Abstract: Device data is obtained from one or more devices for an individual. The one or more devices include one or more medical monitoring devices. Data is also obtained from one or more exogenous sources, and the data includes current data relating to one or more medical resources. The device data obtained from the one or more devices and the data from the one or more exogenous sources are analyzed using an artificial intelligence agent. Based on the analyzing, one or more recommendations are provided. The one or more recommendations include an indication of a device to use that is different from the one or more devices to obtain different device data for the individual.

Abstract: An approach is provided for automatically performing claim preemptive subrogation. An intelligent agent in an artificial intelligence system is activated. An occurrence of a vehicular event is detected. Using the intelligent agent, a mesh network of devices positioned within an environment surrounding the vehicular event is established. Property, event, and environmental data describing the vehicular event is collected and stored in a blockchain node. A smart contract is established on the blockchain node. The smart contract provides authorized parties with an access to the stored property, event, and environmental data. Based on the stored property, event, and environmental data and rule(s), a preemptive subrogation is performed by determining a cause of the vehicular event.

Abstract: This disclosure outlines a method, which enables a vehicle driver to achieve increased fuel efficiency by implementing least-cost route planning based on terrain data and derived from advanced mapping, logging and location based services. Actual fuel efficiency is recorded and correlated by vehicle conditions, time of day and date, and then referenced to achieve the most accurate least-cost route plan for the intended destination.

Abstract: This disclosure outlines a method, which enables a vehicle driver to achieve increased fuel efficiency by implementing least-cost route planning based on terrain data and derived from advanced mapping, logging and location based services. Actual fuel efficiency is recorded and correlated by vehicle conditions, time of day and date, and then referenced to achieve the most accurate least-cost route plan for the intended destination.