LKS Next – Deep Learning Systems for Actionable Healthcare Knowledge Generation LKS Next Sector: Health Business Case Healthcare organisations are increasingly interested in the application of artificial intelligence (AI) to […]
Cardiva – Demand Forecasting and Logistics Optimisation Cardiva Sector: Health Business Case Cardiva is a company in the healthcare sector. Among other products, it manufactures single-use packs for operating rooms.
Ceit – MIRAGED: Strategic positioning in virtual models and digital twins for industry 4.0 Ceit Sector: Manufacturing Business Case Digital twins to optimise the operation of industrial manufacturing processes Objectives
Data Value Management – Prediction and Reduction of Micro-Stops Data Value Management Sector: Industry Business Case The challenge is to develop a system capable of detecting the primary causes that
GHI Smart Furnaces – Automatic loading point in tilting rotary furnaces GHI Smart Furnaces Sector: Industry Business Case It is a GHI Smart Furnaces initiative aimed at optimising the charging
HUPI – Energy Consumption Prediction and Behavioural Modelling of an Entity HUPI Sector: Industry Business Case Automatic energy demand prediction for the next period of time (12 months?), with a
HUPI – INGURU PREDICT Evaluation and prediction of the impact of port activities on environmental indicators (turbidity, chlorophyll, hydrocarbons) based on satellite images. HUPI Sector: Mobility Business Case How can
Ikerlan – Federated Models for Predicting the Evolution of ICU Patients Ikerlan Sector: Health Business Case The company currently aims to deliver technological solutions for the healthcare sector, focusing on
Inzu Group – Predictive Maintenance of Railway Diversion Elements (SMART DIVERTER) Inzu Group Sector: Mobility Business Case Railway diversions are crucial components of the infrastructure and are significantly impacted in
Inzu Group – Federated Artificial Intelligence for Predictive Maintenance on Bridges (FAI4CIM) Inzu Group Sector: Industry Business Case Currently, there is no cost-effective method for automatically detecting structural issues in
