Abstract: Various aspects described herein generally relate to visualizing a vehicle history using extended reality. In some implementations, an extended reality device may obtain image data corresponding to one or more vehicle parts that are visible in a field of view of the extended reality device. The extended reality device may identify one or more anchor points in a coordinate space corresponding to the field of view of the extended reality device and obtain a vehicle history report based on an identifier associated with the vehicle. The extended reality device may obtain digital content based on one or more records contained in the vehicle history report and an expected visual appearance of the one or more parts of the vehicle. The extended reality device may render the digital content on a display of the extended reality device. Various other aspects are provided.

Abstract: Various embodiments are generally directed to techniques to provide specific vehicle recommendations to generic user requests. A method for providing the specific vehicle recommendation includes: receiving a generic automobile request from a user, applying a machine learning model (MLM) trained by a corpus of reviews to the received request, and generating, by the MLM, a recommendation for at least one specific automobile feature based on the generic automobile request.

Abstract: Techniques for providing indirect local geo-positioning using AR markers are disclosed. A first moveable AR marker can be located or found by a computing device. A location of the first moveable AR marker can be known and shared with the computing device. The location of the first moveable AR marker can be based on distance between the first moveable AR marker and a fixed AR marker. A distance to the first moveable AR marker can be determined. Based on the known location of the first moveable AR marker and the distance to the first moveable AR marker from the computing device, an estimate of the location of the computing device can be determined without having line-of-sight (LOS) to the fixed AR marker.

Abstract: A credit history blockchain wallet of the user account in one or more blocks of a credit history blockchain may be searched to identify a plurality of credit event records associated with a user account responsive to a loan request. A first loan offer may be received for the user account based on the plurality of credit event records in the credit history blockchain. First information associated with the first loan offer may be recorded in the credit history blockchain wallet, the first information associated with the user. An acceptance of the first loan offer may be received from the user account. Second information associated with the accepted first loan offer may be recorded in the credit history blockchain wallet of the user account in the credit history blockchain.

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: Various embodiments may be directed to systems, devices, apparatuses to perform techniques such as determining vehicle data for a plurality of vehicles, wherein the vehicle data may be based on detections made by input devices of a plurality of mobile devices. Embodiments may further include determining vehicle attributes for the plurality of vehicles and environmental data. Embodiments also include training a machine-learning model with the vehicle data, the vehicle attributes, and the environmental data, and the machine-learning model may be trained to detect anomalies associated with vehicles having the at least one of the vehicle attributes. Embodiments may also include a trained machine-learning model to data to detect anomalies associated with a vehicle.

Abstract: Embodiments may generally be directed components and techniques to receive and process an indication of a web-based search performed for an item of a plurality of items and determine a co-occurrence matrix comprising rows and columns having entries associated with the plurality of items. Each of the entries of the co-occurrence matrix may indicate a number of co-occurrences of two of the plurality items. Embodiments also include techniques to determine related pairs of the plurality of items based on the number of co-occurrences for each entry and a relationship threshold value indicating two of the items are related and provide an indication of each item of the plurality of items that is related to the item searched based on the related pairs determination.

Abstract: A device receives transaction data associated with an individual that is participating in a transaction for a vehicle. The device identifies transaction term values relating to the transaction. The device determines scores indicating likelihoods of the transaction term values contributing to prevention of completion of the transaction. The device receives vehicle inventory data describing vehicles. The device identifies one or more recommended vehicles, of the vehicles, based on performing a vehicle search of the vehicles described by the vehicle inventory data, where the vehicle search identifies the one or more recommended vehicles based on one or more filters. The device provides vehicle offer data for the one or more recommended vehicles to one or more other devices to permit the one or more other devices to use the vehicle offer data as part of another transaction for a particular vehicle of the one or more vehicles.

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: A sensor device may detect that a vehicle is running in an enclosed environment monitored by the sensor device based on one or more artificial intelligence algorithms and detect that the vehicle is emitting exhaust into the enclosed environment based on the artificial intelligence algorithms. To ventilate the exhaust, the sensor device generates a first command that causes a door in the enclosed environment to open based on detecting that the vehicle is emitting the exhaust into the enclosed environment. Furthermore, to stop the vehicle from running and/or emitting the exhaust into the enclosed environment, the sensor device may generate a second command that causes an ignition switch on the vehicle to disengage. The sensor device transmits the first command and the second command to one or more devices for execution such that the exhaust is ventilated from the enclosed environment and the ignition switch on the vehicle is disengaged.

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: Various embodiments are generally directed to techniques to provide specific vehicle recommendations to generic user requests. A method for providing the specific vehicle recommendation includes: receiving a generic automobile request from a user, applying a machine learning model (MLM) trained by a corpus of reviews to the received request, and generating, by the MLM, a recommendation for at least one specific automobile feature based on the generic automobile request.

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: 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: Various aspects described herein generally relate to visualizing a vehicle history using extended reality. In some implementations, an extended reality device may obtain image data corresponding to one or more vehicle parts that are visible in a field of view of the extended reality device. The extended reality device may identify one or more anchor points in a coordinate space corresponding to the field of view of the extended reality device and obtain a vehicle history report based on an identifier associated with the vehicle. The extended reality device may obtain digital content based on one or more records contained in the vehicle history report and an expected visual appearance of the one or more parts of the vehicle. The extended reality device may render the digital content on a display of the extended reality device. Various other aspects are provided.

Abstract: Methods and systems for rendering virtual displays using cryptographic symbols are disclosed. In one aspect, a display device is disclosed that includes a processor and data storage including instructions that, when executed by the processor, cause the system to perform operations. The operations include emitting infrared light toward a cryptographic symbol associated with a surface, receiving a reflection of the emitted natural or man-made sunlight from the cryptographic symbol, and, based on the reflection, decrypting the cryptographic symbol to determine a unique identifier. The operations further include, based on the identifier, generating a first virtual display, and rendering the first virtual display on an image of the surface, through a heads up display, or projected onto the surface.

Abstract: Systems and methods for locating and/or tracking objects in an environment are discussed. The system may include non-visible light emitters and a camera and server system including an image geometry module configured to determine the location of an identified object in the environment. Objects may be identified based on a predefined frequency and/or pattern of pulses.

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: A device receives, from multiple cameras, streaming video data associated with multiple vehicles and provides the streaming video data to a user device associated with a user. The device receives, from the user device, a request to control a first camera and provides, to the user device, first streaming video data associated with the first camera. The device receives, from the user device, a camera control command for the first camera and causes the first camera to perform an action. The device receives updated first streaming video data from the first camera and provides, to the user device, the updated first streaming video data. The device receives, from the user device, information identifying a first vehicle in the updated first streaming video data and identifies first augmented reality vehicle information associated with the first vehicle. The device provides the first augmented reality vehicle information to the user device.

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.