Abstract:
Systems and methods are provided for designing a preferred route for a vehicle. The route designing system receives a request from the vehicle for a preferred route from a first geographical point to a second geographical point. The route designing system analyzes the request and obtains driving scores associated with drivers of other vehicles. The route designing unit may identify a set of preferred and non-preferred vehicles based on the driving scores. The route designing system then determines a preferred route based, at least in part, on the driving scores associated with drivers of the other vehicles. The preferred route is designed to minimize the likelihood of proximity to non-preferred vehicles and maximize the likelihood of proximity to preferred vehicles.
Abstract:
Methods and systems disclosed herein describe generating products using data objects and/or entities that comply with a canonical/governed model(s). The data objects and/or entities may be obtained from an enterprise model or a combination of an enterprise model and one or more local models within a central repository to generate the new product data structures. Once all the data objects and/or entities have been added to the new product, one or more simplification rules may be applied to the new product to flatten (optimize for consumption) the data structure of the product such that superfluous or extraneous code snippets may be removed, or reduced, in such a way that the product complies with the canonical model. The new product may then be exported to an executable data format, which can either be incorporated in another application or used as a standalone product.
Abstract:
A system includes one or more privacy vaults. At least one of the one or more privacy vaults is associated with at least one individual user, stores contents associated with the associated at least one individual user, and stores specific identification of a plurality of third-party entities, authorized to access at least a portion of the contents stored by the one or more privacy vaults, along with access permissions, one or more of the access permissions defined for each of the plurality of third-party entities. At least one of the access permissions defines accessibility of the contents for at least one of the plurality of third-party entities for which the at least one access permission is defined.
Abstract:
Aspects of the disclosure relate to using ultrasonic or other types of signals to determine a distance between a transmitter and one or more mobile devices. The distance may be used to facilitate travel on foot or in a vehicle. One aspect disclosed provides a computing platform that may receive ultrasonic sensing data associated with mobile devices in a vehicle from a signal transmitter. Unique identifiers of the mobile devices may be determined. Based on the ultrasonic sensing data and the unique identifier, a relative distance from the signal transmitter to each mobile device in the vehicle may be determined. The computing platform may use a machine learning classifier to determine that a particular occupant is a driver in the vehicle based on the relative distance.
Abstract:
Aspects of the disclosure relate to using computer vision methods for asset evaluation. A computing platform may receive historical images of a plurality of properties and corresponding historical inspection results. Using the historical images and historical inspection results, the computing platform may train a roof waiver model (which may be a computer vision model) to output inspection prediction information directly from an image. The computing platform may receive a new image corresponding to a particular residential property. Using the roof waiver model, the computing platform may analyze the new image to output of a likelihood of passing inspection. The computing platform may send, to a user device and based on the likelihood of passing inspection, inspection information indicating whether or not a physical inspection should be performed and directing the user device to display the inspection information, which may cause the user device to display the inspection information.
Abstract:
Methods, computer-readable media, software, and apparatuses include receiving, from a plurality of risk information sources, risk information associated with a user account, wherein the risk information includes a plurality of risk components, determining, for each of the plurality of risk components, an impact score and a risk probability by applying a machine learning model to risk information associated with the user account, generating an interactive risk index dashboard including a plurality of interactive risk index elements, wherein each of the plurality of interactive risk index elements is associated with a risk component of the plurality of risk components, and displaying, on the display of the apparatus, the interactive risk index dashboard, wherein each of the plurality of interactive risk index elements is displayed in a portion of the interactive risk index dashboard in accordance with a respective determined impact score and risk probability.
Abstract:
Methods, computer-readable media, software, systems and apparatuses may receive, from a user device, notification of a user enrolling in a privacy incident protection application, receive, from the user device, user account information associated with one or more user accounts of the user, where the user account information includes a plurality of contextual settings, determine a risk footprint associated with the user based on the user account information, monitor the one or more user accounts, receive an indication of an incident based on monitoring the one or more user accounts and based on the risk footprint, and transmit an incident notification to a data server provider associated with the incident. The incident notification may include instructions to perform a mitigation action associated with the incident.
Abstract:
Aspects of the disclosure relate to using machine learning for optimized call routing. A computing platform may receive requests to establish a voice call session. Based on corresponding phone numbers, the computing platform may identify demographic information for corresponding clients. Using a machine learning model and based on the demographic information and representative performance data, the computing platform may score potential client-representative combinations to indicate likelihoods of a successful outcome resulting from establishing a voice call session between the respective client and representative. Scoring the potential client-representative combinations may be based on fall off rates, indicating changes in representative effectiveness as hold time increases. The computing platform may adjust the scores based on a historical frequency of interaction between each representative and clients corresponding to the identified demographic information. Based on the adjusted scores, the computing platform may select at least one of the potential client-representative combinations.
Abstract:
Methods, computer-readable media, software, systems and apparatuses may retrieve, via a computing device and over a network, information related to one or more characteristics of a particular application or service deployed in a computing environment. The particular application or service may be associated with a class of applications or services based on the information. A type of personal data collected may be determined for each application or service in the associated class. For the particular application or service, a risk metric indicative of a type of personal data collected by the particular application or service in relation to the type of personal data collected by other applications or services in the associated class may be determined. An additional application or service with a lower risk than the particular application or service may be recommended.
Abstract:
Methods and systems disclosed herein describe a universal access layer that allows a plurality of applications to obtain data and/or information from a plurality of heterogeneous data stores. The universal access layer may include one or more application data objects to validate requests, transform a format of the request, determine which data stores comprise the requested data and/or information, encrypt the request, combine responses into a single response, and retransform the response prior to sending it to the requesting application. By using the universal access layer, applications may improve the speed with which they access data and/or information from the plurality of heterogeneous data stores.