Topics for Projects

MoleNet

Design, Performance Analysis and Applications of Wireless Underground Sensor Networks

Wireless Underground Sensor Networks (WUSNs) allow for the deployment of sensing devices where an over-the-ground installation would be difficult, e.g. in the area of agriculture, environmental monitoring, smart cities etc. WUSN devices and the communication they use however have to face harsh conditions such as a humid environment with varying and often difficult signal propagation characteristics. Since the devices are buried into the ground and cannot be frequently accessed, a long battery lifetime is also desired.

In the MoleNet project, we look at WUSN devices at different stages. We design the hardware using low-energy microcontrollers and providing interfaces for various types of sensors. We develop algorithms and software which control the communication and data collection, and we deploy nodes in the field for different applications. We measure the performance of the nodes w.r.t. the quality and reliability of the communication and develop methods for efficient power management to extend the battey lifetime.

In the scope of the MoleNet project, we are continuously looking for motivated students with good knowledge of hardware development and/or programming and setting up testbeds. Dependent on the type of work, a task can be arranged as a Bachelor/Master project or thesis, or as a student job.

References:

• A new fuzzy logic approach for reliable communications in wireless underground sensor networks (2022)
• Demo: Design and Evaluation of MoleNet for Wireless Underground Sensor Networks (2016)
• MoleNet Blog
• MoleNet GitHub

Supervisor: Dr. Andreas Könsgen

AquAlert

Water Quality Monitoring and Pollution Localization

Water pollution is a significant global issue and efforts are required to prevent it or mitigate its effects, as highlighted by the UN Sustainable Development Goals 3, 6, and 14. In the AquAlert project, we are aiming to develop novel methods for monitoring water quality and localizing sources of pollution in water bodies. A special focus lies on point-sources and rivers. The scope of the project includes IoT, sensors, design and testing of monitoring stations, machine and deep learning for parameter prediction, simulation of pollution behavior, and data analysis.

References: 

• Where does that even come from?! Localizing Water Pollution through IoT and Modeling (2024)
• IoT-Based Anomaly Detection for Identifying Point Sources of Water Pollution (2024)
• AquAlert GitHub

Supervisor: Julia Steiwer