US-20260127145-A1 - PROCESSING SPATIALLY REFERENCED DATA

US20260127145A1US 20260127145 A1US20260127145 A1US 20260127145A1US-20260127145-A1

Abstract

A computer implemented method is provided for compressing spatial data records ( 220 ), where a respective spatial data record ( 221 , 321 ) includes a spatial reference ( 222 , 322 ) within a space ( 218 ), and a plurality of attribute values ( 323 , 324 ) of respective attribute types. The method includes meshing ( 201 ) the space ( 218 ) in meshing elements ( 230 - 245 ), where a relative position of a meshing element has a relative spatial reference ( 255 ). The method further includes parsing ( 202 ) the spatial data records, having, for a respective spatial data record ( 321 ): compressing ( 203 ) the spatial reference ( 322 ) to the relative spatial reference ( 355 ) of the meshing element in which the spatial reference is located; compressing ( 301 ) the plurality of attribute values ( 323 , 324 ) to a plurality of respective numerical values ( 328 , 329 ) according to respective attribute dictionaries ( 325 , 326 ) having a mapping between attribute values and numerical values for a respective attribute type The plurality of numerical values are compressed ( 302 ) to a state value ( 332 ) according to a state dictionary ( 331 ) having a mapping between sets of numerical values and respective state values.

Inventors

Bart ADAMS
Lida Lea Jean JOLY

Assignees

XYZT.AI BV

Dates

Publication Date: 20260507
Application Date: 20230925
Priority Date: 20220928

Claims (17)

1 . A computer implemented method for compressing spatial data records, wherein a respective spatial data record comprises a spatial reference within a space, and a plurality of attribute values of respective attribute types; the method comprising: meshing the space in meshing elements, wherein a relative position of a meshing element that has a relative spatial reference; and parsing the spatial data records, comprising, for a respective spatial data record: compressing the spatial reference to the relative spatial reference of the meshing element in which the spatial reference is located; compressing the plurality of attribute values to a plurality of respective numerical values according to respective attribute dictionaries comprising a mapping between attribute values and numerical values for a respective attribute type; and compressing the plurality of numerical values to a state value according to a state dictionary comprising a mapping between sets of numerical values and respective state values.
2 . The computer implemented method according to claim 1 , wherein parsing the spatial data records further comprises generating the attribute dictionaries and/or the state dictionary.
3 . The computer implemented method according to claim 1 , wherein the attribute dictionaries further comprise a mapping between intervals of attribute values and numerical values, or between one or more characters and numerical values.
4 . The computer implemented method according to claim 1 , wherein meshing a space further comprises meshing the space in meshing elements having equal surface areas according to a predetermined resolution.
5 . The computer implemented method according to claim, wherein parsing the spatial data records further comprises, for a respective spatial data record, assigning the relative spatial reference and the state value to a data structure associated with the space for storing compressed spatial data records comprising a spatial reference located within the space.
6 . The computer implemented method according to claim 5 , wherein parsing the spatial data records further comprises, if a size of the data structure associated with the space exceeds a size threshold, dividing a space into subspaces and dividing the data structure associated with the space in data sub-structures associated with the respective subspaces for storing compressed spatial data records comprising a spatial reference located within the respective subspaces.
7 . The computer implemented method according to claim 6 , wherein dividing a space into subspaces further comprises: meshing the respective subspaces in meshing elements, wherein a relative position of a meshing element within a subspace is that has a relative sub-spatial reference; updating the relative spatial references with the relative sub-spatial references; and assigning ( 405 ) the relative sub-spatial references and the state value ( 332 ) to the data sub-structure.
8 . The computer-implemented method according to claim 6 , wherein dividing a space into subspaces is performed according to a space portioning tree.
9 . The computer implemented method according to claim 4 , further comprising obtaining relative sub-spatial references according to at least one lower resolution by aggregating meshing elements of the predetermined resolution.
10 . The computer implemented method according to claim 9 , further comprising obtaining aggregated subspaces that include a predetermined number of meshing elements of the at least one lower resolution; and obtaining aggregated data structures associated with the aggregated subspaces for storing compressed spatial data records comprising a spatial reference located within the aggregated subspaces.
11 . The computer implemented method according to claim 6 , further comprising: receiving a request for a digest of spatial data records located within an inspection space; fetching one or more data sub-structures associated with the subspaces that at least partially overlap with the inspection space; and generating the digest by rendering the numerical values of at least one attribute type on the meshing elements within the inspection space based on the relative spatial references.
12 . The computer implemented method according to claim 9 , wherein the fetching further comprises: determining a resolution for the digest based on the inspection space; selecting the predetermined resolution or the at least one lower resolution based on the determined resolution; and fetching, based on the selected resolution, one or more data sub-structures, or one or more aggregated data structures.
13 . The computer implemented method according to claim 11 , wherein the request for a digest further comprises a selection of attribute types to be rendered; and wherein generating the digest is limited to rendering the attribute types included in the selection.
14 . The computer implemented method according to claim 11 , wherein generating the digest further comprises decoding the state values of the compressed spatial data records to the plurality of numerical values based on the state dictionary.
15 . A data processing system configured to perform the computer implemented method according to claim 1 .
16 . A computer program comprising instructions which, when the program is executed by a computer, cause the computer to perform the computer implemented method according to claim 1 .
17 . A computer-readable medium comprising instructions which, when executed by a computer, cause the computer to perform the computer implemented method according to claim 1 .

Description

FIELD OF THE INVENTION The present invention generally relates to processing spatially referenced data. BACKGROUND OF THE INVENTION The location of real-world assets such as cars, planes, vessels, containers, and people can be tracked in time to generate spatially and temporally referenced data. These assets may be pinpointed in space and time by means of Bluetooth Low Energy, BLE, cellular triangulation, computer vision, or a global positioning system, GPS. An increasing number of assets is being tracked, resulting in vast amounts of spatially referenced data. Spatial analysis software typically allow to interact with spatially referenced data stored in a database, e.g. by generating data visualizations. This can allow identifying trends, patterns, and phenomena to obtain insights into, for example, traffic flows, maritime circulation, people flows, and air traffic. Most interactions with the spatially referenced data require querying or searching the entire database, which results in substantial processing times. To cope with the vast amounts of data, the spatial analysis software is typically run on hardware that is optimized to process the spatially referenced data, e.g. a plurality of Graphic Processing Units, GPUs. This results in a large overhead and limited scalability as the hardware is costly. In addition to the spatial information, the spatially referenced data may include attributes or metadata, e.g. speed, tire pressure, or cargo. Spatial analysis software typically requires clean data that is structured according to a predetermined format. To this end, the spatially referenced data is typically pre-processed. This can be time and resource intensive as the pre-processing may at least partially be performed manually, e.g. by a data engineer. It is thus a problem to efficiently process spatially referenced data. SUMMARY OF THE INVENTION It is an object of the present invention, amongst others, to solve or alleviate the above identified problems and challenges by improving the processing of spatially referenced data. According to a first aspect, this object is achieved by a computer implemented method for compressing spatial data records, wherein a respective spatial data record comprises a spatial reference within a space, and a plurality of attribute values of respective attribute types. The method comprises meshing the space in meshing elements, wherein a relative position of a meshing element is characterized by a relative spatial reference. The method further comprises parsing the spatial data records, comprising, for a respective spatial data record: compressing the spatial reference to the relative spatial reference of the meshing element in which the spatial reference is located; compressing the plurality of attribute values to a plurality of respective numerical values according to respective attribute dictionaries comprising a mapping between attribute values and numerical values for a respective attribute type; and compressing the plurality of numerical values to a state value according to a state dictionary comprising a mapping between sets of numerical values and respective state values Parsing the spatial data records refers to recursively processing respective spatial data records from a dataset, i.e. ingesting the respective spatial data records one by one. A spatial reference characterizes a physical location, e.g. by a set of coordinates according to any coordinate system. The spatial reference may, for example, include x, y, and z coordinates representing longitude, latitude, and elevation on the surface of the Earth, respectively. The relative spatial reference is indicative for the position of a meshing element according to a relative reference frame, which may be characterized by a point of reference, one or more axes, and/or a scale for the one or more axes. The point of reference, also origin, may be an outer end of the meshed space, e.g. an outer corner of the meshed space. The one or more axes may extend from the origin along one or more respective outer edges of the meshed space. The scale may be defined by the meshing elements along the one or more axes, i.e. the units of the one or more axes may be expressed in meshing elements. As such, the relative spatial reference may characterize the relative position of a meshing element by means of one or more integer values. For example, the relative spatial references may have the form (α, β), wherein α is the distance of a meshing element to a first axis expressed in a number of meshing elements, and β is the distance of the meshing element to a second axis expressed in a number of meshing elements. This allows compressing the spatial reference of a spatial data record to the relative spatial reference of the meshing element in which the spatial reference is located. In doing so, a more memory efficient representation of the spatial reference is obtained as the relatively memory intensive spatial reference, e.g. floating-poin