Research – Projects

Research Fields
Application Areas

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.

With the rise of Ubiquitous Computing, computers and therefore sensors have become omnipresent in our daily life. Likewise, Industry 4.0 strategies have introduced sensors in the supply chain and production processes. The TECO research group develops and analyses improvements in how these sensors collect information, connect with each other, and interchange and process data to enable innovative processes throughout society in business, Smart City, industrial and private settings.

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.

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Research Fields
Application Areas


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SDIL – Smart Data Innovation Lab

Description The Smart Data Innovation Lab (SDIL) is a German nationwide research initiative from the Work Group 6 of national IT Summit The SDIL has been launched by national politics and IT industry on 8th January, 2014 at the Karlsruhe Institute of Technology (KIT). The goal of the SDIL more…

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Smart Data Solutions for SMEs in Baden-Württemberg

Besides the BMBF-funded Project SDI-X this project is the second pillar of the state support of the SDIL. The project is funded by the Ministry of science, research and art Baden-Württemberg (MWK) as part of the Smart Data Solution Center Baden-Württemberg (SDSC-BW) to explore the use of suitable smart data technologies for SMEs. more…


Overview image of project "SmarAQnet"

Air quality and the associated subjective and health-related quality of life are among the important topics of our time. However, it is very difficult for many cities to take measures that to accommodate today’s needs concerning e.g. mobility, housing and work, because a consistent data base with fine-granular data and information on causal chains is more…

SDI-X: Smart Data Innovation processes, tools and operational concepts

The BMBF-funded project Smart Data Innovation processes, tools and operational concepts (SDI-X) researches appropriate tools and best practices to not only facilitate extensive data analysis projects between different research and industry partners, but also enable their prompt implementation. The project is one of the publicly-funded pillars that support the operation of the SDIL and as more…


EUHubs4Data Most of Europe’s SMEs lag behind in data-driven innovation. To tackle this problem, the EU-funded EUHubs4Data project will build a European federation of Data Innovation Hubs based on existing key players in this area and connecting with data incubators and platforms, SME networks, AI communities, skills and training organisations and open data repositories. A more…



Coronazä is the most up to date counter of Corona Cases for Germany. It uses unique Web-Crawling technology and intelligent information recognition and AI to keep the information up to date and to prognose future development. 

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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…

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HelioPas AI

HelioPas AI is a startup spin-off which monitors agricultural fields on parameters like crop health and soil moisture. The latest research in data science enables HelioPas AI to produce unparalleled in spatial resolution and prediction accuracy. The data is used by farmers to monitor fields further away to better plan their field work and to more…

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Within the BMBF-funded project “Lehre hoch Forschung”, several measures to establish research-oriented teaching at a much earlier stage than in traditional university teaching are implemented at KIT – both in individual institutes as well as in the central institutions. TECO / the Chair for Pervasive Computing Systems is involved in the more…

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AI driven autocalibration of a heterogeneous sensor network

Environmental sensors must be calibrated regularly in order to correctly take into account construction-related and external influences in the interpretation of the raw data and to correct them accordingly. Only then can any meaning be ascribed to the measurement data. Low-cost sensors are preferably used in Citizen Science applications, whereby a lengthy calibration with an more…

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Software Campus: Data Driven Decision Recommendation for Administrative Bodies Based on Collective Intelligence

The enormous amount of data created by people using every day mobile devices with increasingly sensing capabilities, such as image, location and other data, has led to the establishment of a new crowdsourcing concept called Participatory Sensing. It describes people voluntarily sensing their local environment and sharing this data using mobile phones and the web, more…

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AR Sensors

Servicing the factory of the future raises challenges for the service teams and organizations. The industrial plant environment is changing rapidly due to the impact of the market and new autonomously operating information technologies such as on site information and communication services, an Internet of Things (IoT), smart sensors and intelligent automation devices as well more…

GPU + In-Memory Data Management for Big Data Analytics

In this project, we develop a tool chain based on In-Memory Data Management and Parallel Data Processing in GPU using CUDA for large and intensive Smart Meter analytics.


Software Campus: PreTIGA

The Software Campus project PreTIGA is about optimizing player experience in game environments based on a generalizable model. The objectives are to build a game model generalizable to diverse game environments as a foundation to predict situations of interest like a decrease in fun or the drop-out of players and to proactively prevent such situation. more…

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Towards a Mobile Cloud: an EIT ICT LABS ACTIVITY

Overview of the Research Scenario

The project Towards a Mobile Cloud is an activity in the Computing in the Cloud action line of EIT ICT Labs. It conducts research in order to support next-generation elastic mobile clouds, where mobile scenarios are consistently supported by cloud environments. Benchmarking and Evaluation Tools for assessing more…

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