Equipping classrooms with inexpensive sensors for data collection can provide students and teachers with the opportunity to interact with the classroom in a smart way. In this paper two approaches to acquiring contextual data from a classroom environment are presented. We further present our approach to analysing the collected room usage data on site, using low cost single board computer, such as a Raspberry Pi and Arduino units, performing a significant part of the data analysis on-site. We demonstrate how the usage data was used to model specifcic room usage situation as cases in a Case-based reasoning (CBR) system. The room usage data was then integrated in a room recommender system, reasoning on the formalised usage data, allowing for a convenient and intuitive end user experience based on the collected raw sensor data. Having implemented and tested our approaches we are currently investigating the possibility of using (XML)Schema-informed compression to enhance the security and efficiency of the transmission of a large number of sensor reports generated by interpreting the raw data on-site, to our central data sink. We are investigating this new approach to usage data transmission as we are aiming to integrate our on-going work into our vision of the Smart University to ensure and enhance the Smart University's data literacy
