Research – Projects
Since its founding in 1993, the TECO research group has been directing a multitude of projects across a wide range of research topics which can be divided into three broader Research Fields: Analytics, Human-Computer Interaction, and Sensors and Systems.
With partners from relevant industry sectors and the core idea to tie research and industry closer together, all of these projects are tightly linked to one or multiple Application Areas, most importantly Big Data, the Internet of Things & Industry 4.0, Mobile & Wearable Computing, and Smart Cities.
Other projects study how people interact with electronic devices and which tools can assist individuals or teams in different environments to benefit from technological advancement. Finding new forms of preparing and conveying information by using Augmented Reality or special feedback methods suited for particular contexts is essential to maximize the efficiency and usability of these computer systems.
Filter
OpenEarable
OpenEarable is a new, open-source, Arduino-based platform for ear-based sensing applications.It supports a series of sensors and actuators: a 9-axis inertial measurement unit, an ear canal pressure and temperature sensor, an inward facing ultrasound microphone as well as a speaker, a push button, and a controllable LED. We demonstrate the versatility of the prototyping platform more…
ML4Print
ML4Print In the ML4Print project, we collaborate with E.I.N.S. Software Solutions and Japico Dietz GmbH to tackle the document fraud using Artificial Intelligence. Document fraud is a major concern for the border control and hence for the security of the countries and current solutions lack the ability to identify the fraud in the documents successfully. more…
TreuMoDa – Treuhandstelle für Mobilitätsdaten [Mobility Data Trust Center]
TreuMoDa (TMD) will be designed as an independent and non-profit interface that will enable data from the field of mobility to be made available and used by science, industry and society in accordance with transparent criteria and in compliance with data protection regulations. It will be a building block for strengthening science and innovation by more…
Startup Radar | EUHub4Data
Startup Radar Startup Radar is an advanced Startup Scouting System for Benchmarking & Tech Due Diligence. The system utilizes publicly available information to offer valuable insights into the tech startup ecosystem, including traditionally overlooked markets, such as women-led startups. It aims to level the playing field for investors, end-users, and clients, especially for those, such more…
SoftNeuro
SoftNeuro is a project focused on the development of resource-constrained artificial intelligence for soft robotics and wearables, utilizing neuromorphic systems and soft electronics. The project aims to create a new paradigm for artificial intelligence that overcomes the limitations of traditional computing in soft and wearable devices. The project will leverage the latest advances in neuromorphic more…
edge-ml
edge-ml is a browser based, end-to-end machine learning framework for time-series data on microcontrollers. Data can be ingested using various methods, including live collection. Labeling is supported in a user-friendly manner with a graphical user interface. Based on the datasets and labels, users can train machine learning models which are deployable onto microcontrollers.
FreshIndex | EUHub4Data
FreshIndex in EUHub4Data is a project that focuses on enhancing the safety and sustainability of the food sector by utilizing AI and IoT technologies. The project aims to develop a comprehensive monitoring system that tracks food quality and safety from farm to table, while reducing waste and promoting sustainability throughout the food supply more…
ARCTUS – Monitoring refrigerator condensing units | EUHubs4Data
In the ARCTUS project we develop machine learning (ML) models to monitor refrigerator condensing units (RCU). Such ML models can bring significant value since they provide information on upcoming malfunctions that could stop the operation of an RCU and also predict future energy consumption. For this project we use public datasets as well as data more…
FF4EuroHPC: AI4CAD
AI-Platform for automated training of object detection models based on cad data The manual assembly of devices consisting of many individual parts is a time-consuming, tedious and error-prone industrial process, which could in principle be supported by automated recognition technologies. As a typical example, Gabler is a manufacturer of production machines for packaging goods, each more…