Knowledge discovery and data mining for enhanced sustainability of physical ecosystems

In this paper, we propose a methodology for real-time characterization of the operational state of a subsystem, device or process in an ecosystem, with the goal of improving its sustainability. The objective is to re-describe the operational state, identified by a set of relevant sensor measurements and other parameters, in terms of known operational patterns. Each pattern is also associated with an operational efficiency attribute, which can incorporate a number of criteria, such asTCO (total cost of ownership), and sustainability metrics such as exergy, power consumption and carbon footprint. This attribute quantifies the desirability of operating the system in that state. The aim is to monitor these patterns and determine if it is possible to transform the current operational state to another more efficient pattern. Domain knowledge required to move from one pattern to another, where feasible, can be encoded into actionable rules.