# US 2020/0401641 A1 · Context information from crowd-sourced data > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2020/0401641 A1 - Document ID: US20200401641A1 - Status: Published application - Kind: A1 - Application number: 16/905,639 - Filed: 2020-06-18 - Published: 2020-12-24 - Earliest claimed: 2019-06-21 - Assignees: HERE Global B.V. - Applicants: HERE Global B.V. - Inventors: Henri Jaakko Julius NURMINEN; Pavel IVANOV; Lauri Aarne Johannes WIROLA - Web page: https://patentgrep.com/patent/US20200401641A1 ## CPC - G01S 5/02525: {Gathering the radio frequency fingerprints} - G06F 16/9536: Search customisation based on social or collaborative filtering - G01S 5/02524: {Creating or updating the radio-map} - G06N 20/00: Machine learning - H04W 4/02: Services making use of location information - H04W 4/029: Location-based management or tracking services - H04W 52/0254: {detecting a user operation or a tactile contact or a motion of the device} - H04W 64/00: Locating users or terminals {or network equipment} for network management purposes, e.g. mobility management - G01S 5/02521: {using a radio-map} - G01S 5/02522: {The radio-map containing measured values of non-radio values} - H04W 4/80: Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication - H04W 16/18: Network planning tools - Y02D 30/70: in wireless communication networks - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) - Y02D: CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE ## Abstract A method is provided that includes obtaining one or more pieces of crowd-sourced information. A respective crowd-sourced information is at least indicative of a location at which the respective crowd-sourced information was gathered. The method determines a set of tiles at least partially based on the one or more geographical areas. For at least one tile, the method obtains one or more pieces of fingerprint information comprised by the one or more pieces of crowd-sourced information that were gathered within the respective area of the respective tile and determines an area type and/or context information indicative of a type of venue located within the respective tile and/or context the respective area of the respective tile is used for. The area type and/or context information is determined at least partially based on the one or more pieces of fingerprint information. A corresponding apparatus and computer program product are also provided. ## Claims ### Claim 1 A method, comprising: obtaining one or more pieces of crowd-sourced information, wherein a respective crowd-sourced information of the one or more pieces of crowd-sourced information is at least indicative of a location at which the respective crowd-sourced information was gathered; determining a set of tiles, wherein the set of tiles is determined at least partially based on the one or more geographical areas, wherein the one or more geographical areas are divided into one or more smaller areas of a pre-defined size, wherein a respective tile of the set of tiles represents a respective smaller area of the one or more smaller areas; and the method further comprises for at least one tile of the set of tiles: obtaining one or more pieces of fingerprint information comprised by the one or more pieces of crowd-sourced information, wherein the one or more pieces of fingerprint information were gathered within the respective area of the respective tile; and determining an area type and/or context information indicative of a type of venue located within the respective tile and/or context the respective area of the respective tile is used for, wherein the area type and/or context information is determined at least partially based on the one or more pieces of fingerprint information. ### Claim 2 (depends on 1) The method according to claim 1, further comprising: determining a feature information indicative of one or more feature values for the respective area of the respective tile, wherein the feature information is determined based on the one or more pieces of fingerprint information, and the area type and/or context information is determined further based on the feature information. ### Claim 3 (depends on 1) The method according to claim 1, further comprising: determining a priority information indicative of a crowd-sourcing priority value for the respective area of the respective tile, wherein the priority information is determined at least partially based on the area type and/or context information; and associating the respective tile of the set of tiles with the determined priority information. ### Claim 4 (depends on 3) The method according to claim 3, wherein the crowd-sourcing priority represents whether or not further gathering one or more pieces of fingerprint information for the respective geographic area of the tile is needed or not. ### Claim 5 (depends on 3) The method according to claim 3, further comprising: providing the respective priority information and/or the respective tile of the set of tiles associated with the respective priority information. ### Claim 6 (depends on 5) The method according to claim 5, further comprising: obtaining one or more pieces of crowd-sourced information in response to at least one provided priority information and/or respective tile of the set of tiles associated with the respective priority information, wherein said obtained one or more pieces of crowd-sourced information were gathered in one or more respective areas of the one or more respective tiles with which the at least one provided priority information is associated. ### Claim 7 (depends on 1) The method according to claim 1, wherein the area type and/or context information is determined by a machine learning network, and wherein the method further comprises: determining one or more parameters of the machine learning network at least partially based on one or more pieces of fingerprint information comprised or represented by the one or more pieces of crowd-sourced information, wherein the one or more parameters are indicative of one or more adaptive variables used by the machine learning network to determine an output, and wherein the output represents an area type and/or context information. ### Claim 8 (depends on 1) The method according to claim 1, wherein each piece of the one or more pieces of fingerprint information comprises or represents one or more of the following: a reference position at which a respective crowd-sourced information was gathered; one or more identifiers of one or more radio nodes which sent one or more signals that were observable at the position at which a respective crowd-sourced information was gathered; and one or more received signal strength values, wherein the one or more received signal strength values were gathered based on one or more signals sent by one or more radio nodes, which sent one or more signals of the one or more radio nodes that were observable at the position at which a respective crowd-sourced information was gathered. ### Claim 9 A method, performed by at least one mobile device, comprising: obtaining one or more pieces of priority information and/or one or more tiles of a set of tiles, wherein the one or more tiles of the set of tiles are associated with a respective priority information of the one or more pieces of priority information, wherein the set of tiles is indicative of one or more geographical areas that are divided into one or more smaller areas of a pre-defined size, wherein a respective tile of the set of tiles represents a respective smaller area of the one or more smaller areas; and gathering one or more pieces of fingerprint information at least partially based on the obtained one or more pieces of priority information. ### Claim 10 (depends on 9) The method according to claim 9, further comprising: providing the gathered one or more pieces of fingerprint information. ### Claim 11 (depends on 9) The method according to claim 9, wherein the one or more pieces of fingerprint information are gathered in case the at least one mobile device is located within a respective geographic area of a tile of the one or more tiles with which at least one priority information of the one or more pieces of priority information is associated with. ### Claim 12 (depends on 9) The method according to claim 9, wherein the one or more pieces of fingerprint information are gathered in case one or more further requirements are met, wherein the one or more further requirements are indicative of available resources of the at least one mobile device. ### Claim 13 (depends on 9) The method according to claim 9, further comprising: determining whether or not the one or more pieces of fingerprint information are gathered prior to the gathering of the one or more pieces of fingerprint information, wherein a comparison of a respective priority information of a respective tile and a pseudo-random number is performed and/or controlled, so that the gathering of one or more pieces of fingerprint information is more likely in case a respective priority information represents a high priority than in case the respective priority information represents a low priority. ### Claim 14 An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause an apparatus at least to: obtain one or more pieces of crowd-sourced information, wherein a respective crowd-sourced information of the one or more pieces of crowd-sourced information is at least indicative of a location at which the respective crowd-sourced information was gathered; determine a set of tiles, wherein the set of tiles is determined at least partially based on the one or more geographical areas, wherein the one or more geographical areas are divided into one or more smaller areas of a pre-defined size, wherein a respective tile of the set of tiles represents a respective smaller area of the one or more smaller areas; and for at least one tile of the set of tiles: obtain one or more pieces of fingerprint information comprised by the one or more pieces of crowd-sourced information, wherein the one or more pieces of fingerprint information were gathered within the respective area of the respective tile; and determine an area type and/or context information indicative of a type of venue located within the respective tile and/or context the respective area of the respective tile is used for, wherein the area type and/or context information is determined at least partially based on the one or more pieces of fingerprint information. ### Claim 15 (depends on 14) The apparatus according to claim 14, wherein the at least one memory and the computer program code are further configured to, with the at least one processor, cause an apparatus to: determine a feature information indicative of one or more feature values for the respective area of the respective tile, wherein the feature information is determined based on the one or more pieces of fingerprint information, and the area type and/or context information is determined further based on the feature information. ### Claim 16 (depends on 14) The apparatus according to claim 14, wherein the at least one memory and the computer program code are further configured to, with the at least one processor, cause an apparatus to: determine a priority information indicative of a crowd-sourcing priority value for the respective area of the respective tile, wherein the priority information is determined at least partially based on the area type and/or context information; and associate the respective tile of the set of tiles with the determined priority information. ### Claim 17 (depends on 16) The apparatus according to claim 16, wherein the at least one memory and the computer program code are further configured to, with the at least one processor, cause an apparatus to: provide the respective priority information and/or the respective tile of the set of tiles associated with the respective priority information. ### Claim 18 (depends on 17) The apparatus according to claim 17, wherein the at least one memory and the computer program code are further configured to, with the at least one processor, cause an apparatus to: obtain one or more pieces of crowd-sourced information in response to at least one provided priority information and/or respective tile of the set of tiles associated with the respective priority information, wherein said obtained one or more pieces of crowd-sourced information were gathered in one or more respective areas of the one or more respective tiles with which the at least one provided priority information is associated. ### Claim 19 (depends on 14) The apparatus according to claim 14, wherein the area type and/or context information is determined by a machine learning network, and wherein the at least one memory and the computer program code are further configured to, with the at least one processor, cause an apparatus to: determine one or more parameters of the machine learning network at least partially based on one or more pieces of fingerprint information comprised or represented by the one or more pieces of crowd-sourced information, wherein the one or more parameters are indicative of one or more adaptive variables used by the machine learning network to determine an output, and wherein the output represents an area type and/or context information. ### Claim 20 (depends on 14) The apparatus according to claim 14, wherein each piece of the one or more pieces of fingerprint information comprises or represents one or more of the following: a reference position at which a respective crowd-sourced information was gathered; one or more identifiers of one or more radio nodes which sent one or more signals that were observable at the position at which a respective crowd-sourced information was gathered; and one or more received signal strength values, wherein the one or more received signal strength values were gathered based on one or more signals sent by one or more radio nodes, which sent one or more signals of the one or more radio nodes that were observable at the position at which a respective crowd-sourced information was gathered.