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Predicting Energy Measurements of Service-Enabled Devices in the Future Smartgrid
Savio, D.; Karlik, L.; Karnouskos, S.

This paper appears in: Computer Modelling and Simulation (UKSim), 2010 12th International Conference on
Issue Date: 24-26 March 2010
On page(s): 450 - 455
Location: Cambridge
Print ISBN: 978-1-4244-6614-6
In the future Internet of Things devices will generate massive amounts of data that will flow to enterprise systems and provide a timely view on the execution of business processes. Being able to estimate data generated by devices may have significant effects on planning and execution of business applications. We present some methodologies for mining data gathered from devices in the energy domain i.e. web service enabled smart meters and home appliances. We present here an approach that realise short-term prediction based on neural networks or support vector machines. We consider detailed information about energy consumption coming from service-enabled devices in the broader smart grid envisioned future infrastructure.

Document Type:
Technical paper