Abstract

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 buildings on our campus and label the ground truth metadata for all the sensors in these buildings manually. Using a combination of hierarchical clustering and random forest classifiers we show that Zodiac can successfully classify sensors with an average accuracy of 98{\%} with 28{\%} fewer training examples when compared to a regular expression based method.

Bibtex

@inproceedings{Balaji:2015:ZOL:2821650.2821674,
    author = "Balaji, Bharathan and Verma, Chetan and Narayanaswamy, Balakrishnan and Agarwal, Yuvraj",
    year = "2015",
    title = "Zodiac: Organizing Large Deployment of Sensors to Create Reusable Applications for Buildings",
    booktitle = "Proceedings of the 2Nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments",
    pages = "13--22",
    doi = "10.1145/2821650.2821674"
}

Plain Text

Bharathan Balaji, Chetan Verma, Balakrishnan Narayanaswamy, and Yuvraj Agarwal. Zodiac: organizing large deployment of sensors to create reusable applications for buildings. In Proceedings of the 2Nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments, 13–22. 2015. doi:10.1145/2821650.2821674.