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Ubiquitous Computing

Lupe [1]
© Service-centric Networking

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.

Team
  • Felix Beierle [2]
  • Dr. [3]  [4]Sandro Rodriguez Garzon [5]
  • Philip Raschke [6]
  • Friedhelm Victor [7]
  • Sebastian Zickau [8]

Projects

  • CATLES [9]
  • COMGREEN [10]
  • Context Data Cloud [11]
  • Contextfencing [12]
  • Curcuma [13]
  • FlashPoll [14]
  • Indoor Analytics [15]
  • OpenMobileNetwork [16]
  • PARADISE [17]
  • STEAM [18]
  • Street Smart Retail [19]

Publications

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Beierle, F. and Probst, T. and Allemand, M. and Zimmermann, J. and Pryss, R. and Neff, P. and Schlee, W. and Stieger, S. and Budimir, S. (2020). Frequency and duration of daily smartphone usage in relation to personality traits [27]. Digital Psychology. facultas, 20–28.

Grunert, K. (2020). Overview of JavaScript Engines for Resource-Constrained Microcontrollers [28]. 5th International Conference on Smart and Sustainable Technologies 2020(SpliTech 2020)

Beierle, F. and Egger, S. (2020). MobRec – Mobile Platform for Decentralized Recommender Systems [29]. IEEE Access. IEEE, 185311 - 185329.

Beierle, F. and Tran, V.T. and Allemand, M. and Neff, P. and Schlee, W. and Probst, T. and Zimmermann, J. and Pryss, R. (2020). What data are smartphone users willing to share with researchers? Designing and evaluating a privacy model for mobile data collection apps [30]. Journal of Ambient Intelligence and Humanized Computing. Springer, 2277–2289.

Rodriguez Garzon, S. and Küpper, A. (2019). Pay-Per-Pollution: Towards an Air Pollution-Aware Toll System for Smart Cities [31]. 2019 IEEE International Conference on Smart Internet of Things (SmartIoT). IEEE, 361-366.

Rodriguez Garzon, S. and Deva, B. (2019). Sensafety: Crowdsourcing the Urban Sense of Safety [32]. Advances in Cartography and GIScience of the ICA. Copernicus Publications, 12.

Beierle, F. and Eichinger, T. (2019). Collaborating with Users in Proximity for Decentralized Mobile Recommender Systems [33]. Proceedings of the IEEE 16th International Conference on Ubiquitous Intelligence and Computing (UIC 2019). IEEE, 1192–1197.

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 [34]. Proceedings of the 16th IEEE International Conference on Ubiquitous Intelligence and Computing (UIC 2019). IEEE.

Plass, J. and Zickau, S. (2019). PARADISE - Wie Ortungstechnologien den Datenschutz im Anti-Doping verbessern können [35]. Kritik des Anti-Doping - Eine konstruktive Auseinandersetzung zu Methoden und Strategien im Kampf gegen Doping. Nils Zurawski, Marcel Scharf, 131-157.

Victor, F. and Zickau, S. (2018). Geofences on the Blockchain: Enabling Decentralized Location-based Services [36]. 2018 IEEE International Conference on Data Mining Workshops (ICDMW), 97-104.

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 [37]. 2018 ACM/IEEE 5th International Conference on Mobile Software Engineering and Systems (MOBILESoft '18). ACM, 72-75.

Rodriguez Garzon, S. and Walther, S. and Pang, S. and Deva, B. and Küpper, A. (2018). Urban Air Pollution Alert Service for Smart Cities [38]. Proceedings of the 8th International Conference on the Internet of Things. Association for Computing Machinery.

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). Context Data Categories and Privacy Model for Mobile Data Collection Apps [39]. Procedia Computer Science, 18-25.

Beierle, F. (2018). Do You Like What I Like? Similarity Estimation in Proximity-based Mobile Social Networks [40]. Proceedings 2018 IEEE International Conference On Trust, Security And Privacy In Computing And Communications (TrustCom). IEEE, 1040-1047.

Schanzenbach, M. and Zickau, S. (2017). Identity and Access Management in a Doping Control Use Case [41]. Datenschutz und Datensicherheit - DuD

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TU Berlin - Service-centric Networking - TEL 19
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10587 Berlin, Germany
Phone: +49 30 8353 58811
Fax: +49 30 8353 58409
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