Machine Learning – Page 5

SEIDOR – ARIM – Autonomous Robotic Sea-Floor Infrastructure

SEIDOR – ARIM – Autonomous Robotic Sea-Floor Infrastructure SEIDOR Sector: Industry Business Case Within the scope of a European project, Deusto SEIDOR is responsible for developing artificial vision software to detect, classify, and automatically count benthopelagic species (those living near the bottom) from images captured by aquatic observatories (LoVe Observatory), and autonomous aquatic robots (crawlers). […]

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Tecnalia – WTURBO Wind Turbine Power Train Digital Twin

Quality / Iñaki Suarez

Tecnalia – WTURBO Wind Turbine Power Train Digital Twin Tecnalia Sector: Energy Business Case Operation and maintenance (O&M) costs represent 25 to 35% of the LCOE (levelised cost of energy) of wind turbines. Corrective maintenance is responsible for 30 to 60% of O&M costs. This challenge involves developing a digital twin for the electrical components

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Vicomtech – Optimising the Design of Large CV Joints Using AI

Quality / Iñaki Suarez

Vicomtech – Optimising the Design of Large CV Joints Using AI Vicomtech Sector: Industry Business Case The design and implementation of software based on machine learning involve the analysis of parameters and proposed designs to identify potential failure modes, eliminating the continuous use of test benches. This approach is expected to result in significant energy,

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Ikerlan – Intelligent Digital Assets in Elevation Production Environments

Support / Iñaki Suarez

Ikerlan – Intelligent Digital Assets in Elevation Production Environments Ikerlan Sector: Industry Business Case Need for improvement in the following aspects: Development of advanced predictive models with flexible deployment capabilities in production environments for failure detection. Intelligent elevators capable of communicating and interacting with the user and maintainer. Objectives Intelligent and safe elevating systems that

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IRISBOND – Mamu, Low Resolution Eye-Tracking Software

Support / Iñaki Suarez

IRISBOND – Mamu, Low Resolution Eye-Tracking Software IRISBOND Sector: Health Business Case The proposal involves the development of a computer vision-based eye tracking algorithm for mobile devices. Taking the capabilities of high-resolution eye tracking devices (Hiru) as a reference to try to replicate such functionalities by lowering the costs of having a dedicated hardware. Objectives

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Tecnalia – MAIA Multimodal, Adaptive and Interactive AI System for Acting in Multiple Contexts

Support / Iñaki Suarez

Tecnalia – MAIA Multimodal, Adaptive and Interactive AI System for Acting in Multiple Contexts Tecnalia Sector: Health Business Case Millions of patients worldwide suffer motor disability as a result of stroke, traumatic brain injury, etc. Neuroprostheses allow these patients to control assistive or rehabilitative devices by means of their own biological signals for the replacement

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Versia – Automatic Incident Resolution

Support / Iñaki Suarez

Versia – Automatic Incident Resolution Versia Sector: Logistics Business Case This NLP application records incidents reported via email and, following classification using various NLP techniques, automatically initiates the appropriate corrective actions. (Project in progress. Scheduled for production launch: 30/6/2023). Objectives Reduce human involvement in incident handling. (Operations Management). Reduce procurement problems (stock-outs) due to the

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Vicomtech – Synthetic Data Generation Using AI for the Implementation of an Assembly Assistance System

Support / Iñaki Suarez

Vicomtech – Synthetic Data Generation Using AI for the Implementation of an Assembly Assistance System Vicomtech Sector: Industry Business Case Design and implementation of a system to assist operators during the assembly process of electronic components in assembly lines, using augmented reality. Objectives Develop a system capable of automatically recognising electronic components in real time

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SEIDOR – DS VISUALT

Support / Iñaki Suarez

SEIDOR – DS VISUALT SEIDOR Sector: Health Business Case Online eye tracking system for diagnosing visual problems. Objectives Enable the early diagnosis of visual issues that impede children’s learning, facilitating prompt treatment, and minimising the potential consequences of these problems. Enable the student to return to a normal learning rhythm in the shortest possible time.

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