Industries such as the construction sector involve complex processes where environmentally friendly design takes a long time. TerraNEXT wants to accelerate the transformation with an AI solution.
Construction industry responsible for high share of emissions worldwide
The construction industry is one of the largest contributors to global emissions. The building sector is responsible for up to 35 per cent of energy consumption and 38 per cent of energy and process-related emissions.
The conclusion: a sustainable transformation must take place in the construction sector. The only problem is that the processes are complex. A building alone has several steps in its life cycle that need to be considered in an environmentally friendly approach: From planning, to construction, to active habitation and finally the end of life phase.
“For example, it’s about how much energy we consume during the utilisation phase. A lot of questions come up, which is a big challenge,” explains Zahra Mehdipour from TerraNEXT.
AI solution from TerraNEXT to accelerate sustainable processes
TerraNEXT wants to start right here and simplify the change. To achieve this, they are relying on digitalisation and artificial intelligence. The aim is to accelerate sustainability by driving the whole thing forward with data ecosystems and advanced digitalisation.
“We need better and simpler processes that help us make intelligent decisions and be agile,” Mehdipour explains. “When we are talking about this amount of data, we need AI.”
TerraNEXT’s TerranAI as an AI-based data ecosystem
TerraNEXT’s AI-based data ecosystem is called TerranAI. It is designed to enable access to the amount of data and optimise analyses for architects, suppliers, etc.
In a nutshell, TerranAI is the AI Buildings Cloud, which is intended to serve as the first collaborative AI data ecosystem for the construction industry. It is intended to connect players and create an overview.
“AI solution is much faster than it would otherwise be”.
“It’s the future that all the different players come together and still have secure and independent data exchange and transport systems,” explains Mehdipour. “The AI solution is much faster than it would otherwise be. We don’t have the feeling that sustainability is costly, but instead focus on the better solution.”
Structured design of a rating system for high-quality data
However, there are currently still complications regarding the value of the data used to feed the AI. High-quality data is needed. But you first have to check which data actually fulfils the required high quality.
“Data quality needs an evaluation system. The system is not yet in place, but we are working on it. We also have a research project so that we can set up this evaluation system in a structured way.”
