Klipsk Energy - smart building saves energy
|Funding from Vinnova||SEK 300 000|
|Project duration||March 2017 - June 2017|
|Call||Innovativa startups fas 1 Våren 2017|
Purpose and goal
Klipsk AB has built a platform for applying semantically structured data and machine learning to the management of large commercial buildings. With collected data, a model for energy saving management has been developed.
Expected results and effects
We have developed an ontology for building systems, structure and usage. We have implemented a platform to collect data from several heterogeneous systems, and used it to train a machine learning model that regulates power consumers at power peaks. The model is validated and reduces energy costs, energy consumption and transmission costs. The platform is in operation for more than 15000 m².
Planned approach and implementation
We have built the platform on existing technologies for streaming data and IoT sensors. An ontology has been developed to describe structure and energy use in buildings. It handles more than 20 different building design standards (BIM, CoClass, etc.), climate control (Belok, etc.) and new IoT standards (IPSO, Semantic Sensor Network, etc.). Thanks to the ontology, we have obtained coherent training data from different buildings where completely different sensors and systems are installed.