# US 2019/0378351 A1 · Cognitive learning for vehicle sensor monitoring and problem detection > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0378351 A1 - Document ID: US20190378351A1 - Status: Published application - Kind: A1 - Application number: 16/004,659 - Filed: 2018-06-11 - Published: 2019-12-12 - Earliest claimed: 2018-06-11 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Austin J. Dorenkamp; Jonathan C.F. Fouk; Paul F. Gerver - Web page: https://patentgrep.com/patent/US20190378351A1 ## CPC - G07C 5/006: {Indicating maintenance} - G07C 5/008: {communicating information to a remotely located station (transmission systems for measured values G08C)} - G07C 5/0808: {Diagnosing performance data (testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005)} - G07C 5/0816: {Indicating performance data, e.g. occurrence of a malfunction} - G07C 5/085: {using electronic data carriers} - G07C: TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE ## Abstract A computer-implemented method for vehicle event management. The method receives one or more sets of vehicle sensor data from a first vehicle, wherein the one or more sets of vehicle sensor data correspond to one or more sensor systems of the first vehicle. The method further maps the received one or more sets of vehicle sensor data with one or more candidate vehicle events, based on one or more sets of archived vehicle sensor data. The method further identifies one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events, and provides an alert, to the first vehicle, with the identified one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events. ## Claims ### Claim 1 A computer-implemented method for vehicle event management, the method comprising: receiving one or more sets of vehicle sensor data from a first vehicle, wherein the one or more sets of vehicle sensor data correspond to one or more sensor systems of the first vehicle; mapping the received one or more sets of vehicle sensor data with one or more candidate vehicle events, based on one or more sets of archived vehicle sensor data; identifying one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events; and providing an alert, to the first vehicle, with the identified one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, further comprising: determining that the identified one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events achieve an authenticity threshold; and adding the identified one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events to the one or more sets of archived vehicle sensor data. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, further comprising: receiving a first set of vehicle sensor data corresponding to a first set of vehicle sensors; receiving a second set of vehicle sensor data corresponding to a second set of vehicle sensors; determining a correlation between the first set of vehicle sensors and the second set of vehicle sensors; and building a correlation model between the first set of vehicle sensors and the second set of vehicle sensors, based on the determined correlation. ### Claim 4 (depends on 3) The computer-implemented method of claim 3, further comprising: detecting that the first set of vehicle sensors has encountered a failure event; and associating the failure event of the first set of vehicle sensors with the one or more candidate vehicle events, based on the correlation model. ### Claim 5 (depends on 3) The computer-implemented method of claim 3, further comprising: in response to detecting that the first set of vehicle sensors has encountered a failure event, receiving a snapshot of the one or more sensor systems of the first vehicle; aggregating the snapshot of the one or more sensor systems of the first vehicle; determining one or more associations between the failure event and the received snapshot of the one or more sensor systems of the first vehicle; and updating the correlation model to include the one or more associations between the failure event and the received snapshot of the one or more sensor systems of the first vehicle. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, wherein a second vehicle detects the one or more candidate vehicle events of the first vehicle, wherein the second vehicle is within a pre-defined proximity of the first vehicle. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, further comprising: monitoring, continuously, the one or more sets of vehicle sensor data from the one or more sensor systems, of the first vehicle, to identify the one or more candidate vehicle events. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, further comprising: receiving user feedback from the first vehicle, in response to the provided alert; and incorporating the received user feedback into confidence level data, for the one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events. ### Claim 9 (depends on 1) The computer-implemented method of claim 1, further comprising: correlating the one or more sets of vehicle sensor data from the first vehicle with the one or more sensor systems of the first vehicle; detecting a failed sensor associated with the one or more sensor systems of the first vehicle; and simulating the failed sensor using the correlated one or more sets of vehicle sensor data associated with the one or more sensor systems of the first vehicle. ### Claim 10 A computer program product, comprising a non-transitory tangible storage device having program code embodied therewith, the program code executable by a processor of a computer to perform a method, the method comprising: receiving one or more sets of vehicle sensor data from a first vehicle, wherein the one or more sets of vehicle sensor data correspond to one or more sensor systems of the first vehicle; mapping the received one or more sets of vehicle sensor data with one or more candidate vehicle events, based on one or more sets of archived vehicle sensor data; identifying one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events; and providing an alert, to the first vehicle, with the identified one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events. ### Claim 11 (depends on 10) The computer program product of claim 10, further comprising: determining that the identified one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events achieve an authenticity threshold; and adding the identified one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events to the one or more sets of archived vehicle sensor data. ### Claim 12 (depends on 10) The computer program product of claim 10, further comprising: receiving a first set of vehicle sensor data corresponding to a first set of vehicle sensors; receiving a second set of vehicle sensor data corresponding to a second set of vehicle sensors; determining a correlation between the first set of vehicle sensors and the second set of vehicle sensors; and building a correlation model between the first set of vehicle sensors and the second set of vehicle sensors, based on the determined correlation. ### Claim 13 (depends on 12) The computer program product of claim 12, further comprising: detecting that the first set of vehicle sensors has encountered a failure event; and associating the failure event of the first set of vehicle sensors with the one or more candidate vehicle events, based on the correlation model. ### Claim 14 (depends on 12) The computer program product of claim 12, further comprising: in response to detecting that the first set of vehicle sensors has encountered a failure event, receiving a snapshot of the one or more sensor systems of the first vehicle; aggregating the snapshot of the one or more sensor systems of the first vehicle; determining one or more associations between the failure event and the received snapshot of the one or more sensor systems of the first vehicle; and updating the correlation model to include the one or more associations between the failure event and the received snapshot of the one or more sensor systems of the first vehicle. ### Claim 15 (depends on 10) The computer program product of claim 10, further comprising: correlating the one or more sets of vehicle sensor data from the first vehicle with the one or more sensor systems of the first vehicle; detecting a failed sensor associated with the one or more sensor systems of the first vehicle; and simulating the failed sensor using the correlated one or more sets of vehicle sensor data associated with the one or more sensor systems of the first vehicle. ### Claim 16 A computer system, comprising: one or more computer devices each having one or more processors and one or more tangible storage devices; and a program embodied on at least one of the one or more storage devices, the program having a plurality of program instructions for execution by the one or more processors, the program instructions comprising instructions for: receiving one or more sets of vehicle sensor data from a first vehicle, wherein the one or more sets of vehicle sensor data correspond to one or more sensor systems of the first vehicle; mapping the received one or more sets of vehicle sensor data with one or more candidate vehicle events, based on one or more sets of archived vehicle sensor data; identifying one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events; and providing an alert, to the first vehicle, with the identified one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events. ### Claim 17 (depends on 16) The computer system of claim 16, further comprising: determining that the identified one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events achieve an authenticity threshold; and adding the identified one or more relationships between the received one or more sets of vehicle sensor data and the one or more candidate vehicle events to the one or more sets of archived vehicle sensor data. ### Claim 18 (depends on 16) The computer system of claim 16, further comprising: receiving a first set of vehicle sensor data corresponding to a first set of vehicle sensors; receiving a second set of vehicle sensor data corresponding to a second set of vehicle sensors; determining a correlation between the first set of vehicle sensors and the second set of vehicle sensors; and building a correlation model between the first set of vehicle sensors and the second set of vehicle sensors, based on the determined correlation. ### Claim 19 (depends on 18) The computer system of claim 18, further comprising: detecting that the first set of vehicle sensors has encountered a failure event; and associating the failure event of the first set of vehicle sensors with the one or more candidate vehicle events, based on the correlation model. ### Claim 20 (depends on 18) The computer system of claim 18, further comprising: in response to detecting that the first set of vehicle sensors has encountered a failure event, receiving a snapshot of the one or more sensor systems of the first vehicle; aggregating the snapshot of the one or more sensor systems of the first vehicle; determining one or more associations between the failure event and the received snapshot of the one or more sensor systems of the first vehicle; and updating the correlation model to include the one or more associations between the failure event and the received snapshot of the one or more sensor systems of the first vehicle.