embodiment of a data transmission system 1, which is essentially based on the embodiment 1 is based on the evaluation unit 5 of the receiving module 3 having a prediction module 21 . The prediction module 21 is designed to determine an analysis data prediction based on the decompressed application data, in particular the analysis data 8 comprised of the aggregation data 11 . The analysis data prediction describes a reconstruction of the time series of the analysis data 8 and is provided to the processing module 18 . To determine the analysis data prediction, the prediction module 22 executes the application module 6e, which was obtained in the application 5 in the app store.

The rating module 10 also carries out an analysis data prediction, in particular based on the same application module 6e. For this purpose, the rating module 10 is provided with the decompressed and/or decoded analysis data as a data stream 23 . Based on the analysis data prediction 22, the analysis data 8 and the data stream 23, the rating module 10 determines the relevance of the respective analysis data 8, for example based on the deviation of the analysis data prediction. If the rating module 10 determines that the analysis data 8 has a relevance greater than or equal to the threshold relevance, the triggering 13 takes place to cause the early provision and/or the sending of the aggregation data 11 to the recipient 3.

4 shows an embodiment of a data transmission system 1, that based on the embodiment 1 and 3 is. In this case, instead of the transfer module 12, the data transmission device 2 comprises an extended transfer module 24 comprising a compression module 25 and a selection module 26. The analysis module 7 is again designed to determine the analysis data 8 based on the input signal 4. The analysis data 8 are made available to the rating module 10 and saved in a temporary storage module 25 . The analysis data 8 are made available to the extended module 24 or the selection module 26 . The rating module 10 is designed to prematurely transmit analysis data 8 having a relevance greater than or equal to the threshold value relevance, in particular to trigger the module 24 to transmit, send and/or provide the receiving module 3 early.

The selection module 26 is designed to make a preselection 27 for the analysis data 8 provided, in particular the analysis data with a lower relevance than the threshold value relevance. The pre-selection 27 includes selected analysis data 8, in particular selected based on the analysis data prediction 21. The compression module 25 is designed to determine compressed aggregation data 14. For this purpose, based on the pre-selection 27, in particular using the pre-selection 27 as analysis data 8 of the aggregation data 11, data compression is carried out. The data compression in the compression module 25 forms in particular a delta coding, with a residue 28 being determined as the difference between the compressed data and the original data. The residue 28 is made available to the selection module 26, the selection module 26 being designed to adapt the preselection 27, in particular to iteratively adapt it, based on the residues, e.g. as a measure of the deviation of the compressed data from the original data. If a desired accuracy is achieved, the aggregation data 11 from the last iteration and/or the data to be compressed from the last iteration are made available to a further memory module 30, stored there and made available to the selection module 26 and the rating module 10. The compressed aggregation data 14 are made available to the receiving module 3 and processed there for further use as explained. In particular, the application 5 includes an application module 6f, which is executed as a preselection 27 by the selection module 26 for the selection of the analysis data 8 .

5 shows an exemplary embodiment of a data transmission arrangement 1, in which the modules, in particular the selection module 26 and the compression module 25, are otherwise distributed between the data transmission device 2 and the receiving module 3.

The data transmission device 2 includes the analysis module 7, the rating module 10, the aggregation module 9 and the transfer module 12 and is designed to provide the aggregation data 11 to the receiving module 3 based on the input signal 4 . For this purpose, the receiving module 3 comprises a buffer module 31 which temporarily stores the aggregation data 11 provided, in particular the analysis data 8 contained therein, and provides the aggregation data 11 to the selection module 26 . The selection module 26 is combined with the compression module 25 to form a logical unit 32 that is designed iteratively to determine a data basis for compression data 32 . The selection module 26 selects a pre-selection 27 from the analysis data 8 , in particular from the aggregation data 11 , and makes this available to the compression module 25 , compresses this data and determines a residue 28 which is made available to the selection module 26 is posed. The selection module 26 is designed, based on the residue 28 and the preselection 27, to correct and/or change the preselection 27 if necessary, for example to add or delete further analysis data 8 . If the pre-selection 27 has been made according to the criteria, this pre-selection is used by the compression module 25 as a data basis for generating the compression data 32 and the compression data 32 is made available to the storage module 16 . The storage module 16 is designed to provide the data provided, in particular the compression data 32, to the selection module 26, for example to determine a deviation, and to the processing module 18 for further use.

QUOTES INCLUDED IN DESCRIPTION

This list of documents cited by the applicant was generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Patent Literature Cited

• DE 102018208058 A1 [0004]

Claims (15)

Data transmission device (2), wherein the data transmission device (2) is provided with an input signal (4), with an analysis module (7), wherein the analysis module (7) is designed to determine analysis data (8) based on an analysis of the input signal (4). , wherein the analysis data (8) form in particular a time series (19), with a transfer module (12) and an aggregation module (9) for determining aggregation data (11), wherein the aggregation module (9) is provided with the analysis data (8) and that Aggregation module (9) is designed to aggregate analysis data (8) as the aggregation data (11) until a target size is reached and to provide the aggregation data (11) to the transfer module (12) when the target size is reached, the transfer module (12) being designed providing the provided aggregation data (11) to a recipient and/or sending it to the recipient, characterized by a rating module (10), wherein the rating module (10) is provided with the analysis data (8) and the rating module (10) is designed for the Analysis data (8) to determine a relevance, the rating module (10) being designed to cause analysis data (8) having a threshold relevance to premature transmission of the analysis data (8) and/or aggregation data (11) by the transfer module (12). Data transmission device (2) after claim 1 , characterized in that the transfer module (12) is designed to compress the aggregation data (11) and to provide the compressed aggregation data (11) to the recipient and/or to send it to the recipient. Data transmission device (2) after claim 1 or 2 that the aggregation module (9) is designed to provide the aggregation data (11) for analysis data (8) without threshold value relevance only after the target size and/or target quantity has been reached to the transfer module (12), the aggregation module (9) being designed for analysis data (8) having the threshold value relevance to provide the aggregation data (11) to the transfer module (12) immediately and/or before the target size and/or the target quantity is reached. Data transmission device (2) according to one of the preceding claims, characterized in that the rating module (10) is designed to determine the relevance based on an anomaly analysis of the analysis data (8). Data transmission device (2) after claim 4 , characterized in that the rating module (10) has a prediction module (22) and the prediction module (22) is designed to make an analysis data prediction (21) for the analysis data (8) and/or the time series (19) of the analysis data (8). determine, in particular based on a physical model, a mechanical model, a simulation and/or a neural network, the rating module (10) being designed to determine the relevance based on the deviation of the analysis data (8) from the analysis data prediction (21). . Data transmission device (2) according to one of the preceding claims, characterized in that the input signal (4) comprises image data, the analysis module (7) being designed based on the image data as analysis data (8) for a trajectory and/or tracking of an object determine. Data transmission device (2) after claim 5 or 6 , characterized by a selection module (26), wherein the selection module (26) is designed to select a pre-selection (27) of analysis data (8) for aggregation, wherein the prediction module (22) is designed to determine a certainty statement, the certainty statement describing whether the time series (19) of the analysis data (8) can be reconstructed based on the pre-selection (27) of the analysis data (8) by the selection module (26), the selection module (26) being designed based on the certainty statement of the pre-selection (27 ) to add further analysis data (8) and/or to remove analysis data (8). Data transmission device (2) after claim 7 , characterized in that the selection module (26) has an adjustable resolution and is designed to select the pre-selection (27) of analysis data (8) based on the adjustable resolution. Data transmission device (2) after claim 7 or 8th , characterized in that the rating module (10) is designed to determine a reconstructed time series (19) of the analysis data (8) based on the pre-selection (27), the rating module (10) being designed to determine a deviation between the reconstructed time series (19 ) of the analysis data (8) and time series (19) of the analysis data (8), the selection module (26) being designed to add further analysis data (8) and/or to remove analysis data (8) until the deviation falls below a maximum deviation and/or a minimum reconstruction accuracy is reached. Data transmission arrangement (1) with the data transmission device (2) according to one of the preceding claims, with a receiving unit as receiver, wherein the receiving unit comprises an evaluation unit (15), wherein the evaluation unit (15) is designed to decompress the aggregation data (11), to store and/or process. Data transmission arrangement (1) after claim 10 , characterized by a client module, wherein the client module comprises the analysis module (7), the rating module (10), the selection module (26) and/or the transfer module (12), the evaluation unit (15) of the receiving module (3) having a compression module ( 17), wherein the compression module (17) is designed to compress and/or decode the aggregation data (11) provided. Data transmission arrangement (1) after claim 10 or 11 , characterized in that the client module comprises the selection module (26) and is designed to select analysis data (8) as a compression selection based on the aggregation data (11) provided, the selection module (26) being designed to add further analysis data (8) to the compression selection and / or to remove it until, based on the pre-selection (27), in particular by the prediction module (22), the time series (19) of the analysis data (8) can be reconstructed. Method for data transmission, in which a provided and/or received input signal (4) is analyzed and analysis data (8) are determined, in which the analysis data (8) describe and/or form a time series (19), the analysis data (8) becoming aggregation data (11) are aggregated, with as much and/or as long analysis data (8) being added to the aggregation data (11) until a target size is reached, with the aggregation data (11) being provided to a recipient when the target size is reached, wherein for the Analysis data (8) a relevance is determined, wherein analysis data (8) having a relevance of at least one threshold relevance before reaching the target size of the aggregation data (11) are provided and / or sent to the recipient. Computer program comprising instructions which cause the data transmission device (2) according to one of Claims 1 - 9 and / or the data transmission arrangement (1) according to one of Claims 10 - 12 the procedural steps Claim 13 executes Machine-readable medium on which the computer program is based Claim 14 is saved.

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