Abstract: A session continuity platform may detect a user action during a first user session associated with a first user device, wherein the first user session is associated with a first platform. The session continuity platform may determine identification information of a user associated with the user session. The session continuity platform may determine a continuity record identifier associated with the identification information. The session continuity platform may obtain, based on the continuity record identifier, activity data from a plurality of continuity records of a distributed ledger. The session continuity platform may determine, based on the activity data, activity information associated with the user action and the second user session. The session continuity platform may cause the first user device to present the activity information via a display of the user device.

Abstract: A device receives user rendering data for a 3-D rendering of a user. The 3-D rendering is a proportional representation of the user and the user rendering data is available via an application. The device determines user characteristics of the user. The device receives an indication that a user device has submitted a vehicle search request. The device identifies vehicles to recommend to the user based on an analysis of: the user characteristics, and vehicle characteristics for a collection of vehicles being offered via the application. The device causes vehicle description data for the vehicles to be displayed via an interface of the application. The device receives user interaction data that indicates a user selection of vehicle. The device causes, based on receiving the user interaction data, the interface of the application to display a placement of the 3-D rendering of the user into a 3-D rendering of the vehicle.

Abstract: A device may process, after obtaining an image that includes image data concerning a product, first audio data obtained concerning a first utterance of a user of a user device, and first video data obtained concerning a first eye gaze direction of the user, to determine a first reaction of the user to the image. The device may process, after causing display of the image and an overlay superimposed on the image by the user device, second audio data obtained concerning a second utterance of the user, and second video data obtained concerning a second eye gaze direction of the user, to determine a second reaction of the user to the image and the overlay. The device may retrain a product recommendation model using the first reaction and the second reaction, and may generate and cause display of a product recommendation based on the product recommendation model.

Abstract: A computer-implemented method for determining an actual cost of ownership of a purchase product may include determining a baseline value of the purchase product, and receiving usage information representative of usage of a user product from a computing device in communication with the user product. The purchase product and the user product may belong to a same class of products. The method also may include determining a user cost component based on the received usage information, and determining an actual cost of ownership of the purchase product based on at least the baseline value and the user cost component.

Abstract: Embodiments disclosed herein provide for a system and method for recalibrating an augmented reality experience in mobile devices using a plurality of physical markers. The system and methods provide for realigning the digital representation to the physical world using known physical locations associated with the physical markers that map directly to the digital representation.

Abstract: Aspects described herein may facilitate an automated trade-in of a vehicle with limited human interaction. A server may receive a request to begin a value determination of a vehicle associated with the user. The server may receive first data comprising: vehicle-specific identifying information, and multimedia content showing a first aspect of the vehicle. The user may be directed to place the vehicle within a predetermined staging area. The server may receive, from one or more image sensors associated with the staging area, second data comprising multimedia content showing a second aspect of the vehicle. The server may create a feature vector comprising the first data and the second data. The feature vector may be inputted into a machine learning algorithm corresponding to the vehicle-specific identifying information of the vehicle. Based on the machine learning algorithm, the server may determine a value of the vehicle.

Abstract: Various embodiments are generally directed to techniques of overlaying a virtual object on a physical object in augmented reality (AR). A computing device may receive one or more images of the physical object, perform analysis on the images (such as image segmentation) to generate a digital outline, and determine a position and a scale of the physical object based at least in part on the digital outline. The computing device may configure (e.g., rotate, scale) a 3D model of the physical object to match the determined position and scale of the physical object. The computing device may place or overlay a 3D virtual object on the physical object in AR based on a predefined location relation between the 3D virtual object and the 3D model of the physical object, and further, generate a composite view of the placement or overlay.

Abstract: Aspects described herein may allow for vehicle tracking. Systems and methods described herein may allow a vehicle to automatically detect the presence of a physical marker at a parking space. An image of the physical marker may be processed to determine the location of the vehicle, which may be stored and/or output for display.

Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for filtering vehicle information. For instance, the method may include receiving a vehicle search request from a user device, the vehicle search request including conditions with corresponding weights. The method may also include, in response to receiving the vehicle search request, forming a search query based on the conditions and the weights of the vehicle search request; obtaining vehicle information; filtering the vehicle information based on the search query to obtain a result set and a partial match set; and transmitting a search result message based on the result set and the partial match set to the user device.

Abstract: Techniques to leverage machine learning for search engine optimization (SEO). Some techniques are applicable to turnkey e-commerce solutions operating on the Internet as an online platform. These techniques use machine learning to gain insights into patterns/relationships between search terms and items for sale on the online platform. Depending on a relevancy or an accuracy of a search term to a particular item for sale, the online platform inserts the search term into the online platform such that a public search engine crawler increases a search engine result position for the online platform. Other embodiments are described and claimed.

Abstract: Aspects described herein may facilitate an automated trade-in of a vehicle with limited human interaction. A server may receive a request to begin a value determination of a vehicle associated with the user. The server may receive first data comprising: vehicle-specific identifying information, and multimedia content showing a first aspect of the vehicle. The user may be directed to place the vehicle within a predetermined staging area. The server may receive, from one or more image sensors associated with the staging area, second data comprising multimedia content showing a second aspect of the vehicle. The server may create a feature vector comprising the first data and the second data. The feature vector may be inputted into a machine learning algorithm corresponding to the vehicle-specific identifying information of the vehicle. Based on the machine learning algorithm, the server may determine a value of the vehicle.

Abstract: In certain embodiments, a vehicle may obtain a video stream via a camera system of the vehicle. The video stream may be processed to extract one or more feature vectors from the video stream. Based on the feature vectors extracted from the video stream, vehicle description information related to one or more parked vehicles in the parking area may be determined. Space information indicating locations of the parked vehicles relative to available parking spaces in the parking area may also be determined based on the feature vectors extracted from the video stream. A mapping of the parking area may then be generated based on the vehicle description information and the space information.

Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for filtering vehicle information. For instance, the method may include receiving a vehicle search request from a user device, the vehicle search request including conditions with corresponding weights. The method may also include, in response to receiving the vehicle search request, forming a search query based on the conditions and the weights of the vehicle search request; obtaining vehicle information; filtering the vehicle information based on the search query to obtain a result set and a partial match set; and transmitting a search result message based on the result set and the partial match set to the user device.

Abstract: An electronic device may include logic to provide a trust credential for linking to a permissioned network over a local network, comprising a plurality of user devices; retrieve a document in an initial status for editing, corresponding to a first state of a distributed ledger, maintained by the permissioned network; generate a first change in the document, wherein the document is in a second status; send, to the permissioned network via the local network, the first change for storage in the distributed ledger, in a second state; retrieve the document in a third status, including a second change, performed subsequently to the first change, the second change being generated by a user device, external to the electronic device, and coupled to the local network; and link to the distributed ledger to retrieve a third state of the distributed ledger, the third state comprising the first change and the second change.

Abstract: Embodiments are directed to systems, devices, methods, and techniques to determine words or word combinations of search engine queries and selected items corresponding to the words or word combinations. Embodiments also include applying a machine learning model to the word or word combinations and the selected items to determine a mapping between a word or word combination and a particular selected item, and updating attribute data in a web document with the word or word combination, wherein the web document is associated with the particular item such that a search including the word or word combination returns a result including the web document.

Abstract: A vehicle receives sensor data that includes image data of frames that depict one or more individuals outside of the vehicle, and identifies, by analyzing the sensor data using one or more attribute recognition techniques, a set of attributes of an individual of the one or more individuals. The vehicle determines a set of scores indicating a set of likelihoods of a set of vehicle configurations being a preferred vehicle configuration for the individual, based on a data model performing a machine-learning-driven analysis of attribute data identifying the set of attributes, and/or location data identifying a location of the individual relative to the vehicle. The vehicle selects a particular vehicle configuration based on a score that indicates a likelihood of the particular vehicle configuration being the preferred vehicle configuration and provides an instruction to cause a vehicle component to implement the particular vehicle configuration by updating a configurable value.

Abstract: A device having extended reality capabilities may capture a video feed including one or more video frames depicting an object that is visible in a field of view of the device. The device may provide the one or more video frames to a machine learning model that identifies the object and one or more parts of the object that are depicted in the one or more video frames. The device may obtain positional tracking information that represents a position and an orientation associated with the object relative to a coordinate space that corresponds to the field of view of the device. The device may obtain a workflow including a sequence of content items for visually inspecting the object using the extended reality capabilities of the device. The device may render digital content associated with the workflow using the extended reality capabilities of the device.

Abstract: One or more embodiments are generally directed to techniques to provide specific vehicle recommendations. Various techniques, methods, systems, and apparatuses include utilizing user web-traffic and/or one or more tags generated by application of a machine learning model to a data source, where the data source may include language with respect to one or more automobiles or vehicles, to provide a recommendation for a particular automobile.

Abstract: A computer-implemented method for using a machine-learning trained predictive engine to predict failures includes receiving electronic prior transaction data corresponding to a plurality of prior successful transactions and a plurality of prior unsuccessful transactions, and training a machine learning predictive engine based on the plurality of prior successful transactions and the plurality of prior unsuccessful transactions. Electronic transaction data may be received, the electronic transaction data being associated with a user, an item, and candidate transaction terms, the electronic transaction data being associated with a candidate transaction. The machine learning predictive engine may determine a likelihood of success of the candidate transaction based on the electronic transaction data, and display the likelihood of success of the candidate transaction.

Abstract: Systems and methods for providing a disposal recommendation for an owned vehicle are provided. The method includes generating a profile for the owned vehicle, the profile including age, mileage, and location of the owned vehicle, receiving monitoring data of the owned vehicle, and receiving sales data for non-owned vehicles corresponding to the profile. The method may further include generating predicted depreciation data of the owned vehicle, based on the sales data and the monitoring data, and providing a recommended disposal time for the owned vehicle, based on the predicted depreciation data.