Abstract: An apparatus for high-frequency policy underwriting of real-time dynamic pricing includes a computing device that receives real-time data from telematic devices. The apparatus process a suite of modules designed for a nuanced assessment and dynamic adjustment of insurance premiums. At policy initiation, policyholders may opt to install telematic devices, which continually transmit driving data to centralized servers. Advanced machine learning algorithms process this data, enabling the apparatus to assess individual risk profiles and adjust premiums in real-time. The dynamic pricing module, pivotal to the apparatus, allows for frequent premium modifications, reflecting a policyholder's driving behavior. Additionally, an incentive module is introduced, rewarding exemplary driving with benefits ranging from cashbacks to lowered deductibles.

Abstract: A system for increasing the safety of voice conversations between drivers and remote parties, wherein the system includes an in-vehicle subsystem, wherein the in-vehicle subsystem is configured to communicate wirelessly with a remote subsystem accessible to the remote parties in an initial state, a plurality of sensors, and a computing apparatus, wherein the computing apparatus is configured to received monitoring data from the plurality of sensors, determine risk levels as a function of the monitoring data, and alter a state of the communication between the in-vehicle and the remote subsystem as an automatic safety response according to the risk levels, wherein altering the state of the communication includes switching the initial state to a second state as a function of a transition between a first risk level and a second risk level, and transmitting an alert to the remote subsystem as a function of the automatic safety response.

Abstract: A system for increasing the safety of voice conversations between drivers and remote parties is shown. The system includes an in-vehicle subsystem and a remote subsystem. The system includes a plurality of sensors which are configured to generate monitoring data. The system includes a computing device, which may be distributed between the subsystems and is configured to calculate a risk level as a function of the monitoring data. The computing device may engage an automatic safety response as a function of the risk level, that may include suspension or termination of on-going conversations among the parties, together with notification about the status of the communication channel. The safety response may be communicated to the driver by generating an alert. The in-vehicle and the remote subsystems communicate using a wireless connection and collaborate in engaging the automatic safety response and communicating any alerts to the driver and remote party using notifications.

Abstract: In an aspect, a system for using artificial intelligence to evaluate, correct, and monitor user attentiveness includes a forward-facing camera, the forward-facing camera configured to capture a video feed of a field of vision on a digital screen, at least a user alert mechanism configured to output a directional alert to a user, a processing unit in communication with the forward-facing camera and the at least a user alert mechanism, a screen location to spatial location map operating on the processing unit, and a motion detection analyzer operating on the processing unit, the motion detection analyzer designed and configured to detect, on the digital screen, a rapid parameter change, determine a screen location on the digital screen of the rapid parameter change, retrieve, from the screen location to spatial location map, a spatial location based on the screen location, and generate, using the spatial location, the directional alert.