Imagine your building had a digital brain that knew exactly how much energy it used and where it wasted it. This system connects all the building's data into one map to predict future energy needs and suggest the best time to heat or cool rooms. It's like having a smart assistant that manages your property's health and bills automatically.
Building managers struggle with fragmented data, making it hard to predict energy needs or plan renovations accurately. This leads to wasted energy, higher costs, and poor occupant comfort.
["DBPM Toolkit: A digital twin system using BIM data for building performance management.", "LD2S Toolkit: An AI-powered decision support system for renovation and sustainability planning.", "Data-Sharing Platform: A secure system ensuring data sovereignty and interoperability."]
If you are a property manager dealing with unpredictable energy costs across a portfolio — this project developed a Data-driven Building Performance Management toolkit that uses digital twins to optimize energy and thermal flexibility.
If you are a consultant dealing with inaccurate renovation planning — this project developed an AI-enhanced Lifecycle Data-driven Decision Support toolkit that provides evidence-based pathways for sustainability and renovation.
If you are an operator dealing with high maintenance costs and occupant discomfort — this project developed a Smart Sustainability & Comfort Balancing Module using non-intrusive load monitoring to balance energy use and comfort.
Based on available project data, no specific pricing or cost structure is mentioned; the project focuses on developing the toolkits and a supportive market framework.
Yes, the project specifically aims to develop tools for both individual building and building portfolio management using a scalable data architecture.
Based on available project data, the project prioritizes data sovereignty to ensure ownership control, but specific licensing terms for the software are not provided.
It uses an XML-based framework following international Open BIM standards to integrate structured and unstructured data from multiple sources into a digital twin.
The project runs from 2024-06-01 to 2027-08-31, indicating that final tools will be ready toward the end of this period.
The consortium is well-balanced for commercialization, featuring 16 partners across 7 countries. With an industry ratio of 38% (6 companies, including 5 SMEs), there is a strong link between academic research and market application, ensuring the tools are built for real-world business needs rather than just theoretical study.
Contact the National Centre for Research and Technology Development (EL)
Contact us to connect with the DATAWiSE consortium for early access to the DBPM toolkit.
