Patent Issued for Roadside Assistance System (USPTO 10,553,119)
2020 FEB 17 (NewsRx) -- By a
The patent’s inventors are Shah, Hiral T. (
This patent was filed on
From the background information supplied by the inventors, news correspondents obtained the following quote: “A vehicle failure can happen unexpectedly and may be a difficult problem to solve for the driver of the vehicle. Vehicle-based computer systems, such as on-board diagnostics (OBD) systems and telematics devices, may be used in automobiles and other vehicles, and may be capable of collecting various vehicle data relating to a vehicle failure.
“In addition, adding roadside assistance functionality to new or existing applications, internet of things devices, voice recognition devices and others can take a great deal of time and effort for developers. Application programming interfaces can assist developers by providing a set of microservices that allow developers to add functionality to an application. An application programming interface that provides a set of roadside assistance microservices would help remedy the above mentioned issues.”
Supplementing the background information on this patent, NewsRx reporters also obtained the inventors’ summary information for this patent: “The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosure. The summary is not an extensive overview of the disclosure. It is neither intended to identify key or critical elements of the disclosure nor to delineate the scope of the disclosure. The following summary merely presents some concepts of the disclosure in a simplified form as a prelude to the description below.
“Aspects of the disclosure relate to systems, apparatuses, computer-implemented methods, and computer-readable media for enabling roadside assistance functionality and evaluating data received from one or more devices to identify potential issues requiring roadside assistance. According to some aspects of this disclosure a roadside assistance application programming interface (API) may allow any type of application, internet of things device, voice recognition device, and others to provide roadside assistance functionality. The API may provide roadside assistance functionality to one or more applications, enabling developers to quickly and efficiently modify and add roadside assistance functionality in the one or more applications.
“According to some aspects of this disclosure a device (such as a smart phone, tablet, listening device, etc.) may communicate with sensors or an on-board diagnostics system of a vehicle and retrieve vehicle data. The device may generate a recommendation for a service, such as a roadside assistance service, based on the vehicle data. The device may send a request for roadside assistance. The device may be used to enroll a user as a member of a roadside assistance benefits program. The above mentioned steps may all be performed via, in some examples, a single application executing on the device. According to some aspects of this disclosure a device may process a roadside assistance request and determine a roadside assistance service provider for a user that requested roadside assistance.
“Other features and advantages of the disclosure will be apparent from the additional description provided herein.”
The claims supplied by the inventors are:
“The invention claimed is:
“1. A method comprising: receiving, by a mobile device and from an on-board diagnostic system of a vehicle, vehicle information indicating a service is needed for the vehicle, wherein the mobile device is executing an application implementing a roadside assistance application programming interface (API); displaying, on a display of the mobile device via the application, information related to the service; receiving, by the mobile device, voice input from a user corresponding to the information; determining, by parsing the voice input with a neural network, an intent of the voice input, wherein the intent of the voice input indicates a roadside assistance request; sending, from the mobile device and to a roadside assistance server, the roadside assistance request, wherein the roadside assistance request comprises a type of service to be performed on the vehicle and a location of the vehicle; receiving, from the roadside assistance server, a benefits enrollment prediction, wherein the benefits enrollment prediction is generated using machine learning; sending, based on the benefits enrollment prediction, enrollment information to the roadside assistance server; and receiving service information via the application, wherein the service information comprises a location of a service provider vehicle that is scheduled to respond to the roadside assistance request.
“2. The method of claim 1, further comprising: generating a feature vector based on the vehicle information; outputting the feature vector to a recommender system; and generating, by the recommender system, a recommended type of roadside service for the vehicle, wherein the type of service is the recommended type of roadside service.
“3. The method of claim 2, wherein the vehicle information comprises tire pressure information obtained from a tire pressure sensor of the vehicle and engine speed information obtained from an engine speed sensor of the vehicle.
“4. The method of claim 1, wherein the roadside assistance request further comprises a benefits enrollment request and further comprising: receiving, by the mobile device and via the application executing on the mobile device, a notification indicating that the user has been enrolled in a benefits program and indicating a type of benefits plan in which the user is enrolled.
“5. The method of claim 1, wherein the location of the vehicle is obtained from a global positioning system (GPS) of the vehicle.
“6. The method of claim 1, wherein the application comprises a social media application.
“7. The method of claim 1, wherein the service information further comprises an estimated time of arrival, a make, a model, and a license plate number of the service provider vehicle.
“8. The method of claim 1, further comprising: engaging in a conversation with the user via a natural language processing engine of the application, wherein the roadside assistance request is generated based on the conversation.
“9. A system comprising: a computing device associated with a vehicle and an apparatus, wherein the computing device comprises one or more processors, and memory storing machine readable instructions that, when executed by the one or more processors of the computing device cause the computing device to: receive, by a mobile device and from an on-board diagnostic system of a vehicle, vehicle information indicating a service is needed for the vehicle, wherein the mobile device is executing an application implementing a roadside assistance application programming interface (API); display, on a display of the mobile device via the application, information related to the service receive by the mobile device, voice input from a user corresponding to the information; determine, by parsing the voice input with a neural network, an intent of the voice input, wherein the intent of the voice input indicates a roadside assistance request; send, from the mobile device and to a roadside assistance server, the roadside assistance request, wherein the roadside assistance request comprises a type of service to be performed on the vehicle and a location of the vehicle; receive, from the roadside assistance server, a benefits enrollment prediction, wherein the benefits enrollment prediction is generated using machine learning; send, based on the benefits enrollment prediction, enrollment information to the roadside assistance server; and receive service information via the application, wherein the service information comprises a location of a service provider vehicle that is scheduled to respond to the roadside assistance request; and wherein the apparatus comprises one or more processors, and memory storing machine readable instructions that, when executed by the one or more processors, cause the apparatus to: receive the roadside assistance request from the computing device.
“10. The system of claim 9, wherein the machine readable instructions that, when executed by the one or more processors of the computing device further cause the computing device to: generate a feature vector based on the vehicle information; output the feature vector to a recommender system; and generate by the recommender system, a recommended type of roadside service for the vehicle, wherein the type of service is the recommended type of roadside service.
“11. The system of claim 10, wherein the vehicle information comprises tire pressure information obtained from a tire pressure sensor of the vehicle and engine speed information obtained from an engine speed sensor of the vehicle.
“12. The system of claim 9, wherein the roadside assistance request further comprises a benefits enrollment request and wherein the machine readable instructions that, when executed by the one or more processors of the computing device further cause the computing device to: receive, by the mobile device and via the application executing on the mobile device, a notification indicating that the user has been enrolled in a benefits program and indicating a type of benefits plan in which the user is enrolled.
“13. The system of claim 9, wherein the location of the vehicle is received from a global positioning system (GPS) of the vehicle.
“14. The system of claim 9, wherein the application comprises a social media application.
“15. The system of claim 9, further comprising: engaging in a conversation with the user via a natural language processing engine of the application, wherein the roadside assistance request is generated based on the conversation.
“16. An apparatus comprising: one or more processors; and memory storing machine readable instructions that, when executed by the one or more processors cause the apparatus to: receive, by a mobile device and from an on-board diagnostic system of a vehicle, vehicle information indicating a service is needed for the vehicle, wherein the mobile device is executing an application implementing a roadside assistance application programming interface (API); display, on a display of the mobile device via the application, information related to the service; receive, by the mobile device, voice input from a user corresponding to the information; determine, by parsing the voice input with a neural network, an intent of the voice input, wherein the intent of the voice input indicates a roadside assistance request; send, from the mobile device and to a roadside assistance server, the roadside assistance request, wherein the roadside assistance request comprises a type of service to be performed on the vehicle and a location of the vehicle; receive, from the roadside assistance server, a benefits enrollment prediction, wherein the benefits enrollment prediction is generated using machine learning; send, based on the benefits enrollment prediction, enrollment information to the roadside assistance server; and receive service information via the application, wherein the service information comprises a location of a service provider vehicle that is scheduled to respond to the roadside assistance request.
“17. The apparatus of claim 16, wherein the machine readable instructions that, when executed by the one or more processors cause the apparatus to: generate a feature vector based on the vehicle information; output the feature vector to a recommender system; and generate, by the recommender system, a recommended type of roadside service for the vehicle, wherein the type of service is the recommended type of roadside service.
“18. The apparatus of claim 16, wherein the vehicle information comprises tire pressure information obtained from a tire pressure sensor of the vehicle and engine speed information obtained from an engine speed sensor of the vehicle.
“19. The apparatus of claim 16, wherein the location of the vehicle is obtained by the application from a global positioning system (GPS) of the vehicle.
“20. The apparatus of claim 16, wherein the service information further comprises an estimated time of arrival, a make, a model, and a license plate number of the service provider vehicle.”
For the URL and additional information on this patent, see: Shah, Hiral T.; Singh,
(Our reports deliver fact-based news of research and discoveries from around the world.)
Walla Walla County releases information about flood recovery requirements
National Women's Law Center Issues Public Comment on EEOC Proposed Rule
Advisor News
Annuity News
Health/Employee Benefits News
Life Insurance News