AI for the real world

AI Projects

EAISI focuses on the use of data and algorithms in machines, such as robots, autonomous cars and medical equipment, which has always been a strong aspect of 黑料福利网 and the Eindhoven Brainport region. In addition, we focus on the interaction between humans and systems, including trustworthy and transparent methods resulting in moral and ethical AI. EAISI has defined three main application areas: Health, High-Tech Systems and Mobility.

AI projects in Health

Health related AI applications are:

  • Improved diagnostics
  • Personalized and wearable health systems
  • Better understanding of personal health states
  • Preventive health management
ADVANCING CANCER CARE AND CARDIAC CARE THROUGH INTERPRETABLE AI

ACACIA

The ACACIA project aims to advance cancer and cardiac care with AI, taking a patient-centered and physician-centered approach to address unresolved challenges that hamper adoption of AI in clinical practice.

House as Robot

By developing extreme scenarios and building mock-up鈥檚, we aim to evolve everyday living spaces to adaptive living organisms that understand and empathize with the user. By Masi Mohammadi

AI projects in High-Tech systems and robotics

High-Tech Systems and Robotics applications are:

  • Guaranteed machine performance
  • Autonomous machine operation and smart
  • human-operator support
  • Multi-agent robotics
  • Predictive maintenance
An EAISI Impulse project with ASML

DACCLET

DACCLET focuses on the development of a reliable calculation tool for air entrapment in cooling circuits for lithographic exposure tools, which can be used for the optimal design of a cooling circuit and filling strategies to avoid trapped air. Run time from 2022 - 2026

Digital Twins and Linked Building Data

Web-based information systems are developed, which collect various sorts of data about a building in a decentralized manner, including detailed 3D object models, point clouds, image data, semantic data, sensor data. By Pieter Pauwels

AI in manufacturing

Manufacturing of complex geometries (parametric and structurally optimized structures with minimal material use) will be enabled by digital manufacturing techniques, e.g. robotics in construction and additive manufacturing. By Rob Wolfs

Automated fault detection in photovoltaic (PV) systems

Large-scale monitoring of distributed PV systems in comparison with expected PV output generated by a digital twin network, taking into account dynamic weather conditions, partial shading due to urban surroundings (e.g. from LiDAR data) and the non-linear characteristics of inverters and power systems. By Roel Loonen

Expert systems for spatial-structural-physics design generation

The built environment is responsible for about 40% of the worldwide energy and material resources in a growing market. This requires fully optimized (renovated) buildings and optimized design processes. An open source available toolbox has been developed, providing super structured and super structure free spatial design representations; expert systems to generate, modify, and assess discipline specific representations. By H猫rm Hofmeyer

AI in Mobility projects

Mobility AI applications are:

鈥�    Vision and sensor capabilities for automated driving
鈥�    Data analytics for effective transportation systems and distributed traffic management
鈥�    Advanced Driver Assistance Systems
鈥�    Battery Management Systems
鈥�    Energy use optimization, smart grids
鈥�    Multi-modal transport applications and planning

Machine learning and sensor data

Based on various machine learning algorithms including Bayesian belief networks and decision trees, an integrated data analytics tool is developed to generate the spatial and temporal information related to travel and activities. By Tao Feng

SWT and Linked Data in Autonomous Mobility

Using ideas behind Linked Data and Semantic Web, allows the AI in charge of handling Autonomous Vehicles to consume valuable information from the surrounding ecosystem in order to achieve more optimal calculation of control parameters of the vehicle while using minimal amount of network resources. By Milos Viktorovic

Self-adaptive personal information systems

A Bayesian method for incremental learning an individual鈥檚 preferences based on his or her choice behavior is developed and applied in personal travel information systems. By Theo Arentze

For an overview of all 黑料福利网 project please check out the Research Projects page.