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TUHH > Forschungsbericht > 2025

Forschungsbericht 2025

Networked Cyber-Physical Systems E-17

Leitung: Landsiedel, Olaf
Oberingenieur: Venzke, Marcus

Institut auf TORE
Institutswebsite

The Institute for Networked Cyber-Physical Systems (NCPS) is part of the School of Electrical Engineering, Computer Science, and Mathematics at the Hamburg University of Technology (TUHH).

Our work is driven by three trends:

  • Sensors are everywhere and give near real-time insights in every aspect of the world.
  • AI is here to stay.
  • Nearly everything gets programmable, see RISE-Lab at https://rise.cs.berkeley.edu/ .

We do - mainly data-driven - systems research on networked and intelligent systems. We are particularly passionate about the Internet of Things (IoT), Cyber-Physical Systems, Edge & Fog Computing, Edge AI and TinyML. We love to build systems and play with them (= run experiments and write papers about them). We release our results as open source and evaluate our work on large-scale testbeds with hundreds of wireless nodes. Software releases of projects in which we were involved are published on GitHub (at https://github.com/tuhh-ncps/ , https://github.com/ds-kiel/ , and https://github.com/iot-chalmers/ ).

Currently, our Institute focuses on the following directions:

Deep Learning

  • Adaptive Machine Learning: Adaptive and flexible Deep Neural Networks
  • Edge AI and TinyML: Resource-efficient and embedded ML
  • Distributed Machine Learning: split computing and federated learning

Internet of Things

  • Low-Power Wireless Networking: Bluetooth (BLE), ZigBee / 802.15.4, LoRa, UWB
  • Wireless Networking: 5G, 6G, 802.11
  • Resilient Internet of Things: Synchronous transmissions for resilient low-latency wireless networking in low-power wireless networks

Edge Computing

  • Distributed Computing: Distributed computing in dynamic and resource-constrained environments
  • Swarms of Autonomous Devices: Coordinating maneuvers, positioning and localization in dynamics and mobile environments
  • Process Mining: Mining of processes on distributed event sources

Publikationen

Projekte

TU Hamburg
Technische Universität
Hamburg (TU Hamburg)
Am Schwarzenberg-Campus 1
21073 Hamburg
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