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Large scale deployment of sensors is essential to practical applications in cyber physical systems. For instance, instrumenting a commercial building for 'smart energy' management requires deployment and operation of thousands of measurement and metering sensors and actuators that direct operation of the HVAC system. Each of these sensors need to be named consistently and constantly calibrated. Doing this process manually is not only time consuming but also error prone given the scale, heterogeneity and complexity of buildings as well as lack of uniform naming schemas. To address this challenge, we propose Zodiac - a framework for automatically classifying, naming and managing sensors based on active learning from sensor metadata. In contrast to prior work, Zodiac requires minimal user input in terms of labelling examples while being more accurate. To evaluate Zodiac, we deploy it across four real …