# US 2023/0345199 A1 · Method and system for criterion-based localization of mobile devices > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2023/0345199 A1 - Document ID: US20230345199A1 - Status: Published application - Kind: A1 - Application number: 17/727,027 - Filed: 2022-04-22 - Published: 2023-10-26 - Earliest claimed: 2022-04-22 - Assignees: Mapsted Corp. - Inventors: Ahmed Mahmood; Sean Huberman; Xuyang Han; Eros Gulo - Web page: https://patentgrep.com/patent/US20230345199A1 ## CPC - H04W 4/021: Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences - H04W 4/029: Location-based management or tracking services - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) ## Abstract A method and a device for criterion-based calibration for localization of mobile devices are described. In an example, sensorial data for a zone in the indoor space is obtained. The zone can have a set of factors influencing a behavior of the sensorial data therein. A component of instantaneous localization in the zone is determined based on the sensorial data by simulating variation of the component. The estimation is evaluated based on a ground truth value of the component and, on the basis thereof, a localization criterion is associated with the zone. The localization criterion is indicative of a selectivity in use of the sensorial data for localizing the mobile device in the zone. ## Claims ### Claim 1 A method of calibrating an indoor space for localizing a mobile device, the method comprising: obtaining sensorial data for a zone in the indoor space, the zone being associated with a set of factors influencing a behavior of the sensorial data in the zone; estimating at least one component of instantaneous localization in the zone based on the sensorial data, wherein the estimating comprises simulating variation of the at least one component; evaluating the estimation of the at least one component based on a ground truth value of the at least one component; and associating a localization criterion with the zone, wherein the localization criterion is indicative of a selectivity in use of the sensorial data for localizing the mobile device in the zone. ### Claim 2 (depends on 1) The method of claim 1, wherein estimating comprises: classifying the sensorial data into a plurality of localization parameter sets, based on a predetermined classification parameter; estimating, individually, the at least one component in the zone based on each of the plurality of localization parameter sets; evaluating the estimation of the at least one component, for each of the plurality of localization parameter set, based on the ground truth value of the at least one component; and assigning a weightage with each of the plurality of localization parameters sets, based on the evaluation, the weightage being indicative of a reliability score associated with each of the plurality of localization parameters in estimating the at least one component. ### Claim 3 (depends on 2) The method of claim 2, wherein the predetermined classification parameter includes at least a source of the sensorial data, the source of the sensorial data being at least one of signal sensors and inertial sensors. ### Claim 4 (depends on 1) The method of claim 1, wherein the evaluating comprises determining an error in estimating the at least one component in the zone. ### Claim 5 (depends on 4) The method of claim 4, wherein the evaluating comprises selecting an evaluation technique based on at least a source of the sensorial data. ### Claim 6 (depends on 1) The method of claim 1, wherein the associating comprises assigning a weightage with each type of the sensorial data, based on a reliability score linked with each type of the sensorial data in estimating the at least one component. ### Claim 7 (depends on 1) The method of claim 1, wherein the factors comprise at least one of a size of the zone, a shape of the zone, a type of the zone, a number of users passing through the zone, and predicted movement patterns of the mobile device in the zone. ### Claim 8 (depends on 1) The method of claim 1, wherein the at least one component comprises at least one of a trajectory of the mobile device, a variation in speed along the trajectory, a variation in elevation along the trajectory, and an allowable threshold variation in the at least one component. ### Claim 9 (depends on 1) The method of claim 1, further comprising performing a qualitative validation of the sensorial data based on a set of qualitative modifiers. ### Claim 10 (depends on 9) The method as claimed in claim 9, wherein the set of qualitative modifiers comprises at least one of a density of visits in the zone, a density of the sensorial data collected for the zone, a density of sources of sensorial data in the zone, a stability of the sources of the sensorial data in the zone, an average deviation in the sensorial data in the zone, a diversity in the sensorial data collected from the zone, a frequency of collection of sensorial data from the zone, and an average localization accuracy in the zone. ### Claim 11 A server computing device comprising: a processor; and a memory storing a set of instructions, the instructions executable in the processor to: obtain sensorial data for a zone in the indoor space, the zone being associated with a set of factors influencing a behavior of the sensorial data in the zone; estimate at least one component of instantaneous localization in the zone based on the sensorial data, wherein the estimating comprises simulating variation of the at least one component; evaluate the estimation of the at least one component based on a ground truth value of the at least one component; and associate a localization criterion with the zone, wherein the localization criterion is indicative of a selectivity in use of the sensorial data for localizing the mobile device in the zone. ### Claim 12 (depends on 11) The server computing device of claim 11 further comprising instructions to: classify the sensorial data into a plurality of localization parameter sets, based on a predetermined classification parameter; estimate, individually, the at least one component in the zone based on each of the plurality of localization parameter sets; evaluate the estimation of the at least one component, for each of the plurality of localization parameter set, based on the ground truth value of the at least one component; and assign a weightage with each of the plurality of localization parameters sets, based on the evaluation, the weightage being indicative of a reliability score associated with each of the plurality of localization parameters in estimating the at least one component. ### Claim 13 (depends on 12) The server computing device of claim 12, wherein the predetermined classification parameter is at least a source of the sensorial data, the source of the sensorial data being at least one of signal sensors and inertial sensors. ### Claim 14 (depends on 11) The server computing device of claim 11, further comprising instructions to determine an error in estimating the at least one component in the zone. ### Claim 15 (depends on 14) The server computing device of claim 14 further comprising instructions to select an evaluation technique to determine error based on at least a source of the sensorial data. ### Claim 16 (depends on 11) The server computing device of claim 11 further comprising instructions to assign a weightage with each type of the sensorial data, based on a reliability score linked with each type of the sensorial data in estimating the at least one component. ### Claim 17 (depends on 11) The server computing device of claim 11, wherein the factors comprise at least one of a size of the zone, a shape of the zone, a type of the zone, a number of users passing through the zone, and predicted movement patterns of the mobile device in the zone. ### Claim 18 (depends on 11) The server computing device of claim 11, wherein the at least one component comprises at least one of a trajectory of the mobile device, a variation in speed along the trajectory, a variation in elevation along the trajectory, and an allowable threshold variation in the at least one component. ### Claim 19 (depends on 1) The server computing device of claim 1 further comprising instructions to perform a qualitative validation of the sensorial data based on a set of qualitative modifiers. ### Claim 20 (depends on 19) The server computing device of claim 19, wherein the set of qualitative modifiers comprises at least one of a density of visits in the zone, a density of the sensorial data collected for the zone, a density of sources of sensorial data in the zone, a stability of the sources of the sensorial data in the zone, an average deviation in the sensorial data in the zone, a diversity in the sensorial data collected from the zone, a frequency of collection of sensorial data from the zone, and an average localization accuracy in the zone.