Machine Learning – Page 3

BCAM – Probabilistic Predictions for Energy Management Based on Continuous Learning

BCAM – Probabilistic Predictions for Energy Management Based on Continuous Learning BCAM Sector: Energy Business Case Obtaining accurate energy demand predictions is difficult due to the continuous changes in consumption patterns (concept drift). Accurate forecasts can optimise the planning of energy production as well as its distribution, resulting in efficient generation and minimising the risk […]

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CAF – Passenger Counter Based on Computer Vision

Prediction / Iñaki Suarez

CAF – Passenger Counter Based on Computer Vision CAF Sector: Mobility Business Case We propose to develop a passenger counter based on computer vision. There is currently one infrared sensor per door for passenger counting. In general, each functionality needs independent sensors. We are looking for a comprehensive solution that combines different functionalities in one

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Cardiva – Demand Forecasting and Logistics Optimisation

Prediction / Iñaki Suarez

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. Thanks to the digitisation of the demand management process, Cardiva has been able to service its business model and commercialise these packs under a pay-per-use

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Data Value Management – Prediction and Reduction of Micro-Stops

Prediction / Iñaki Suarez

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 provoke a large number of micro-stops in the different production lines of a company, in order to reduce their occurrence. Additionally, a secondary system is

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HUPI – Energy Consumption Prediction and Behavioural Modelling of an Entity

Prediction / Iñaki Suarez

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 precise level of granularity: it predicts the level of energy consumption that each specific customer or building will need in the next day/week/month. Objectives Estimate

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Ikerlan – Federated Models for Predicting the Evolution of ICU Patients

Prediction / Iñaki Suarez

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 two main aspects: first, developing predictive models for assessing ICU patient outcomes (improvement, exitus, etc.); and second, implementing these models within a Federated Learning framework

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Inzu Group – Predictive Maintenance of Railway Diversion Elements (SMART DIVERTER)

Prediction / Iñaki Suarez

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 their regular operation. Additionally, the construction material, manganese steel, while noble, tends to develop cracks in hidden areas and is resistant to traditional inspection methods,

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Inzu Group – Federated Artificial Intelligence for Predictive Maintenance on Bridges (FAI4CIM)

Prediction / Iñaki Suarez

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 bridges (10% in Europe, 30% in the USA). Inspection (procedure for assessing the condition of an infrastructure in use) was based on subjective criteria. The

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ITP Aero – ML-Based Turning Process Capability Improvement

Prediction / Iñaki Suarez

ITP Aero – ML-Based Turning Process Capability Improvement ITP Aero Sector: Industry Business Case The goal is to enhance the capability indices of the turning process (Cp, Cpk) through the application of ML techniques. Models based on data from the process itself will be used to make the process self-adaptive. Objectives Improve process capability (reduction

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Mondragon Innovation | Humanity at work – Prediction of Polymer Creep Moduli using Machine Learning

Prediction / Iñaki Suarez

Mondragon Innovation | Humanity at work – Prediction of Polymer Creep Moduli using Machine Learning Mondragon Innovation | Humanity at work Sector: Industry Business Case Polymers gradually lose their stiffness over time when subjected to a constant load, a phenomenon known as creep. Tests to measure this phenomenon are very time-consuming and expensive, meaning the

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