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We present a new, open source, computationally capable datalogger for collecting and analyzing high temporal resolution residential water use data. Using this device, execution of water end use disaggregation algorithms or other data analytics can be performed directly on existing, analog residential water meters without disrupting their operation, effectively transforming existing water meters into smart, edge computing devices. Computation of water use summaries and classified water end use events directly on the meter minimizes data transmission requirements, reduces requirements for centralized data storage and processing, and reduces latency between data collection and generation of decision-relevant information. The datalogger couples an Arduino microcontroller board for data acquisition with a Raspberry Pi computer that serves as a computational resource. The computational node was developed and calibrated at the Utah Water Research Laboratory (UWRL) and was deployed for testing on the water meter for a single-family residential home in Providence City, UT, USA. Results from field deployments are presented to demonstrate the data collection accuracy, computational functionality, power requirements, communication capabilities, and applicability of the system. The computational node's hardware design and software are open source, available for potential reuse, and can be adapted to specific research needs.

Residential Water Meters as Edge Computing Nodes: Disaggregating End Uses and Creating Actionable Information at the Edge