Abstract: A system, a method, and a computer program product may be provided for charging an unmanned aerial vehicle (UAV). The system may include a memory configured to store computer executable instructions and a processor configured to execute the computer executable instructions to obtain a set of UAV attributes and location information associated with an UAV, identify a plurality of electric power lines in proximity of the UAV based on the location information, obtain a set of electric power line attributes for the plurality of electric power lines, and identify one or more electric power lines from the plurality of electric power lines based on the set of UAV attributes, the set of electric power line attributes and a trained first machine learning model. The processor is configured to direct the UAV to the identified one or more electric power lines for charging the UAV.

Abstract: Systems and methods for determining an optimal placement of a package at a location are provided. For example, a method for determining an optimal placement of a package at a location includes determining a first area for placement of a package at a location based on historical delivery data. The method also includes determining a second area for placement of the package at the location based on map data. The method also includes determining an optimal area for placement of the package at the location based on the first area and the second area.

Abstract: An approach is provided for preventing traffic over-reporting via identifying misleading traffic data. The approach involves, for example, detecting a connection attempt between a wireless communication infrastructure device and a plurality of probe devices. The wireless communication infrastructure device is associated with a known height. The approach also involves processing one or more wireless signals associated with the connection attempt to determine height data of the plurality of probe devices. The approach further involves determining based on the height data that at least two of the plurality of probe devices are carried by a single entity. The approach further involves providing data indicating the at least two of the plurality of probe devices as an output.

Abstract: An approach is provided for preventing traffic over-reporting via identifying misleading traffic data. The approach involves, for example, detecting a connection attempt between a wireless communication infrastructure device and a plurality of probe devices. The wireless communication infrastructure device is associated with a known height. The approach also involves processing one or more wireless signals associated with the connection attempt to determine height data of the plurality of probe devices. The approach further involves determining based on the height data that at least two of the plurality of probe devices are carried by a single entity. The approach further involves providing data indicating the at least two of the plurality of probe devices as an output.

Abstract: A method and a system are disclosed for predicting that a road object is in a road zone or not. The method may include receiving at least one road object observation associated with the road object; extracting at least one feature associated with the road object or surroundings thereof based on the received at least one road object observation; and predicting, using a trained machine learning model, that the road object is in the road zone or not based on the extracted at least one feature, wherein the machine learning model is trained based on a training data set comprising a combination of at least one training feature and a ground truth label data, wherein the ground truth label data comprises at least one of a road zone data and a non-road zone data.