Abstract:
An approach is provided for visualizing future events to a passenger of a vehicle. The approach involves collecting sensor data, contextual data, or a combination thereof during an operation of a vehicle. The approach also involves processing the sensor data, the contextual data, or a combination thereof to predict a future event that is expected to occur proximate to the vehicle. The approach further involves generating a simulation of the future event. The approach further involves presenting the simulation in a user interface.
Abstract:
Examples of the present disclosure provide a method, apparatus and computer program configured to cause performance of the following: detecting movement of a device; detecting at least one ambient condition of the device; and determining whether to trigger an alert in dependence upon the detected movement and the detected at least one ambient condition.
Abstract:
An approach is provided for routing an aerial drone while preserving privacy. The approach involves processing model data depicting at least one structure to determine one or more privacy-sensitive features of the at least one structure. The approach also involves calculating line-of-sight data between a route of an aerial drone and the one or more privacy-sensitive features. The approach further involves configuring a routing of the aerial drone based on the line-of sight data when the aerial drone is traveling near the at least one structure.
Abstract:
An approach for providing mapping information and route information based on exception information received from various users travelling within a common area is described. A navigation system processes travel information associated with one or more devices for comparison against predetermined route information. The navigation system also determines one or more exceptions based, at least in part, on the comparison. The predetermined route information, mapping information, or a combination thereof it then caused to be updated based, at least in part, on the processing of the one or more exceptions.
Abstract:
An apparatus, method and computer program the apparatus comprising: processing circuitry (5); and memory circuitry (7) including computer program code (11); the memory circuitry and the computer program code configured to, with the processing circuitry, cause the apparatus at least to perform: obtaining information from a plurality of sensors wherein the plurality of sensors are located on a plurality of vehicles; analysing the obtained information to determine whether at least one vehicle is exposed to risk; and if it is determined that at least one vehicle is exposed to risk, enabling one or more of the plurality of vehicles to activate a defensive mode of operation.
Abstract:
An apparatus, method and computer program product are provided for predicting charging efficiency rates for solar-powered vehicles. In one example, the apparatus receives historical data of events in which solar-powered vehicles equipped with solar panels were electrically charged by receiving solar beams at the solar panels. The historical data indicate factors of the events that induced objects forming on the solar panels and obstructing, at least in part, the solar beams. The apparatus uses the historical data to train a machine learning model to output a charging efficiency rate of a target solar-powered vehicle as a function of at least one attribute associated with a location.
Abstract:
Embodiments include apparatus and methods for determining link level wind factors and providing routes for drones based on the wind factors. At least a portion of the route corresponds to airspace above a road network. Wind factor values are assigned to a range of altitudes of drone air space above a road link of the road network based on a wind model and stored in a database. The wind model is applied to a location based on wind condition data and three-dimensional (3D) features from 3D map data associated with the location. The route is optimized based on the determined wind factors.
Abstract:
Embodiments include apparatus and methods for determining link level wind factors and providing routes for drones based on the wind factors. At least a portion of the route corresponds to airspace above a road network. Wind factor values are assigned to a range of altitudes of drone air space above a road link of the road network based on a wind model and stored in a database. The wind model is applied to a location based on wind condition data and three-dimensional (3D) features from 3D map data associated with the location. The route is optimized based on the determined wind factors.
Abstract:
An approach is provided for routing an aerial drone while preserving privacy. The approach involves processing model data depicting at least one structure to determine one or more privacy-sensitive features of the at least one structure. The approach also involves calculating line-of-sight data between a route of an aerial drone and the one or more privacy-sensitive features. The approach further involves configuring a routing of the aerial drone based on the line-of sight data when the aerial drone is traveling near the at least one structure.
Abstract:
An apparatus, method and computer program wherein the apparatus comprises: processing circuitry; and memory circuitry including computer program code; the memory circuitry and the computer program code configured to, with the processing circuitry, cause the apparatus at least to perform: obtaining information from at least one sensor wherein the information comprises a current location of a vehicle; using the obtained information to determine an autonomous evacuation strategy for the vehicle; and enabling the vehicle to access the autonomous evacuation strategy when an emergency is detected.