As the field of physical activity recognition matures, we can build more and more robust pervasive systems and slowly move towards tracking knowledge acquisition tasks. We are especially interested one particular cognitive task, namely reading (the decoding of letters, words and sentences into information) Reading is a ubiquitous activity that many people even perform in transit, such as while on the bus or while walking. Tracking reading and other high level user actions gives us more insights about the knowledge life of the users enabling a whole range of novel applications. Yet, how can we extract high level information about human activities (e.g. reading) and complex real world situations from heterogeneous ensembles of simple, often unreliable sensors embedded in commodity devices? The paper focuses on how to use body-worn devices for activity recognition and how to combine them with infrastructure sensing, in general. In the second part, we take lessons from the physical activity recognition field and see how we can leverage to track knowledge acquisition tasks (in particular recognizing reading activities). We discuss challenges and opportunities.