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Sustainable Management With Artificial Intelligence

With artificial intelligence (AI), statistical relationships can be found in complex amounts of data. As a result, efficiency gains can be achieved that can be used for more sustainable management and better environmental protection. The AI ​​innovation competition of the BMWK illustrates this potential.

As a global challenge, climate change is forcing a change in perspective in how we live and do business. The Federal Ministry of Economics and Climate Protection (BMWK) takes this changed perspective by expanding the social market economy model to include an ecological regulatory framework.

The “ecological-social market economy” also pursues the goal of maintaining Germany’s competitiveness and offering its citizens a high level of prosperity. This goal also includes considering planetary resources and the protection of global environmental goods such as the climate or biodiversity.

Several projects in the BMWK ‘s AI innovation competition offer good examples of how ecology and economy can be promoted with the model of the ecological-social market economy. The technology program promotes the applicability of AI in important sectors of the German economy, such as production, construction, health care, and agriculture. It is primarily geared towards small and medium-sized enterprises (SMEs). By merging data and analysing it with the help of AI, many products, services, and processes in these areas can be made more sustainable.

Sustainable Agriculture Through The Agricultural AI Ecosystem

For example, two projects in the AI ​​innovation competition are developing the basis for using AI-supported applications in agriculture. The Agri-Gaia project is creating an open data infrastructure for this, based on the European Gaia-X standard, among other things. The aim is to develop an agricultural ecosystem where agricultural AI solutions are developed, offered, and used by farmers as services.

The NaLamKI project also uses such a data space for agriculture (Agriculture Data Space) to make existing agricultural data usable for AI services. Specifically, the projects are testing applications. For example, the threat to plants from pests can be precisely determined for the respective location and thus also be able to analyse and calculate whether and how much pesticide should be applied.

Reduce Food Waste With AI

Every year, millions of tons of food are destroyed in Germany before reaching the consumer’s home. An important reason for this is a lack of data and information exchange across all value chains in the food industry.

As a solution to this challenge, the REIF project is developing a platform to optimise the exchange of data and information between agriculture, industry, and trade. The platform can be used to develop and offer AI-based services that enable better forecasts of consumer demand, for example, and adapt food production processes to the current raw material quality in real-time. As a result, the industry can produce food that conserves resources.

Increase Energy Efficiency With Smart Living

In the building industry, smart living applications can do a lot to increase the energy efficiency of buildings, for example, by intelligently controlling the heating system. However, smart living applications from different manufacturers cannot yet be combined.

Therefore, the Foresight project plans to develop a platform for context-sensitive, intelligent, and forward-looking smart living services. It brings together the housing industry, technology providers for buildings, associations, and science to jointly test AI methods for economical operation in the living environment for the first time. In this way, people’s everyday lives and at home should become safer, more energy-efficient, and more comfortable. In the future, applications will cooperate in an overall system and be used for the sustainable use of heating energy and electricity.

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