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Ubiquitous Computing

Lupe

The Ubiquitous Computing paradigm describes a world in which electronic devices are not only unobtrusively embedded within the human’s environment but also in which electronic devices are interacting with each other to support humans in their daily life. Hence, Ubiquitous Computing deals with a wide range of research topics related to Pervasive Computing, Wearable Computing, Ambient Intelligence, Intelligent Environments, Automotive Computing and Smart Homes. Thereby, the context- and location-awareness of Ubiquitous Computing systems are the key enablers for many application scenarios such as carsharing, navigation systems, location-based marketing, home automation or context-aware services in general. The Ubiquitous Computing field is highly dependent on the underlying wireless communication technologies such as 5G networks, WLAN, Bluetooth, NFC etc., and many research questions deal with the optimization of protocols and algorithms that are applied over these wireless communication networks. 

Our research related to Ubiquitous Computing focuses on developing context-aware middlewares for smart mobile devices like smartphones, wearables or tablets. Our work encompasses the design and development of proactive context or location-based service infrastructures for indoor and outdoor environments as well the investigation of new methods for the datafication of mobile data. By enhancing context-aware systems with latest spatiotemporal data analytics techniques, we envision intelligent environments which are able to autonomically learn typical behavior patterns and adapt mobile applications according to situational needs. These self-adaptive systems come along with several interesting research challenges like automatic data processing and analysis, energy-efficient context-awareness and profile-based adaptation of mobile devices, which are all addressed within our research group.

Publications

Salem, M. and Ruppel, P. and Bareth, U. and Küpper, A. (2012). X-centric Positioning: A Combination of Device-centric and Multi-RAT Network-centric Positioning Approaches. Globecom Workshops (GC Wkshps 2012). IEEE, 1741-1746.


Zickau, S. and Küpper, A. (2012). Towards Location-based Services in a Cloud Computing Ecosystem. Ortsbezogene Anwendungen und Dienste - 9. Fachgespräch der GI/ITG-Fachgruppe Kommunikation und Verteilte Systeme. Universitätsverlag Chemnitz, 187-190.


Bareth, U. and Küpper, A. (2011). Energy-Efficient Position Tracking in Proactive Location-based Services for Smartphone Environments. Proceedings of the IEEE 35th Annual Computer Software and Applications Conference (COMPSAC 2011). IEEE, 516-521.


Zickau, S. and Beierle, F. and Denisow, I. (2015). Securing Mobile Cloud Data with Personalized Attribute-based Meta Information. Proceedings of the 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (Mobile Cloud 2015). IEEE, 205-210.


Kjärgaard, M. B. and Treu, G. and Ruppel, P. and Küpper, A. (2008). Efficient Indoor Proximity and Separation Detection for Location Fingerprinting. Proceedings of the 1st Intl. Conference on MOBILe Wireless MiddleWARE, Operating Systems, and Applications (Mobilware 2008)


Rodriguez Garzon, S. and Arbuzin, D. and Küpper, A. (2017). Geofence Index: A Performance Estimator for the Reliability of Proactive Location-Based Services. 2017 18th IEEE International Conference on Mobile Data Management (MDM), 1-10.


S. Rodriguez Garzon and M. Elbehery and B. Deva and A. Küpper (2016). Reliable Geofencing: Assisted Configuration of Proactive Location-based Services. 2016 IEEE International Conference on Mobile Services (MS), 204-207.


Beierle, F. and Grunert, K. and Göndör, S. and Schlüter, V. (2017). Towards Psychometrics-based Friend Recommendations in Social Networking Services. 2017 IEEE 6th International Conference on AI & Mobile Services (AIMS 2017). IEEE, 105–108.


Beierle, F. and Tran, V.T. and Allemand, M. and Neff, P. and Schlee, W. and Probst, T. and Pryss, R. and Zimmermann, J. (2018). TYDR - Track Your Daily Routine. Android App for Tracking Smartphone Sensor and Usage Data. 2018 ACM/IEEE 5th International Conference on Mobile Software Engineering and Systems (MOBILESoft '18). ACM, 72-75.


Grunert, K. (2020). Overview of JavaScript Engines for Resource-Constrained Microcontrollers. 5th International Conference on Smart and Sustainable Technologies 2020(SpliTech 2020)


Beierle, F. and Eichinger, T. (2019). Collaborating with Users in Proximity for Decentralized Mobile Recommender Systems. Proceedings of the IEEE 16th International Conference on Ubiquitous Intelligence and Computing (UIC 2019). IEEE (in press).


Rodriguez Garzon, S. and Pöllabauer, T. and Zickau, S. and Küpper, A. (2019). Interactive Design of Geofences for Proactive Location-based Services in Smart Cities. Proceedings of the 16th IEEE International Conference on Ubiquitous Intelligence and Computing (UIC 2019). IEEE.


Rodriguez Garzon, S. and Küpper, A. (2019). Pay-Per-Pollution: Towards an Air Pollution-Aware Toll System for Smart Cities. 2019 IEEE International Conference on Smart Internet of Things (SmartIoT). IEEE, 361-366.


Victor, F. and Zickau, S. (2018). Geofences on the Blockchain: Enabling Decentralized Location-based Services. 2018 IEEE International Conference on Data Mining Workshops (ICDMW), 97-104.


Rodriguez Garzon, S. and Walther, S. and Pang, S. and Deva, B. and Küpper, A. (2018). Urban Air Pollution Alert Service for Smart Cities. Proceedings of the 8th International Conference on the Internet of Things. Association for Computing Machinery.


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