Boosting renovation industry with AI
The RenovAIte project aims to optimize large-scale energy renovations of buildings as well as road renovations.
how can ai and data support renovation industry in europe
The RenovAIte project is developping artificial intelligence technologies for the entire renovation value chain. Starting with the renovation of housing and roads, the RenovAIte project aims to accelerate and optimize several key stages of renovation projects (from financing to infrastructure operation) to achieve environmental and economic performance gains.
Our partners
In a consortium led by Leonard for the VINCI group with A major French social landlord, ALLONIA and OFFIS, RenovAIte aims to become a player that supports the renovation of all European infrastructures in their ecological and digital transition.
RENOVATION WITH IA
The RenovAIte consortium will soon offer innovative solutions for the renovation of buildings and roads based on construction-related data (BIM, photogrammetry, etc.) and artificial intelligence: new visualization tools, prioritization of the renovation plan, optimization of conceptions or diagnosis of climate resilience.
INTEREST
The risks associated with climate change present us with a major challenge. challenge. To mitigate the effects of climate change, buildings are being extensively renovated, with better insulation and new heating systems. renovated, with better insulation and new heating systems designed to reduce energy designed in particular to reduce energy requirements and CO² emissions. However, from an adaptation perspective, climate change also requires us to rethink the way in which structures are renovated. For example insulation solutions designed to keep the building warm in winter, may not be sufficient to guarantee cooling in summer, which would result in an increase cooling in summer, leading to an increase in energy consumption for air conditioning. air conditioning.
GOAL
The aim of this Franco-German project is the resilient planning and design of building and road renovation projects. of building and road renovation projects. To achieve this, we the potential of AI for decision support, the data and expertise of the consortium partners, but also on the production of new information management tools. expertise of the consortium partners, but also on the production of new new data. Our work will result in simulation models that will make it possible to examine and optimise renovation projects using machine learning adversarial learning for resilience
USE
Our work will generate simulation models that will facilitate the examination and optimisation of renovation projects, based on learning learning about adversarial resilience as a core technology.
Testimonials
The progressive deployment of these solutions will impact one million households and 70,000 kilometers of roads by 2025.
RenovAIte is an ambitious project in a vital field for the world’s journey toward climate neutrality. The possible impact of the project results in the construction industry is enormous. This potential is an essential motivation for all project partners to contribute to the outcome. The possibility of applying our AI knowledge to a new domain and testing predeveloped methodologies on new problems is scientifically important for OFFIS. It is a welcome challenge to our knowledge, adaptability, and the performance of scientific results in real-life applications. The bonus of being a French-German project allows the partners to exchange ideas, technologies, and expertise. This reduces the risk of the project results becoming island solutions that only work on one specific use case in a particular company and increases the possibility of adaption throughout the EU.
