Human Activity Detection Using Smartphones and Maps

This dissertation provides systems, methods, and algorithms for the detection of human activities from smartphones and maps. Knowledge of automated human activities derived from travelers’ smartphones enables data service innovations where mobile services are created based on patterns related to individuals as well as communities. Some examples of human activities that we propose to derive from travelers’ mobile phones are transportation modes (indoor and outdoor) and street parking status. Using information about individual travelers, the dissertation shows how community patterns such as the parking availability on a street block can be estimated.