Research Projects
On-Going Projects
MoleNet (2015 - open end)
MoleNet is an internally financed long-term project, which targets two main topics: (1) To develop a reliable and flexible underground sensing system for various environmental and agricultural monitoring scenarios; and (2) to train young researchers hands-on in Internet of Things (IoT) techniques and methodologies. More information can be found under the dedicated MoleNet website. The developed hardware and software can be found on the project's GitHub page.
Contact: Jens Dede
AquAlert (2024 - )
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. A dedicated GitHub page documents the developed software and utilized hardware.
Contact: Julia Steiwer
VerZi (2021 - )
Automatic Behavior Assessment in Dairy Goats
The group housing of livestock in any housing system harbors the potential for competition for scarce resources such as the best resting place, the watering place, or the feeding place. In addition, there are situations in which this competition is intensified by technical disturbances and biological processes in the context of mating behavior. In all animal species, the agonistic interactions resulting from competition entail an increased risk of injury for conspecifics and the humans handling the animals.
The VerZi project aims to automate the process of herd monitoring using artificial intelligence (AI), signal conspicuous animal behavior to the owner, and document the events automatically. This gives farmers a tool to evaluate the effectiveness of their measures.
Developing AI models to detect animal behavior requires collecting and preprocessing data, such as video data while considering ethical implications. Next, suitable AI techniques are selected, and models are designed and trained using labeled datasets. Their performance is validated and tested using metrics like accuracy and precision. Once trained, the models are deployed in real-world systems, like monitoring tools, and are continuously monitored and updated to ensure accuracy.
The project is a collaboration between Vereinigte Informationssysteme Tierhaltung w.V. (vit), ACARiS GmbH, University of Bremen, Justus Liebig University Giessen (JLU) and Forschungsinstitut für Nutztierbiologie (FBN).
Contact: Asanga Udugama and Jens Dede
Network of Excellence in Advanced ICT for Tropical Medicine (2022 - 2025)
This project funded by the DAAD aims to build a community and training repository around the topic of using advanced ICT for various problems and applications in Tropical Medicine. The cooperation between the Mahidol University (Thailand) and University of Bremen organizes workshops and summer schools to teach public health personal about ICT and IoT solutions for use in medical fields. Vectorborne disease detection and response is a main research focus, with topics such as surveillance, prediction and risk modelling, clinical decision support, and disease control. The dedicated ICT-TropMed website offers updates on research and training activities.
Contact: Anna Förster
DFG CRUST (2022 - 2025)
Our project “CRUST” has received financing from the Deutsche Forschungsgemeinschaft (DFG) from its priority program, called Resilient Worlds (https://www.resilient-worlds.org/). The project is now running from the beginning of October 2022 until the end of 2025. Together with the Technical University of Darmstadt, we will devise fundamental solutions to operate unattended IoT systems resiliently and securely.
In Work Package 1, we focus on detecting and classifying adverse events, such as destroyed or manipulated sensors utilizing only the devices’ physical context. Various events are covered, irrespective of the cause of the event (intentional attack, severe weather conditions, continuous degradation, etc.).
In Work Package 2, we design a secure ultra-low latency control channel for IoT systems, which allows forming of secure, collective IoT systems. We further devise enhanced autonomous security schemes for operation in unattended IoT systems by utilizing a security facilitator.
Finally, in Work Package 3, we harness the networked and collective nature of IoT systems and design collective recognition of adverse events and collective self-protection through reconfiguration and self-defence. Moreover, we validate the concepts based on collective intelligence in (existing) real-world testbeds in two representative scenarios: (i) an off-the-grid smart fence for repelling predators such as wolves from livestock and (ii) a smart streetlight deployment for smart city applications.
Contact: Shadi Attarha
Smarter Road, Safer World (2021-2025)
Road safety has become an increasingly critical issue in recent decades, primarily due to the growing number of vehicles on the road, which has led to a rise in traffic accidents. The global vehicle population is expected to increase from 1 billion in 2010 to 2 billion by 2030. This surge is likely to contribute to higher accident rates and significant economic burdens.
One promising solution to mitigate these challenges is the deployment of Vehicular Ad Hoc Networks (VANETs), which allow vehicles to communicate and share information in real time. In Europe, the European Telecommunications Standards Institute (ETSI) is responsible for developing and standardizing VANET protocols. ETSI has introduced several safety-related message standards within the facilities layer of ITS G5, among which Collective Perception Messages (CPMs) play a vital role in improving road safety.
CPMs enable V2X-equipped vehicles to share information about detected objects in their surroundings, including other vehicles, pedestrians, cyclists, and more. This exchange of data enhances situational awareness and helps reduce the risk of collisions. However, excessive transmission of CPMs can lead to channel congestion, resulting in packet loss and increased latency.
At ComNets, we are actively working on optimizing the CPM standard through simulation and mathematical modeling. Our goal is to enhance the effectiveness of collective perception services in future Intelligent Transportation Systems.
Contact: Thenuka Karunathilake
The Living Habitat (2021 - 2024)
This project is financed by the Center for Materials and Processes (MAPEX) (link: https://www.uni-bremen.de/mapex) and runs from December 2021 to November 2024. It is a cooperation project with Prof. Vera Hagemann and Dr. Christiane Heinicke.
Living inside a habitat on Mars will be an unprecedented psychological challenge, imposed by the isolation from other human beings and the nearly uninterrupted confinement. The environment outside the habitat is lethal for humans, meaning that inhabitants must entrust their lives to the life support system (LSS) of the habitat. This trust will be influenced greatly by how well the human crew can understand and control the LSS.
The long-term vision of our idea, for which the proposed project will help lay the foundation, is to develop and investigate human-centered habitat technologies such that they, together with the human crew, form a union that will result in a safe and overall successful stay on Mars.
Our project aims to integrate an LSS component into the habitat. Our use case will be a photobioreactor (PBR) as the air revitalization component of an LSS, to be integrated into the MaMBA habitat laboratory at the ZARM. Our cyanobacterium-hosting PBR shall be able to respond quickly to changes in the human demand for oxygen. We plan to develop situationally aware and interactive sensor networks that will be instrumental for the crew in monitoring the PBR. Since both the PBR and the sensor network will actively respond to crew input, we consider them part of the “living habitat”. From a psychological perspective, we will investigate the living habitat and the crew as members of the same human-agent team.
ComNets’ contribution is to develop a general framework for a system of sensors that is situationally aware, interactive and can be adapted to various components of a LSS, specifically to (1) the PBR in MaMBA and (2) the greenhouse of Eden ISS. The sensing system must recognize high-level events in a responsive and real-time way, such as air quality, particular problems with the LSS, and health issues of the crew members.
Contact: Saurabh Band
mAInZaun (2021 - 2025)
The project mAInZaun (https://www.intelligenter-herdenschutz.de) is developing a new type of fences to protect farm animals like sheep and horses from predators like wolfs. In contrast to classical protection solution, the protection will not be implemented in building tall, strong and expensive classical fences. Instead, cameras, artificial intelligence and advanced deterring technologies are used to reduce the attacks on the farm animals ideally to zero.
The system basically consists of two parts: The sensing part uses cameras and additional sensors to detect an intruder. Artificial intelligence evaluates the data and calculates the risk of a possible attack. In case of an attack, the persons or institutions in charge are notified. Additionally, the second part of the system gets active: Special devices are build to deter the predators using several technologies and approaches. These technologies focus on the main senses of the predators, i.e. sound, light and tactile, to chase them away from the farm animals.
The challenges in the mAInZaun project are manifold. First of all, the system is focussed on mobile fences. Therefore, all components have to be light and easy to transport. They should also be as self-sustaining as possible with a long battery lifetime and not depend on an external power supply. This holds for both, i.e. the sensor and the actor elements.
The second challenge is the reliable detection of intruders and at the same time a low number of false alarms. On one hand, wolves should be detected at all possible light and weather conditions. On the other one, the repellent actions should not be triggered by a normal dog and its owner. Thirdly, the system has to communicate between the devices and also to a central point for status updates and alarm messages. Depending on the area, classical cellular connection cannot be guaranteed.
Our department of sustainable communication networks is responsible for developing, building and optimising the above mentioned devices. Together with the department of Animal Husbandry, Behaviour and Welfare from the Justus-Liebig-University in Giessen and the fence maker RoFlexs, the developed system is evaluated and tested.
mAInZaun is funded by the Federal Ministry of Food and Agriculture.
Contact: Jens Dede
Smart Farming Made Simple (2022 - open end)
Smart farming is an approach in order to make agriculture more resource-efficient. Water for irrigation is a scarce resource in many regions on Earth, and the usage of fertilizer and chemicals such as herbicides and pesticides should be reduced in order to minimize cost and the impact for the environment. In order to maximize the efficiency, in the first place monitoring of the environmental conditions is needed. Irrigation should be controlled dependent on the rain and exposure of the field to the Sun. Fertilizer and other chemicals should be deployed dependent on the conditions in the soil and the growth of the plants. The goal of monitoring the field is achieved by a set of sensors above the ground and in the soil. The data is collected, analysed and reported to the farmer, as well as input to the technical equipment used for bringing out water and chemicals.
Existing smart farming solutions are often expensive and technically complex. Furthermore, they require a profound knowledge about the interpretation of environmental and soil parameters and their meaning for plant growth. Technical know-how in order to integrate the equipment into the given environment and run it in the daily operation is needed as well. In addition, there is no unified solution for different types of crops, different stages of the plant growth etc. Therefore, such smart farming solutions are nowadays mainly suitable for the large-scale industrialised farming in developed countries where the required financial and expert knowledge resources are available.
Our goal is to adapt smart farming solutions to small-scale farming which is widely common in the developing world. This means that any equipment has to be available at low cost and should be usable as flexibly as possible. The equipment should be easy to handle, for monitoring and control an app on a mobile device should be sufficient. The app assists the farmer when deploying the sensor devices in the first place, also considering e.g. the type of crop, and automatically sets up the devices. Based on the measurement data obtained over the time recommendations are given to the farmer how much irrigation and fertilization is needed at which time and also whether the location of individual sensing devices should be changed. When new devices are included, they are automatically integrated into the network without user intervention so that the system can be scaled or modified with changing needs.
This is an internally funded project which is based on the hardware platform developed in MoleNet. The focus here is the automation of all processes involved in running and using the network. On the communications level, this means setting up the wireless communication links, device identfication and controlling the collection of measurement data. In a second step. a knowledge base should then be included which helps to interpret the values and infer recommendations for the farmer.
OMNeT++ Development
Our department is very active in developing and using OMNeT++ in various research projects and in teaching. We are also often involved in the organisation of the annual OMNeT++ Summit (https://summit.omnetpp.org). Here is a short overview of our current research involvement with OMNeT++ and network simulation in general:
- An overview of published papers on the topic of network simulation is available on research gate: https://www.researchgate.net/project/Network-Simulation-and-Models.
- We are actively developing the OPS framework for opportunistic networking: https://github.com/ComNets-Bremen/OPS.
- Additionally to OPS, we also develop benchmarks for opportunistic networks and offer a simulation-as-a-service platform to run benchmarking scenarios: Simulation-as-a-Service to Benchmark Opportunistic Networks.
- We teach network simulation and OMNeT++ in our classes and offer many student projects on this topic: https://www.uni-bremen.de/comnets/studies/topics-for-projects.
Finished Projects
ESA WHISKIES (2020 - 2023)
WHISKIES - Wound Healing In Space: Key challenges towards Intelligent and Enabling Sensing platforms - is a project funded by the European Space Agency (ESA). The project focuses on the monitoring of human wound healing in remote locations such as future manned space habitats e.g. on Mars. Since medical treatment is restricted at such location, great care has to be taken that a wound heals properly in order to avoid e.g. infections. Therefore, it is necessary to understand the details of the wound healing process and the effect on vital parameters such as the body temperature. Furthermore, sensors needed to be developed which measure the vital parameters. With this knowledge at hand, a monitoring system then needs to be designed which is worn by the injured person. The system continously observes the body parameters and gives an alarm if they deviate from the expected values, e.g. in case of an upcoming wound infection. For logging purposes, the measurements and inferences the monitoring system takes should be sent to a server by the wireless on-board network of the space habitat.
WHISKIES is an interdiscipinary project with the participation of a number of research departments and specialized companies across Europe. ComNets Bremen contributes to the project by designing the wearable monitoring hardware and the wireless communication. A major challenge for the design of wearable devices that they should disturb the user as little as possible. Therefore, they need to be easy to wear, so the device should be small and not be a rigid box, but be designed as a mechanically flexible unit. Furthermore, in order to avoid large batteries or frequent battery changes, minimum power consumption is another design goal. An attractive option to reduce battery consumption or even fully avoid the need for a battery is energy harvesting, i.e. generating electric power using energy available in the environment such as body heat. Since the output of such energy harvesting devices is small, i.e. below the power intake of the microcontroller and wireless communication circuit, the full circuit should not run continuously. Instead, it has to sleep most of the time so that the power generated by the harvesting device can be buffered. Once the main circuit runs, the required power is then provided by the buffer.
NAVEL (2020 - 2022)
Any country requires home grown solutions to solve problems faced by different stake holders of the society of those countries. One such area is in finding solutions to problems in ensuring the safety of food during transporting. The ideas and easy-to-use technology that is associated with the Internet of Things (IoT) enable developing cost-effective solutions to many such problems. NAVEL is a project funded by the German Aerospace Centre (DLR) to build a Logistics Innovation Centre in Cameroon. The aim of the project is to build a "Fab Lab" with computing hardware and the know-how, available to entrepreneurs to try out new ideas and technological solutions required in their businesses.
To demonstrate the possibilities of the Fab Lab, we have developed a meat and milk monitoring device to be used in transportation, using the computing hardware available in the Fab Lab. The picture shows the prototype developed. For more information about the prototype and other material, see the link at <https://github.com/ComNets-Bremen/NAVEL.git>.