Ambient Intelligence
The group studies efficient algorithms that enable intelligent spaces and interaction, including on-body and environmental sensing, usable security, optimization and machine learning methods.
The group develops algorithms for Pervasive and Mobile Systems, in particular with regard to Activity Recognition and Usable Security. The algorithms are analysed, and optimized with respect to constraints in mobile and pervasive environments and their performance is empirically verified in rigorous experimental studies. The results are regularly demonstrated through instrumentations ranging from mobile devices to prototype sensing hardware.
Contact
The research group is led by Professor Stephan Sigg.
Group members
Sahar Golipoor
Visiting Doctoral Researcher
Latest publications
Towards Green Edge Intelligence
Sami Ben Cheikh, Stephan Sigg
2024
IoT 2023 - Proceedings of the 13th International Conference on the Internet of Things
Direction-agnostic gesture recognition system using commercial WiFi devices
Yuxi Qin, Stephan Sigg, Su Pan, Zibo Li
2024
Computer Communications
Message from the general and tpc co-chairs
Abhishek Dubey, Niki Trigoni, Aron Laszka, Stephan Sigg
2023
2023 IEEE International Conference on Smart Computing (SMARTCOMP)
Accurate RF-sensing of complex gestures using RFID with variable phase-profiles
Sahar Golipoor, Stephan Sigg
2023
2023 IEEE 32nd International Symposium on Industrial Electronics, ISIE 2023 - Proceedings
An Application Programming Interface for Android to support dedicated 5G network slicing
Julián Jerónimo Bañuelos, Jose Costa-Requena, Jiayuan He, Flora Salim, Stephan Sigg
2023
IoT 2023 - Proceedings of the 13th International Conference on the Internet of Things
Detecting an Ataxia-Type Disease from Acceleration Data
Eileen Kranzle, Stephan Sigg
2023
2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023
Introduction to the Special Issue on Wireless Sensing for IoT
Huadong Ma, Yuan He, Mo Li, Neal Patwari, Stephan Sigg
2023
ACM Transactions on Internet of Things
Knowledge Sharing in AI Services: A Market-based Approach
Thaha Mohammed, Si-Ahmed Naas, Stephan Sigg, Mario Di Francesco
2023
IEEE Internet of Things Journal
Fast converging Federated Learning with Non-IID Data
Si Ahmed Naas, Stephan Sigg
2023
2023 IEEE 97th Vehicular Technology Conference, VTC 2023-Spring - Proceedings
A Joint Radar and Communication Approach for 5G NR using Reinforcement Learning
Dariush Salami, Wanru Ning, Kalle Ruttik, Riku Jantti, Stephan Sigg
2023
IEEE Communications Magazine
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