Ongoing team projects (FSS 2017 - HWS 2017)
- Active and Online Learning - Your Personal Assistant for Lifestyle Improvement
- Topic Monitoring in the Pharmaceutical Industry
- Knowledge Extraction from WikiFarms
Ongoing team projects (HWS 2016 - FSS 2017)
- Exploring the Future Warehouse
- FitFor4: Semantics-based Integration of Cyber-Physical Systems in the Industrial Internet
Active and Online Learning - Your Personal Assistant for Lifestyle Improvement
The development of wearable devices such as smart-phones features a variety of sensors and provides new opportunities for continuous monitoring and supporting. In this project, we focus on inertial sensors (e.g. Accelerometer, Gyroscope) to recognize common physical activites such as climbing stairs, walking, and standing. We want to develop an application that allows to learn and update online a classification model that should recognize the physical activities. Further, an important aspect is also to query the user concerning uncertain results of the classificiation model. Especially the feasability to query the user is an important aspect of this project. The goal is an Android app that records automatically the performed activities but also interacts with the user in a comfortable way.
Topic Monitoring in the Pharmaceutical Industry
Companies are interested in understanding how they and their products and services are perceived by the public. In this project, we use social media, such as Facebook and Twitter, to address the following questions: (1) what topics related to a company are currently discussed in social media? (2) what topics are trending, recurring, or declining? (3) Are there any geographical differences in the topic coverage?
The topic is performed together with the pharmaceutical company AbbVie.
Knowledge Extraction from WikiFarms
Large-scale public knowledge graph, such as DBpedia or YAGO, are most often only created using a smal set of sources, usually parts of Wikipedia. They have a good coverage w.r.t. well-known entities (such as: big cities or famous athletes), but only a bad coverage of less well-known entities (such as: small villages or minor league athletes). On the other hand, smaller, specialized Wikis, such as fan-created Wikis at WikiFarms, contain detailed information about very specific topics.
In this project, we aim at filling the long tail of DBpedia from thousands of small-scale Wikis. We investigate the potential of a large-number of small-scale Wikis, as well as challenges in data quality and data integration.
Exploring the Future Warehouse
Recognizing, validating, and optimizing activities of workers in logistics is increasingly aided by smart devices like glasses, gloves, and sensor enhanced wristbands. This project focuses on developing a system that recognizes the movement and actions of warehouse employees by processing video and sensor data from a data glass. In the end a mobile application for the data glass will be developed that can aid logistics workers in their tasks.
FitFor4: Semantics-based Integration of Cyber-Physical Systems in the Industrial Internet
Many industry companies are currently adapting or plan to adapt their production processes according to Industry 4.0 standards. Due to the circumstance that lifecycles of production machines tend to be traditionally rather long (i.e. from years to decades), companies are facing several conceptual as well as technical problems such as high integration effort and non-compatibility between interfaces. Therefore this master team project tries to tackle aforementioned problems by constructing an Industry 4.0 compliant infrastructure based on semantic interface descriptions. The results will be then used by Big Data Tools and be evaluated at a real-case industry demonstrator in proceedings of a large IT summit.
- Prof. Dr. Simone Paolo Ponzetto (responsible)
- Dr. Christian Bartelt (contact)
- Fabian Burzlaff (contact)