The key advantage of smart meters over traditional metering devices is their ability to transfer consumption information to remote data processing systems. Besides enabling the automated collection of a customer’s electricity consumption for billing purposes, the data collected by these devices makes the realization of many novel use cases possible. However, the large majority of such services are tailored to improve the power grid’s operation as a whole. For example, forecasts of household energy consumption or photovoltaic production allow for improved power plant generation scheduling. Similarly, the detection of anomalous consumption patterns can indicate electricity theft and serve as a trigger for corresponding investigations. Even though customers can directly influence their electrical energy consumption, the range of use cases to the users’ benefit remains much smaller than those that benefit the grid in general. In this work, we thus review the range of services tailored to the needs of end-customers. By briefly discussing their technological foundations and their potential impact on future developments, we highlight the great potentials of utilizing smart meter data from a user-centric perspective. Several open research challenges in this domain, arising from the shortcomings of state-of-the-art data communication and processing methods, are furthermore given. We expect their investigation to lead to significant advancements in data processing services and ultimately raise the customer experience of operating smart meters.

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Exchanging data as character-separated values (CSV) is slow, cumbersome and error-prone. Especially for time-series data, which is common in Activity Recognition, synchronizing several independently recorded sensors is challenging. Adding second level evidence, like video recordings from multiple angles and time-coded annotations, further complicates the matter of curating such data. A possible alternative is to make use of standardized multi-media formats. Sensor data can be encoded in audio format, and time-coded information, like annotations, as subtitles. Video data can be added easily. All this media can be merged into a single container file, which makes the issue of synchronization explicit. The incurred performance overhead by this encoding is shown to be negligible and compression can be applied to optimize storage and transmission overhead.

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