Manage
SEAS contains the software and specifications for plugging into a heterogeneous set of devices in the field with one unified view to the data. It defines identifiers that allow pointing at each device unambiguously and data specifications that let systems do unit conversions and the interpretation of data automatically.
Predict
Handling timeseries of production and consumption is the bread and butter of energy management systems. Historical values of the past, especially those that match the same season of the year the year before or similar weather conditions, are the basis of creating a prediction of what happens in similar conditions in the future. Consequently SEAS has an extensive set of timeseries handling features that allow exchangin such data between systems accurately, unifying the data, and using mathematical methods to reveal correlations that feed into the predictive models.
Assign targets
In energy management, it is not necessarily wise to try to remotely micro manage complex targets such as large buildings. The buildings themselves have internal structure that is usually something that cannot be known without very detailed knowledge of who occupies it and when. Consequently, a better way is to just set broad targets, preferably with some heads-up margin, instead of specific commands. The local systems can take appropriate action to perform the actual actions that lead to that target. SEAS models such targets and then delegates them within the infrastructure.
Trigger action
There is a range of factors that for instance building automation systems react to. These include for instance timers that deactivate systems after office hours, carbon dioxide sensors that adjust the air conditioning, temperature sensors that drive the heating systems, and much more. SEAS contains technology to monitor not only the values in real-time but also follow the triggering of events. The events can then be linked together in logic engines to further create local and remote control logic.
