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.
A driving accident simulation may be used to inform a driver of the driver's potential liability under different insurance options. The simulation may determine damages caused by the simulated accident, and identify multiple insurance options and the resulting user liability under each option. The simulation may also be used to assess an insurance adjuster's ability to estimate damages from an accident, by receiving the adjuster's estimate and comparing it to the simulation's own estimate of damages. In some embodiments, the simulation may present a driver with a simulated view from a point of view of another party to the simulated accident.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for providing information and assessing data for motor club services, namely, emergency automobile towing and travel information for members; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in providing and maintaining information related to automobile maintenance, repair services, automobile, providers, roadside assistance services, emergency road services, and general cost estimates for automobile repairs; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use with sales and consultation services for Exclusive Agents and Independent Agents; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use with the administration of employee benefit plans concerning insurance and financial aspects of retirement; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in enhancing computer security services for protecting personal data, identity theft, personal communications, and restricting unauthorized access to websites; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in monitoring websites and online publications for personal information; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in managing online accounts, online subscriptions, and personal information; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in insurance brokerage services; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in selecting extended warranties for electronic products namely, mobile phones, computers, GPS navigation devices, televisions, and tablets; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in selecting extended warranties for home appliances, namely, air conditioning units, dishwashers, refrigerators, and washing machines; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in selecting extended warranties for consumer products, namely, home and garden tools, air purifiers, air conditioners, home security systems, audio and video equipment and systems, electronic musical instruments and sound systems, video games, and electronic games; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in assessing insurance policies, claims, and accident assessments; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for assessing and enrolling in insurance plans; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in assessing and arranging subscriptions for trade-in programs for smart devices; Downloadable computer software featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use with alerts related to automobile maintenance and repair services, cost estimates for automobile repairs, scheduling for repairs, and roadside assistance Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in providing information and assessing data for motor club services, namely, emergency automobile towing and travel information for members; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in providing and maintaining information related to automobile maintenance, repair services, automobile, providers, roadside assistance services, emergency road services, and general cost estimates for automobile repairs; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use with sales and consultation services for Exclusive Agents and Independent Agents; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use with the administration of employee benefit plans concerning insurance and financial aspects of retirement; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in enhancing computer security services for protecting personal data, identity theft, personal communications, and restricting unauthorized access to websites; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in monitoring websites and online publications for personal information; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in managing online accounts, online subscriptions, and personal information; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in insurance brokerage services; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in selecting extended warranties for electronic products namely, mobile phones, computers, GPS navigation devices, televisions, and tablets; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in selecting extended warranties for home appliances, namely, air conditioning units, dishwashers, refrigerators, and washing machines; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in selecting extended warranties for consumer products, namely, home and garden tools, air purifiers, air conditioners, home security systems, audio and video equipment and systems, electronic musical instruments and sound systems, video games, and electronic games; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use in assessing insurance policies, claims, and accident assessments; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for assessing and enrolling in insurance plans; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for assessing and arranging subscriptions for trade-in programs for smart devices; Software as a service (SaaS) services featuring an artificial intelligence chat bot, large language models, agentic and generative artificial intelligence (AI) software for use with alerts related to automobile maintenance and repair services, cost estimates for automobile repairs, scheduling for repairs, and roadside assistance
4.
SYSTEM AND METHOD FOR SIMULATING TRAFFIC USING AGENT-BASED MODELING
Implementations claimed and described herein provide systems and methods for simulating traffic using synthetic data based on agent-based modeling that simulates real drivers in a particular geographic area and time frame. In one implementation, inputting, in a machine-learning model of a simulation system, real-world agent-based position data associated with a custom selection of a geographic area and a time frame. The machine-learning model of the simulation system outputs metrics associated with synthetic agent-based position data over time within a map for the simulated environment and the variation of the simulated environment, wherein the metrics represents synthetic movement behavior of agents associated with synthetic individuals based on real movement behavior associated with the geographic area and the time frame.
G06F 30/27 - Optimisation, vérification ou simulation de l’objet conçu utilisant l’apprentissage automatique, p. ex. l’intelligence artificielle, les réseaux neuronaux, les machines à support de vecteur [MSV] ou l’apprentissage d’un modèle
G01C 21/00 - NavigationInstruments de navigation non prévus dans les groupes
5.
CONSUMER ENGAGEMENT AND MANAGEMENT PLATFORM USING MACHINE LEARNING FOR INTENT DRIVEN ORCHESTRATION
Aspects of the disclosure relate to computing platforms that utilize machine learning to perform output generation based on intent identification. The computing platform may train intent orchestration models (e.g., intent identification, output generation, or communication channel) using historical data. The computing platform may data corresponding to an individual. Based on the data, the computing platform may select intent identification models, and may use them to identify an intent. Based on the intent of the individual, the computing platform may select engagement output generation models, and may use them to generate a customer engagement output. The computing platform may use a communication channel model to identify a communication channel. The computing platform may send commands directing display of the customer engagement output, which may cause a user device to display the customer engagement output using the communication channel.
Systems and methods in accordance with embodiments of the invention can proactively determine if a vehicle has stopped during a trip and calculate a likelihood that the vehicle is in need of roadside assistance. Information can be collected from a variety of devices, such as mobile phones, including the vehicle's location, the type of road, passing vehicles, and/or ambient noise. The likelihood of needing roadside assistance can be determined based on a configurable probability that the vehicle is experiencing a roadside event. The arrangements described herein provide for receiving and processing data in real-time to efficiently and accurately detect stopped vehicles, determine whether the vehicle is stopped for an urgent or non-urgent situation reason, and provide assistance accordingly.
G07C 5/02 - Enregistrement ou indication du temps de circulation, de fonctionnement, d'arrêt ou d'attente uniquement
G01C 21/28 - NavigationInstruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier avec corrélation de données de plusieurs instruments de navigation
G01S 19/25 - Acquisition ou poursuite des signaux émis par le système faisant intervenir des données d'assistance reçues en provenance d'un élément coopérant, p. ex. un GPS assisté
G06Q 30/016 - Fourniture d’une assistance aux clients, p. ex. pour assister un client dans un lieu commercial ou par un service d’assistance après-vente
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
G08G 1/052 - Détection du mouvement du trafic pour le comptage ou la commande avec des dispositions pour déterminer la vitesse ou l'excès de vitesse
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
36 - Services financiers, assurances et affaires immobilières
37 - Services de construction; extraction minière; installation et réparation
39 - Services de transport, emballage et entreposage; organisation de voyages
Produits et services
(1) Downloadable software for providing information relating to roadside assistance services and for contacting roadside assistance services. (1) Motor club services, namely, membership club services in the nature of arranging discounts for members of an automobile club from vendors of hotels and automobile rentals.
(2) Insurance services; Motor club services, namely, automotive club services, namely, providing reimbursement for legal fees related to traffic offenses.
(3) Motor club services, namely, emergency roadside services, namely emergency roadside vehicle repair services; emergency roadside assistance services, namely, responding to calls for roadside assistance, flat tire changing, emergency fuel supplying, and battery jump starting.
(4) Motor club services, namely, emergency automobile towing, emergency roadside assistance services, namely, towing, winch-out and key delivery services.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
36 - Services financiers, assurances et affaires immobilières
37 - Services de construction; extraction minière; installation et réparation
39 - Services de transport, emballage et entreposage; organisation de voyages
Produits et services
(1) Downloadable software for providing information relating to roadside assistance services and for contacting roadside assistance services. (1) Motor club services, namely, membership club services in the nature of arranging discounts for members of an automobile club from vendors of hotels and automobile rentals.
(2) Insurance services; Motor club services, namely, automotive club services, namely, providing reimbursement for legal fees related to traffic offenses.
(3) Motor club services, namely, emergency roadside services, namely emergency roadside vehicle repair services; emergency roadside assistance services, namely, responding to calls for roadside assistance, flat tire changing, emergency fuel supplying, and battery jump starting.
(4) Motor club services, namely, emergency automobile towing, emergency roadside assistance services, namely, towing, winch-out and key delivery services.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
36 - Services financiers, assurances et affaires immobilières
37 - Services de construction; extraction minière; installation et réparation
39 - Services de transport, emballage et entreposage; organisation de voyages
Produits et services
(1) Downloadable software for providing information relating to roadside assistance services and for contacting roadside assistance services. (1) Motor club services, namely, membership club services in the nature of arranging discounts for members of an automobile club from vendors of hotels and automobile rentals.
(2) Insurance services; Motor club services, namely, automotive club services, namely, providing reimbursement for legal fees related to traffic offenses.
(3) Motor club services, namely, emergency roadside services, namely emergency roadside vehicle repair services; emergency roadside assistance services, namely, responding to calls for roadside assistance, flat tire changing, emergency fuel supplying, and battery jump starting.
(4) Motor club services, namely, emergency automobile towing, emergency roadside assistance services, namely, towing, winch-out and key delivery services.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
36 - Services financiers, assurances et affaires immobilières
37 - Services de construction; extraction minière; installation et réparation
39 - Services de transport, emballage et entreposage; organisation de voyages
Produits et services
(1) Downloadable software for providing information relating to roadside assistance services and for contacting roadside assistance services. (1) Motor club services, namely, membership club services in the nature of arranging discounts for members of an automobile club from vendors of hotels and automobile rentals.
(2) Insurance services; Motor club services, namely, automotive club services, namely, providing reimbursement for legal fees related to traffic offenses.
(3) Motor club services, namely, emergency roadside services, namely emergency roadside vehicle repair services; emergency roadside assistance services, namely, responding to calls for roadside assistance, flat tire changing, emergency fuel supplying, and battery jump starting.
(4) Motor club services, namely, emergency automobile towing, emergency roadside assistance services, namely, towing, winch-out and key delivery services.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
36 - Services financiers, assurances et affaires immobilières
37 - Services de construction; extraction minière; installation et réparation
39 - Services de transport, emballage et entreposage; organisation de voyages
Produits et services
(1) Downloadable software for providing information relating to roadside assistance services and for contacting roadside assistance services. (1) Motor club services, namely, membership club services in the nature of arranging discounts for members of an automobile club from vendors of hotels and automobile rentals.
(2) Insurance services; Motor club services, namely, automotive club services, namely, providing reimbursement for legal fees related to traffic offenses.
(3) Motor club services, namely, emergency roadside services, namely emergency roadside vehicle repair services; emergency roadside assistance services, namely, responding to calls for roadside assistance, flat tire changing, emergency fuel supplying, and battery jump starting.
(4) Motor club services, namely, emergency automobile towing, emergency roadside assistance services, namely, towing, winch-out and key delivery services.
12.
System and Method for Providing Vehicle Services Based on Driving Behaviors
Systems and methods are provided for encouraging and rewarding safe driving. A safe driving evaluation system determines the safe driving behaviors necessary to earn safe driving points. The safe driving evaluation system receives vehicle telematics data from a telematics device configured to obtain vehicle telematics data during the operation of a vehicle, and determines safe driving points based on the safe driving behaviors exhibited by the vehicle telematics data. Safe driving rewards are provided where the total number of safe driving points earned by a driver exceeds predefined thresholds. The safe driving rewards may be redeemed for discounts on products or vehicle services, or for fixed prices on gas. In addition, the safe driving points may be transferred to another individual for redemption.
A driving analysis server may be configured to receive vehicle location data and/or operation data from one or more vehicle systems, identify driving trips and/or driving patterns based on the vehicle data, determine risk assessment values corresponding to the driving trips and driving patterns, and calculate driver scores based on the analyzed driving trip and driving pattern data. Destination locations may be identified for a vehicle's driving trips, and information relating to the destination locations may be retrieved and analyzed to determine risk factors and risk assessment values associated with driving to and from the destination, as well as parking at the destination. Specific driving trip types or purposes may be identified, and driving scores may be calculated based on the vehicle location and time data, including the risk factors, risk assessment values, and the determined trip types or purposes.
G07C 5/02 - Enregistrement ou indication du temps de circulation, de fonctionnement, d'arrêt ou d'attente uniquement
G01S 19/01 - Systèmes de positionnement par satellite à radiophares émettant des messages horodatés, p. ex. GPS [Système de positionnement global], GLONASS [Système global de navigation par satellite] ou GALILEO
Implementations claimed and described herein provide systems and methods for determining fuel efficiency based on sensor data from a mobile device. In one implementation, sensor data from a mobile device is collected. The sensor data includes a dataset that reflects a last trip on a vehicle by the mobile device, wherein the sensor data is collected from at least one of global position system (GPS) data and micro-electro-mechanical system (MEMS) sensor data of the mobile device. Driving events comprising at least one of one or more braking events, one or more speeding events, and one or more acceleration events are determined based on the sensor data. A fuel consumption prediction is predicted via a trained prediction model based on the driving events.
Systems and methods for notifying a user of a vehicle include at least one processor and a vehicle tire sensor of a vehicle associated with at least one tire. The vehicle tire sensor generates at least one vehicle tire metric associated with the at least one tire of the vehicle. Machine readable instructions stored in a memory cause the vehicle notification system to perform at least the following when executed by the processor: receive the at least one vehicle tire metric from the vehicle tire sensor associated with the at least one tire of the vehicle, receive a weather tire type of the at least one tire of the vehicle, generate, based on the on the at least one vehicle tire metric and the weather tire type, at least one determined metric, and generate an alert for a user of the vehicle of the at least one determined metric.
Systems and methods include generating a notification using audio, visual, tactile and/or other notification features via a vehicle notification system to a driver of a vehicle based on vehicle sensor data and/or external vehicle data regarding driver interest items such as road conditions, road hazards, nearby points of interest augmented image displays, pre-approved evacuation expenses, new driver quotes based on predicted new driver scores, insurance quotes based on bank account data, preapproved insurance related medical expenses, and the like.
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de transfert électronique de fondsArchitectures de paiement spécialement adaptées aux systèmes de banque à domicile
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer application software for mobile devices, namely, software for accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents Insurance services, namely underwriting automobile and home insurance policies Software as a service (SaaS) services featuring software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents; providing temporary use of non-downloadable cloud hosted computer software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents
18.
INTELLIGENT SYSTEMS AND METHODS FOR MONITORING A MACHINE LEARNING MODEL
Systems and methods for intelligent machine learning model monitoring may include executing statistical test(s) for metric(s) to determine whether at least one of data used or an output in each machine learning model is statistically similar to expectations based on at least one of training data or test data for each model; when a first test failure of a tested model of a plurality of machine learning models occurs based on the statistical test(s) for the metric(s) exceeding a first test threshold, automatically executing an additional test based on the first test failure and additional historical data; and automatically generating an alert of test failure for the tested model based on the additional test exceeding an additional test threshold as a second test failure. The second test failure is representative of verification of the first test failure.
Intelligent prediction systems and methods of use to analyze one or more uploaded images to generate one or more processed images via a data analytics module, determine by a neural network model a point of view and angle of view determination for each processed image, retrieve a claim identifier and associated total loss score, and generate an automated predicted total loss determination based on the total loss score and the one or more processed images from the data analytics module.
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer application software for mobile devices, namely, software for accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents Insurance services, namely underwriting automobile and home insurance policies Software as a service (SaaS) services featuring software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents; providing temporary use of non-downloadable cloud hosted computer software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer application software for mobile devices, namely, software for accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents Insurance services, namely underwriting automobile and home insurance policies Software as a service (SaaS) services featuring software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents; providing temporary use of non-downloadable cloud hosted computer software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer application software for mobile devices, namely, software for accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents Insurance services, namely underwriting automobile and home insurance policies Software as a service (SaaS) services featuring software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents; providing temporary use of non-downloadable cloud hosted computer software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents
23.
SYSTEMS AND METHODS FOR INSURANCE RATING BASED ON TELEMATICS
Systems and methods for intelligent adjustable price-per-metric rate determination include receiving telematics data comprising one or more telematics factors associated with one or more vehicles; based on the telematics data, determining a price-per-metric rate of insurance for a user of a user vehicle of the one or more vehicles; and assigning the price-per-metric rate of insurance to the user for the user vehicle.
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer application software for mobile devices, namely, software for accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents Insurance services, namely underwriting automobile and home insurance policies Software as a service (SaaS) services featuring software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents; providing temporary use of non-downloadable cloud hosted computer software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer application software for mobile devices, namely, software for accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents Insurance services, namely underwriting automobile and home insurance policies Software as a service (SaaS) services featuring software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents; providing temporary use of non-downloadable cloud hosted computer software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer application software for mobile devices, namely, software for accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents Insurance services, namely underwriting automobile and home insurance policies Software as a service (SaaS) services featuring software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents; providing temporary use of non-downloadable cloud hosted computer software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer application software for mobile devices, namely, software for accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents Insurance services, namely underwriting automobile and home insurance policies Software as a service (SaaS) services featuring software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents; providing temporary use of non-downloadable cloud hosted computer software platforms for selecting and enrolling in insurance plans, accessing insurance policy information, making payments, making claims, selecting insurance claim payment options, selecting insurance deductible payment options, and accessing information about accidents
28.
CRYPTOGRAPHICALLY PROTECTING DATA TRANSFERRED BETWEEN SPATIALLY DISTRIBUTED COMPUTING DEVICES USING AN INTERMEDIARY DATABASE
Aspects of the disclosure relate to a system and method for cryptographically protecting data transferred between spatially distributed computing devices. An intermediary database may be used to facilitate the protected data transfer and/or record the data transfers. A first computing device may transfer, to the intermediary database, encrypted data that may be securely transferred to other computing devices. A second computing device may generate a GUI used to view data available from the intermediary database. Once data is selected by the second device, the second device may transfer a key (or other encryption mechanism) to the first device. The first computing device may encrypt the data using the received key and transmit the encrypted data to the intermediary database. The intermediary database may transmit the encrypted data to the second computing device, and the second computing device may decrypt and use the data.
Intelligent prediction systems and methods of use to analyze one or more uploaded and labeled images to generate one or more processed images via a data analytics module, determine an identified property type from the processed images, generate a match between the identified property type and a reported property type associated with a claim identifier and a total loss score, and generate an automated predicted total loss determination based on the total loss score, the one or more processed images from the data analytics module, and the match.
Systems and methods provide for configuring and transferring multiple data files including image data files using a mobile device. A mobile device may acquire multiple data files including image files from disparate sources and transmit them to an enhanced image processing server. The enhanced image processing server may analyze the received image files using various techniques. To aid in analysis, the server may also interface with various internal and external databases storing reference images or other reference data of previously analyzed similar data. Further still, the enhanced image processing server may transmit a result of the analysis back to a mobile device.
Systems and methods for automatically generating quotes for a circle of protection insurance plan include identifying a type of device of network-connected device connected to a central connection hub based on information from a global device repository communicatively coupled to the central connection hub, determining, using a machine learning-based determination module and one or more connectivity rules, whether the network-connected device is eligible for the circle of protection insurance plan and generating, using an underwriting module and based on a determination that the network-connected device is eligible for the circle of protection insurance plan, a quote to update the circle of protection plan to include the network-connected device.
Methods, computer-readable media, software, and apparatuses provide a system that may facilitate communications so that parents or other superiors may monitor driving behavior of a vehicle carrying children or other subordinates. The system may allow communications to be sent from a parent computing device to a particular child computing device to set conditions for notifying the parent or superior of the driving behavior of a vehicle. Child computing devices may collect drive data (e.g., vehicle telematics data) for the system to evaluate and determine whether conditions are met (e.g., whether parental restrictions, like a geo-fence, are violated). Further, the system may send notifications to child computing devices and parent computing devices indicating whether the drive data meets the conditions of an agreement between a parent and teen. The system may also provide a web portal for use in forming the agreement between parents and their teens.
Systems, methods, and computer-readable media, are disclosed in which a variety of data describing the condition of an object can be obtained and probabilistic likelihoods of causes and/or value of damages to the object can be calculated. In a variety of embodiments, data obtained from third-party systems can be utilized in these calculations. Any of a number of machine classifiers can be utilized to generate the probabilistic likelihoods and confidence metrics in the calculated liabilities. A variety of user interfaces for efficiently obtaining and visualizing the object, the surrounding geographic conditions, and/or the probabilistic likelihoods can further be utilized as appropriate. User interfaces can include a scene sketch tool application program interface and/or a liability tool user interface and various data sources can be used to dynamically generate diagrams of object damage and/or the environment in which the object was damaged.
G06F 16/587 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation
G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
34.
SYSTEMS AND METHODS FOR AUTOMATED APPLICATION DEPLOYMENT
Systems and methods in accordance with embodiments of the present disclosure can analyze a variety of software applications, modify the software applications, and/or automatically deploy the software applications to a distributed computing system. Distributed computing systems can provide software applications in a scalable, low cost manner that can be dynamically scaled to demand. Software deployment systems in accordance with embodiments of the present disclosure can automatically process software applications to determine the suitability of the software application to be deployed to a distributed computing system and/or modify the software application for deployment. A variety of machine classifiers can be used to score various aspects of a software application to identify portions of the application for modification and/or suitability for deployment.
H04L 67/00 - Dispositions ou protocoles de réseau pour la prise en charge de services ou d'applications réseau
H04L 67/1097 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour le stockage distribué de données dans des réseaux, p. ex. dispositions de transport pour le système de fichiers réseau [NFS], réseaux de stockage [SAN] ou stockage en réseau [NAS]
36 - Services financiers, assurances et affaires immobilières
37 - Services de construction; extraction minière; installation et réparation
Produits et services
Arranging subscriptions for trade-in and upgrade programs
for smart devices; online retail store services featuring
smart devices; online auction services featuring bidding and
purchasing of smart devices. Providing extended warranties on consumer electronic
products, appliances, and consumer products, namely, home
and garden tools, air purifiers and air conditioning units,
home security systems, audio and video equipment and
systems, electronic musical instruments and sound systems,
video games and electronic games, photography equipment,
mobile phones, computers, GPS navigation devices,
televisions, tablet computers, electronic readers, mp3
players, headphones, watches, fitness trackers, dishwashers,
refrigerators, washing machines for clothes, and clothes
dryers; insurance underwriting. Maintenance and repair of cell phone related hardware.
36.
Vehicle Telematics System to Promote Good Driving Behavior Using Positive Feedback and Award Points
A system and method are disclosed to promote good driving among users. A user-customizable good driving (GD) wish list may be created, populated, modified, and/or used to promote good driving. The GD wish list may be used in conjunction with a vehicle telematics unit (VTU) to monitor, process, detect, and/or record good driving events, and communicate and/or generate positive feedback for the user. In addition to positive feedback, good driving (GD) points may be accumulated based on driving behavior. The accumulated GD points may be used in conjunction with a product and/or service offering, such as by an insurance company. Furthermore, in some examples, the system encourages users to promote good driving behavior by pledging themselves to a challenging GD wish list that will earn them more GD points and the associated benefits.
Systems and apparatuses for generating surface dimension outputs are provided. The system may collect an image from a mobile device. The system may analyze the image to determine whether they comprise one or more standardized reference objects. Based on analysis of the image and the one or more standardized reference objects, the system may determine a surface dimension output. The system may determine one or more settlement outputs and one or more repair outputs for the driver based on the surface dimension output.
As described herein, a base model based on imbalanced data may be selected for a machine learning process associated with a specific application. A first false positive error rate may be generated based on the selected base model. A plurality of imbalanced data sets may be generated based on the imbalanced data associated with the base model. A plurality of models may be generated based on the generated plurality of imbalanced data sets. A subset of the outputs of the plurality of models may be ensembled and a second false positive error rate may be generated based on the ensembled output of the subset of the plurality of models. The second false positive error rate may be determined to be less than the first false positive error rate.
Systems and methods are disclosed for determining the efficacy of an autonomous vehicle driving system in exhibiting safe driving behavior during test track scenarios. Testing parameters eliciting autonomous vehicle driving system behavior may be chosen for the test track scenario. The autonomous vehicle driving system may be tested in the test track and autonomous vehicle driving system behavior may be observed in response to the presentations of testing parameters. A safe driving score may be calculated for the autonomous vehicle driving system based on measured autonomous vehicle performance and operational data generated responsive to the presentation of testing parameters in the test track. A benchmark insurance premium may be calculated for an autonomous vehicle driving system based on the calculated safe driving score.
B60R 16/023 - Circuits électriques ou circuits de fluides spécialement adaptés aux véhicules et non prévus ailleursAgencement des éléments des circuits électriques ou des circuits de fluides spécialement adapté aux véhicules et non prévu ailleurs électriques pour la transmission de signaux entre des parties ou des sous-systèmes du véhicule
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
Systems, methods, apparatuses and computer-readable media for receiving data from one or more sensors associated with one or more home devices, such as appliances, home systems, etc. are provided. The data may be used to determine whether the home device is operating within an expected range or, if it is outside of an expected range or threshold, whether a home event has occurred. Upon occurrence of the home event, an insurance claim to cover any damage caused by the home event may be initiated and/or processed. In some examples, repair of any damage may also be coordinated by the system. In some arrangements, the initiation and/or processing of the claim, and/or coordination of the repair may be performed without any additional input from the user associated with the policy, home device, etc. or with limited additional input from the user.
Methods, computer-readable media, software, and apparatuses may determine that an expected vehicle demand will exceed an expected supply in a vehicle sharing application. In order to meet the demand, one or more users may be contacted with a request to provide a vehicle for sharing on a particular date. A machine learning algorithm may be used in determining that the expected vehicle demand will exceed the expected vehicle supply.
A method may include inputting, in a machine-learning collision prediction model, a set of one or more kinematic variables associated with a trigger event, which may be based on movement of a mobile device and may be recorded over a duration of time. The machine-learning collision prediction model may include a convolutional neural network (CNN) model layer, a long short-term memory (LSTM) model layer, and a prediction model layer. The CNN model may extract features for time segments of the duration of time, and the respective features associated with respective time segments are fed into the LSTM model layer. The machine-learning collision prediction model may generate a prediction score based on the set of one or more kinematic variables and associated with the event. The prediction score may determine a prediction that the event is a type of impact and outputting the prediction. The outputted prediction may be time-oriented.
Implementations claimed and described herein provide systems and methods for map routing matching system, wherein the one or more machine-learning models scores link candidates of location data points to determine a most probable route. In one implementation, use a machine-learning model to calculate a probability score for a plurality of link candidates. The machine-learning model scores each link candidates based on weighting set by training data, wherein the weighting associated with at least one of travel time, match distance, heading difference, speed conformity, road curvature, road classification, or travel distance versus time delay. A plurality of total probability scores derived from one or more combinations of probability scores for respective link candidates is calculated, wherein one link candidate is selected for each location data point.
Implementations include an integrated ratemaking platform utilizing a common rating core that combines the functionality of an analytics rating engine and the production rating engine. Through the platform, one or more rating plans may be generated from rating plan configurations provided to the system, analyzed for performance, and utilized in response to a rating call received at the platform. The platform may include ratemaking analytics components to analyze and evaluate rating plans based on one or more business rules and production rating components to implement the evaluated rating plans. The various components may use a common data schema for sharing data. Certified rating plans may be promoted and published to the production rating components for use in generating the rate quotes from the certified rating plans.
One or more driving analysis computing devices in a driving analysis system may be configured to analyze driving data, determine driving behaviors, and calculate driver scores based on driving data transmitted using vehicle-to-vehicle (V2V) communications. Driving data from multiple vehicles may be collected by vehicle sensors or other vehicle-based systems, transmitted using V2V communications, and then analyzed and compared to determine various driving behaviors by the drivers of the vehicles. Driver scores may be calculated or adjusted based on the determined driving behaviors of vehicle drivers, and also may be calculated or adjusted based on other the driver scores of nearby vehicles.
G08G 1/00 - Systèmes de commande du trafic pour véhicules routiers
G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
G08G 1/0967 - Systèmes impliquant la transmission d'informations pour les grands axes de circulation, p. ex. conditions météorologiques, limites de vitesse
G09B 19/16 - Conduite des véhicules ou autres moyens de transport
A method may include inputting, in a machine-learning collision prediction model, a set of one or more kinematic variables associated with a trigger event, which may be based on movement of a mobile device and may be recorded over a duration of time. The machine-learning collision prediction model may include a convolutional neural network (CNN) model layer, a long short-term memory (LSTM) model layer, and a prediction model layer. The CNN model may extract features for time segments of the duration of time, and the respective features associated with respective time segments are fed into the LSTM model layer. The machine-learning collision prediction model may generate a prediction score based on the set of one or more kinematic variables and associated with the event. The prediction score may determine a prediction that the event is a type of impact and outputting the prediction. The outputted prediction may be time-oriented.
G06N 3/0442 - Réseaux récurrents, p. ex. réseaux de Hopfield caractérisés par la présence de mémoire ou de portes, p. ex. mémoire longue à court terme [LSTM] ou unités récurrentes à porte [GRU]
Implementations claimed and described herein provide systems and methods for map routing matching system, wherein the one or more machine-learning models scores link candidates of location data points to determine a most probable route. In one implementation, use a machine-learning model to calculate a probability score for a plurality of link candidates. The machine-learning model scores each link candidates based on weighting set by training data, wherein the weighting associated with at least one of travel time, match distance, heading difference, speed conformity, road curvature, road classification, or travel distance versus time delay. A plurality of total probability scores derived from one or more combinations of probability scores for respective link candidates is calculated, wherein one link candidate is selected for each location data point.
Systems and apparatuses for generating object dimension outputs and predicted object outputs are provided. The system may collect an image from a mobile device. The system may analyze the image to determine whether it contains one or more standardized reference objects. Based on analysis of the image and the one or more standardized reference objects, the system may determine an object dimension output. The system may also determine a predicted object output that includes additional objects predicted to be in a room corresponding to the image. Using object dimension outputs and the predicted object output, the system may determine an estimated repair cost.
Methods, computer-readable media, software, and apparatuses include receiving sensor data from a sensor system associated with a vehicle during operation of the vehicle over a plurality of modes of operation, computing, based on the sensor data, a vehicle fingerprint comprising one or more vehicle characteristics over the plurality of modes of operation, monitoring additional received sensor data from the sensor system during further operation of the vehicle, determining whether an anomaly exists based on comparing the additional received sensor data to the vehicle fingerprint, and based upon determining that an anomaly exists, providing an alert to a communication interface associated with the vehicle.
B60R 25/25 - Moyens pour enclencher ou arrêter le système antivol par biométrie
B60R 25/102 - Équipements ou systèmes pour empêcher ou signaler l’usage non autorisé ou le vol de véhicules actionnant un dispositif d’alarme un signal étant envoyé vers un lieu distant, p. ex. signal radio transmis à un poste de police, à une entreprise de sécurité ou au propriétaire du véhicule
B60R 25/24 - Moyens pour enclencher ou arrêter le système antivol par des éléments d’identification électroniques comportant un code non mémorisé par l’utilisateur
B60R 25/32 - Détection relative au vol ou autres événements relatifs aux systèmes antivol de paramètres dynamiques du véhicule, p. ex. de la vitesse ou de l’accélération
B60R 25/33 - Détection relative au vol ou autres événements relatifs aux systèmes antivol de la géo-localisation, p. ex. en fournissant les coordonnées de géo-localisation (GPS)
Aspects of the present disclosure generally relate to systems and methods for implementing a state engine, and more specifically, to implementing a state engine for managing rescue operations. An example apparatus generally includes: an interface of a state engine receiving an input indicating a transition to a target state of the state engine, the target state being a state associated with a vehicle rescue operation; a verification component coupled to the interface, the verification component identifying whether the transition to the target state is valid based on one or more constraints associated with the state engine; and a transition component coupled to the verification component, the transition component performing the transition to the target state based on the identification of whether the transition to the target state is valid.
Location analysis computing devices, methods, and computer-readable media are disclosed herein for determining the position of a mobile device (smartphone, tablet computer) within an interior of a vehicle. The position of the mobile device may be calculated by detecting changes in accelerometer data. The accelerometer data may first need to be translated to determine corresponding axes, since the device may not be right side up (e.g., in a pocket). The vehicle may travel over road discontinuities such as bumps, and calculating the position of the mobile device may be based on the different magnitude and angle resulting from a first tire and a second tire hitting the bump. Data from vehicle sensors or other mobile device sensors may also be used in the calculating. Once the position is determined, commands may be sent to the mobile device to deactivate certain functionality, or to a remote server for further processing.
H04W 4/02 - Services utilisant des informations de localisation
G01C 21/10 - NavigationInstruments de navigation non prévus dans les groupes en utilisant des mesures de la vitesse ou de l'accélération
G01S 19/05 - Éléments coopérantsInteraction ou communication entre les différents éléments coopérants ou entre les éléments coopérants et les récepteurs fournissant des données d'assistance
G01S 19/14 - Récepteurs spécialement adaptés pour des applications spécifiques
H04W 4/40 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons
H04W 4/48 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons pour la communication dans le véhicule
Disclosed herein are systems and/or methods for determining an insurance status for one or more drivers and/or vehicles. The system may identify a driver of a vehicle, such as by facial recognition or a retinal scan. Based on the identification, the system may determine the insurance status of the driver. If there is an issue with the insurance status, the system may prompt the driver to take some action. The system may also institute limitations upon the vehicle if there is an issue with the insurance status. In some instances, the system may determine the insurance status for multiple drivers in the area, and may warn a driver if he or she is in the vicinity of one or more underinsured drivers and/or vehicles.
An intelligent prediction system includes one or more processors, one or more memory components, and machine-readable instructions that cause the intelligent prediction system to: receive text data comprising a plurality of speaker turn segments of a transcription of a conversation, each speaker turn segment of the plurality of speaker turn segments representative of a turn in the conversation, the plurality of speaker turn segments collectively representative of the conversation up to a point of time, generate a point in time bind probability based on a speaker turn segment bind probability of a speaker turn segment at the point in time and memory data associated with the plurality of segments up to the point in time, and generate a speaker turn segment impact score at the point in time by subtracting an immediately preceding point in time bind probability from the point in time bind probability.
G06Q 10/0639 - Analyse des performances des employésAnalyse des performances des opérations d’une entreprise ou d’une organisation
G06F 17/18 - Opérations mathématiques complexes pour l'évaluation de données statistiques
G06Q 30/0202 - Prédictions ou prévisions du marché pour les activités commerciales
G10L 15/06 - Création de gabarits de référenceEntraînement des systèmes de reconnaissance de la parole, p. ex. adaptation aux caractéristiques de la voix du locuteur
G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
G10L 15/26 - Systèmes de synthèse de texte à partir de la parole
A driving analysis server may be configured to receive vehicle operation data from vehicle sensors and telematics devices of a first vehicle, and may use the data to identify a potentially high-risk or unsafe driving behavior by the first vehicle. The driving analysis server also may retrieve corresponding vehicle operation data from one or more other vehicles, and may compare the potentially high-risk or unsafe driving behavior of the first vehicle to corresponding driving behaviors in the other vehicles. A driver score for the first vehicle may be calculated or adjusted based on the comparison of the driving behavior in the first vehicle to the corresponding driving behaviors in the other vehicles.
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
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.
Aspects of the present disclosure relate to using vehicle telematics to detect, evaluate, and respond to driving behaviors observed during a trip in a vehicle. The vehicle telematics information may characterize the observed driving behaviors, the segments traveled in the vehicle, and type of use of the vehicle. A rate to charge a driver may be based on the observed driving behaviors and a range of rates associated with the driver. The rate may fluctuate across a series of observation periods based on the driving behaviors observed during those observation periods. The rate may be presented to the driver in real-time while the driver operates a vehicle during a trip. The rate to charge the driver may further be based on use of the vehicle for personal use, ride shares, or vehicle shares.
Systems and methods are disclosed for providing roadside service through a synchronized interactive voice response (IVR) system and graphical user interface (GUI). One method may include: receiving, based on an incoming phone call from a vehicle user device, a request for roadside service for a disabled vehicle of a vehicle user; sending a text to a phone number of the vehicle user device, wherein the text includes a link to a mobile application for roadside service requests; receiving, from the vehicle user device and via the mobile application, information associated with the request for roadside service; determining, based on a location sensor of the vehicle user device, a location of the disabled vehicle; matching a roadside service provider with the disabled vehicle based on the request for roadside service; and enabling the vehicle user to track the service status of the roadside service provider through the mobile application.
36 - Services financiers, assurances et affaires immobilières
37 - Services de construction; extraction minière; installation et réparation
Produits et services
Arranging subscriptions to services for trade-in and upgrade
of smart devices for others; online retail store services
featuring smart devices for buying and selling; online
auction services featuring bidding and purchasing of smart
devices. Providing extended warranties on consumer electronic
products, appliances, and consumer products, namely, home
and garden tools, air purifiers and air conditioning units,
home security systems, audio and video equipment and
systems, electronic musical instruments and sound systems,
video games and electronic games, photography equipment,
mobile phones, computers, GPS navigation devices,
televisions, tablet computers, electronic readers, mp3
players, headphones, watches, fitness trackers, dishwashers,
refrigerators, washing machines for clothes, and clothes
dryers; insurance underwriting. Maintenance and repair of cell phone related hardware.
59.
MULTI-PLATFORM MODEL PROCESSING AND EXECUTION MANAGEMENT ENGINE
Systems and methods are disclosed for managing the processing and execution of models that may have been developed on a variety of platforms. A multi-model execution module specifying a sequence of models to be executed may be determined. A multi-platform model processing and execution management engine may execute the multi-model execution module internally, or outsource the execution to a distributed model execution orchestration engine. A model data monitoring and analysis engine may monitor the internal and/or distributed execution of the multi-model execution module, and may further transmit notifications to various computing systems.
Methods, computer-readable media, systems and apparatuses for determining and implementing hazard unit based insurance policies are presented. A user may input a preliminary navigational route. The preliminary navigational route may be parsed into a plurality of road segments. Sensor data may be received from one or more databases. The sensor data may provide information associated with driving behaviors of the user, environmental conditions of the routes on which the vehicle has traveled, and the like. A road segment hazard score may be calculated for each road segment based in part on the sensor data. A total route hazard score may be calculated based on the road segment hazard score calculated for each road segment. The total route segment score may be transmitted to a real-time vehicular service exchange. One or more bids may be received from one or more computing devices of the real-time vehicular service exchange. A bid from the one or more received bids may be selected to insure the vehicle as it travels along the preliminary navigational route.
One or more devices in an accident detection and recovery computing system may be configured to determine that vehicle accidents have occurred, collect and analyze accident characteristics and other related data, and providing customized accident recovery services. Mobile computing devices, alone or in combination with vehicle-based systems and external devices, may detect accidents or receive accident indication data. After determining that an accident has occurred, mobile computing devices and/or vehicle-based systems may be configured to determine accident characteristics, retrieve vehicle data and vehicle occupant data from one or external servers, determine the damages or potential damages resulting from the accident, and determine one or more accident recovery options or recommendations based on the accident damages. Various user interface screens may be generated and displayed via the user's mobile device and/or a vehicle-based display device to provide the user with accident information, damages, and recovery options or recommendations.
G01P 3/00 - Mesure de la vitesse linéaire ou angulaireMesure des différences de vitesses linéaires ou angulaires
G01P 3/56 - Dispositifs caractérisés par l'utilisation de moyens électriques ou magnétiques pour comparer deux vitesses
G01P 15/00 - Mesure de l'accélérationMesure de la décélérationMesure des chocs, c.-à-d. d'une variation brusque de l'accélération
G01P 15/04 - Mesure de l'accélérationMesure de la décélérationMesure des chocs, c.-à-d. d'une variation brusque de l'accélération en ayant recours aux forces d'inertie pour indiquer une valeur maximale
G16H 10/60 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients pour des données spécifiques de patients, p. ex. pour des dossiers électroniques de patients
H04W 4/02 - Services utilisant des informations de localisation
63.
INTELLIGENT STRUCTURAL PROTECTION SYSTEMS AND METHODS
Systems and methods for deployment of a protective component, generation of a customized design for the protective component, or combinations thereof are associated with a structure comprising a portion, a neural network model, processor(s), and memory storing machine readable instructions. When executed for deployment, the neural network model predicts the likelihood of the occurrence of the natural event in the geographic area within the time frame as high as defined by when the likelihood is above a threshold, and deploys the protective component for protecting the portion of the structure when the likelihood is high. For customized design, the neural network model is used to access dimension and weather data associated with a structure and weather data to generate the customized design of the protective component for the structure.
G01W 1/10 - Dispositifs pour la prévision des conditions météorologiques
G01S 19/14 - Récepteurs spécialement adaptés pour des applications spécifiques
G05B 13/02 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques
G06F 30/27 - Optimisation, vérification ou simulation de l’objet conçu utilisant l’apprentissage automatique, p. ex. l’intelligence artificielle, les réseaux neuronaux, les machines à support de vecteur [MSV] ou l’apprentissage d’un modèle
Systems and methods are provided for evaluating aggregate risk exposure of insurance policies associated with a geographical area. An insurance system may include an aggregate risk management system, which calculates an aggregate risk exposure of insurance policies associated with a geographical area, and compares the aggregate risk exposure with a maximum tolerable risk exposure for the geographical area. Based on the comparison, the aggregate risk management system determines whether more insurance policies may be issued associated with the geographical area. The aggregate risk management system may issue a block at an insurance system to prevent new insurance policies associated with a geographical area based on the aggregate risk exposure for that geographical area.
Systems and methods are disclosure for using sensors to deliver educational content to vehicle users during critical events. One method comprises: receiving, by a first computing device having at least one processor and from a user device of a vehicle user via a wireless data connection, a notification of a critical event for a vehicle of the vehicle user and a vehicle identification of the vehicle; receiving, from the user device via the first wireless data connection, user input soliciting educational content to remedy the critical event; determining, based on the received user input, a first set of search parameters; for each of the search parameters in the first set of search parameters, selecting educational content for a first list of educational content from a second list of educational content; and displaying, on the user device, the first list of educational content based on the first set of search parameters.
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
66.
ASSESSING PROPORTIONAL FAULT IN AN AUTOMOBILE ACCIDENT
Methods, computer-readable media, software, and apparatuses may assist in assessing proportional fault in an automobile accident involving an automobile having one or more autonomous features. An expected behavior of an autonomous feature is compared to an observed outcome of an accident and a fault proportion between a human driver and the autonomous feature may be determined, based on the comparison.
G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
67.
Detecting Device Movement And/Or Device Usage Within A Vehicle
Systems and methods are disclosed for receiving and transmitting accelerometer data and/or usage data, and analyzing the data to detect movement or usage of the device within a vehicle. A device, such as a mobile device, may detect a device movement event or a device usage event associated with the device. Based on the detection of the device movement event or the device usage event, a time associated with the event may be stored. The device may determine whether another event associated with the device occurs within a threshold amount of time from the time associated with the event. Based on a determination of whether the other event occurs within the threshold amount of time, the device may determine an event session associated with the device. The event session may comprise an instantaneous event or a continuous event. Data indicative of the event session may be transmitted to a server.
H04M 1/72409 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles avec des moyens de soutien local des applications accroissant la fonctionnalité par interfaçage avec des accessoires externes
H04M 1/72463 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles avec des moyens permettant d’adapter la fonctionnalité du dispositif dans des circonstances spécifiques pour limiter la fonctionnalité du dispositif
68.
SYSTEMS AND METHODS FOR GENERATING A USER INTERFACE
Implementations claimed and described herein provide systems and methods for generating an user interface in response to a request associated with a product or service. The systems and methods use one or more machine learning models to generate the user interface. The user interface is transmitted to a user device for display.
An interaction voice response apparatus and method includes obtaining, from a chat bot, interaction data from an interaction with a user and based on a prompt, generating, with a large language model communicatively coupled to the chat bot and directed by the prompt, content based on the interaction data from the interaction with the user corresponding to data fields in a format defined by the prompt, wherein the content comprises direct extractions directly extracted from the interaction data, inferences deduced from the interaction data, or combinations thereof, generating, with the large language model, deduction flag indications, wherein a positive deduction flag indication of the deduction flag indications is generated when the content comprises an inference of the inferences, and outputting a data set comprising at least one next intent recommendation as a deduction based on the content and the indications in the format.
Systems and apparatuses for using machine learning to generate a safety output are provided. In some examples, data may be received from a plurality of sources, may be analyzed and one or more machine learning datasets may be generated based on the analyzed data. In some arrangements, data may be received from one or more vehicles. The vehicles may be autonomous, semi-autonomous, or non-autonomous, and/or configured to operate in one or more of those modes. The data may be evaluated based on the one or more machine learning datasets to determine a safety output associated with the data. The safety output may then be used to classify the data and/or to generate one or more instructions for operation of an autonomous vehicle. The instruction(s) may be transmitted to the autonomous vehicle and may modify operation of the vehicle (e.g., to improve safety associated with the vehicle).
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
B60W 30/00 - Fonctions des systèmes d'aide à la conduite des véhicules routiers non liées à la commande d'un sous-ensemble particulier, p. ex. de systèmes comportant la commande conjuguée de plusieurs sous-ensembles du véhicule
G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
G08G 1/0967 - Systèmes impliquant la transmission d'informations pour les grands axes de circulation, p. ex. conditions météorologiques, limites de vitesse
71.
Data processing system for guidance, control, and testing autonomous vehicle features and driver response
Systems and methods are disclosed for guidance, control, and testing of autonomous vehicle features and a driver's response thereto. The system may activate a plurality of autonomous driving features of an autonomous vehicle. In response to a determination to initiate a driving test, the system may generate an indication to a driver of the autonomous vehicle of the initiation of the driving test and may deactivate or adjust parameters of one or more of the plurality of autonomous driving features. The system may receive, from one or more sensors of the autonomous vehicle or one or more sensors of a mobile computing device within the autonomous vehicle, driving data associated with the autonomous vehicle. Based on the driving data associated with the autonomous vehicle, the system may determine the driver's response time and actions taken by the driver during the driving test. Moreover, in response to a determination to end the driving test, the system may reactivate the one or more of the plurality of autonomous driving features previously deactivated or may readjust previously adjusted parameters. In some aspects, based on the driver's response time and actions taken by the driver during the driving test, a drive score may be generated for the driver.
B60W 50/00 - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier
B60W 10/04 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des ensembles de propulsion
B60W 10/184 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage avec des freins de roues
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
B60W 30/16 - Contrôle de la distance entre les véhicules, p. ex. pour maintenir la distance avec le véhicule qui précède
Methods, computer-readable media, software, and apparatuses may determine that an expected vehicle demand will exceed an expected supply in a vehicle sharing application. In order to meet the demand, one or more users may be contacted with a request to provide a vehicle for sharing on a particular date. A machine learning algorithm may be used in determining that the expected vehicle demand will exceed the expected vehicle supply.
Implementations claimed and described herein provide systems and methods for predicting demand associated with a product or service. The systems and methods use a machine learning model to determine a potential consumer is likely to purchase a product or a service. A notification is generated based on the determination that the potential consumer is likely to purchase the product or the service.
Implementations claimed and described herein provide systems and methods for responding to a query associated with a product or service. The systems and methods use a machine learning model to generate a recommendation and a user interface. The recommendation is transmitted to a user device for display via the user interface.
Implementations described herein provide systems, methods, and devices for vehicle occupant detection based on wireless transmission(s) from one or more wireless transmitter devices (e.g., beacons) located in the vehicle. The wireless transmitter devices can be standalone devices, such as portable low energy beacons, and/or the wireless transmitter devices can be integrated into other components of the vehicle, such as an on-board dash computer or a door handle. The systems disclosed herein receive the wireless transmission and determine transmission metrics associated with the transmission, such as a signal strength value or a transmission angle. A driver status determination and/or a passenger status determination is based on the transmission metrics. A data file converter generates a driver status data file representing the driver status determination and/or the passenger status determination. The driver status data file is sent to an application for which the driver status data file is configured.
G01S 5/02 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance utilisant les ondes radioélectriques
G01S 1/04 - Radiophares ou systèmes de balisage émettant des signaux ayant une ou des caractéristiques pouvant être détectées par des récepteurs non directionnels et définissant des directions, situations ou lignes de position déterminées par rapport aux émetteurs de radiophareRécepteurs travaillant avec ces systèmes utilisant les ondes radioélectriques Détails
H04W 4/48 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons pour la communication dans le véhicule
H04W 4/80 - Services utilisant la communication de courte portée, p. ex. la communication en champ proche, l'identification par radiofréquence ou la communication à faible consommation d’énergie
Implementations claimed and described herein provide systems and methods for responding to a query associated with a product or service. The systems and methods use a machine learning model to generate a recommendation and a user interface. The recommendation is transmitted to a user device for display via the user interface.
Implementations claimed and described herein provide systems and methods for predicting demand associated with a product or service. The systems and methods use a machine learning model to determine a potential consumer is likely to purchase a product or a service. A notification is generated based on the determination that the potential consumer is likely to purchase the product or the service.
As described herein, a base model based on imbalanced data may be selected for a machine learning process associated with a specific application. A first false positive error rate may be generated based on the selected base model. A plurality of imbalanced data sets may be generated based on the imbalanced data associated with the base model. A plurality of models may be generated based on the generated plurality of imbalanced data sets. A subset of the outputs of the plurality of models may be ensembled and a second false positive error rate may be generated based on the ensembled output of the subset of the plurality of models. The second false positive error rate may be determined to be less than the first false positive error rate.
Aspects of the disclosure relate to computing platforms that utilize machine learning to perform output generation based on intent identification. The computing platform may train intent orchestration models (e.g., intent identification, output generation, or communication channel) using historical data. The computing platform may data corresponding to an individual. Based on the data, the computing platform may select intent identification models, and may use them to identify an intent. Based on the intent of the individual, the computing platform may select engagement output generation models, and may use them to generate a customer engagement output. The computing platform may use a communication channel model to identify a communication channel. The computing platform may send commands directing display of the customer engagement output, which may cause a user device to display the customer engagement output using the communication channel.
An agent interaction apparatus, systems, and methods include obtaining streaming interaction data contemporaneously generated from an interaction with a user; determining, with a large language model, an intent expressed in the streaming interaction data; generating a prompt comprising one or more inquiries based on the intent expressed in the streaming interaction data; generating, from the streaming interaction data fed into the large language model and directed by the prompt, text corresponding to one or more responses from the user to the one or more inquiries; generating, with the large language model, at least one guidance request based on an absence of a response to, a need for clarification of, or supplemental information to request for at least one of the one or more inquiries based on the one or more responses from the user; and outputting the at least one guidance request within a guidance section of an interface.
In one aspect, a method includes receiving a telematics data associated with a vehicle collected from one or more data sources and determining, using a machine-learning model trained to identify high-risk driving behaviors using telematics data, one or more predictions based on the telematics data. A prediction of the one or more predictions is associated with a current time. The method may further include generating a time-based report of the one or more predictions. The time-based report identifies instances of the one or more predictions that reach a threshold value.
Methods and systems for entity assignment to assign an entity of a plurality of entities to a lead resource of at least two lead resources may include receiving a score for each entity of the plurality of entities. The method may further include determining a ranking of the plurality of entities based upon the score for each entity and receiving a distance between each entity of the plurality of entities and each lead resource of the at least two lead resources, wherein the plurality of entities are greater in number than the at least two lead resources. The method may also include applying an optimization algorithm based on the ranking and the distance between each entity and each lead resource and updating the optimization algorithm in real-time until each entity of the plurality of entities is paired to one of the at least two lead resources.
Aspects of the disclosure relate to a dynamic processing system for roadside service control and output generation. A computing platform may receive, from a client device, video content corresponding to a disabled vehicle, which may include geotagging information corresponding to a location of the disabled vehicle. Based on the video content and the geotagging information, the computing platform may determine a provider output indicating a potential service provider for assisting with the disabled vehicle. The computing platform may send, to the client device, an indication of the provider output. In response to receiving an indication that the potential service provider is acceptable, the computing platform may send a request to dispatch a driver of the potential service provider to the location of the disabled vehicle.
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
G06Q 10/20 - Administration de la réparation ou de la maintenance des produits
G06Q 50/40 - Procédés d’affaires s’appliquant à l’industrie du transport
G08G 1/00 - Systèmes de commande du trafic pour véhicules routiers
G08G 1/137 - Systèmes de commande du trafic pour véhicules routiers indiquant la position de véhicules, p. ex. de véhicules à horaire déterminé à l'intérieur du véhicule l'indicateur étant sous la forme d'une carte
84.
GEOGRAPHICAL RISK HEATMAP BASED ON VARIABLE RISK FACTORS
Implementations described herein provide systems and methods for generating a geographical heatmap based on variable factors. One implementation can include aggregating a plurality of data associated with a geographical location, generating a respective asset for a respective region within the geographical location, associating a respective subset of the plurality of data with the respective asset, determining a respective first type score for a respective first type data, determining a respective second type score for a respective second type data, generating a respective overall score based on the respective first type score and the respective second type score, constructing a map including each of the respective assets, and displaying, as a heatmap, the map with each respective asset.
A system for computer vision data acceptability analysis and methods of use to receive a plurality of computer vision data comprising data processed via a computer vision model with one or more rules, generate one or more metrics for each of the plurality of computer vision data based on the one or more rules, compare a compared metric of the one or more metrics for each of the plurality of computer vision data to an acceptability threshold, determine the computer vision data to be acceptable when the compared metric associated with the computer vision data is equal to or above the acceptability threshold, generate an overall acceptability score for the plurality of computer vision data, and automatically generate feedback for computer vision model processing based on the overall acceptability score to improve acceptability.
Implementations described herein provide systems and methods for generating a geographical heatmap based on variable factors. One implementation can include aggregating a plurality of data associated with a geographical location, generating a respective asset for a respective region within the geographical location, associating a respective subset of the plurality of data with the respective asset, determining a respective first type score for a respective first type data, determining a respective second type score for a respective second type data, generating a respective overall score based on the respective first type score and the respective second type score, constructing a map including each of the respective assets, and displaying, as a heatmap, the map with each respective asset.
A system includes a privacy vault storing user-associated contents. The vault also stores access permissions defined for third-parties with whom the user has a sharing relationship. An access permission defines, for at least one third party, procurement and utilization policies for vault contents accessed by the third-party. The system may access a user account to recover user-associated contents stored by the accessed account and stores the recovered contents in the privacy vault. The system receives a request from a third-party to access identified contents stored in the privacy vault and determines if the contents are procurable by the third party based on an access permission defined, in the privacy vault, for the third-party. The system provides procurable contents to the third party along with indication of any constraints on the contents defined by utilization policies of the access permission defined for the third party.
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.
Implementations claimed and described herein provide systems and methods for generating a driving behavior assessment using telematics data. The systems and methods use different types of telematics data generated via different data connections. Vehicle behavior telematics data is generated using a first type of connection with a vehicle (e.g., using an onboard diagnostics (OBD) device) and personal mobility telematics data is generated using a second type of connection via a mobile device associated with a vehicle operator. One or more driving attributes associated with the vehicle operator are determined by the system based on at least one of the vehicle behavior telematics data or the personal mobility telematics data. Scoring factors are calculated based on the one or more driving attributes. Furthermore, a policy level rate structure for an insurance policy can be generated based on the one or more scoring factors.
Apparatuses, systems, and methods are provided for the utilization of vehicle control systems to cause a vehicle to take preventative action responsive to the detection of a near short term adverse driving scenario. A vehicle control system may receive information corresponding to vehicle operation data and ancillary data. Based on the received vehicle operation data and the received ancillary data, a multi-dimension risk score module may calculate risk scores associated with the received vehicle operation data and the received ancillary data. Subsequently, the vehicle control systems may cause the vehicle to perform at least one of a close call detection action and a close call detection alert to lessen the risk associated with the received vehicle operation data and the received ancillary data.
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
B60Q 1/08 - Agencement des dispositifs de signalisation optique ou d'éclairage, leur montage, leur support ou les circuits à cet effet les dispositifs étant principalement destinés à éclairer la route en avant du véhicule ou d'autres zones de la route ou des environs les dispositifs étant des phares réglables, p. ex. commandés à distance de l'intérieur du véhicule automatiquement
B60Q 1/46 - Agencement des dispositifs de signalisation optique ou d'éclairage, leur montage, leur support ou les circuits à cet effet les dispositifs ayant principalement pour objet d'indiquer le contour du véhicule ou de certaines de ses parties, ou pour engendrer des signaux au bénéfice d'autres véhicules pour engendrer des signaux à éclats durant la marche, autres que pour signaler le changement de direction, p. ex. appels de phares
B60Q 1/50 - Agencement des dispositifs de signalisation optique ou d'éclairage, leur montage, leur support ou les circuits à cet effet les dispositifs ayant principalement pour objet d'indiquer le contour du véhicule ou de certaines de ses parties, ou pour engendrer des signaux au bénéfice d'autres véhicules pour indiquer d'autres intentions ou conditions, p. ex. demandes d'attente ou de dépassement
B60Q 9/00 - Agencement ou adaptation des dispositifs de signalisation non prévus dans l'un des groupes principaux
B60R 25/00 - Équipements ou systèmes pour empêcher ou signaler l’usage non autorisé ou le vol de véhicules
B60R 25/10 - Équipements ou systèmes pour empêcher ou signaler l’usage non autorisé ou le vol de véhicules actionnant un dispositif d’alarme
B60T 7/12 - Organes d'attaque de la mise en action des freins par déclenchement automatiqueOrganes d'attaque de la mise en action des freins par déclenchement non soumis à la volonté du conducteur ou du passager
B60T 7/18 - Organes d'attaque de la mise en action des freins par déclenchement automatiqueOrganes d'attaque de la mise en action des freins par déclenchement non soumis à la volonté du conducteur ou du passager provoqués par une commande à distance, c.-à-d. moyens de mise en action non montés sur le véhicule actionnés par un appareil sur le bord de la route
B60T 7/22 - Organes d'attaque de la mise en action des freins par déclenchement automatiqueOrganes d'attaque de la mise en action des freins par déclenchement non soumis à la volonté du conducteur ou du passager déclenchés par le contact du véhicule, p. ex. du pare-chocs, avec un obstacle extérieur, p. ex. un autre véhicule
B60W 50/08 - Interaction entre le conducteur et le système d'aide à la conduite
G05B 15/02 - Systèmes commandés par un calculateur électriques
G06N 7/01 - Modèles graphiques probabilistes, p. ex. réseaux probabilistes
Systems and methods are disclosed for generating vehicle insurance rates based on driver-independent variables and/or driver-dependent variables. Vehicle insurance rates may additionally or alternatively be based on changes in the level of autonomy of vehicles. In some embodiments, a density of vehicles near a target vehicle may be tracked. Vehicle insurance rates may be determined based on the vehicle density. Furthermore, systems and methods are disclosed for analyzing a driver's use of autonomous vehicle features and/or the driver's maintenance of the autonomous vehicle. The driver may also be taught certain driving skills by enabling vehicle teaching features. The driver's response to these teaching features may be monitored, and a reward or recommendation may be generated and provided to the driver based on the driver's response.
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.
A multi-stop route selection system may include a telematics device associated with a vehicle having one or more sensors arranged therein, a mobile device, and a server computer. The server computer may receive driving data of a driver of the vehicle and a vehicle location from the telematics device, determine one or more driving behaviors of the driver based on the driving data, receive data regarding a calendar of the driver from the mobile device, identify a plurality of appointments in the calendar, determine a route comprising multiple destinations for the driver based on the vehicle location, the one or more driving behaviors, and the plurality of appointments, transmit the route to the mobile device, receive a request to add a new destination to the route from the mobile device, generate a modified route comprising the new destination, and transmit the modified route for the driver to the mobile device.
G01C 21/34 - Recherche d'itinéraireGuidage en matière d'itinéraire
G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
H04W 4/40 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons
H04W 4/44 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons pour la communication entre véhicules et infrastructures, p. ex. véhicule à nuage ou véhicule à domicile
Systems and methods in accordance with embodiments of the invention can proactively determine if a vehicle has stopped during a trip and calculate a likelihood that the vehicle is in need of roadside assistance. Information can be collected from a variety of devices, such as mobile phones, including the vehicle's location, the type of road, passing vehicles, and/or ambient noise. The likelihood of needing roadside assistance can be determined based on a configurable probability that the vehicle is experiencing a roadside event. The arrangements described herein provide for receiving and processing data in real-time to efficiently and accurately detect stopped vehicles, determine whether the vehicle is stopped for an urgent or non-urgent situation reason, and provide assistance accordingly.
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
G01C 21/00 - NavigationInstruments de navigation non prévus dans les groupes
G01C 21/28 - NavigationInstruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier avec corrélation de données de plusieurs instruments de navigation
G01S 19/00 - Systèmes de positionnement par satellite à radiopharesDétermination de position, de vitesse ou d'attitude au moyen de signaux émis par ces systèmes
G01S 19/25 - Acquisition ou poursuite des signaux émis par le système faisant intervenir des données d'assistance reçues en provenance d'un élément coopérant, p. ex. un GPS assisté
G06Q 30/016 - Fourniture d’une assistance aux clients, p. ex. pour assister un client dans un lieu commercial ou par un service d’assistance après-vente
G07C 5/02 - Enregistrement ou indication du temps de circulation, de fonctionnement, d'arrêt ou d'attente uniquement
G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
G08G 1/052 - Détection du mouvement du trafic pour le comptage ou la commande avec des dispositions pour déterminer la vitesse ou l'excès de vitesse
95.
BILATERAL COMMUNICATION IN A LOGIN-FREE ENVIRONMENT
A method, medium, and apparatus for allowing evaluation of property, such as damaged property, remotely and efficiently. A mobile computing device may be used to conduct bilateral communication between a client and an agent for evaluating property. Systems and methods may be used to efficiently automate intake of communications and intelligently load-balance resources for handling calls.
Implementations claimed and described herein provide systems and methods for generating instructions for a mobile electric vehicle (EV) charging station to meet an EV at a particular time and place. In one implementation, EV trip data including a remaining range of the EV and an intended route of the EV is collected to determine a range of locations that the EV can stop at along its route without running out of power. Instructions to one of the locations are generated for a mobile EV charging station that is a best fit for arriving at the particular location and for the EV to reach the same location.
Methods and systems disclosed herein describe deploying a plurality of microservices to calculate an insurance rate. The plurality of microservices may operate in parallel to calculate a plurality of partial rates that are combined (e.g., added up) to determine the insurance rate. During the calculating steps, one or more rating factors may be cached and/or stored. The plurality of microservices may reduce the time and/or resources required by a processor to calculate an insurance rate, while the stored rating factors may be displayed to the user to provide greater transparency into how the insurance rate was calculated.
Aspects of the disclosure relate to computing platforms that utilize improved mitigation analysis and policy management techniques to improve onboarding security. A computing platform may determine that a predetermined period of time has elapsed since finalizing an onboarding process. The computing platform may receive spot check verification inputs indicative of a user identity and may direct a mitigation analysis and output generation platform to analyze the spot check verification inputs. The computing platform may receive an indication of a correlation between the spot check verification inputs and expected spot check verification inputs. In response to determining that the correlation exceeds a predetermined threshold, the computing platform may determine that an additional verification test should be conducted, and may direct the mobile device to display an interface that prompts for additional onboarding verification inputs.
G06F 21/32 - Authentification de l’utilisateur par données biométriques, p. ex. empreintes digitales, balayages de l’iris ou empreintes vocales
G06F 21/40 - Authentification de l’utilisateur sous réserve d’un quorum, c.-à-d. avec l’intervention nécessaire d’au moins deux responsables de la sécurité
Methods, systems, and apparatuses are described for engaging autonomous driving algorithms based on driver frustration levels and vehicle conditions. A frustration level of a driver of a vehicle may be determined using one or more sensors. Based on a determination that the frustration level satisfies a threshold, one or more automated driving algorithms which may be engaged by the vehicle to improve the safety of the driver may be determined. The threshold may be based on a road segment traveled by the vehicle, the user, or similar considerations. Based on a determination that the frustration level satisfies a threshold, engagement of the one or more automated driving algorithms may be caused.
Aspects of the disclosure relate to enhanced processing systems for providing dynamic driving metric outputs using improved machine learning methods. A computing platform may receive sensor data from vehicle sensors. The computing platform may generate a pattern deviation output corresponding to an output of a sensor data analysis model, an actual outcome associated with a lowest TTC value, and driving actions that occurred over a prediction horizon corresponding to the pattern deviation output. The computing platform may cluster the pattern deviation outputs to maximize a ratio of inter-cluster variance to intra-cluster variance. The computing platform may train a long short term memory (LSTM) for each cluster, and may verify consistency of the pattern deviation outputs in the respective clusters. After verifying the consistency of the pattern deviation outputs in each cluster, the computing platform may modify the sensor data analysis model to reflect pattern deviation outputs associated with verified consistency.
