Abstract: Apparatuses, systems and methods are provided for generating and transmitting data representative of a vehicle operation mode. More particularly, apparatuses, systems and methods are provided for generating data representative of a vehicle operation mode based on vehicle interior image data.

Abstract: A method and system is provided for providing local business-based recommendations or search results to visitors. In response to a request for a digital map of a geographic area, the system determines whether a user is familiar with the geographic area based on the user's location history. In response to determining that the user is unfamiliar with the geographic area and therefore is a visitor of the geographic area, the system provides recommendations, suggestions, or search results to the user which includes local businesses which are of interest to the user. The local businesses may include local businesses which are related to a geographic search query provided by the user, or may include local businesses recommended by the system according to the time of day, time of year, events within the geographic area such as events stored in the user's virtual calendar, reviews of the local businesses, etc.

Abstract: Apparatuses, systems and methods are provided for generating a vehicle driver signature. More particularly, apparatuses, systems and methods are provided for generating a vehicle driver signature based on current image data, previously classified image data, and vehicle dynamics data.

Abstract: A method of training and using a machine learning model that controls for consideration of undesired factors which might otherwise be considered by the trained model during its subsequent analyses of new data. For example, the model may be a neural network trained on a set of training images to evaluate an insurance applicant based upon an image or audio data of the insurance applicant as part of an underwriting process to determine an appropriate life or health insurance premium. The model is trained to probabilistically correlate an aspect of the applicant's appearance with a personal and/or health-related characteristic. Any undesired factors, such as age, sex, ethnicity, and/or race, are identified for exclusion. The trained model receives the image (e.g., a “selfie”) of the insurance applicant, analyzes the image without considering the identified undesired factors, and suggests the appropriate insurance premium based only on the remaining desired factors.

Abstract: A method of training and using a machine learning model that controls for consideration of undesired factors which might otherwise be considered by the trained model during its subsequent analyses of new data. For example, the model may be a neural network trained on a set of training images to evaluate an insurance applicant based upon an image or audio data of the insurance applicant as part of an underwriting process to determine an appropriate life or health insurance premium. The model is trained to probabilistically correlate an aspect of the applicant's appearance with a personal and/or health-related characteristic. Any undesired factors, such as age, sex, ethnicity, and/or race, are identified for exclusion. The trained model receives the image (e.g., a “selfie”) of the insurance applicant, analyzes the image without considering the identified undesired factors, and suggests the appropriate insurance premium based only on the remaining desired factors.

Abstract: Apparatuses, systems and methods are provided for vehicle operator gesture recognition and transmission of related gesture data. More particularly, apparatuses, systems and methods are provided for vehicle operator gesture recognition and transmission of related gesture data to at least one geographic map programming interface.

Abstract: Systems and methods for generating and communicating challenges that are intended to improve driving behavior are provided. According to certain aspects, a backend server may receive vehicle data describing the vehicle's operation or the vehicle operator from sensors or an electronic device. The backend server may compare target parameters and the vehicle data and, optionally, data from an external information source, to determine differences and calculate risk. The backend server may transmit challenges to the electronic device, and may generate a comparison factor and process an account of a the vehicle operator based on updated vehicle data received from the electronic device.

Abstract: Apparatuses, systems and methods are provided for vehicle operator gesture recognition and transmission of related gesture data. More particularly, apparatuses, systems and methods are provided for vehicle operator gesture recognition and transmission of related gesture data to at least one geographic map programming interface.

Abstract: A computer-implemented method for authentication using a hashed fried password may include receiving a password value of a user, a salt key, a pepper key, and/or a temporary and randomly generated fry key, or otherwise modifying/appending the password with the salt key, pepper key, and/or fry key. The method may include hashing the modified password, such as performing a hash operation similar to Hash (Password, Salt Key, Pepper Key, Temporary Fry Key). The randomly generated fry key is not saved or otherwise stored, either locally or remotely. A remote server attempting to authenticate the user's password may check for each possible fry key, such as checking against a set of preapproved fry keys, that the hashed fried password may have been modified with in parallel. As a result, an online customer experience requiring a password is not impacted or impeded, while an attacker's attempts to learn the password are frustrated.

Abstract: A method of training and using a machine learning model that controls for consideration of undesired factors which might otherwise be considered by the trained model during its subsequent analyses of new data. For example, the model may be a neural network trained on a set of training images to evaluate an insurance applicant based upon an image or audio data of the insurance applicant as part of an underwriting process to determine an appropriate life or health insurance premium. The model is trained to probabilistically correlate an aspect of the applicant's appearance with a personal and/or health-related characteristic. Any undesired factors, such as age, sex, ethnicity, and/or race, are identified for exclusion. The trained model receives the image (e.g., a “selfie”) of the insurance applicant, analyzes the image without considering the identified undesired factors, and suggests the appropriate insurance premium based only on the remaining desired factors.

Abstract: Apparatuses, systems and methods are provided for generating a vehicle driver signature. More particularly, apparatuses, systems and methods are provided for generating a vehicle driver signature based on vehicle interior image data and vehicle dynamics data. The vehicle interior image data may be representative of an identification of a particular individual. The vehicle dynamics data may be representative of a particular driving style, or driving behavior, associated with a particular individual.

Abstract: Systems and methods relate to, inter alia, receiving a set of sensor data from a set of sensors communicatively coupled to the electronic mobile device. The systems and methods may further include determining automatically from the set of sensor data that the collision event occurred during the operation of the automotive device. The systems and methods may further include initiating, in response to determining that the collision event occurred, a reverse communication session between the electronic mobile device and a collision management server. The electronic mobile device, via the initiated reverse communication session, may be configured to receive a first offer from a first service provider and a second offer from a second service provider. The first offer and the second offer are for servicing the automotive device by the first service provider and the second service provider, respectively.

Abstract: Systems and methods for improving vehicular safety are disclosed. According to embodiments, an electronic device may collect or accumulate various sensor data associated with operation of a vehicle by an individual, including image data, telematics data, and/or data indicative of a condition of the individual. The electronic device may analyze the sensor data to determine whether the individual is distracted and whether the vehicle is approaching a location that may be prone to incidents. The electronic device may accordingly generate and present a notification to the individual to mitigate any posed risks.

Abstract: Apparatuses, systems and methods are provided for determining vehicle driver distractions. More particularly, apparatuses, systems and methods are provided for determining distracted drivers associated with vehicle driving routes based on postures of vehicle occupants.

Abstract: Apparatuses, systems and methods are provided for generating and transmitting data representative of a vehicle operation mode. More particularly, apparatuses, systems and methods are provided for generating data representative of a vehicle operation mode based on vehicle interior image data.

Abstract: Systems and methods for analyzing vehicle occupant data to improve the driving experience are provided. According to certain aspects, image sensor data of a vehicle occupant may be used to determine the emotional state of the vehicle occupant which may be used by businesses in proximity to the vehicle to effectively advertise to the vehicle occupant. An electronic device may be used to display the advertisement of a business in proximity to the vehicle.

Abstract: Systems and methods for assessing accident events are disclosed According to certain aspects, an electronic device may access sensor data associated with operation of a vehicle, and analyze the sensor data to determine that an accident event has occurred. In response, the electronic device may dynamically and automatically retrieve additional sensor data from at least one additional electronic device via a short range communication. The electronic device may compile or aggregate the additional sensor data with the original sensor data to provide a thorough representation of the accident event.

Abstract: Systems and methods for improving vehicular safety are disclosed. According to embodiments, an electronic device may collect or accumulate various sensor data associated with operation of a vehicle by an individual, including image data, telematics data, and/or data indicative of a condition of the individual. The electronic device may analyze the sensor data to determine whether the individual is distracted and whether the vehicle is approaching a location that may be prone to incidents. The electronic device may accordingly generate and present a notification to the individual to mitigate any posed risks.

Abstract: Apparatuses, systems and methods are provided for determining vehicle driver distractions. More particularly, apparatuses, systems and methods are provided for determining distractions at particular geographic locations.

Abstract: Systems and methods for using collecting and analyzing device sensor data to determine whether an individual is an operator or a passenger of a vehicle are disclosed. According to certain aspects, an electronic device associated with the individual may collect or access sensor data that is indicative of or associated with an operation of the vehicle. The electronic device may transmit pertinent portion(s) of the sensor data to a backend server, which may input the portion(s) into a neural network for analysis. The neural network may output a probability metric(s) indicative of whether the individual is a passenger or an operator of the vehicle.