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Seminar

Selected Topics in Sustainable Communication Networks

June 2022

Wednesday,

June 29th

 

16:00 - 17:00

 

Zoom

Adaptive Protocol Parameters for WSNs

Speaker: Piumika Karunanayake

Wireless Sensor Networks (WSN) are an infrastructure less network and  widely used for multi-disciplinary applications. According to the requirements and the environment, the network is designed and the protocol is tuned to obtain the best performance of the WSN. In real world applications, all nodes in the network have a common protocol parameter set, irrespective of their position in the network.  Tuning protocol parameters for each node manually is tedious and may not be practical for large number of nodes. In this presentation adaptive protocol parameters are introduced using reinforcement learning.

 

Wednesday,

June 15th

 

16:00 - 17:00

 

Zoom

Collective Perception for Road Intersections

Speaker: Thenuka Karunathilake

Vehicular networks has become a major research field because of its promising applications mainly sefety related applications. However, market penetration of V2X enabled vehicles still quiet slow. Therefore, during this long transition period from conventional vehicles to V2X vehicles, collective perception was introduced to increase the road safety by transmitting perceived objects from local sonsors additionally to Collective Awareness Messages (CAM). In this talk, we will discuss the feasibility of using collective perception in a realistic intersection.

 

Wednesday,

June 1st

 

16:00 - 17:00

 

Zoom

Detecting Wolves: Challenges in Image Recognition

Speaker: Jens Dede

After being almost completely absence for more than 100 years, wolves are returning back to Germany since at least two decades. Their continuously increasing population leads to more and more contacts between humans, farm animals and the wolves. The growing number of kills of farm animals – especially sheep, horses and goats – increases the demand for protection technologies.

Traditional fences which offer sufficient protection from wolves are inflexible and expensive. Therefore, alternative and smarter solutions have to be found.

The objective of the mAInZaun project is to develop a smart fence which detects wolves, alarms the owner of the farm animals and starts scare-off stimuli. For this, cameras continuously monitor the environment around the farm animals. If wolves are detected, the eviction will be started automatically.

This talk gives an overview of the current status of the work: What are the challenges of detecting wolves, which frameworks are available and which pitfalls are showing up during the implementation.

 

May 2022

Wednesday,

May 25th

 

16:00 - 17:00

 

Zoom

The Living Habitat for Mars (Humans on Mars)

Speaker: Saurabh Band

Living on Mars will pose immense challenges for humans. One of the many reasons is the lethal environment on the planet. Therefore, the crew will have to live in a habitat that ensures its survival with the help of a life support system (LSS). Hence, it is of utmost importance that the crew can trust this system and that it is designed with the crew in mind. The Living habitat will be equipped with a robust sensor network which is intelligent enough to monitor the habitat as well as diagnose faults in the system itself.
 

 

Wednesday,

May 18th

 

16:00 - 17:00

 

Zoom

Service Management for Enabling Self-Awareness in Low-Power IoT Edge devices

Speaker: Shadi Attarha

In the context of Internet-of-Things (IoT), efficient and flexible service management techniques are essential to improve performance and cost-effectiveness. In this regard, it is crucial to equip the IoT devices with tools that allow a flexible, well-performing, and automated way of efficient services provisioning. Current IoT low-power edge devices have been designed in a way that embedded services can not be monitored and re-configured during the run-time. Hence, finding a trade-off between design requirements, specific performance targets, and services manageability are necessary. The presented project focuses on the idea of service isolation and modularisation at the level of edge devices to observe IoT services and manage them under real-time requirements in extremely resource-constrained IoT environments.

 

Wednesday,

May 11th

 

16:00 - 17:00

 

Zoom

Spatial models to describe indoor environments and to reason about object perspectives

Speaker: Zoe Falomir Llansola

On one hand the challenge is to show how to use spatial models to communicate about indoor environments. For that, first intelligent systems must recognize (i.e. using classical computer vision and machine learning algorithms) and locate objects in space. Then, addressing the following research questions is crucial: which kind of spatial features must the system describe? which kind of reference frames must use? Intelligent systems must have common grounding with users so that they can align spatial representations and communicate with each other.

Then, we will continue to discuss if there are aspects to improve, for example, in the classical algorithms we currently use for recognizing objects. For that, I will show some spatial reasoning tests about object perspectives which are applied to measure students’ intelligence. These tests involve spatial reasoning. And there are psychological experiments that show that people with better spatial reasoning skills are more innovative and successful in science, technology and maths. So, can artificial systems apply some spatial reasoning to evolve their objects' recognition methods to be more cognitive? or even more efficient?

 

Wednesday,

May 4th

 

16:00 - 17:00

 

Zoom

IoT in Academic Institutions in Developing Countries: Lessons learned

Speaker: Marco Zennaro

This talk will present the general topic of IoT4D (IoT for Development). Lessons learned from using IoT in more than 30 workshops in academic institutions in Developing Countries and some success stories will be discussed. The final part of the talk will cover the latest evolution of IoT: Intelligence of Things.

 

April 2022

Wednesday,

April 27

 

16:00 - 17:00

 

Zoom

Machine Learning for Vehicular Networks: challenges and means of solution

Speaker: Minette Zongo Meyo

Road congestion in urban traffic can sometimes be paralyzing. And the increasing volume of road vehicles has made transportation efficiency to become a challenge. Intelligent Transportation Systems are expected to make everyday vehicular operation safer, greener, and more efficient. Machine learning-based platforms for transportation are a valuable solution to achieve this. In fact, ML models can successfully make use of historical data from IoT devices to either control congestion or provide efficient route planning solutions to drivers platforms. However, some challenges hinder the  applicability of ML in the transportation domain. This presentation describes some of them and provide research topics worth exploring. A traffic flow prediction system using ML models is explored at the end of the presentation.

 

Wednesday,

April 20th

 

16:00 - 17:00

 

Zoom

Energy-Driven Computing: Rethinking the Design of Energy Harvesting Systems

Speaker: Geoff Merrett

Energy harvesting computing has been gaining increasing traction over the past decade, fuelled by technological developments and rising demand for autonomous and battery-free systems. Using energy harvesting instead of batteries introduces numerous challenges to embedded systems, not least the transition from an energy-limited source (which can provide virtually unlimited power) to a power-limited source that is highly unpredictable and dynamic (both spatially and temporally, and with a range spanning many orders of magnitude). The typical approach to overcome this is the addition of intermediate energy ‘buffer’ (a small battery or supercapacitor) to smooth out the temporal dynamics of both power supply and consumption. This has the advantage that, if correctly sized, the system ‘looks like’ a battery-powered system; however, it also adds volume, mass, cost and complexity and, if not sized correctly, unreliability. In this talk, I will present a different class of computing to conventional approaches, namely energy-driven computing, where systems are designed from the outset to operate from an energy harvesting source. Such systems typically contain little or no additional energy storage (instead relying on tiny parasitic and decoupling capacitance), alleviating the aforementioned issues. Examples of energy-driven computing include intermittent systems (which power down when the supply disappears and efficiently continue execution when it returns) and power-neutral systems (which operate directly from the instantaneous power harvested, gracefully modulating their consumption and performance to match the supply).

 

April 2022

Wednesday,

April 27

 

16:00 - 17:00

 

Zoom

Machine Learning for Vehicular Networks: challenges and means of solution

Speaker: Minette Zongo Meyo

Road congestion in urban traffic can sometimes be paralyzing. And the increasing volume of road vehicles has made transportation efficiency to become a challenge. Intelligent Transportation Systems are expected to make everyday vehicular operation safer, greener, and more efficient. Machine learning-based platforms for transportation are a valuable solution to achieve this. In fact, ML models can successfully make use of historical data from IoT devices to either control congestion or provide efficient route planning solutions to drivers platforms. However, some challenges hinder the  applicability of ML in the transportation domain. This presentation describes some of them and provide research topics worth exploring. A traffic flow prediction system using ML models is explored at the end of the presentation.

 

Wednesday,

April 20th

 

16:00 - 17:00

 

Zoom

Energy-Driven Computing: Rethinking the Design of Energy Harvesting Systems

Speaker: Geoff Merrett

Energy harvesting computing has been gaining increasing traction over the past decade, fuelled by technological developments and rising demand for autonomous and battery-free systems. Using energy harvesting instead of batteries introduces numerous challenges to embedded systems, not least the transition from an energy-limited source (which can provide virtually unlimited power) to a power-limited source that is highly unpredictable and dynamic (both spatially and temporally, and with a range spanning many orders of magnitude). The typical approach to overcome this is the addition of intermediate energy ‘buffer’ (a small battery or supercapacitor) to smooth out the temporal dynamics of both power supply and consumption. This has the advantage that, if correctly sized, the system ‘looks like’ a battery-powered system; however, it also adds volume, mass, cost and complexity and, if not sized correctly, unreliability. In this talk, I will present a different class of computing to conventional approaches, namely energy-driven computing, where systems are designed from the outset to operate from an energy harvesting source. Such systems typically contain little or no additional energy storage (instead relying on tiny parasitic and decoupling capacitance), alleviating the aforementioned issues. Examples of energy-driven computing include intermittent systems (which power down when the supply disappears and efficiently continue execution when it returns) and power-neutral systems (which operate directly from the instantaneous power harvested, gracefully modulating their consumption and performance to match the supply).

 

February 2022

Wednesday,

February 2nd

 

16:00 - 17:00

 

Zoom

Deep-Space Communication

Speaker: Dr.Andreas Könsgen

This presentation gives an overview about deep-space communication, i.e. primarily the communication to control the spacecraft themselves and to offload payload such as measurement data from observation missions. The presentation explains the conditions and facilities for deep-space communication, gives some examples for research on the topic and an outlook into possible future developments.

 

January 2022

Wednesday,

January 26th

 

16:00 - 17:00

 

Zoom

Offloading an Energy-Efficient IoT Solution to the Edge: A Practical Solution for Developing Countries

Speaker: Gibson Kimutai

Agriculture contributes to the economies of many developing countries. Tea is the most popular crop in Kenya as it contributes majorly to her economy. Among the various stages of processing tea, fermentation is the most important as it determines the final quality of the processed tea.
Presently, the process of monitoring is done manually by tea tasters by tasting, smelling, and touching tea which compromises the quality of tea. In this paper, a deep learner dubbed “TeaNet” is deployed in Edge and Fog environments for real-time monitoring of tea fermentation. We power the
system using a Photovoltaic (PV) energy source to overcome the challenge of unreliable power supply from the grid. Further, the energy consumption of the solution is reduced by applying duty cycling, where idle components are designed to sleep. We used the Analysis of variance (ANOVA) and Post-hoc for data analysis. From the results, Edge registered the lowest latency
compared to the Cloud and Fog environments. During deployment of the energy-optimized model, 50.6559Wh amount of energy was saved.

 

Wednesday,

January 19th

 

16:00 - 17:00

 

Zoom

Imperceptible Sensor Systems for Healthcare Applications

Speaker: Prof.Björn Lüssem

Flexible, stretchable, sometimes even “imperceptible” sensor systems have been intensively studied for their application in the healthcare and wellness sector. Although first systems were based on conventional, silicon-based electronics, the field has experienced a recent boost by the introduction of so called mixed organic conductors.

Mixed organic materials conduct ionic and electric charge equally well, which enables completely new design principles for electronic devices used, e.g., in highly sensitive organic biosensors or neuromorphic devices. In particular, the strong coupling between ion and charge transport observed in these organic mixed conductors has made them a key driver in novel organic bioelectronics based on Organic Electrochemical Transistors (OECTs), with various technological demonstrations in the healthcare sector that include in-situ measurements of brain activity, collection of electrocardiograms, and the tracking of eye movement.

In this presentation, recent advances in the use of flexible and almost imperceptible sensor systems for healthcare monitoring or treatment are presented. An emphasis is put on Organic Electrochemical Transistors, whose working mechanism is reviewed. Current bottlenecks for device optimization are summarized, stressing the need for advanced two-dimensional device modeling and a targeted design of improved semiconductors, electrolytes, and contact materials.

 

Wednesday,

January 12th

 

16:00 - 17:00

 

Zoom

Detecting Wolves: Challenges in Image Recognition

Speaker: Jens Dede

After being almost completely absence for more than 100 years, wolves are returning back to Germany since at least two decades. Their continuously increasing population leads to more and more contacts between humans, farm animals and the wolves. The growing number of kills of farm animals – especially sheep, horses and goats – increases the demand for protection technologies.

Traditional fences which offer sufficient protection from wolves are inflexible and expensive. Therefore, alternative and smarter solutions have to be found.

The objective of the mAInZaun project is to develop a smart fence which detects wolves, alarms the owner of the farm animals and starts scare-off stimuli. For this, cameras continuously monitor the environment around the farm animals. If wolves are detected, the eviction will be started automatically.

This talk gives an overview of the current status of the work: What are the challenges of detecting wolves, which frameworks are available and which pitfalls are showing up during the implementation.

 

December 2021

Wednesday,

December 1st

 

16:00 - 17:00

 

Zoom

Mobile Road Side Units for VANETs

Speaker: Thenuka Karunathilake

The number of vehicles on the road is increasing day by day and due to this, the number of fatal accidents on the road is also increasing. One solution for safer roads is to deploy Vehicular Networks (VANETs). The main application of VANETs is enhancing vehicular safety by enabling Vehicle-to-Vehicle communication and Vehicle-to-Infrastructure communication. A major issue for safety-related applications in VANETs is the very short latency requirements because of the high traveling speeds of vehicles. In order to meet these latency requirements, VANETs has introduced the new networking component 'Road Side Unit (RSU)'. However, due to large investment cost-related RSU, the expected level of deployment was not achieved. As a solution for this, the idea of mobile RSUs was introduced. In this speech, we are going to talk about the current status of mobile RSUs in VANETs.

 

November 2021

Wednesday,

November 24th

 

16:00 - 17:00

 

Zoom

Context-aware Enhancements to Epidemic Routing in Opportunistic Networks

Speaker:VishnupriyaParimalam

Opportunistic networks enables the devices to communicate as and when the opportunity rises. This property of OppNets has been explored in routing approaches in a similar operating manner as the traditional infrastructure networks. Specifically, context-aware routing approaches have been the major focus of OppNets in the recent literature. However, the potential of OppNets also extends to data dissemination in destination-less networks. Forwarding approaches in such a network need context such that the data dissemination is favored without the necessity to reach a particular set of users or a particular destination. Hence, the context-awareness need to be defined differently for destination-less OppNets as compared to OppNets in destination-oriented scenarios.

 

Wednesday,

November 17th

 

16:00 - 17:00

 

Zoom

 

 

Opportunistic Networking - Augmenting the Networks of Future

Speaker: Suvadip Batabyal

The future networking architecture will include both terrestrial and the aerial networks with a multitude of devices communicating amongst themselves using different communication technologies. With such an exponential growth in the dimension of network and co-existence of varied wireless technologies, the primary challenge will be the effective and efficient usage of scarce spectrum for a high bandwidth communication. One of the naive technologies which helps in alleviating this problem through spectrum reuse is device-to-device communication underlay cellular networks along with the notion of multi-hop communication paradigm. However, the future networks will also need to service high speed mobile devices (upto 300kmph) which is yet another challenge that needs to be solved. In such scenarios, the opportunistic networking paradigm can improve network availability through opportunistic link establishment. Opportunistic networking paradigm aims to provide an infrastructureless communication by exploiting device proximity. In this presentation we will discuss how the opportunistic networking paradigm can augment the networks of the future and help in improving
service availability and quality of experience for the end user. We shall look at some of the use-cases where opportunistic networking may be employed and how it can be incorporated into modern networking architectures.

 

Wednesday,

November 10th

 

16:00 - 17:00

 

Zoom

 

 

On Communication Networks for Distributed Control in Smart Grids

Speaker: Leonard Fisser

Energy grids and especially distribution grids are in rapid change. The shift to green energies introduces a multitude of new components, such as batteries, electric vehicles (EV) and photovoltaic (PV).The fact that these components express highly dynamic behavior and service requirements are high, forces Distribution System Operators (DSO) to implement active operation management.

In this seminar, we present our current work on distributed control in future distribution grids from the view of communication networks. We focus on our current DFG project nick-named OUREL. After a brief introduction to the control-theoretic aspect of our project, we have a look at the communication network side, highlight key challenges and how we can approach them. We present our work on an all-to-all flooding protocol, designed to effectively disseminate periodic status updates in Smart Grid topologies. Afterwards, we have a look at advanced topics which are part of my PhD-work and include Topology Modeling, Network Coding and Age of Information. If times allows for it, I would like to give you a short demo of our currently work-in-progress full system real-time emulator.

 

October 2021

Wednesday,

October 27th

 

16:00 - 17:00

 

Zoom

 

 

Impact of digital technologies for future industries

Speaker: Dr. Thushara Weerawardane

The process of the industry revolutionised over years from mechanisation to cyber physical systems. The productivity, cost and speed changes within the production process from material to finish product in time varying physical system. Globally, many industries face numerous challenges of handling uncertainties in supply & demand variation of the supply chain & logistics for both raw material and finish products. During manufacturing processes, the reliability of equipment & plant plays key roles to minimise the downtime from the performance and efficiency perspectives. The rapid development in technology and automation created vast improvement in manufacturing systems by providing high quality product and services to a competitive market environment during the last century. Modern technology advancements have created a cyber physical environment in the industry through the integration of automated systems by providing reliable and ubiquitous connectivity among manufacturing processes and systems. With development of industrial internet of thing (IIOT) and AI based technologies, data becomes main fuel for many digital industries. The real-time information availability over the manufacturing process and systems, creates efficient and high quality production platforms. AI technologies provide predictive maintenance and prescriptive analytics within manufacturing industries to create cost effective reliable systems. Currently many industries are moving towards the process of digital transformation within an integrated automated cyber-physical system in order to be competitive in the market.

 

Wednesday,

October 13th

 

16:00 - 17:00

 

Zoom

A Multi-agent-based simulation system for crowd evacuation in the fire emergency environment

Speaker: Gayamini Shanmuganathan

Evacuation and personal safety are major concerns from wide areas or indoors under emergency. Every disaster, whether man-made or natural, we face many unexpected problems, for instance, fatal accidents, and property damage. In some moments like this, panic among pedestrians beings is frequent. Everyone wants to save their lives. As a result of panic, some people lose the energy of thinking. It can also trigger conflicts among pedestrians. In emergencies there is less time to react; This can lead to a large loss of life, since many people who are caught may unaware of the exit to get out from there and are more likely to run in the wrong direction. To prove this, several investigations indicate that a substantial number of deaths occur due to wrong decisions residents make within the available evacuation time. Besides, the conclusion from the past analysis relieves guiding residents during evacuation proves to be more effective because it decreases the average escape time thereby increasing the chance of survival in a fire emergency. However, widespread fire disaster has the highest occurrence of frequency in several concentrated short periods among disasters. To provide a better solution to the issue, systems have been developed to alert or warn pedestrians in the presence of a fire emergency, so they can act promptly. Several approaches are done by past researchers to simulate the crowd evacuation, Nevertheless, the concept of autonomous agents has been bringing into play successfully to investigate collective human behavior during an emergency evacuation over the past decades. Similarly, artificial intelligence is strongly making its footprint in all disciplines. Our first and foremost objective is to evacuate residents safely in the shortest possible time in the event of a fire. With the support of reinforcement learning, which is a subfield of AI, we have done the pedestrian evacuation simulation system in the fire emergency environment. Several steps were taken to develop our system to achieve efficiency in an evacuation, in other words, safely evacuate residents within a short time. When considering a large-scale environment, it has many features, and only a few selected features are designed by ArcMap to enforce as the foundation of the system environment. We adopt the multi-agent concept to train the agents in the NetLogo environment. IIOne important point is that the moment we start training, any resident can only attend the training if they become pedestrians, and they will then share their experience with
others. Also, the deep reinforcement learning algorithm leads them to achieve the optimal policy. Besides, the A* algorithm directed the pedestrians to designated shelters. As well as fire dynamics are created by fire agencies. These results demonstrate empirically that the proposed simulation system is effective with time efficiency and the system has a strong capability to describe, represent, and explain the reality of evacuation.

 

July 2021

Wednesday, July 21st

 

16:00 - 17:00

 

Zoom

Early warning system for landslides using Wireless Sensor Networks

Speaker: Piumika Karunanayake

Landslide is a natural disaster which causes a considerable damage to the natural habitat,
environment, economy and other resources. Due to the randomness of the event, monitoring,
predicting and controlling are major challenges associated with landslides. Yet, developing an
accurate prediction mechanism with an effective early warning system has become a need of
the hour since the damages and the losses occurred due to the landslides are intolerable. There
exist expensive, advanced mechanisms deployed to predict the possibility of occurring
landslides by using satellites and radar systems with artificial intelligence capabilities.
Comparing with the existing high-end systems, a cost effective wireless sensor network which is
capable of identifying the underground movements and soil conditions is introduced as a
practical solution. Yet, dealing with a large number of sensor data and identifying the
correlation of the variables and the occurrence of a landslide is difficult. Hence in this work,
machine learning is used to predict the occurrence of landslide with a set of sensor data
gathered for a period of two years on a land which is identified as prone for land slide in Sri
Lanka. After developing three models for prediction, one model was selected as its performance
measurements are better compared to other two including an accuracy of 99.8%. An prototype
of warning system is also built which takes the model output and display a web based warning
message. Although the developed machine learning model is site specific, similar approach can
be implemented in other landslide prone areas to improve the efficiency of the disaster
management system in Sri Lanka.

 

Wednesday, July 7th

 

16:00 - 17:00

 

Zoom

 

 

Collecting Data in Ubiquitous Infrastructures: How to Engage Communities and Make Sense of Large Volumes of Data

Speaker: Catia Prandi

In this talk, I will present some case studies where crowdsourcing/crowdsensing, and participatory sensing were applied to ubiquitous infrastructures to investigate how to gather data regarding relevant issues (such as urban accessibility and environmental sustainability). In presenting these studies, I will focus on how the systems have been designed and evaluated using HCI methodologies, and I will point to strategies for involving users, such as gamification/gameful experiences and data visualization, in collecting data and making sense of large volumes of data to benefit the different communities.

 

June 2021

Wednesday, June 9th

 

17:00 - 18:00

 

Zoom

LDACS: Self-organizing air-to-air communication

Speaker: Sebastian Lindner (Research Fellow at TUHH)

The Single European Sky Air Traffic Management Research (SESAR) program is a joint undertaking to overhaul and modernize European air traffic management. During all phases of flight, modern digital data links shall realize the Future Communications Infrastructure (FCI). The air-to-air (A2A) component of the FCI is the L-band Digital Aeronautical Communications System (LDACS) A2A mode, which is currently in early stages of development.
In this talk, we would like to present the challenges such a mobile network must tackle and give an overview on the self-organizing medium access control (MAC) that is being researched. Also, an offshoot project towards a Machine Learning-based predictive MAC that realizes coexistence with legacy communication systems in the same frequency band will be discussed.