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CALSCALE:GREGORIAN
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METHOD:PUBLISH
X-WR-TIMEZONE:Europe/Berlin
X-WR-CALNAME:sds-cm
X-IBR-DESCRIPTION:Seminar der Master-, Bachelor- und Projekt-Arbeiten
VERSION:2.0
BEGIN:VTIMEZONE
TZID:Europe/Berlin
X-LIC-LOCATION:Europe/Berlin
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:19700329T020000
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DTSTART:19701025T030000
RRULE:FREQ=YEARLY;INTERVAL=1;BYDAY=-1SU;BYMONTH=10
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Dana Lachmann: KI-gestützte Auswertung von Messdaten aus V2X
 -Simulationen (Project Thesis Final Presentation\, Fynn Schu
 lze)
DTSTART;TZID=Europe/Berlin:20250401T150000
DURATION:PT45M
X-IBR-TYPE:final-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2025-04-01T15-00-00-1-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ss25/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Einführung Vehicle-to-Everything (V2X) bezeichnet die Kommun
 ikationstechnologie\, die es Fahrzeugen ermöglicht\, unterei
 nander sowie mit ihrer Umgebung zu kommunizieren. Durch V2X 
 können Fahrzeuge direkt Daten mit einer sehr niedrigen Laten
 z austauschen\, um die Verkehrssicherheit zu verbessern\, de
 n Verkehrsfluss zu optimieren und neue Möglichkeiten für aut
 omatisiertes Fahren und intelligente Verkehrssysteme zu scha
 ffen. \n Ein großer Teil der V2X-Forschung findet in Simulat
 ionen statt. Dabei werden meist viele Simulationen mit versc
 hiedenen Parametern gleichzeitig durchgeführt. Bisher müssen
  die dabei entstehenden Daten anschließend manuell ausgewert
 et werden. Aufgabenbeschreibung Am Ende der Projektarbeit so
 ll die KI in der Lage sein\, bei der Auswertung der Messerge
 bnisse zu helfen. Dabei soll sie insbesondere natürliche Spr
 ache verstehen und einen Plot aus der Anfrage erzeugen könne
 n. Eine Anfrage könnte z.B. wie folgt aussehen: \"Erstelle m
 ir einen Boxplot von der Channel-Busy-Ratio von allen Bussen
  im Zeitraum von 10s bis 15s aufgeteilt nach Market-Penetrat
 ion-Rate\". \n \n Dazu sind folgende Schritte notwendig: Die
  Ergebnisse jeder Simulation liegen in je einer eigenen SQLi
 te Datenbank. Diese Datenbanken sollen in einer großen Daten
 bank zusammengefasst werden. Ein passender Datenbanktyp und 
 ein Datenbankschema sollen recherchiert und ausgewählt werde
 n. Eine passende KI muss recherchiert und ausgewählt werden.
  Im Sinne der guten wissenschaftlichen Praxis ist es insbeso
 ndere wichtig\, dass die Ergebnisse reproduzierbar sind und 
 dokumentiert werden können. Die KI muss also auch ausgeben\,
  wie sie zu dem Ergebnis gekommen ist. Außerdem dürfen die M
 essergebnisse die IBR-Server nicht verlassen. Die Daten dürf
 en also nicht an ChatGPT o.ä. weitergeleitet werden. Eine Mö
 glichkeit hierfür wäre Vanna.AI. Die in Schritt 1 und 2 ausg
 ewählten Lösungen sollen implementiert und nutzbar gemacht w
 erden. Die KI muss auf unser Datenmodell trainiert werden\, 
 sodass anschließend Anfragen wie die oben genannten möglich 
 sind. Kontakt Falls Ihr Interesse habt\, meldet euch bei: Fy
 nn Schulze
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Not Available
DTSTART;TZID=Europe/Berlin:20250513T150000
DURATION:PT45M
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2025-05-13T15-00-00-2-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ss25/sds-cm/index.html
LOCATION:IZ105
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Lennart Kügler: Entwicklung eines Multi-Connectivity-fähigen
  Routingprotokolls für WSNs (Bachelor Thesis Final Presentat
 ion\, Lara Jüschke)
DTSTART;TZID=Europe/Berlin:20250527T150000
DURATION:PT45M
X-IBR-TYPE:final-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2025-05-27T15-00-00-3-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ss25/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Robin Etzrodt: AI Assisted Evaluation of V2X Simulation Data
  (Project Thesis Final Presentation\, Fynn Schulze)
DTSTART;TZID=Europe/Berlin:20250527T154500
DURATION:PT45M
X-IBR-TYPE:final-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2025-05-27T15-45-00-4-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ss25/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Einführung Vehicle-to-Everything (V2X) bezeichnet die Kommun
 ikationstechnologie\, die es Fahrzeugen ermöglicht\, unterei
 nander sowie mit ihrer Umgebung zu kommunizieren. Durch V2X 
 können Fahrzeuge direkt Daten mit einer sehr niedrigen Laten
 z austauschen\, um die Verkehrssicherheit zu verbessern\, de
 n Verkehrsfluss zu optimieren und neue Möglichkeiten für aut
 omatisiertes Fahren und intelligente Verkehrssysteme zu scha
 ffen. \n Ein großer Teil der V2X-Forschung findet in Simulat
 ionen statt. Dabei werden meist viele Simulationen mit versc
 hiedenen Parametern gleichzeitig durchgeführt. Bisher müssen
  die dabei entstehenden Daten anschließend manuell ausgewert
 et werden. Aufgabenbeschreibung Am Ende der Projektarbeit so
 ll die KI in der Lage sein\, bei der Auswertung der Messerge
 bnisse zu helfen. Dabei soll sie insbesondere natürliche Spr
 ache verstehen und einen Plot aus der Anfrage erzeugen könne
 n. Eine Anfrage könnte z.B. wie folgt aussehen: \"Erstelle m
 ir einen Boxplot von der Channel-Busy-Ratio von allen Bussen
  im Zeitraum von 10s bis 15s aufgeteilt nach Market-Penetrat
 ion-Rate\". \n \n Dazu sind folgende Schritte notwendig: Die
  Ergebnisse jeder Simulation liegen in je einer eigenen SQLi
 te Datenbank. Diese Datenbanken sollen in einer großen Daten
 bank zusammengefasst werden. Ein passender Datenbanktyp und 
 ein Datenbankschema sollen recherchiert und ausgewählt werde
 n. Eine passende KI muss recherchiert und ausgewählt werden.
  Im Sinne der guten wissenschaftlichen Praxis ist es insbeso
 ndere wichtig\, dass die Ergebnisse reproduzierbar sind und 
 dokumentiert werden können. Die KI muss also auch ausgeben\,
  wie sie zu dem Ergebnis gekommen ist. Außerdem dürfen die M
 essergebnisse die IBR-Server nicht verlassen. Die Daten dürf
 en also nicht an ChatGPT o.ä. weitergeleitet werden. Eine Mö
 glichkeit hierfür wäre Vanna.AI. Die in Schritt 1 und 2 ausg
 ewählten Lösungen sollen implementiert und nutzbar gemacht w
 erden. Die KI muss auf unser Datenmodell trainiert werden\, 
 sodass anschließend Anfragen wie die oben genannten möglich 
 sind. Kontakt Falls Ihr Interesse habt\, meldet euch bei: Fy
 nn Schulze
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Development and Evaluation of an SDN Service providing Extri
 nsic Resilience via an intend-based networking API (Bachelor
  Thesis Final Presentation\, Torben Petersen)
DTSTART;TZID=Europe/Berlin:20250708T150000
DURATION:PT45M
X-IBR-TYPE:final-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2025-07-08T15-00-00-5-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ss25/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Task Implementing extrinsic resilience Evaluating the perfor
 mance of extrinsic resilience
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Frederik Poschmann: Strategic Deployment of RSUs with Collec
 tive Perception Capabilities (Master Thesis Preliminary Pres
 entation\, Fynn Schulze)
DTSTART;TZID=Europe/Berlin:20250708T154500
DURATION:PT45M
X-IBR-TYPE:preliminary-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2025-07-08T15-45-00-6-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ss25/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Einführung ... Aufgabenbeschreibung ...
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Lennart Lutz: Energy-Efficient Synchronization in TDMA Proto
 cols for WSNs: An In-Depth Evaluation (Master Thesis Final P
 resentation\, Dr. Jan Schlichter)
DTSTART;TZID=Europe/Berlin:20250715T150000
DURATION:PT45M
X-IBR-TYPE:final-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2025-07-15T15-00-00-7-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ss25/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Introduction Einleitung Task Aufgabe Contact Kontakt If you 
 are interested just contact Dr. Jan Schlichter to discuss fu
 rther details. Wenn du Interesse an dem Thema hast\, melde d
 ich bei Dr. Jan Schlichter um weitere Einzelheiten zu bespre
 chen.
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Maximilian Schwarz: Implementation and Evaluation of PKI and
  Key Distribution for Securing RPL (Master Thesis Preliminar
 y Presentation\, Leonard Zurek)
DTSTART;TZID=Europe/Berlin:20250812T150000
DURATION:PT45M
X-IBR-TYPE:preliminary-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2025-08-12T15-00-00-8-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ss25/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Introduction Wireless Sensor Networks are commonly used in m
 ulti-hop and mesh scenarios. Routing in these lossy networks
  is challenging due to the continuously changing conditions.
  To address this issue\, the Routing Protocol for Low-Power 
 and Lossy Networks (RPL) can be used. Task This thesis aims 
 at filling the gap of secured RPL messages in the widely use
 d embedded operating system RIOT-OS. Contact If you are inte
 rested just contact Leonard Zurek to discuss further details
 .
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Karen Meliksetian: Finding Performance Bottlenecks in WebAss
 embly Applications (Bachelor Thesis Final Presentation\, Len
 nart Almstedt)
DTSTART;TZID=Europe/Berlin:20250819T150000
DURATION:PT45M
X-IBR-TYPE:final-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2025-08-19T15-00-00-9-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ss25/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Aufgabe TBD Anforderungen Interesse an WebAssembly Gute Prog
 rammierkenntnisse in C/C++ Bei Interesse wenden Sie sich bit
 te per E-Mail an Lennart Almstedt . Geben Sie dabei Studieng
 ang\, eventuelle Schwerpunkte\, Ihr Fachsemester sowie Ihre 
 Programmierkenntnisse an.
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Daijiang Chen: Detection and Classification of a Wireless Co
 mmunication Disruption (Master Thesis Preliminary Presentati
 on\, Shashank Jhansale)
DTSTART;TZID=Europe/Berlin:20250924T090000
DURATION:PT45M
X-IBR-TYPE:preliminary-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2025-09-24T09-00-00-10-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ss25/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Motivation The digital revolution is lately being driven by 
 Internet of Things (IoT) devices\, especially in areas where
  real time data analytic is essential. One of the wide sprea
 d usage is in the area of industrial automation where modern
  day industrial equipment have evolved to exploit the advanc
 ements in the smart factory context. With its wireless inter
 faces\, the IoT devices can be portable to carry around and 
 also provide simple means of data accessibility. Although ab
 undant research has been conducted on the wireless communica
 tion\, it is evident that guaranteeing highly reliable commu
 nication over a long period of time could still be challengi
 ng. This holds true specifically in industries where multipl
 e communication technologies interfere with one another. The
  primary reason behind such a behavior is the sharing of the
  unlicensed band of frequency spectrum. The implications of 
 an unreliable communication could be catastrophic with heavy
  machinery and human beings working in close quarters. Topic
  In order to improve reliability in communication\, it is es
 sential to design a network which is resilient to communicat
 ion disruptions. The primary component behind a resilient ne
 twork is its ability to identify disruptions\, by constant m
 onitoring. This helps in taking counter measures to mitigate
  the adversities. The usage of Artificial Intelligence has p
 rovided promising improvements in the field of wireless comm
 unication. It could be used to classify communication disrup
 tions by modelling with suitable inputs. The following activ
 ities are necessary: Creating a simple ad-hoc wireless netwo
 rk using COTS devices and generating background traffic usin
 g IEEE 802.15.4 to induce disruption Developing test applica
 tion to measure and gather network characteristics such as l
 atency\, throughput\, energy metrics for multiple scenarios 
 Designing machine learning models to classify the network st
 ate based on the network characteristics Evaluating the accu
 racy of the model for different combinations of network prop
 erties like latency\, throughput\, etc Note: This thesis has
  to be written in English. In case you are interested in thi
 s topic\, feel free to contact me for an appointment. Skills
  required Python\, Git Linux experience What you will learn 
 Networking in Linux Artificial Intelligence modelling Refere
 nces LSTM-Based Jamming Detection and Forecasting Model Usin
 g Transport and Application Layer Parameters in Wi-Fi Based 
 IoT Systems
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Malte Wiegmann: Evaluation of Discrete Access Point Placemen
 t Algorithm in Physics-Based Ray Tracing Simulation (Bachelo
 r Thesis Final Presentation\, Shashank Jhansale)
DTSTART;TZID=Europe/Berlin:20260414T150000
DURATION:PT45M
X-IBR-TYPE:final-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2026-04-14T15-00-00-1-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ss26/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Motivation Many Access Point (AP) placement algorithms are p
 resent in the literature. Some rely on continuous heatmaps\,
  whereas others use discrete tile-based methods. Continuous 
 placement searches over any point within the region\, while 
 discrete placement of AP limits the options to a predefined 
 set of feasible locations (such as tiles) that capture insta
 llation constraints. In this thesis\, a physics-based simula
 tion environment using Sionna is used to evaluate different 
 tile-based AP placement algorithms to evaluate their effecti
 veness in coverage despite abstract tile nature.
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:CoDaS Theses (Master Thesis \, Shashank Jhansale)
DTSTART;TZID=Europe/Berlin:20260421T150000
DURATION:PT90M
X-IBR-TYPE:intermediate-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2026-04-21T15-00-00-2-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ss26/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Motivation
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Steve Hamann: Evaluation of Path Selection Algorithms and Me
 trics for a Multi-Connectivity Routing Protocol (Bachelor Th
 esis Final Presentation\, Lara Jüschke)
DTSTART;TZID=Europe/Berlin:20251014T150000
DURATION:PT45M
X-IBR-TYPE:final-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2025-10-14T15-00-00-1-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ws2526/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Frederik Poschmann: Strategic Deployment of RSUs with Collec
 tive Perception Capabilities (Master Thesis Final Presentati
 on\, Fynn Schulze)
DTSTART;TZID=Europe/Berlin:20251111T150000
DURATION:PT45M
X-IBR-TYPE:final-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2025-11-11T15-00-00-2-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ws2526/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Einführung ... Aufgabenbeschreibung ...
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Maximilian Schwarz: Implementation and Evaluation of PKI and
  Key Distribution for Securing RPL (Master Thesis Final Pres
 entation\, Leonard Zurek)
DTSTART;TZID=Europe/Berlin:20251216T160000
DURATION:PT45M
X-IBR-TYPE:final-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2025-12-16T16-00-00-3-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ws2526/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Introduction Wireless Sensor Networks are commonly used in m
 ulti-hop and mesh scenarios. Routing in these lossy networks
  is challenging due to the continuously changing conditions.
  To address this issue\, the Routing Protocol for Low-Power 
 and Lossy Networks (RPL) can be used. Task This thesis aims 
 at filling the gap of secured RPL messages in the widely use
 d embedded operating system RIOT-OS. Contact If you are inte
 rested just contact Leonard Zurek to discuss further details
 .
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Viktoria Lammers: Prediction of a Wireless Communication Dis
 ruption (Bachelor Thesis Final Presentation\, Shashank Jhans
 ale)
DTSTART;TZID=Europe/Berlin:20260113T150000
DURATION:PT45M
X-IBR-TYPE:final-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2026-01-13T15-00-00-4-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ws2526/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Motivation The digital revolution is lately being driven by 
 Internet of Things (IoT) devices\, especially in areas where
  real time data analytic is essential. One of the wide sprea
 d usage is in the area of industrial automation where modern
  day industrial equipment have evolved to exploit the advanc
 ements in the smart factory context. With its wireless inter
 faces\, the IoT devices can be portable to carry around and 
 also provide simple means of data accessibility. Although ab
 undant research has been conducted on the wireless communica
 tion\, it is evident that guaranteeing highly reliable commu
 nication over a long period of time could still be challengi
 ng. This holds true specifically in industries where multipl
 e communication technologies interfere with one another. The
  primary reason behind such a behavior is the sharing of the
  unlicensed band of frequency spectrum. The implications of 
 an unreliable communication could be catastrophic with heavy
  machinery and human beings working in close quarters. Topic
  In order to improve reliability in communication\, it is es
 sential to design a network which is resilient to communicat
 ion disruptions. The ability to predict disruptions helps in
  taking counter measures to mitigate the adversities. The us
 age of Artificial Intelligence has provided promising improv
 ements in the field of wireless communication. It could be u
 sed to classify communication disruptions by modelling with 
 suitable inputs. The following activities are necessary: Des
 igning machine learning models to predict the network state 
 based on the network characteristics Evaluating the accuracy
  of the model for different combinations of network properti
 es like latency\, throughput\, etc Note: This thesis has to 
 be written in English. In case you are interested in this to
 pic\, feel free to contact me for an appointment. Skills req
 uired Python\, Git Linux experience What you will learn Netw
 orking in Linux Artificial Intelligence modelling References
  LSTM-Based Jamming Detection and Forecasting Model Using Tr
 ansport and Application Layer Parameters in Wi-Fi Based IoT 
 Systems
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Daijiang Chen: Detection and Classification of a Wireless Co
 mmunication Disruption (Master Thesis Final Presentation\, S
 hashank Jhansale)
DTSTART;TZID=Europe/Berlin:20260127T120000
DURATION:PT45M
X-IBR-TYPE:final-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2026-01-27T12-00-00-5-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ws2526/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:Motivation The digital revolution is lately being driven by 
 Internet of Things (IoT) devices\, especially in areas where
  real time data analytic is essential. One of the wide sprea
 d usage is in the area of industrial automation where modern
  day industrial equipment have evolved to exploit the advanc
 ements in the smart factory context. With its wireless inter
 faces\, the IoT devices can be portable to carry around and 
 also provide simple means of data accessibility. Although ab
 undant research has been conducted on the wireless communica
 tion\, it is evident that guaranteeing highly reliable commu
 nication over a long period of time could still be challengi
 ng. This holds true specifically in industries where multipl
 e communication technologies interfere with one another. The
  primary reason behind such a behavior is the sharing of the
  unlicensed band of frequency spectrum. The implications of 
 an unreliable communication could be catastrophic with heavy
  machinery and human beings working in close quarters. Topic
  In order to improve reliability in communication\, it is es
 sential to design a network which is resilient to communicat
 ion disruptions. The primary component behind a resilient ne
 twork is its ability to identify disruptions\, by constant m
 onitoring. This helps in taking counter measures to mitigate
  the adversities. The usage of Artificial Intelligence has p
 rovided promising improvements in the field of wireless comm
 unication. It could be used to classify communication disrup
 tions by modelling with suitable inputs. The following activ
 ities are necessary: Creating a simple ad-hoc wireless netwo
 rk using COTS devices and generating background traffic usin
 g IEEE 802.15.4 to induce disruption Developing test applica
 tion to measure and gather network characteristics such as l
 atency\, throughput\, energy metrics for multiple scenarios 
 Designing machine learning models to classify the network st
 ate based on the network characteristics Evaluating the accu
 racy of the model for different combinations of network prop
 erties like latency\, throughput\, etc Note: This thesis has
  to be written in English. In case you are interested in thi
 s topic\, feel free to contact me for an appointment. Skills
  required Python\, Git Linux experience What you will learn 
 Networking in Linux Artificial Intelligence modelling Refere
 nces LSTM-Based Jamming Detection and Forecasting Model Usin
 g Transport and Application Layer Parameters in Wi-Fi Based 
 IoT Systems
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTAMP:20250724T143447Z
SUMMARY:Managing Interfaces for Roaming in WiFi Multi-Connectivity N
 etworks (Master Thesis Preliminary Presentation\, David Nied
 erprüm)
DTSTART;TZID=Europe/Berlin:20260319T133000
DURATION:PT45M
X-IBR-TYPE:preliminary-presentation
STATUS:CONFIRMED
CLASS:PUBLIC
UID:sds-cm-2026-03-19T13-30-00-6-v2@ibr.cs.tu-bs.de
URL:http://www.ibr.cs.tu-bs.de/courses/ws2526/sds-cm/index.html
LOCATION:IZ105
DESCRIPTION:
END:VEVENT
END:VCALENDAR