Research

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: 

  1. sensors are everywhere and give near real-time insights in every aspect of the world,
  2. AI is here to stay,
  3. nearly everything gets programmable, see RISE-Lab.

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, often with hundreds of nodes. Software releases of projects in which we were involved are published on GitHub (GitHub TUHH-NCPSGitHub DS-KielGitHub 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

Current Projects at Hamburg University of Technology

DFG Project EdgeMine, part of Research Unit: "SOURCED – Process Mining on Distributed Event Sources"

Distributed, locality-aware process mining and process mining on resource-constrained IoT devices.

Logo

Current Projects at Kiel University

KIMMCO: AI-controlled monitoring of marine microalgae as CO2 sinks

“Understanding the relationship between biodiversity and the CO2 storage capacity of phytoplankton is a key prerequisite for effective marine conservation,” says Prof. Dr Anja Engel, project leader and Professor of Biological Oceanography at the GEOMAR Helmholtz Centre for Ocean Research Kiel.

This is precisely where KIMMCO comes in. The researchers combine approaches at different scales – from in situ sensor measurements and microscopic camera systems to optical water properties and satellite-based remote sensing. AI applications analyse and integrate the collected data, providing a near real-time picture of phytoplankton productivity and species composition.

“With KIMMCO, our goal is to make large-scale measurements more efficient and accurate, while reducing resource usage and speeding up the process,” explains Prof. Dr Kevin Köser, Head of the Marine Data Science group at Kiel University. “This not only saves time and ship operations, but also aims to reduce the CO2 footprint of marine observation itself.”

  • Project website
  • Role: Co-PI
  • Year(s): 2025-2027 (2.5 years)
  • Volume: 325k Euro
Logo
Intelligent Underwater Monitoring, part of “Helmholtz School for Marine Data Science”

Intelligent underwater monitoring systems combining distributed underwater sensor networks with cloud-based digital twins.

Logo
X-Ferry - Building Acceptance For Autonomous Transit Through Understanding

Understanding creates acceptance. This is the premise behind the new CAPTN project X-Ferry. With this research project, the CAPTN initiative is taking another step towards realizing its idea of developing a mobility chain of self-driving, safe and clean vehicles. After the Fjord Area, 5G and Flex projects, which laid the foundation for autonomous shipping in Kiel, the focus is now on explaining the technical processes and communicating with users. Initially, the focus will remain on ships. The new project will research systems that will increase the acceptance of autonomous vehicles.

Logo
An INnovative, intelligent SYSTem for coastal water monitoring using artificial intelligence (INSYST)

Data-driven prediction and event detection for underwater sensing.

Logo