Prof. Dr.-Ing. Gisela Lanza: Artificial Intelligence - The new production manager
The possible industrial applications of artificial intelligence (AI) are manifold. There are AI systems that perform quality inspection more reliably than humans as well as systems that support engineers in the design phase. Thus, will entire factories soon be managed by AI? Practical examples demonstrate what AI systems can already do, where they are already applied and what limits prevail. Altogether, the new role of production managers will be projected.
Dr. Hannes Sieling: AI-Enabled Price Markdowns for Groceries in Real-Time
AI allows retailers to translate business decisions at scale with a high degree of automation. As grocery retailers experience intensifying competition, they need to manage pricing processes for expiring products to balance profitability and waste. Learn how AI enables the full utilization of intraday POS data and real-time decision making to manage markdowns. Markdown pricing contributes to sustainability goals by minimising and controlling waste based on the retailer’s business strategy.
Guillaume Cazenave: Computer Vision for gains in efficiency and cost saving
There are a growing number of Computer Vision (CV) use cases for increasing efficiency and cost savings of organisations. Prior the Edge AI CV revolution, cameras were used by agents for limited visual monitoring actions. Most of the time, agents could at best see an incident at it was occurring or investigate after it happened. With the implementation of Edge AI CV, a single agent can monitor multiple sites remotely and leverage camera infrastructure and AI to prevent incidents and take proactive decisions. This result in significant improvement in business process and reduction in product loss for an increase in ROI of organisations.
Sébastien Picardat: The challenges of AI and data in agriculture
Decision tools used in precision agriculture and integrating AI are designed using useful digital agricultural data. These data come from the many connected objects in place in farms: weather sensors, drones, electronic loops, etc. By relying on reliable data, exchanged with the consent of farmers, AI can make a major contribution to the sustainability of the agricultural sector.