Development of a less polluting, automated facade system integrated into building management systems

Project facts

Project promoter:
Staticus(LT)
Project Number:
LT-INNOVATION-0002
Status:
Completed
Final project cost:
€3,183,256
Donor Project Partners:
Oslo Metropolitan University(NO)
SINTEF AS(NO)
Other Project Partners
Kaunas University of Technology(LT)

Description

The aim of the project is to create an innovative, less polluting, automated and integrated facade system integrated into building management systems, which will have a number of innovative features. The new modular façade product will allow to offer expected CO2 saving to 70-75% and integrated data management system to create the digital ecosystem with enhanced building serviceability and environmental data system. Looking forward all those new features will contribute to sustainability trends while digital implementation will allow building owners, investors, habitants to implement higher level of automatization, data research models, contribute to digital city concept. 

The project is implemented together with three partners - scientific and research institutions - Oslo Metropolitan University and SINTEF in Norway, as well as Kaunas University of Technology. Goals of the project are very complex and require high level of expertise in very separate field of engineering. Expertise varies from materials research, hardware manufacturing, data management, programming, various product testing, 3D twin modelling and management. For this complex expertise partnership with two universities and one science institution is envisaged. By having experienced partners, integration of different technologies and methodologies to create a new product as well to create learning cases and find any possible integration with studies programmers is expected to be achieved.

Summary of project results

Project aimed at reducing the construction industry’s share of greenhouse gas emissions by substituting aluminum systems with timber and integrating IoT sensors, the project seeked to decrease the facade’s CO2 footprint to 70-75% and non-renewable energy consumption to 53-56%.

The company developed and tested a facade system that reduces CO2 emissions, created a monitoring system for the building’s elements, integrated facade constructions into the building’s digital twin, created an AI-driven predictive maintenance model, used timber materials produced in Lithuania and Norway to produce modular facade elements.

The project was new on a market scale because:

no modular facade element were found on the market with factory-installed sensors for real-time monitoring of building, environment and partition physical parameters;

no product traceability system was capable of VR (AR) environment trace the facade components linked to the ERP system, technical documentation;

building facades were not subject to a predictive service model informing about possible critical changes in physical and mechanical parameters of the facade system, leading to system failures.


Project target group: local and foreign real estate project developers and managers. Their main need is to contribute to the reduction of negative environmental impact through various energy saving measures, which will are served by the innovative facade system. 

Summary of bilateral results

First partner – OsloMet – is the youngest university in Norway, dedicated to adopting new technologies and developing innovative solutions for the social welfare state in Europe. SINTEF is one of the continent’s largest independent research organisations, involved in thousands of projects each year. Kaunas University of Technology is one of the region’s largest STEM-oriented schools. Together with the partners the project aimed to reduce the construction industry’s share of greenhouse gas emissions and pave the way for sustainable habitation around the world.

Information on the projects funded by the EEA and Norway Grants is provided by the Programme and Fund Operators in the Beneficiary States, who are responsible for the completeness and accuracy of this information.