Toward an Integrated Approach to Localizing Failures in Community Water Networks (DEMO)

摘要

We present a cyber-physical-human (CPHS) distributed computing framework, AquaSCALE, for gathering, analyzing and localizing anomalous operations of increasingly failure-prone community water services. Today, detection of water pipe leaks takes hours to days. AquaSCALE leverages dynamic data from multiple information sources including IoT (Internet of Things) sensing data, geophysical data, human input and simulation/modeling engines to create a sensor-simulation-data integration platform that can locate multiple simultaneous pipe failures at fine level of granularity with high level of accuracy and detection time reduced by orders of magnitude (from hours/days to minutes).