The high potential of new generation smartphones in terms of resources capability as well as availability of embedded sensors and radio interfaces has opened new perspectives to developers, which came out with a massive number of applications for mobile phones. Most of them are location based, where location data is used either as main or as auxiliary information. However, the location service is power hungry. Thus, a major challenge is the optimization of the trade-off between resources usage of the location service and its accuracy. We introduce the architecture of the Enhanced Localization Solution (ELS), an efficient localization strategy for smartphones which smartly combines the standard location tracking techniques (e.g., GPS, GSM and WiFi localization), the newly built-in technologies, as well as Human Mobility Modelling and Machine Learning techniques. This solution aims to provide a continuous and ubiquitous service while reducing the impact on the device's resources usage.