Automated metadata transformation for a-priori deployed sensor networks
Arka Bhattacharya, David Culler, Dezhi Hong, Kamin Whitehouse, Jorge Ortiz · 2014
Sensor network research has facilitated advancements in various domains, such as industrial monitoring, environmental sensing, etc., and research challenges have shifted from creating infrastructure to utilizing it. Extracting meaningful information from sensor data, or control applications using the data, depends on the metadata available to interpret it, whether provided by novel networks or legacy instrumentation. Commercial buildings provide a valuable setting for investigating automated metadata acquisition and augmentation, as they typically comprise large sensor networks, but have limited, obscure metadata that are often meaningful only to the facility managers. Moreover, this primitive metadata is imprecise and varies across vendors and deployments.