Self Learning Efficient builDings and open Spaces
SEEDS project focuses on harnessing advances in self-learning methods, wireless sensor technology and building technology to develop a novel system for Self Learning Energy Efficient builDings and open Spaces (SEEDS). It will aim to develop an energy management system that will allow buildings to continuously learn to maintain user comfort whilst minimising energy consumption and CO2 emissions.
SEEDS will develop an open architecture suitable both for retrofitting existing buildings and open spaces and for new building design.
SEEDS will be based on research and scientific advances in wireless sensor technology, machine learning, and Bayesian networks, as well as standard statistical methods to enable the relationships between key variables to be continuously learned, facilitate prediction and enable control.
SEEDS’ results will be validated in two pilots at opposite sites of Europe: i) part of a university campus (Stavanger, Norway) including several buildings and open spaces and ii) an office building plus parking area (Madrid, Spain).
The Consortium includes organisations from the building, electronic and ICT and energy sector. The dissemination and active contribution to forums such as ICT4EB will assure the impact of the project.
The economical and environmental benefits of the project are:
- (i) Reduction of energy consumption and costs and CO2 emissions;
- (ii) Reduction of first adjustment and maintenance costs;
- (iii) Maintenance of natural resources and reduction of generated waste.