Best Paper Runner-up at ACM e-energy'21

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Best Student Paper Nominee at IEEE SmartGridComm'20

This paper presents the Plug-Load Appliance Identification Dataset (PLAID), a labelled dataset containing records of the electrical voltage and current of domestic electrical appliances obtained at a high sampling frequency (30 kHz). The dataset contains 1876 records of individually-metered appliances from 17 different appliance types (e.g., refrigerators, microwave ovens, etc.) comprising 330 different makes and models, and collected at 65 different locations in Pittsburgh, Pennsylvania (USA). Additionally, PLAID contains 1314 records of the combined operation of 13 of these appliance types (i.e., measurements obtained when multiple appliances were active simultaneously). Identifying electrical appliances based on electrical measurements is of importance in demand-side management applications for the electrical power grid including automated load control, load scheduling and non-intrusive load monitoring. This paper provides a systematic description of the measurement setup and dataset so that it can be used to develop and benchmark new methods in these and other applications, and so that extensions to it can be developed and incorporated in a consistent manner.

Best Paper Award at ACM BuildSys'20

Global urbanization projections suggest that a great majority of human beings will be living in urban areas by the middle of this century. This trend imposes significant strains on urban infrastructure systems and adds additional challenges to achieving environmental, social and economic sustainability goals set by many city governments. Smart city products and services, backed by IoT systems, have been proposed as effective solutions to increase efficiency, reduce costs and improve services. However, as with any technology, IoT solutions for smart cities bring about great opportunities and, at the same time, threats to, among others, governance, security, privacy and community autonomy. As we accumulate experience with these smart city deployments, we must ask ourselves: What would we later regret not regulating now? What good opportunities might certain types of regulation hold back and how can this be mitigated? We offer our perspective on these questions and argue in favor of human-centered IoT systems that are owned, operated and managed much in the same way that other public urban infrastructure systems (e.g., wastewater) are.