Abstract: An augmented reality system including processors and storage devices storing instructions. The instructions may configure the processors to perform operations including determining a location of a mobile device, identifying a facility based on the location, requesting mapping data from a facility server, the mapping data comprising a plurality of vehicles, vehicle location data, and landmarks, identifying one location attribute in a video feed captured by an augmented reality viewer displayed in the mobile device, and determining whether the one location attribute matches the plurality of vehicles or the landmarks. The operations may also include identifying qualified vehicles from the vehicles based on qualification criteria, determining whether the qualified vehicles is in a field of view of the augmented reality viewer based on object attributes and the vehicle location data, and generating a modified video feed by providing an indication associated with qualified vehicles in the field of view.

Abstract: Aspects described herein may allow for generating a filter list to facilitate users to refine their online search. Data items displayed on a web page may be determined based on the user's input data, for example, based on a selection command selecting the data items. Each data item corresponds to a feature of a product. Filters corresponding to the data items may be determined and the weight of each filter may be updated. A filter list may be generated and displayed to facilitate the user to refine his search for a class of products. The filters on the filter list may be automatically ordered based on the weight of each filter. In this way, a user may be able to find filters that are associated with features that he cares about the most and therefore use the filter list to obtain more satisfying results.

Abstract: Disclosed herein are various embodiments for a vehicle listing generation and optimization system. An embodiment operates by receiving a request to generate a vehicle listing to sell a vehicle on a website. A plurality of vehicle listings similar to the vehicle to be sold are determined, the plurality of vehicle listings including a plurality of features providing information about a respective vehicle featured in the vehicle listing and a performance metric indicating an effectiveness of a respective listing. A first cluster of listings from the plurality of vehicle listings similar to the vehicle are identified based on based on performing artificial intelligence clustering with respect to the metric. Common features amongst a subset of the first cluster of listings are identified. A user interface of a sales template for selling the vehicle associated with the request via the website is generated, wherein the sales template includes the common identified features.

Abstract: Aspects described herein may allow for generating a filter list to facilitate users to refine their online search. Data items displayed on a web page may be determined based on the user's input data, for example, based on a selection command selecting the data items. Each data item corresponds to a feature of a product. Filters corresponding to the data items may be determined and the weight of each filter may be updated. A filter list may be generated and displayed to facilitate the user to refine his search for a class of products. The filters on the filter list may be automatically ordered based on the weight of each filter. In this way, a user may be able to find filters that are associated with features that he cares about the most and therefore use the filter list to obtain more satisfying results.

Abstract: A set of queries from an application executing on a client computing device is obtained. A first database based on the set of queries is searched to select a set of event types. A set of predicted parameters associated with the set of event types is sent to the application. The application includes instructions to obtain a first parameter and the set of predicted parameters via a user interface of the application and generate a message comprising the first parameter and an indicator identifying the set of predicted parameters. The first parameter and the indicator are obtained via the second message. A combined query including the first parameter and the set of predicted parameters is generated in response to obtaining the indicator. A vehicle record from the vehicle database is obtained based on the combined query. Values of the vehicle record are sent to the client computing device.

Abstract: Aspects described provide systems and methods that relate generally to image analysis and, more specifically, identifying individual components and elements in an image. The systems and methods include a valuation application executing one or more application program interfaces (APIs) communicating with one or more websites via a network, where the user is prompted to enter information and/or take pictures or videos of their vehicle that they would like to sell. The valuation application utilizes a machine learning model to identify and value the various vehicle components within the images and videos. Based on the machine learning model, the valuation application identifies each component according to the images and videos and performs a search to determine the value of the components identified. The valuation application tabulates and summarizes the vehicle component resale values and resell information for the user to view.

Abstract: A system and method that facilitates a private transaction is disclosed. The system can retrieve textual information of a webpage containing vehicle sale related information for a vehicle listed for sale by an individual. Using a natural language processing (NLP) model, the textual information may be analyzed to extract vehicle sale related information for the vehicle. The system can compare the vehicle sale related information to known parameters for the vehicle to verify the authenticity of the vehicle sale related information. Based on verifying the authenticity of the vehicle sale related information, the system can determine whether to approve financing for the vehicle. Based on determining to approve financing for the vehicle, financing terms may be generated for the vehicle. The financing terms may be transmitted to client devices.

Abstract: Disclosed herein are various embodiments for a vehicle listing generation and optimization system. An embodiment operates by receiving a request to generate a vehicle listing to sell a vehicle on a website. A plurality of vehicle listings similar to the vehicle to be sold are determined, the plurality of vehicle listings including a plurality of features providing information about a respective vehicle featured in the vehicle listing and a performance metric indicating an effectiveness of a respective listing. A first cluster of listings from the plurality of vehicle listings similar to the vehicle are identified based on based on performing artificial intelligence clustering with respect to the metric. Common features amongst a subset of the first cluster of listings are identified. A user interface of a sales template for selling the vehicle associated with the request via the website is generated, wherein the sales template includes the common identified features.

Abstract: A set of queries from an application executing on a client computing device is obtained. A first database based on the set of queries is searched to select a set of event types. A set of predicted parameters associated with the set of event types is sent to the application. The application includes instructions to obtain a first parameter and the set of predicted parameters via a user interface of the application and generate a message comprising the first parameter and an indicator identifying the set of predicted parameters. The first parameter and the indicator are obtained via the second message. A combined query including the first parameter and the set of predicted parameters is generated in response to obtaining the indicator. A vehicle record from the vehicle database is obtained based on the combined query. Values of the vehicle record are sent to the client computing device.

Abstract: Aspects described provide systems and methods that relate generally to image analysis and, more specifically, identifying individual components and elements in an image. The systems and methods include a valuation application executing one or more application program interfaces (APIs) communicating with one or more websites via a network, where the user is prompted to enter information and/or take pictures or videos of their vehicle that they would like to sell. The valuation application utilizes a machine learning model to identify and value the various vehicle components within the images and videos. Based on the machine learning model, the valuation application identifies each component according to the images and videos and performs a search to determine the value of the components identified. The valuation application tabulates and summarizes the vehicle component resale values and resell information for the user to view.

Abstract: A system and method that facilitates a private transaction is disclosed. The system can retrieve textual information of a webpage containing vehicle sale related information for a vehicle listed for sale by an individual. Using a natural language processing (NLP) model, the textual information may be analyzed to extract vehicle sale related information for the vehicle. The system can compare the vehicle sale related information to known parameters for the vehicle to verify the authenticity of the vehicle sale related information. Based on verifying the authenticity of the vehicle sale related information, the system can determine whether to approve financing for the vehicle. Based on determining to approve financing for the vehicle, financing terms may be generated for the vehicle. The financing terms may be transmitted to client devices.

Abstract: The disclosure describes a system and methods for implementing a recommendation engine. The recommendation engine can at least receive a travel history log, wherein the travel history log includes a route traversed by a customer; receive a route information from a database for the route, where the route information includes an accident history for the route; generate a route traverse percentage based on the travel history log; generate a route categorization score based on the accident history for the route and the route traverse percentage; and generate a vehicle recommendation based on the route categorization score.

Abstract: A computer-implemented method that includes receiving a request for a target vehicle including input data associated with an operator, a geographic location, and the target vehicle. The method includes determining a depreciation rate based on third-party transaction data retrieved from databases in accordance with the input data associated with the target vehicle, and a decommission rate based on third-party ownership data retrieved from databases in accordance with the input data associated with the target vehicle. The method includes determining a deterioration rate based on local environmental data retrieved from databases in accordance with the input data associated with the geographic location, and generating a regression model configured to compute an estimated value of the target vehicle during a lifetime of the target vehicle using the input data, depreciation rate, decommission rate, and deterioration rate. The method includes determining an output in response to the request for the target vehicle.

Abstract: According to certain aspects of the disclosure, a computer-implemented method may be used for providing vehicle recommendations based on traffic camera data. The method may include acquiring traffic data from a plurality of traffic cameras and determining vehicle information based on the traffic data. Additionally, calculating average idling time of vehicles based on the traffic data from the plurality of traffic cameras. Additionally, determining accident information based on the traffic data from the plurality of traffic cameras and selecting at least one available vehicle for purchase, wherein the at least one available vehicle matches one or more predetermined requirements based on the determined vehicle information, average idling time, and the determined accident information. Additionally, transmitting a recommendation based on the selected at least one available vehicle for purchase.

Abstract: A system, method, and computer-readable medium for associating a person's gestures with specific features of objects is disclosed. Using one or more image capture devices, a person's gestures and the location of that person in an environment is determined. Using determined distances between the person and objects in the environment and scales associated with features of those objects, the list of specific features in the person's field-of-view may be determined. Further, a facial expression of the person may be scored and that score associated with one or more specific features.

Abstract: Aspects described provide systems and methods that relate generally to image analysis and, more specifically, overlaying images onto a three-dimensional model of a vehicle. The systems and methods include a vehicle application that receives vehicle information via a user interface. The vehicle application receives a plurality of images that comprise images of one or more internal components of the vehicle and images of one or more external components of the vehicle. The vehicle application utilizes a machine learning model to classify actual current images and attach, overlay, and wrap the actual current images to a three-dimensional model of the vehicle. The machine learning model and vehicle application meshes the actual current images around the three-dimensional model of the vehicle to create a three-dimensional view of the vehicle. The vehicle application further displays via the user interface the three-dimensional view of the vehicle.

Abstract: Disclosed herein are method, system, and computer program product embodiments for filtering website records based on user gestures. In an embodiment, a method can include presenting, via a user device, at least one of a plurality of search filters or a plurality of website records. Further, the method can include receiving, via a touch screen interface of the user device, a user gesture comprising a graphical representation of a search filter input, the user gesture being provided over at least one of a search filter of the plurality of search filters or a website record of the plurality of website records. Additionally, the method can include determining the search filter input from the user gesture, filtering the plurality of web site records based on the search filter input, and presenting, via the user device, a filtered plurality of website records.

Abstract: According to certain aspects of the disclosure, a computer-implemented method may be used for providing a vehicle recommendation based on user gestures. The method may include displaying an image of a vehicle to a user and receiving at least one gesture from the user performed on the image of the vehicle. Additionally, the method may include assigning a value to the at least one gesture from the user and determining a feature of the vehicle based on the at least one gesture from the user. Additionally, the method may include receiving gesture information related to the at least one gesture and determining a vehicle preference of the user based on the value, the feature of the vehicle, and the gesture information. Additionally, the method may include identifying an available vehicle based on the vehicle preference of the user and displaying the available vehicle to the user.

Abstract: Disclosed herein are various embodiments for a vehicle listing generation and optimization system. An embodiment operates by receiving a request to generate a vehicle listing to sell a vehicle on a website. A plurality of vehicle listings similar to the vehicle to be sold are determined, the plurality of vehicle listings including a plurality of features providing information about a respective vehicle featured in the vehicle listing and a performance metric indicating an effectiveness of a respective listing. A first cluster of listings from the plurality of vehicle listings similar to the vehicle are identified based on based on performing artificial intelligence clustering with respect to the metric. Common features amongst a subset of the first cluster of listings are identified. A user interface of a sales template for selling the vehicle associated with the request via the website is generated, wherein the sales template includes the common identified features.

Abstract: A computer-implemented method for providing product recommendations to a user may include receiving audio data from a user device. The audio data may include human speech from a user associated with the user device. The method may further include: performing a speech-to-text process on the audio data to determine text; segmenting the text into discrete conceptual units; identifying keywords that correspond words in the text; associating keywords with the conceptual units having the corresponding words; performing a first analysis process on the conceptual units to determine a first score; performing a second analysis process portions of the human speech correlated with the conceptual units to determine a second score; determining a keyword score for each keyword based on the first and second scores of the conceptual units; determining a product recommendation based on the keywords associated with conceptual units and the corresponding keyword scores; and causing the user device to output the recommendation.