This thesis investigates two fundamental technological challenges that prevent waterudutilities from deploying infrastructure monitoring apparatus with high spatial and temporal resolution: providing sufficient power for sensor nodes by increasing the powerudoutput from a vibration-driven energy harvester based on piezoelectric transduction,udand the processing and storage of large volumes of data resulting from the increasedudlevel of pressure and flow rate monitoring.udPiezoelectric energy harvesting from flow-induced vibrations within a water mainudrepresents a potential source of power to supply a sensor node capable of taking high-udfrequency measurements. A main factor limiting the amount of power from a piezoelectric device is the damping force that can be achieved. Electronic interface circuitsudcan modify this damping in order to increase the power output to a reasonable level. A unified analytical framework was developed to compare circuits able to do this in termsudof their power output. A new circuit is presented that out-performs existing circuits byuda factor of 2, which is verified experimentally.udThe second problem concerns the management of large data sets arising from resolving challenges with the provision of power to sensor devices. The ability to process largeuddata volumes is limited by the throughput of storage devices. For scientists to executeudqueries in a timely manner, query execution must be performant. The large volume ofuddata that must be gathered to extract information from historic trends mandates a scalable approach. A scalable, durable storage and query execution framework is presentedudthat is able to significantly improve the execution time of user-defined queries.udA prototype database was implemented and validated on a cluster of commodity servers using live data gathered from a London pumping station and transmissionudmains. Benchmark results and reliability tests are included that demonstrate a significant improvement in performance over a traditional database architecture for a range ofudfrequently-used operations, with many queries returning results near-instantaneously.
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