The ubiquity of mobile communication devices such as smartphones enabled the emergence of context aware applications and services that proactively respond to specific user activities or situations. Context information, i.e., the specific state each user is in, allows communication providers to develop and thus offer new, added value, services for a wide range of applications such as social networking, advertising, navigation or leisure. Of growing importance are health related services and applications that rely on the accurate detection of each user's physical activity either at specific instances or throughout days or even weeks. Using this information it is possible to discover and analyze physical activity patterns and, e.g., help individuals to lead healthier lifestyles. The project addresses the key challenges and enabling techniques for context aware application development in three major aspects:Firstly, by researching and developing human activity detection techniques focusing on low energy, and high accuracy.Secondly, by exploring context aggregation approaches and algorithms based on statistical classification, to uncover activity patterns.Lastly, as mobile systems interface will undoubtedly evolve, by developing a middleware and domain specific programming environment for the rapid prototyping of context aware applications and services.The CONTEXTWA approach and techniques will be evaluated using a real prototype consisting of a human activity recognition system based on a smartphone and on an array of sensors mounted on a personal vest and a cloud-based recommendation system having as input the user activities automatically provided.