Abstract: 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.

Abstract: A transactional method and system of incentivizing task performance using token-based exchange for digital media access. The system and method are configured to reward a person with electronic tokens for tasks that are performed and verified by the system. These tokens can then be exchanged by the user for access to desired digital media. Verification can involve the use of natural language processing and image comparison algorithms to determine whether a particular task has been successfully completed.

Abstract: Methods, computer-readable media, systems and apparatuses for determining a blind corner navigational score based on real-time or near real-time navigational analysis using sensor data, digital image data, and a map database are discussed. In some arrangements, detection of a blind sensor may be performing using sensor data, digital image data, and navigational data from a map database system. In at least some arrangements, a warning signal or a vehicle control signal may be transmitted to a vehicle in response to a determination that the blind corner navigational score is above a threshold. In at least some arrangements, route correction and/or route modification based on an upcoming blind corner may be performed if a blind corner navigational score is above a threshold.

Abstract: Methods, computer-readable media, software, and apparatuses may determine that an expected vehicle demand will exceed an expected supply in a vehicle sharing application. In order to meet the demand, one or more users may be contacted with a request to provide a vehicle for sharing on a particular date. A machine learning algorithm may be used in determining that the expected vehicle demand will exceed the expected vehicle supply.

Abstract: The present invention relates to microencapsulated microbial cultures with high storage stability and methods for producing these. In particular, the present invention relates to microbial cultures formulated at high ratios of encapsulation matrix material to core material.

Abstract: A system may be configured to detect an emergency condition at a premises; dispatch one or more autonomous drones to a location associated with the emergency condition; receive from the one or more autonomous drones, sensor data associated with the emergency condition; generate, based on the sensor data, a plan identifying an evacuation route for safely evacuating the premises; and transmit an instruction that causes the one or more autonomous drones to indicate, to one or more persons in a vicinity of the emergency condition, the evacuation route. The system may further detect, based on the sensor data, one or more safe areas in the premises, and the evacuation route may pass through at least one of the one or more safe areas.

Abstract: Aspects of the disclosure relate to using machine learning methods for customized output generation. A computing platform may train a model (using historical data) by classifying the historical data by a trip context, a device interaction context, and physical condition context, or a personality context, and training models using the classified historical data. The computing platform may monitor a data source system to collect new data, which may include information about multiple drivers. The computing platform may generate, by inputting the new data into the model, a customized driving output for a first driver, where the customized driving output is based at least in part on information about a second driver. The computing platform may send, to a computing device, the customized driving output and commands directing the computing device to display the customized driving output, which may cause the computing device to display the customized driving output.

Abstract: A system including a processor and memory may provide for automatically activating or deactivating a feature of a fleet vehicle. For example, one or more fleet vehicles may include one or more of a global-positioning system, a speed governor, electronically-controlled brakes, an electronically-controlled accelerator, a speed limiter, or an on-board computer with a processor and memory. One or more features may be activated by a local or remote computing device or system. For example, a system may determine one or more recommended routes between two or more locations. The system may track a fleet vehicle's progress along a route, and activate a feature of the fleet vehicle based on the fleet vehicle following or not following the recommended route. For example, the system may cause activation of a speed limiter on the fleet vehicle, disable the fleet vehicle, and/or activate or deactivate autonomous features of the fleet vehicle.

Abstract: The present invention relates to microbial starter cultures. More specifically, a method for preparing a microbial culture such as a lactic acid bacteria (LAB) starter culture wherein at least one microbial strain such as a lactic acid bacteria and at least one hemoprotein is inoculated in a culture medium.

Abstract: A speed control system for an electric drive motor of a self-propelled machine can include a switch assembly, speed lever, potentiometer, actuator lever, cable, and controller. The switch assembly can select a requested maximum speed from a plurality of predetermined maximum travel speeds, and can output a maximum speed signal that is indicative of the requested maximum speed. The speed lever can be movable to any of a plurality of travel speeds, including a zero speed. The potentiometer can be configured to output a requested speed signal that is indicative of the requested travel speed. The controller can be configured to output a motor speed signal to the electric drive motor, the motor speed signal is based on the maximum speed signal and the requested speed signal and causes the electric drive motor to operate at an output speed that corresponds to the motor speed signal.

Abstract: Aspects of the disclosure relate to computing platforms that utilize improved mitigation analysis and policy management techniques to improve onboarding security. A computing platform may determine that a predetermined period of time has elapsed since finalizing an onboarding process. The computing platform may receive spot check verification inputs indicative of a user identity and may direct a mitigation analysis and output generation platform to analyze the spot check verification inputs. The computing platform may receive an indication of a correlation between the spot check verification inputs and expected spot check verification inputs. In response to determining that the correlation exceeds a predetermined threshold, the computing platform may determine that an additional verification test should be conducted, and may direct the mobile device to display an interface that prompts for additional onboarding verification inputs.

Abstract: 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.

Abstract: 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.

Abstract: The disclosure provides an early notification system to alert a driver of an approaching unsafe autonomous or semi-autonomous driving zone so that a driver may switch vehicle to a non-autonomous driving mode and navigate safely through the identified location. In response, to a determination of an upcoming unsafe autonomous or semi-autonomous driving zone, the driver or system may take appropriate actions in response to the early notification.

Abstract: Implementations configure hologram interactions with vehicle passengers. A hologram manager can configure a hologram to interact with vehicle passengers, alleviate danger, and/or guide vehicle passengers to safety. The hologram manager can select an input modality for the hologram according to sensed conditions. For example, the hologram manager can determine a state of impairment for a passenger using sensed data and machine learning model(s). The hologram manager can then select an input modality according to the state of impairment. The generated hologram can be configured by the hologram manager to interact with the passenger using the selected input modality. For example, an instruction manager can generate a set of instructions using sensed and/or gathered information, and the hologram manager can configure the hologram to provide the instructions to the passenger using the input modality.

Abstract: 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.

Abstract: Methods, apparatuses, systems, and computer-readable media 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.

Abstract: A route risk mitigation system and method using real-time information to improve the safety of vehicles operating in semi-autonomous or autonomous modes. The method mitigates the risks associated with driving by assigning real-time risk values to road segments and then using those real-time risk values to select less risky travel routes, including less risky travel routes for vehicles engaged in autonomous driving over the travel routes. The route risk mitigation system may receive location information, real-time operation information, (and/or other information) and provide updated associated risk values. In an embodiment, separate risk values may be determined for vehicles engaged in autonomous driving over the road segment and vehicles engaged in manual driving over the road segment.

Abstract: First global navigation satellite systems (GNSS) signal data is obtained from a set of GNSS satellites. First satellite state data comprising estimated orbit data valid at one or more particular times for the set of GNSS satellites is obtained. A non-linear satellite state model is generated by adjusting a plurality of model parameters using one or more machine learning techniques based on the first GNSS signal data and the first satellite state data. The non-linear satellite state model generates output satellite state data based on GNSS signal data. GNSS satellite state analysis instructions are generated that are configured to allow a second computer system to access the non-linear satellite state model to generate updated satellite state data for one or more particular GNSS satellites by applying the non-linear satellite state model to particular GNSS signal data corresponding to the one or more particular GNSS satellites.

Abstract: Systems and apparatuses for receiving data from a plurality of sensors and using the data, as well as other data, to generate a parking recommendation for an autonomous vehicle and instruct the autonomous vehicle to travel to the recommended parking location are provided. Data may be received from a plurality of sensors within a first autonomous vehicle, as well as from other vehicles and/or structures. Historical parking data associated with the first autonomous vehicle may also be extracted. In some examples, an expected future trip of the first autonomous vehicle may be determined. The system may then evaluate the data to generate a parking recommendation for the first autonomous vehicle. The system may generate and transmit instructions for traveling from a current location to the recommended parking location and may cause the first autonomous vehicle to travel to the recommended parking location.