A method for processing insurance claims including receiving, by a provider computing system, background data, generating, by the provider computing system, a damage prediction model based on the background data, receiving, from a customer device, a first insurance claim corresponding to a first storm, generating, by the provider computing system, a first storm damage prediction for the first storm, applying, by the provider computing system, the first storm damage prediction to the first insurance claim, receiving, from the customer device, a first corrected insurance claim based on storm damage data, and generating, by the provider computing system, a first updated damage prediction model based on the background data and the first corrected insurance claim.
Implementations include classifying vehicle trips as similar to previous trips or trips reversed based on location information of a vehicle received from a location device. Unique tile identifiers of the trip, each corresponding to a geographic area and the location information, may be determined and used to generate a fingerprint of the trip. The derived trip fingerprint of the trip information may be compared to stored fingerprints of one or more previously received trips to determine if the new trip is similar to one or more of the previous trips or trips reversed. In one instance, two trips that share a similar route but in opposite directions may be identified as a trip pair and stored in a trip database as the trip pair.
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.
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
4.
SYSTEM AND METHOD FOR IDENTIFYING TRIP SIMILARITIES
Implementations include classifying vehicle trips as similar to previous trips based on location information of a vehicle received from a location device. Unique tile identifiers of the trip, each corresponding to a geographic area and the location information, may be determined and used to generate a fingerprint of the trip. The derived trip fingerprint of the trip information may be compared to stored fingerprints of one or more previously received trips to determine if the new trip is similar to one or more of the previous trips. In one instance, information or data of a new trip may be adjusted based on previous trip data. For example, aspects of the new trip or the previous trip may be updated with information or data of a previous trip if the new trip and the previous trip are similar.
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.
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
6.
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.
Methods and systems for receiving a plurality of documents including short text data and determining a plurality of forward similarity values based on the short text data in each of the plurality of documents, determining a plurality of reverse similarity values based on the short text data in each of the plurality of documents, generating a forward and reverse similarity matrix based on the plurality of forward similarity values and the plurality of reverse similarity values, and generating a plurality of short text similarity based clusters to group the short text data of the plurality of documents based on the forward and reverse similarity matrix.
Implementations claimed and described herein provide systems and methods for behavior assessment for an individual. In one implementation, user data for the individual is obtained from one or more digital sources. Categorized user data is created by transforming the user data into a platform independent format. The categorized user data is associated with a plurality of content-based bins. One or more behavioral insight categories are determined from the categorized user data. A plurality of behavioral metrics is determined based on the one or more behavioral insight categories and the categorized user data. A personality profile for the individual is generated by converting the plurality of behavioral metrics into one or more scores. A risk assessment for the individual is generated based on the personality profile.
Implementations described and claimed herein provide systems and methods for risk assessment. In one implementation, a telematics-centric driving risk value is generated for a specific individual by determining one or more demographic segments corresponding to the specific individual and calculating one or more risk factor values associated with the one or more demographic segments using telematics data. A telematics-weighted personalized risk value is generated by: determining one or more telematics metrics from the telematics data; calculating a telematics persona risk value based on the one or more telematics metrics; calculating a behavioral persona risk value based on one or more behavioral metrics; calculating a household persona risk value based on one or more household metrics; and calculating a finance persona risk value based on one or more finance metrics. A telematics-centric risk prediction value is generated based on the telematics-centric driving risk value and the telematics-weighted personalized risk value.
Implementations include providing travel assistance services via a mobile device to dispatch a travel assistance vehicle to a user and transport the user to a safe destination. For example, a user of the travel assistance system may desire to be removed from a potentially dangerous situation, such as when traveling internationally in which the user may be unable to contact the authorities directly. The travel assistance system may be accessed by the mobile device in response to a situation for which a user may request a type of travel assistance response, such as a travel assistance vehicle or instructions on navigating a potentially unsafe situation. A travel assistance response may be provided based on information obtained from the mobile device, secondary information from databases, and/or a user profile. A risk assessment of the situation may be calculated by the system to determine the travel assistance response.
G06Q 10/08 - Logistique, p.ex. entreposage, chargement ou distribution; Gestion d’inventaires ou de stocks
G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
G08G 1/0967 - Systèmes impliquant la transmission d'informations pour les grands axes de circulation, p.ex. conditions météorologiques, limites de vitesse
G08G 1/00 - Systèmes de commande du trafic pour véhicules routiers
11.
SYSTEMS AND METHODS FOR DATA INSIGHTS FROM CONSUMER ACCESSIBLE DATA
Methods, computer-readable media, software, and apparatuses may provide data insights information to a third-party organization from consumer accessible data, accessible data via private/shared/vendor online data storage, or accessible data to devices under the control and configured by consumers. The third-party organization may compose a query comprising questions that can be answered or filled in with the consumer accessible data. A data insights server may request a response to the query from the consumers, wherein the response is derived from the consumer accessible data. The data insights server may request each of the plurality of consumer devices for the response to the query to be delivered to the requestor directly, without the insights server receiving the response. The data insights server may register responses from consumers to insight requests so as to determine compensation required to be provided from the third-party organization and to each participating/responding consumer.
Methods, computer-readable media, software, and apparatuses may calculate a digital identity score from verifiable credentials from a consumer's digital wallet. The systems and methods may score the consumer's identity based on the type and issuer of the digital credentials or verifiable credentials the consumers holds in the consumer's digital wallet. The systems and methods may issue consumers a digital identity score verifiable credential. The consumers may prove their digital identity score to various digital partners to gain preferential treatment, save time, and save money.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
13.
DYNAMIC FILLABLE FORM RENDERING ENGINE UTILIZING COMPILATIONLESS MODIFICATIONS
Methods and systems for compilationless modification of a fillable form may include receiving a ruleset and generating a script file based upon the ruleset. The method may also include retrieving data from one or more data sources according to the script file and generating a data map file configured to provide a mapping of the retrieved stored data to the fillable form. The method may further include rendering the fillable form according to tagged fields populated with the retrieved stored data via the data map file, wherein the tagged fields correspond to fields in the data map file.
An intelligent scoring system includes a scorecard tool, a user input device, a memory component, a processor; and machine-readable instructions. The scorecard tool includes a scorecard and a neural network model. The machine-readable instructions stored in the memory component cause the intelligent scoring system to: receive a parameter rating for the scorecard for a first portion of a plurality of business performance parameters; automatically input the parameter rating for the scorecard for a second portion of the plurality of business performance parameters; associate a weighting with each parameter rating; estimate a parameter outcome score for each of the first portion and the second portion of the plurality of business performance parameters based on each parameter rating and weighting; automatically estimate an overall outcome score; and automatically generate a recommendation for improving the level of performance of the business unit.
G06Q 10/0639 - Analyse des performances des employés; Analyse des performances des opérations d’une entreprise ou d’une organisation
G06Q 10/0637 - Gestion ou analyse stratégiques, p. ex. définition d’un objectif ou d’une cible pour une organisation; Planification des actions en fonction des objectifs; Analyse ou évaluation de l’efficacité des objectifs
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.
Embodiments include implementing an iterative process to automatically develop a chatbot conversation for a conversation designer by receiving a conversation design input of one or more conversation design inputs from the conversation designer, identifying an intent based on the conversation design input, generating a development event based on the intent, retrieving a conversation chat flow from a set of conversation chat flows of a code sheet based on the development event, the code sheet comprising a set of conversations, the set of conversation chat flows, and a set of rules for code retrieval based on the set of conversations and the set of conversation chat flows, retrieving a chatbot computer program code based on the conversation chat flow and the set of rules from the code sheet, and repeating the iterative process until the chatbot computer program code is automatically retrieved from a code repository for each conversation design input.
H04L 51/00 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p.ex. courriel
G06F 40/00 - Maniement de données en langage naturel
Implementations described herein provide systems and methods for vehicle telematics control. In one implementation, telematics data for a particular user is obtained. The telematics data is captured using at least one sensor associated with a vehicle in connection with an operation of the vehicle by the particular user. A privacy vault of the particular user is identified. The privacy vault has a user-defined access permission set for at least one service provider. The telematics data is stored in the privacy vault. Access to the telematics data stored in the privacy vault by the at least one service provider is controlled. The access to the telematics data controlled according to the user-defined access permission set for the at least one service provider.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds
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.
A system collects ongoing user activity information relating to a predefined activity, using one or more devices having a predefined relationship to a user and determines an environmental impact value of the predefined activity based on environmental impact caused by one or more aspects of the predefined activity. The system determines at least one change to the predefined activity that would achieve a diminished environmental impact, suggests the change to the user via a device interface and, responsive to acceptance of the change, implements a control strategy to assist the user in achieving the change.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
A system receives a request to add one or more permissions for a third-party entity to access a privacy vault associated with a user and determine one or more types of contents that are stored by the privacy vault and that the entity intends to access, the determination based on identification of the one or more types of contents by the entity. The system defines a permissions policy applicable to the entity defining permissions relating to access of contents and that encompasses at least permissions relating to access of the one or more types of contents and determines whether the permissions policy falls within user-defined guidelines for automatic acceptance of new permissions policies. Further, system presents the permissions policy to a user for acceptance or modification responsive to the permissions policy falling outside the user-defined guidelines.
Methods, computer-readable media, software, and system may generally identify, determine, and understand the significance of commute location data using telematics data. The system and methods may identify significant commute location data and points by analyzing telematics data and capturing GPS locations associated with the mobility of a user. The commute location data may be classified as data points including origin, destination, and waypoints. This commute location data may be used with metadata to identify significant locations associated with the user. The commute location data may also be used with metadata to understand mobility behavior of the user. Lastly, the commute location data may be used with metadata to determine risk associated with the user, such as based on a risk map.
Methods, computer-readable media, software, and system may generally build and quantify mobility patterns based on user location data, both at an individual level and an aggregate level. The system may determine the origin and destination data for each trip taken by a user. The system may then define areas of mobility using a mobility graph built from the data. The graph may include nodes and edges. In some examples, the nodes are constructed from the origins and destinations of the trajectories using spatial clustering techniques. Further, the edges between nodes may be constructed based on the trips between them, such as two nodes are connected by an edge if there is at least one trip between them. The edges may be given different weights based on trip frequencies. The system may then determine a region of mobility using the generated mobility graph and data clustering techniques.
Aspects of the disclosure relate to an automated iterative predictive modeling computing platform that iteratively requests additional data from external data sources to iteratively generate a more accurate insurance premium estimation. In some instances, the automated iterative predictive modeling computing platform may generate an insurance premium estimation using affordable insurance data and using estimated data in place of missing data. If the insurance premium estimation does not meet predefined confidence thresholds, the automated iterative predictive modeling computing platform may retrieve additional data that is more expensive but also has a likelihood to generate a more accurate insurance premium estimation. This process may be repeated using different data sets from different external data sources until a sufficiently accurate insurance premium estimate is generated by the automated iterative predictive modeling computing platform.
Aspects of the disclosure relate to using ultrasonic or other types of signals to determine a distance between a transmitter and one or more mobile devices. The distance may be used to facilitate travel on foot or in a vehicle. One aspect disclosed provides a computing platform that may receive ultrasonic sensing data associated with mobile devices in a vehicle from a signal transmitter. Unique identifiers of the mobile devices may be determined. Based on the ultrasonic sensing data and the unique identifier, a relative distance from the signal transmitter to each mobile device in the vehicle may be determined. The computing platform may use a machine learning classifier to determine that a particular occupant is a driver in the vehicle based on the relative distance.
G06V 20/59 - Contexte ou environnement de l’image à l’intérieur d’un véhicule, p.ex. concernant l’occupation des sièges, l’état du conducteur ou les conditions de l’éclairage intérieur
G06V 20/52 - Activités de surveillance ou de suivi, p.ex. pour la reconnaissance d’objets suspects
G06V 10/70 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique
G06V 10/74 - Appariement de motifs d’image ou de vidéo; Mesures de proximité dans les espaces de caractéristiques
G01S 1/72 - 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 émetteu; Récepteurs travaillant avec ces systèmes utilisant des ondes ultrasonores, sonores ou infrasonores
G01S 11/14 - Systèmes pour déterminer la distance ou la vitesse sans utiliser la réflexion ou la reradiation utilisant des ondes ultrasonores, sonores ou infrasonores
25.
COMPUTER VISION METHODS FOR LOSS PREDICTION AND ASSET EVALUATION BASED ON AERIAL IMAGES
Aspects of the disclosure relate to using computer vision methods to forecast damage. A computing platform may receive historical images comprising aerial images of residential properties and historical loss data corresponding to the residential properties. Using the historical images and the historical loss data, the computing platform may train a computer vision model, which may configure the computer vision model to output loss prediction information directly from an image. The computing platform may receive a new image corresponding to a particular residential property, and may analyze the new image, using the computer vision model, which may directly result in a likelihood of damage score. Based on the likelihood of damage score, the computing platform may send likelihood of damage information and one or more commands directing a user device to display the likelihood of damage information, which may cause the user device to display the likelihood of damage information.
Aspects of the disclosure relate to using machine learning methods for identity health scoring. A computing platform may train a machine learning model, using historical event information, by: 1) classifying the historical event information using logical regression, and 2) after classifying the historical event information, performing time series calibration on the classified historical event information, wherein training the machine learning model configures the machine learning model to output identity health information. The computing platform may receive new event information. The computing platform may input the new event information into the machine learning model, which may cause the machine learning model to output the identity health information. The computing platform may send, to a client device, the identity health information and one or more commands directing the client device to display an identity health interface, which may cause the client device to display the identity health interface.
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.
An intelligent adjuster assignment system includes a crowdsourcing platform, one or more processors, one or more memory components, and machine readable instructions that cause the intelligent adjuster assignment system to: receive an insurance claim during a period of time, determine a plurality of real-time adjuster priority scores based on one or more weighted parameters for a plurality of adjusters of an adjuster pool on the crowdsourcing platform during the period of time, determine a top-ranked adjuster from the plurality of adjusters based on the plurality of real-time adjuster priority scores, and assign the insurance claim to the top-ranked adjuster.
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
29.
DATA PROCESSING SYSTEMS WITH MACHINE LEARNING ENGINES FOR DYNAMICALLY GENERATING RISK INDEX DASHBOARDS
Methods, computer-readable media, software, and apparatuses include receiving, from a plurality of risk information sources, risk information associated with a user account, wherein the risk information includes a plurality of risk components, determining, for each of the plurality of risk components, an impact score and a risk probability by applying a machine learning model to risk information associated with the user account, generating an interactive risk index dashboard including a plurality of interactive risk index elements, wherein each of the plurality of interactive risk index elements is associated with a risk component of the plurality of risk components, and displaying, on the display of the apparatus, the interactive risk index dashboard, wherein each of the plurality of interactive risk index elements is displayed in a portion of the interactive risk index dashboard in accordance with a respective determined impact score and risk probability.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
Methods, computer-readable media, software, and apparatuses include activating a telematics system to collect telematics data associated with operation of a vehicle during a first window of time, receiving, by a computing device associated with the vehicle, telematics data from the telematics system during the first window of time, identifying one or more parameters associated with operation of the vehicle based on analyzing the telematics data, determining whether the one or more parameters meets a safe driving threshold, and upon determining that the one or more parameters meets the safe driving threshold, transmitting the telematics data to a third party server or device.
H04W 4/38 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour la collecte d’informations de capteurs
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
Aspects of the present disclosure provide systems and methods for vehicle sharing. One aspect includes a vehicle sharing system including a data collection component configured to receive vehicle owner information and user information. The vehicle sharing system may also include a matching component configured to determine a match between a vehicle owner and a vehicle user based on the vehicle owner information and the user information. In some aspects, the vehicle owner information includes vehicle owner social data and the user information includes vehicle user social data. The vehicle sharing system may also include a communication interface configured to send an indication of the match between the vehicle owner and the vehicle user.
Methods, computer-readable media, software, systems and apparatuses may receive, from a user device, notification of a user enrolling in a privacy incident protection application, receive, from the user device, user account information associated with one or more user accounts of the user, where the user account information includes a plurality of contextual settings, determine a risk footprint associated with the user based on the user account information, monitor the one or more user accounts, receive an indication of an incident based on monitoring the one or more user accounts and based on the risk footprint, and transmit an incident notification to a data server provider associated with the incident. The incident notification may include instructions to perform a mitigation action associated with the incident.
Aspects of the disclosure relate to using machine learning for optimized call routing. A computing platform may receive requests to establish a voice call session. Based on corresponding phone numbers, the computing platform may identify demographic information for corresponding clients. Using a machine learning model and based on the demographic information and representative performance data, the computing platform may score potential client-representative combinations to indicate likelihoods of a successful outcome resulting from establishing a voice call session between the respective client and representative. Scoring the potential client-representative combinations may be based on fall off rates, indicating changes in representative effectiveness as hold time increases. The computing platform may adjust the scores based on a historical frequency of interaction between each representative and clients corresponding to the identified demographic information. Based on the adjusted scores, the computing platform may select at least one of the potential client-representative combinations.
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.
B60W 30/182 - Sélection entre plusieurs modes opératoires, p.ex. confort ou sportif
B60W 50/00 - COMMANDE CONJUGUÉE DE PLUSIEURS SOUS-ENSEMBLES D'UN VÉHICULE, DE FONCTION OU DE TYPE DIFFÉRENTS; SYSTÈMES DE COMMANDE SPÉCIALEMENT ADAPTÉS AUX VÉHICULES HYBRIDES; SYSTÈMES D'AIDE À LA CONDUITE DE VÉHICULES ROUTIERS, NON LIÉS À LA COMMANDE D'UN SOUS-ENSEMBLE PARTICULIER - 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 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
35.
AUTONOMOUS DRIVING ALGORITHM EVALUATION AND IMPLEMENTATION
Methods and systems for autonomous driving algorithm evaluation are described herein. A computing device may receive, via telematics sensors associated with a vehicle, telematics data corresponding to one or more trips taken by the vehicle during a period of time. Portions of the telematics data corresponding to use of an autonomous driving algorithm may be determined. One or more performance metrics of the autonomous driving algorithm may be determined based on the portions of the telematics data corresponding to use of the autonomous driving algorithm. The one or more performance metrics may be compared to one or more other performance metrics, such as those corresponding to other autonomous driving algorithms. An autonomous vehicle score may be assigned to the autonomous driving algorithm. Based on the autonomous vehicle score, an indication of a second autonomous driving algorithm may be sent to the vehicle.
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
Methods and systems for tracking driver behavior across a variety of vehicles are described herein. One or more first performance metrics which indicate performance of a first vehicle when driven by a user may be determined. One or more second performance metrics indicating performance of a second vehicle when driven by the user may be determined. The first vehicle and the second vehicle may be compared to determine a vehicle difference. The performance metrics may be compared. One or more third performance metrics that predict performance of a third vehicle, different from the first vehicle and the second vehicle, when driven by the user may be determined based on the vehicle difference and the comparison. Whether to provide the user access to the third vehicle may be determined based on the one or more third performance metrics.
Aspects of the disclosure relate to using machine learning for remote wake up of a mobile device. A computing platform may receive historical data corresponding to driving trip patterns. The computing platform may train a machine learning model using the historical data corresponding to the driving trip patterns. The computing platform may receive initial data corresponding to a particular individual, and input the initial data into the machine learning model, which may cause output of a predicted trip start time of a driving trip of the particular individual. The computing platform may send, to a mobile device corresponding to the particular individual, one or more commands directing the mobile device to wake up prior to the predicted trip start time and to initiate collection of driving trip data corresponding to the driving trip, which may cause the mobile device to be configured for the collection of driving trip data.
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.
H04W 4/38 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour la collecte d’informations de capteurs
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
B60R 25/10 - VÉHICULES, ÉQUIPEMENTS OU PARTIES DE VÉHICULES, NON PRÉVUS AILLEURS Équipements ou systèmes pour interdire ou signaler l’usage non autorisé ou le vol de véhicules actionnant un dispositif d’alarme
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
39.
INTELLIGENT PREDICTION SYSTEMS AND METHODS FOR CONVERSATIONAL OUTCOME MODELING FRAMEWORKS FOR SALES PREDICTIONS
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.
Methods, computer-readable media, software, systems and apparatuses may retrieve, via a computing device and over a network, information related to one or more characteristics of a particular application or service deployed in a computing environment. The particular application or service may be associated with a class of applications or services based on the information. A type of personal data collected may be determined for each application or service in the associated class. For the particular application or service, a risk metric indicative of a type of personal data collected by the particular application or service in relation to the type of personal data collected by other applications or services in the associated class may be determined. An additional application or service with a lower risk than the particular application or service may be recommended.
Aspects of the disclosure relate to computing platforms that utilize third party data for customized output generation. A computing platform may receive encrypted data corresponding to a travel history. The computing platform may decrypt a portion of the encrypted data, resulting in first decrypted travel history data. The computing platform may direct a user device to display the first decrypted travel history data, along with a first option to continue decrypting a subsequent portion of the encrypted data and a second option to delete the first decrypted travel history data. After receiving a selection of the first option, the computing platform may decrypt the subsequent portion of the encrypted data. After determining that the encrypted data is fully decrypted, the computing platform may process the decrypted data to generate a customized product output, and may direct the user device to display the customized product output.
G09G 5/00 - Dispositions ou circuits de commande de l'affichage communs à l'affichage utilisant des tubes à rayons cathodiques et à l'affichage utilisant d'autres moyens de visualisation
H04L 9/00 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité
Methods, computer-readable media, software, and apparatuses may retrieve, from an industry standard setting scoring system and for a vulnerability, a temporal score based on a pre-revision version of a scoring system, and predict, based on a machine learning model and based on the temporal score for the vulnerability, an updated temporal score based on a post-revision version of the scoring system. A mitigating factor score, indicative of a mitigation applied to the vulnerability by an enterprise organization, may be determined. A risk score may be generated for each vulnerability, as a composite of the updated temporal score and the mitigating factor score. The risk scores for vulnerabilities in a collection of vulnerabilities may be aggregated to determine an enterprise risk score for the enterprise organization. In some instances, the enterprise risk score may be displayed via a graphical user interface.
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.
G06F 7/00 - Procédés ou dispositions pour le traitement de données en agissant sur l'ordre ou le contenu des données maniées
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p.ex. pour le traitement simultané de plusieurs programmes
G06F 17/22 - Manipulation ou enregistrement au moyen de codes, p.ex. dans une séquence de caractères de texte
G06F 17/30 - Recherche documentaire; Structures de bases de données à cet effet
G06Q 40/00 - Finance; Assurance; Stratégies fiscales; Traitement des impôts sur les sociétés ou sur le revenu
44.
NATURAL LANGUAGE PROCESSING PLATFORM FOR AUTOMATED TRAINING AND PERFORMANCE EVALUATION
Aspects of the disclosure relate to computing platforms that utilize improved natural language processing techniques for performance evaluation and training. A computing platform may automatically determine, based on audio transcription files, a model for dynamic performance evaluation and training, which may be dynamically updated as additional audio transcription files are received. The computing platform may receive and analyze an additional audio transcription file using natural language processing and the model, which may result in proficiency scores. Based on the proficiency scores, the computing platform may calculate an overall proficiency score and identify areas for improvement associated with the first individual. Based on the areas for improvement, the computing platform may determine performance feedback tailored to the individual and may send, to a user device associated with the individual, the performance feedback.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
G06Q 50/00 - Systèmes ou procédés spécialement adaptés à un secteur particulier d’activité économique, p.ex. aux services d’utilité publique ou au tourisme
45.
NEARBY DRIVER INTENT DETERMINING AUTONOMOUS DRIVING SYSTEM
An autonomous driving system capable of determining an intent of a nearby human driver and taking an action to avoid a collision is presented. The system may receive a current state of a nearby vehicle, determine an expected action of a human driver of the nearby vehicle by determining a result of a reward function, the reward function being a linear combination of feature functions, where each feature function is a neural network which has been trained to reproduce a corresponding algorithmic feature function, and based on the determined expected action of the human driver, taking an action to avoid a collision.
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.
Methods, computer-readable media, software, and apparatuses may retrieve, from a computing device at a vehicle, driving data, and determine, based on the driving data, a range of time when a driver of the vehicle has a low likelihood of accessing a web resource over a network. An online activity may be detected for an account associated with the driver. In some aspects, a time of the online activity may be compared to the range of time. Based upon a determination that the time of the online activity is within the range of time, a potentially unauthorized activity may be identified. In some aspects, in response to the potentially unauthorized activity, one or more steps may be triggered to protect the driver from the potentially unauthorized activity.
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
G06F 21/78 - Protection de composants spécifiques internes ou périphériques, où la protection d'un composant mène à la protection de tout le calculateur pour assurer la sécurité du stockage de données
G06F 21/80 - Protection de composants spécifiques internes ou périphériques, où la protection d'un composant mène à la protection de tout le calculateur pour assurer la sécurité du stockage de données dans les supports de stockage magnétique ou optique, p.ex. disques avec secteurs
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
Systems and methods in accordance with embodiments of the invention can obtain and use a variety of telematics data to classify trips taken by a vehicle. Trip models can be generated based on telematics data captured during the operation of a vehicle. A variety of features of the trip model, such as the timing and/or location of stops made by the vehicle during one or more trips, can be used to classify the trip as a business trip or a personal trip. In several embodiments, machine classifiers are trained to classify features within the trip models based on historical trips that have been classified as business trips or personal trips. A number of trip models can be combined with other driver attributes to classify a particular vehicle and/or driver as engaged with a transportation network company.
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
G07C 5/02 - Enregistrement ou indication du temps de circulation, de fonctionnement, d'arrêt ou d'attente uniquement
G07C 5/06 - Enregistrement ou indication du temps de circulation, de fonctionnement, d'arrêt ou d'attente uniquement sous forme de graphique
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
G07C 5/12 - 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 sous forme de graphique
49.
PROCESSING SYSTEM FOR DYNAMIC EVENT VERIFICATION & SENSOR SELECTION
Aspects of the disclosure relate to computing platforms that utilize improved techniques for dynamic event verification. A computing platform may receive first source data comprising driving data associated with a vehicle over a time period. Based on the first source data, the computing device may determine that the vehicle experienced an event, resulting in an event output. In response to determining the event output, the computing device may generate a request for second source data associated with the vehicle over the time period. The computing device may receive, from a sensor device, the second source data. Based on a comparison of the first source data to the second source data, the computing platform may determine an event comparison output. The computing platform may determine that the event comparison output exceeds a predetermined comparison threshold, and may send an indication of an event in response.
H04W 4/38 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour la collecte d’informations de capteurs
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
H04W 4/46 - 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 de véhicule à véhicule
H04W 4/90 - Services pour gérer les situations d’urgence ou dangereuses, p.ex. systèmes d’alerte aux séismes et aux tsunamis
B60W 30/08 - Anticipation ou prévention de collision probable ou imminente
B60W 40/10 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés au mouvement du véhicule
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
Aspects described herein may allow for a plug-in device including a base having a plurality of apertures extending therethrough. A first PCB has a first surface defining a first plane, and a plurality of pins connected to and extending outwardly from the first surface, with each pin being received in one of the apertures of the base. A bracket secures the first PCB to the base. A second PCB is secured to the bracket, extending outwardly from the first PCB and defining a second plane, with the second plane being at an acute angle with respect to the first plane. An antenna housing is secured to the bracket and the second PCB and includes at least a first antenna. A cover is releasably secured to the base.
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
H01R 13/66 - Association structurelle avec des composants électriques incorporés
51.
SYSTEMS AND METHODS OF CONNECTED DRIVING BASED ON DYNAMIC CONTEXTUAL FACTORS
Systems including one or more sensors, coupled to a vehicle, may detect sensor information and provide the sensor information to another computing device for processing. A system includes one or more sensors, coupled to a vehicle and configured to detect sensor information, and a computing device configured to communicate with one or more mobile sensors to receive the mobile sensor information, communicate with the one or more sensors to receive the sensor information, and analyze the sensor information and the mobile sensor information to identify one or more risk factors.
G06F 17/00 - TRAITEMENT ÉLECTRIQUE DE DONNÉES NUMÉRIQUES Équipement ou méthodes de traitement de données ou de calcul numérique, spécialement adaptés à des fonctions spécifiques
Methods, computer-readable media, software, and apparatuses may calculate and inform a consumer of company privacy scores corresponding to companies with which the consumer has a corresponding account, or for a company associated with a website that a consumer may visit. A consumer privacy score may also be determined, based on the company privacy scores. The company privacy scores may be based on a calculation including elements of a privacy practice of the corresponding company and elements of a privacy policy of the corresponding company.
Methods, computer-readable media, systems, and/or apparatuses for evaluating movement data to identify a user as a driver or non-driver passenger are provided. In some examples, movement data may be received from a mobile device of a user. The movement data may include sensor data including location data, such as global positioning system (GPS) data, accelerometer and/or gyroscope data, and the like. Additional data may be retrieved from one or more other sources. For instance, additional data such as usage of applications on the mobile device, public transportation schedules and routes, image data, vehicle operation data, and the like, may be received and analyzed with the movement data to determine whether the user of the mobile device was a driver or non-driver passenger of the vehicle. Based on the determination, the data may be deleted in some examples or may be further processed to generate one or more outputs.
H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
Methods, computer-readable media, software, and apparatuses are provided to assist a user and vendor in completing an online trusted transaction. Trusted vendor websites are verified and user identities are confirmed through a cyber-security safe logon credentialing system. The vendor can be confident that the user identity has been verified to be who they say they are and the user can be confident that they are using a trusted verified vendor website.
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
G06F 21/20 - par limitation de l'accès aux nœuds dans un système informatique ou un réseau informatique
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
55.
SYSTEMS AND METHODS FOR OBTAINING DATA ANNOTATIONS
Systems and methods are provided for obtaining data annotations from a crowdsourced group of individuals. The individuals can be provided with a set of data describing damage to an item and a variety of annotations can be applied to the data. In a variety of embodiments, multiple individuals can review the same claim and a final claim outcome can be determined based on the multiple reviews. In many embodiments, machine classifiers can process the set of data to identify particular features within the data. Scoring data can be generated, based on annotations provided by other individuals and/or machine classifiers that reflects the adjuster's skill at identifying features within the data and annotating the data. Claims can be assigned to individuals based on the score assigned to the individual.
Methods and apparatuses for identifying and executing one or more interactive condition evaluation tests and collecting and analyzing user behavior data to generate an output are provided. In some examples, user information may be received and one or more interactive condition evaluation tests may be identified. An instruction may be transmitted to a computing device of a user and executed on the computing device to enable functionality of one or more sensors that may be used in the identified tests. Upon initiating a test, data may be collected from the one or more sensors. The collected sensor data may be transmitted to the system and processed using one or more machine learning datasets. Additionally, user behavior data may be collected and processed using one or more machine learning datasets. The sensor data, the user behavior data, and other data may be used together to generate an output.
Methods, computer-readable media, software, and apparatuses may assist the user in understanding their unique digital footprint and the connections from the data within the footprint to the user's connections online and in the physical world. The determined information may be visually displayed to the user along with recommendations regarding digital safety.
Methods, computer-readable media, software, and apparatuses may assist a consumer in deleting personal information held by a data broker. Entities holding the consumer's personal information may be discovered and automated actions for purging or deleting the consumer's personal information may be determined. The methods, computer-readable media, software, and apparatuses may assist the consumer in updating privacy settings associated with accounts at various entities.
A system including a processor and memory may provide for automated support communications, such as communications with individuals who need assistance. Automated communications may use one or more factors to determine how to adjust communications according to the needs of a user. For example, automated communications may be adjusted based on, e.g., a keyword used by a user in the user's communications, or a location associated with the user's mobile device or user vehicle. Automated communications may be adjusted in timing, frequency, or content. One or more external events (e.g., phone call, dispatch request, additional automated communication) may be triggered based on the automated communications.
H04W 64/00 - Localisation d'utilisateurs ou de terminaux pour la gestion du réseau, p.ex. gestion de la mobilité
H04W 4/02 - Services utilisant des informations de localisation
G08B 25/01 - Systèmes d'alarme dans lesquels l'emplacement du lieu où existe la condition déclenchant l'alarme est signalé à une station centrale, p.ex. systèmes télégraphiques d'incendie ou de police caractérisés par le moyen de transmission
G08B 1/00 - Systèmes de signalisation caractérisés seulement par la forme de transmission du signal
H04W 4/90 - Services pour gérer les situations d’urgence ou dangereuses, p.ex. systèmes d’alerte aux séismes et aux tsunamis
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
G10L 15/18 - Classement ou recherche de la parole utilisant une modélisation du langage naturel
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
Systems and methods in accordance with embodiments of the invention can automatically track the creation of documents, such as source code files and unit tests, along with the development of those documents. The document creation and development workflow can be automatically validated against a defined set of standards to ensure that the documents are properly created. The review of the documents can also be automatically validated to ensure that the review process is properly completed. A variety of metrics can be generated regarding errors and issues identified during the validation processes. These metrics can be used to identify common issues, automatically generate proactive suggestions to avoid issues during document creation and testing, and/or generate developer profiles indicating the performance of particular developers.
THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY (USA)
Inventeur(s)
Aragon, Juan Carlos
Phillips, Derek
Madigan, Regina
Chintakindi, Sunil
Kochenderfer, Mykel
Abrégé
Aspects of the disclosure relate to a dynamic distance estimation output platform that utilizes improved computer vision and perspective transformation techniques to determine vehicle proximities from video footage. A computing platform may receive, from a visible light camera located in a first vehicle, a video output showing a second vehicle that is in front of the first vehicle. The computing platform may determine a longitudinal distance between the first vehicle and the second vehicle by determining an orthogonal distance between a center-of-projection corresponding to the visible light camera, and an intersection of a backside plane of the second vehicle and ground below the second vehicle. The computing platform may send, to an autonomous vehicle control system, a distance estimation output corresponding to the longitudinal distance, which may cause the autonomous vehicle control system to perform vehicle control actions.
G01C 3/12 - Mesure des distances dans la ligne de visée; Télémètres optiques en utilisant un triangle parallactique ayant des angles variables et une base de longueur fixe, dans la station d'observation, p.ex. dans l'instrument avec observation monoculaire en un simple point, p.ex. du type à coïncidence
G01C 3/02 - Mesure des distances dans la ligne de visée; Télémètres optiques - Détails
B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p.ex. en freinant ou tournant
B60W 30/16 - Contrôle de la distance entre les véhicules, p.ex. pour maintenir la distance avec le véhicule qui précède
G06K 9/32 - Alignement ou centrage du capteur d'image ou de la zone image
62.
SYSTEMS AND METHODS FOR AUTOMATING AND MONITORING SOFTWARE DEVELOPMENT OPERATIONS
Systems and methods are disclosed for automating and monitoring software development operations. The systems may facilitate a user to submit a request to receive information related to a software application development across a development operations (DevOps) pipeline, and to efficiently receive an accurate response to the request. A natural language processing application may use query parameters from the request to form a query. The query may be sent to an artificial intelligence markup language (AIML) interpreter to retrieve the requested information from a database. Alternatively or additionally, the query may be sent to an application associated with an integration of a plurality of DevOps tools in the DevOps pipeline. The application may develop a dynamic response to the request.
Methods, computer-readable media, software, and apparatuses may assist a consumer in keeping to their preferred privacy preferences when making a purchase online. Differences between the privacy policy of a vender and the privacy preferences of the consumer may be output for display to the consumer, along with alternative vendor recommendations, including vendors having privacy policies more closely match with the privacy preferences of the consumer.
G06F 15/173 - Communication entre processeurs utilisant un réseau d'interconnexion, p.ex. matriciel, de réarrangement, pyramidal, en étoile ou ramifié
G06F 16/00 - Recherche d’informations; Structures de bases de données à cet effet; Structures de systèmes de fichiers à cet effet
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
G06Q 50/00 - Systèmes ou procédés spécialement adaptés à un secteur particulier d’activité économique, p.ex. aux services d’utilité publique ou au tourisme
A autonomous driving system may self-modify based on observation of driving situations encountered after deployment. The autonomous driving system may take exploratory actions in various driving scenarios and may learn from observing outcomes of the exploratory actions. Driver reaction models corresponding to drivers of nearby vehicles may be determined. Learnings may be shared to and/or received from a central system and/or other autonomous driving systems.
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
B60W 30/00 - 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
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. pilote automatique
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
65.
SAFE HAND-OFF BETWEEN HUMAN DRIVER AND AUTONOMOUS DRIVING SYSTEM
Methods, computer-readable media, software, and apparatuses may determine whether a human driver, or an autonomous driving system, should be in control of a vehicle in response to a detection of an unexpected event. A decision may be made to pass control from the autonomous driving system to the human driver, if it is determined that the human driver can handle the unexpected event more safely than the autonomous vehicle.
B60W 50/00 - COMMANDE CONJUGUÉE DE PLUSIEURS SOUS-ENSEMBLES D'UN VÉHICULE, DE FONCTION OU DE TYPE DIFFÉRENTS; SYSTÈMES DE COMMANDE SPÉCIALEMENT ADAPTÉS AUX VÉHICULES HYBRIDES; SYSTÈMES D'AIDE À LA CONDUITE DE VÉHICULES ROUTIERS, NON LIÉS À LA COMMANDE D'UN SOUS-ENSEMBLE PARTICULIER - 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 50/12 - Limitation de la possibilité de commande du conducteur en fonction de l'état du véhicule, p.ex. moyens de verrouillage des grandeurs d'entrées pour éviter un fonctionnement dangereux
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
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. pilote automatique
66.
SYSTEM AND METHODS FOR ANALYZING ROADSIDE ASSISTANCE SERVICE OF VEHICLES IN REAL TIME
Systems, apparatuses, and methods for providing roadside assistance services are described herein. The system may include network computing devices and computing devices associated with user vehicles and service vehicles. The system may predict incoming requests for roadside assistance services, and may allocate service providers among various geographical regions and/or time slots to handle the incoming requests. The system may receive a request for a roadside assistance service from a user. The system may select an appropriate service provider to assist the user, and may assign the service request to the selected service provider.
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.
G06F 19/00 - Équipement ou méthodes de traitement de données ou de calcul numérique, spécialement adaptés à des applications spécifiques (spécialement adaptés à des fonctions spécifiques G06F 17/00;systèmes ou méthodes de traitement de données spécialement adaptés à des fins administratives, commerciales, financières, de gestion, de surveillance ou de prévision G06Q;informatique médicale G16H)
Systems, apparatuses, and methods for providing roadside assistance services are described herein. The system may include network computing devices and computing devices associated with user vehicles and service vehicles. The system may predict incoming requests for roadside services, and may allocate service providers among various geographical regions and/or time slots to handle the incoming requests. The system may receive a request for a roadside service from a user. The system may select an appropriate service provider to assist the user, and may assign the service request to the selected service provider.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison
According to some aspects of this disclosure a roadside assistance application programming interface (API) may allow any type of application, internet of things device, voice recognition device, and others to provide roadside assistance functionality. According to some aspects of this disclosure a device may communicate with sensors or an on-board diagnostics system of a vehicle and retrieve vehicle data. The device may recommend a service based on the vehicle data. The device may send a request for roadside assistance. The device may be used to enroll a user as a member of a roadside assistance benefits program. The above mentioned steps may all be performed via a single application running on the device. According to some aspects of this disclosure a device may process a roadside assistance request and determine a roadside assistance service provider to send to a user that requested roadside assistance.
H04W 64/00 - Localisation d'utilisateurs ou de terminaux pour la gestion du réseau, p.ex. gestion de la mobilité
H04W 4/02 - Services utilisant des informations de localisation
G08B 25/01 - Systèmes d'alarme dans lesquels l'emplacement du lieu où existe la condition déclenchant l'alarme est signalé à une station centrale, p.ex. systèmes télégraphiques d'incendie ou de police caractérisés par le moyen de transmission
all network access and that encrypts all over the air or over the wire traffic mitigates these risks. However, virtual client networks (VPNs) client applications can be difficult to set up and need to be always on to ensure that all network activity is secure. By embedding a VPN capability and automating the connection process, a safe and secure network connection can be made available to users of computing devices. An embedded private connect VPN system may use Domain Name Server (DNS) functionality to determine which data or content streams are to be transmitted through a generated private connect VPN tunnel.
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p.ex. pour le traitement simultané de plusieurs programmes
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
Systems and methods in accordance with embodiments of the invention can proactively determine if an individual is likely in need of roadside assistance. Information can be collected from the individual's phone, including the person's location, the type of road, ambient noise, and/or motion of nearby objects. If it is determined that the individual likely needs roadside assistance, the system can proactively contact the individual to see if roadside assistance is desired, and if so, initiates roadside assistance. The system also can provide helpful information, such as safety information, and/or automatically contact other individuals to alert them of the roadside event and the location of the individual.
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
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 1/127 - Systèmes de commande du trafic pour véhicules routiers indiquant la position de véhicules, p.ex. de véhicules à horaire déterminé à une station centrale
72.
ADAPTABLE ON-DEPLOYMENT LEARNING PLATFORM FOR DRIVER ANALYSIS OUTPUT GENERATION
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.
Aspects of the disclosure relate to dynamic driving metric output platforms that utilize improved computer vision methods to determine vehicle metrics from video footage. A computing platform may receive video footage from a vehicle camera. The computing platform may determine that a reference marker in the video footage has reached a beginning and an end of a road marker based on brightness transitions, and may insert time stamps into the video accordingly. Based on the time stamps, the computing platform may determine an amount of time during which the reference marker covered the road marking. Based on a known length of the road marking and the amount of time during which the reference marker covered the road marking, the computing platform may determine a vehicle speed. The computing platform may generate driving metric output information, based on the vehicle speed, which may be displayed by an accident analysis platform. Based on known dimensions of pavement markings the computing platform may obtain the parameters of the camera (e.g., focal length, camera height above ground plane and camera tilt angle) used to generate the video footage and use the camera parameters to determine the distance between the camera and any object in the video footage.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06T 7/246 - Analyse du mouvement utilisant des procédés basés sur les caractéristiques, p.ex. le suivi des coins ou des segments
G06T 7/80 - Analyse des images capturées pour déterminer les paramètres de caméra intrinsèques ou extrinsèques, c. à d. étalonnage de caméra
G06T 7/50 - Récupération de la profondeur ou de la forme
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
Methods, computer-readable media, systems, and/or apparatuses for providing offer and insight generation functions are provided. For instance, user input may be received requesting generation of an offer. In response to receiving the request, an application may be transmitted to a device, such as a mobile device of a user. In some examples, the application may be executed by the device and may facilitate establishing a communication session with a third party system, identifying and extracting data from the third party system, and transmitting the extracted data to an entity for evaluation. In some examples, evaluation by the entity may include generating one or more insights, outputs and the like. In some arrangements, the evaluation may be performed using machine learning and, in some examples, may be performed in real-time or near real-time.
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p.ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comport
Aspects of the disclosure relate to a system and method for securely authenticating a device via token(s) and/or verification computing device(s). A verification computing device may generate a pseudorandom number or sequence. Based on the pseudorandom number or sequence, the verification computing device may select a first plurality of parameters associated with a user of a device to be authenticated. The verification computing device may transmit, to the device, the pseudorandom number or sequence, and the device may select a second plurality of parameters. The device may generate a token based on the second plurality of parameters. The device may send the token to another device, and the other device may send the token to the verification computing device. The verification computing device may authenticate the device based on the token.
Aspects of the disclosure provide a computer-implemented method and system for the assignment of crowdsourced roadside assistance service providers to distressed vehicles/drivers requiring roadside assistance. The methods and systems may include a roadside assistance service provider system with a collection module, an assignment module, and a feedback module. The collection module collects roadside assistance service provider information and historical statistics from real-world information and stores the information in a database that may then be analyzed using particular rules and formulas. The assignment module assigns particular roadside assistance service providers to particular distressed vehicles/drivers based on one or more characteristics. The feedback module may provide near real-time cues to the roadside assistance service provider's mobile device, such as alerting when the amount of time spent on a task exceeds a predefined threshold, flagging high priority tasks/assignments, providing a technical reference for the repair.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison
H04W 4/02 - Services utilisant des informations de localisation
Exhaustive driving analytical methods, systems, are apparatuses are described. The methods, systems, are apparatuses relate to monitoring driver and/or driving behaviors in view of an exhaustive list of variables to determine safety factors, identify times to react to events, and contextual information regarding the events. The methods, systems, and apparatuses described herein may determine, based on a systematic model, reactions and reaction times, compare the vehicle behavior (or lack thereof) to the modeled reactions and reaction times, and determine safety factors and instructions 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
78.
LOGICAL CONFIGURATION OF VEHICLE CONTROL SYSTEMS BASED ON DRIVER PROFILES
Apparatuses, systems, and methods are provided for the logical configuration of vehicle control systems based on driver profiles. A vehicle control computer may identify driving behavior of a driver of a vehicle through vehicle operation data provided by one or more of: vehicle sensors, a telematics device, and a mobile device. Based on the driving behavior, the vehicle control computer may develop a first driving profile for the driver of the vehicle. The vehicle control computer transmit the first driving profile to a remote server storing driving profiles of a plurality of users. The vehicle control computer may download a second driving profile associated with a different driver from the remote server. The vehicle control computer may configure vehicle operations based off of the second driving profile associated with the different driver and may actuate vehicle operation based on the configuration.
B60W 50/00 - COMMANDE CONJUGUÉE DE PLUSIEURS SOUS-ENSEMBLES D'UN VÉHICULE, DE FONCTION OU DE TYPE DIFFÉRENTS; SYSTÈMES DE COMMANDE SPÉCIALEMENT ADAPTÉS AUX VÉHICULES HYBRIDES; SYSTÈMES D'AIDE À LA CONDUITE DE VÉHICULES ROUTIERS, NON LIÉS À LA COMMANDE D'UN SOUS-ENSEMBLE PARTICULIER - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier
79.
PROCESSING SYSTEM FOR EVALUATING AUTONOMOUS VEHICLE CONTROL SYSTEMS THROUGH CONTINUOUS LEARNING
Aspects of the disclosure relate to an autonomous vehicle evaluation system that performs continuous evaluation of the actions, strategies, preferences, margins, and responses of an autonomous driving control system. A computing platform may receive sensor data from one or more autonomous vehicle sensors, manufacturer computing platform, or V2X computing platform. Based on this sensor data, the computing platform may determine one or more driving patterns. Based on a primary context corresponding to the one or more driving patterns, the computing platform may group the one or more driving patterns. The computing platform may determine a driving pattern degradation output indicating degradation corresponding to the one or more grouped driving patterns, and the computing platform may send the driving pattern degradation output to an autonomous driving system, which may cause the autonomous driving system to take corrective action accordingly.
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. pilote automatique
Methods, computer-readable media, software, and apparatuses may assist a consumer in keeping track of a consumer's accounts in order to prevent unauthorized access or use of the consumer's identified accounts. Upon discovery of a consumer's accounts, the methods, computer-readable media, software, and apparatuses may determine information that may be shared, used, or transferred by the companies, institutions, or organizations for each of the discovered accounts. The determined information may be visually displayed to the consumer along with recommendations regarding digital safety.
A system may receive information indicating a service area of a shared mobility service, calculate information indicating one or more of risk or revenue associated with the provision of shared mobility services in the service area, determine an adjusted service area, wherein the adjusted service area is associated with one or more of a reduction in risk or an increase in revenue, and transmit information indicating the adjusted service area to a device associated with the shared mobility service.
A system may receive information indicating a driver requesting a shared vehicle, estimate, based on web browsing information associated with the driver, one or more characteristics of the driver, determine, based on the characteristics of the driver, a driver safety score indicating an estimated risk of an accident involving the driver, select, from a plurality of available vehicles, a subset of the plurality of available vehicles based on the driver safety score, and cause the display of a user interface offering the subset of the plurality of available vehicles to the driver.
Electronic display systems, including roadside display devices, vehicle-based devices, personal mobile devices, advertising servers and/or networks, and/or additional external data sources may operate individually or in combination to identify vehicle locations, driving routes, driver and passenger characteristics, driving behavior and patterns, telematics data, and the like. Vehicle and individual characteristics and/or telematics data may be determined based on data received from traffic cameras, vehicle-based devices, personal mobile devices, telematics devices, software applications, etc. Based on the vehicle characteristics, individual characteristics, and telematics data, content, such as digital display or audio content, may be determined for output on various devices, such as electronic roadside displays to be viewable by the approaching vehicles, or other devices to be accessible by associated individuals. Various techniques may be used to determine customized content. Additionally, certain systems may be interactive to allow user responses and follow-up content via on-board vehicle or user devices.
G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds
G08G 1/09 - Dispositions pour donner des instructions variables pour le trafic
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
84.
DATA PROCESSING SYSTEM WITH MACHINE LEARNING ENGINE TO PROVIDE ROADSIDE ASSISTANCE FUNCTIONS
Arrangements for receiving requests for roadside assistance, generating user interfaces and using machine learning to generate roadside assistance instructions are provided. A request for roadside assistance may be received. A user and one or more partners may be identified based on the request. A profile associated with the user, partner or the like may be identified. A user interface may be generated based on the profile and may include features unique to the profile, partner, or the like. In some arrangements, the interface may include a first portion and a second portion. Selection of an option from the first portion may cause the system to identify data for display in the second portion and cause the data to be displayed in the second portion. Machine learning may be used to determine or identify one or more roadside assistance instructions and a roadside assistance instruction may be generated and executed.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
85.
PROCESSING SYSTEM HAVING A MACHINE LEARNING ENGINE FOR PROVIDING A COMMON TRIP FORMAT (CTF) OUTPUT
Aspects of the disclosure relate to enhanced telematics processing systems with improved third party source data integration features and enhanced customized driving output determinations. A computing platform may receive telematics data and third party source data. The computing platform may enrich the telematics data using the third party source data. After generating the enriched telematics data, the computing platform may use machine learning algorithms and datasets to validate the enriched telematics data. The computing platform may ingest, via a batch ingestion process, the enriched telematics data. For example, the computing platform may store the enriched telematics data and generate additional enriched telematics data until expiration of a predetermined period of time. The computing platform may ingest the enriched telematics data associated with each trip. Once the enriched telematics data has been ingested, the computing platform may generate a standardized common trip format output for each trip.
G06F 15/18 - dans lesquels un programme est modifié en fonction de l'expérience acquise par le calculateur lui-même au cours d'un cycle complet; Machines capables de s'instruire (systèmes de commande adaptatifs G05B 13/00;intelligence artificielle G06N)
86.
SYSTEMS AND METHODS FOR GENERATING AN ASSESSMENT OF SAFETY PARAMETERS USING SENSORS AND SENSOR DATA
Systems and methods are disclosed for generating an assessment of safety parameters using sensors and sensor data. One method may include, receiving, by a computing device having one or more processors and from a user device, a request for generating an neighborhood safety assessment for a desired geographic area, wherein the request is based on an assessment of a first neighborhood safety parameter of a plurality of neighborhood safety parameters; determining, by the computing device, one or more sensors associated with the desired geographic area; receiving, by the computing device in real time and from the one or more sensors, a present value for a characteristic of the first neighborhood safety parameter of the one or more neighborhood safety parameters; and generating, based on the received present value, an assessment of the first neighborhood safety parameter of the one or more neighborhood safety parameters for the desired geographic area.
Systems and methods in accordance with arrangements described herein can include identifying a variety of accounts associated with a user and determining a set of actions that can be taken with respect to the accounts. For instance, upon death of a user, a predetermined set of actions can be executed to transfer one or more assets as defined in a digital will. The accounts can be identified by scanning one or more accounts associated with the user. The accounts associated with the user and/or the account actions for the accounts can be automatically maintained over time. On an account transfer event, each of the accounts can be automatically transferred and/or closed in accordance with the determined account actions. In many embodiments, a password manager is maintained to facilitate the review of accounts and the performance of the appropriate actions on the occurrence of a transfer event.
Systems and methods are disclosed for determining whether or not a crash involving a vehicle has occurred. A computing device may receive acceleration measurement(s) measured by one or more accelerometers during a time window. The computing device may determine, for one or more acceleration measurements, a corresponding acceleration magnitude. Based on the corresponding acceleration magnitude(s), the computing device may identify, from the acceleration measurement(s), an acceleration measurement and/or may determine whether the acceleration magnitude exceeds a threshold acceleration magnitude. The computing device may corroborate whether a vehicle associated with the mobile computing device was involved in a crash. Data associated with the acceleration magnitude and/or an event, such as a crash event, may be transmitted to a server.
B60R 21/0136 - Circuits électriques pour déclencher le fonctionnement des dispositions de sécurité en cas d'accident, ou d'accident imminent, de véhicule comportant des moyens pour détecter les collisions, les collisions imminentes ou un renversement réagissant à un contact effectif avec un obstacle
B60R 21/01 - Circuits électriques pour déclencher le fonctionnement des dispositions de sécurité en cas d'accident, ou d'accident imminent, de véhicule
B60R 21/013 - Circuits électriques pour déclencher le fonctionnement des dispositions de sécurité en cas d'accident, ou d'accident imminent, de véhicule comportant des moyens pour détecter les collisions, les collisions imminentes ou un renversement
B60R 21/0132 - Circuits électriques pour déclencher le fonctionnement des dispositions de sécurité en cas d'accident, ou d'accident imminent, de véhicule comportant des moyens pour détecter les collisions, les collisions imminentes ou un renversement réagissant à des paramètres de mouvement du véhicule
89.
CONTROLLING VEHICLES USING CONTEXTUAL DRIVER AND/OR RIDER DATA BASED ON AUTOMATIC PASSENGER DETECTION AND MOBILITY STATUS
A system may determine an initial safety prediction for a driver or rider associated with a shared mobility service. Then the system may receive, from various sensors, sensor data collected during operation of a vehicle. The system may determine a subset of the sensor data related to one or more shared mobility statuses, then determine, based on the subset of the sensor data, a safety score for the driver and/or rider. The system may further perform operations based on the safety score and/or the initial safety prediction.
Aspects of the disclosure relate to multicomputer processing of vehicle operational data from telematics devices and other sources with centralized event control. An event control computing platform may receive vehicle operational data from a telematics device associated with a user. Subsequently, the event control computing platform may identify, based on the received data, whether at least one criterion associated with the user has been satisfied. If the received data indicates that the at least one criterion associated with the user has been satisfied, then the event control computing platform may generate a command configured to cause a change to a subunit of user data and then may transmit the generated command to a subunit provisioning server.
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. pilote automatique
91.
CRYPTOGRAPHICALLY TRANSMITTING AND STORING IDENTITY TOKENS AND/OR ACTIVITY DATA AMONG SPATIALLY DISTRIBUTED COMPUTING DEVICES
Aspects of the disclosure relate to a system and method for cryptographically transmitting and storing identity tokens and/or activity data among spatially distributed computing devices. The system may comprise a plurality of chains, such as an identity chain and an activity chain. In some aspects, identity data associated with a user may be used to generate an identity token for the user. The identity token may be transmitted to a plurality of computing devices for verification. Based on a verification of the identity token, the identity token may be stored in the identity chain. A request to perform an activity may also be received, and identity data associated with the user may be received in order to authenticate the user. The computing device may generate, based on the received identity data, an identity token for the user. The identity token may be compared to the identity token stored in the identity chain, and the user may be authenticated based on the comparison. An activity token for the activity may be generated, and the activity token may be stored in the activity chain.
G06F 21/30 - Authentification, c. à d. détermination de l’identité ou de l’habilitation des responsables de la sécurité
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
Methods, computer-readable media, software, and apparatuses may assist in proactively warning a consumer they are a victim or possible target of a cyber-attack or cyber-threat. To discover whether a consumer may be a victim, the methods, computer-readable media, software, and apparatuses will monitor the Surface Web, Deep Web, and Dark Web for potential cyber-threats and cyber-attacks. If one is discovered, the methods, computer-readable media, software, and apparatuses will compare the criteria of victims of targeted in the cyber-attack and compare that criteria with consumer profiles. If a consumer profile matches the criteria, the methods, computer-readable media, software, and apparatuses will notify the consumer of the threat.
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).
Systems, methods, computer-readable media, and apparatuses for identifying and executing one or more interactive condition evaluation tests to generate an output are provided. In some examples, user information may be received by a system and one or more interactive condition evaluation tests may be identified. An instruction may be transmitted to a computing device of a user and executed on the computing device to enable functionality of one or more sensors that may be used in the identified tests. A user interface may be generated including instructions for executing the identified tests. Upon initiating a test, data may be collected from one or more sensors in the computing device. The data collected may be transmitted to the system and may be processed using one or more machine learning datasets to generate an output.
Aspects of the disclosure relate to facilitating cross-platform transportation arrangements with third party providers. In some instances, a first computing transportation may scrape information from one or more third party computing devices. The first computing device may populate a transportation arrangement resource shell with the scraped information from the one or more third party computing devices. In response to populating the transportation arrangement resource shell, the first computing device may retrieve stored data corresponding to visual elements of the first computing device. Using the retrieved data, the first computing device may generate a composite rendering that provides information associated with the one or more third party computing devices with visually perceptible elements of the retrieved data corresponding to the first computing device.
A system may receive video of a damaged vehicle, perform image analysis of the video to determine one or more frames of the video that include a damaged portion of the vehicle, further analyze the one or more frames of the video that include a damaged portion of the vehicle to determine a damaged cluster of parts of the vehicle, determine whether the damaged cluster of parts should be repaired or replaced, map the damaged cluster of parts to one or more parts in a vehicle-specific database of parts, and generate, based on the mapping, a list of parts for repair or replacement.
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.
G06F 15/18 - dans lesquels un programme est modifié en fonction de l'expérience acquise par le calculateur lui-même au cours d'un cycle complet; Machines capables de s'instruire (systèmes de commande adaptatifs G05B 13/00;intelligence artificielle G06N)
98.
EVENT-BASED CONNECTED VEHICLE CONTROL AND RESPONSE SYSTEMS
Event-based connected vehicle control and response systems, methods, and apparatus are disclosed. An example method comprises identifying the occurrence of an event, storing first data corresponding to apparatus operation for a first threshold amount of time prior to the event, during the occurrence of the event, and for a second threshold amount of time after the event, determining whether a responsive object is involved in or near the event, in response to determining that the responsive object is involved in or near the event, transmitting the first data to the responsive object, and receiving, from the responsive object, second data, analyzing the first data and the second data to determine a party at-fault for the event, aggregating the first data and second data into an event report, and causing, automatically, a response to be initiated through an entity associated with the party at-fault.
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. pilote automatique
99.
PROCESSING SYSTEM HAVING MACHINE LEARNING ENGINE FOR PROVIDING CUSTOMIZED USER FUNCTIONS
Systems and apparatuses for generating customized user output are provided. The system may collect sensor data, associated with the user, from a variety of sources. The system may use the sensor data to generate a customized user output. The system may analyze the sensor data, and determine, based on the sensor data and the customized user output, one or more user recommendation outputs. The system may update the customized user output based on additional or subsequent sensor data, and/or based on whether or not the user recommendation output was completed, as determined from subsequent sensor data.
A61B 5/00 - Mesure servant à établir un diagnostic ; Identification des individus
G06F 19/00 - Équipement ou méthodes de traitement de données ou de calcul numérique, spécialement adaptés à des applications spécifiques (spécialement adaptés à des fonctions spécifiques G06F 17/00;systèmes ou méthodes de traitement de données spécialement adaptés à des fins administratives, commerciales, financières, de gestion, de surveillance ou de prévision G06Q;informatique médicale G16H)
G06Q 50/00 - Systèmes ou procédés spécialement adaptés à un secteur particulier d’activité économique, p.ex. aux services d’utilité publique ou au tourisme
H04W 4/00 - Services spécialement adaptés aux réseaux de télécommunications sans fil; Leurs installations
100.
DISTRIBUTED DATA PROCESSING SYSTEMS FOR PROCESSING REMOTELY CAPTURED SENSOR DATA
Aspects of the disclosure relate to processing remotely captured sensor data. A computing platform having at least one processor, a communication interface, and memory may receive, via the communication interface, from a user computing device, sensor data captured by the user computing device using one or more sensors built into the user computing device. Subsequently, the computing platform may analyze the sensor data received from the user computing device by executing one or more data processing modules. Then, the computing platform may generate trip record data based on analyzing the sensor data received from the user computing device and may store the trip record data in a trip record database. In addition, the computing platform may generate user record data based on analyzing the sensor data received from the user computing device and may store the user record data in a user record database.
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. pilote automatique
G05D 3/00 - Commande de la position ou de la direction
brevets
