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Data Science and Artificial Intelligence for Urban Water Management

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WiSe 2021/22 - WiSe 2021/22

English

Data Science and Artificial Intelligence for Urban Water Management

6

Cominola, Andrea

Benotet

Portfolioprüfung

English

Zugehörigkeit


Fakultät V

Institut für Strömungsmechanik und Technische Akustik

35311100 FG Fluidsystemdynamik-Strömungstechnik der Maschinen und Anlagen

Physikalische Ingenieurwissenschaft

Kontakt


FSD

Cominola, Andrea

andrea.cominola@tu-berlin.de

https://www.tu.berlin/en/swn

Lernergebnisse

During this course, the students will acquire knowledge about the latest advances in Data Science (DS) & Artificial Intelligence (AI) for modelling and managing urban water systems, with theory, methods, and applications. They will learn what the current research challenges in the field of urban water systems management are, with focus on the latest DS and AI technologies. They will approach the practical implementation of solutions to currently relevant problems in the fields of digitalisation of urban water and energy systems (e.g., leak detection in water distribution systems), with guided practical activities. They will learn how to concisely analyze and present a research work.

Lehrinhalte

The digital transition of urban water networks towards more data-driven and intelligent systems represents a primary opportunity to tackle the challenges posed by increasing population, urbanisation, and changing climate conditions. As the data-driven transformation reaches into the economy and society, ever-increasing amounts of data are generated by machines or processes based on emerging technologies, such as the Internet of Things (IoT), connected systems, and advanced modelling. While digital disruption has already transformed a number of other industries globally, the water sector has only recently embraced the digital transformation. This is the key to developing suitable adaption strategies that, relying on better information than in the past, support management and decision-making actions to plan adaptation strategies that enhance the resilience of urban water systems under uncertain future climate and social scenarios. In this course, the phenomenon of digitalization of urban water system will be analysed, with particular focus on Data Science and Artificial Intelligence approaches. The course will be structured around the main topic of modelling and management of water distribution networks and identification of anomalies (e.g., leakages) in their normal operation. In addition, other sub-topics will be touched during the course, enabling the students to get an overview of the different elements of modern urban water systems, acquire knowledge about best technologies, get insights on the interactions of water and energy systems in urban areas, and understand the role of human behaviour and cyber-physical security in such systems. The following 5 topics will be covered: MAIN TOPICS 1. Introduction to Data Science and Artificial Intelligence in Urban Water Systems 2. Modelling and control of Urban Water Systems 3. Leakage detection in Water Distribution Networks OTHER TOPICS 4. Cybersecurity and other anomalies in urban water networks 5. Smart metering and behavioural modelling 6. Water-energy nexus and water and urban development. During the project activity, the students will be actively fostered to develop own solutions for a sample problem (e.g., on leakage detection), where they will be guided to implement data-driven solutions on open available datasets. Assessment includes a final presentation combined with a short oral exam, and a short project report. The lecture will be given in English and will include lectures by international guest professors.

Modulbestandteile

Compulsory area

Die folgenden Veranstaltungen sind für das Modul obligatorisch:

LehrveranstaltungenArtNummerTurnusSpracheSWS ISIS VVZ
Data Science and Artificial Intelligence for Urban Water ManagementIVSoSeen4
ISIS-Kurssuche nach Veranstaltungen des Moduls

Arbeitsaufwand und Leistungspunkte

Data Science and Artificial Intelligence for Urban Water Management (IV):

AufwandbeschreibungMultiplikatorStundenGesamt
Attendance5.010.0h50.0h
Exam1.02.0h2.0h
Exam preparation1.028.0h28.0h
Pre/post processing10.010.0h100.0h
180.0h(~6 LP)
Der Aufwand des Moduls summiert sich zu 180.0 Stunden. Damit umfasst das Modul 6 Leistungspunkte.

Beschreibung der Lehr- und Lernformen

The lectures will be mainly in a frontal presentations format. Slides will be made available to students. The project includes tutoring sessions to guide the student through the solution development process and give them feedback. A short (max 5-7 pages) final report will be delivered at the end of the course. Depending on the restrictions in place due to the COVID-19 outbreak, the course will be provided in a fully online or mixed online and in person format. Further instructions about the format, the dates, and on how to get access to the lectures and exercise materials for the course will be communicated to the registered students via mail or via the e-learning ISIS platform.

Voraussetzungen für die Teilnahme / Prüfung

Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen:

Basic programming knowledge and previous experience with Matlab/Python/R is required. Guided practical activities will be performed using Python and Jupyter Notebooks. Preferred competences (not compulsory): concepts of mathematical modelling, concepts of statistics and data analysis, and basic knowledge of water systems.

Verpflichtende Voraussetzungen für die Modulprüfungsanmeldung:

Dieses Modul hat keine Prüfungsvoraussetzungen.

Abschluss des Moduls

Benotung

Benotet

Prüfungsform

Portfolio examination

Art der Portfolioprüfung

100 Punkte insgesamt

Sprache(n)

English

Prüfungselemente

NamePunkteKategorieDauer/Umfang
Oral exam50mündlichKeine Angabe
Project report50schriftlich28

Notenschlüssel

Notenschlüssel »Notenschlüssel 1: Fak IV (1)«

Gesamtpunktzahl1.01.31.72.02.32.73.03.33.74.0
100.0pt86.0pt82.0pt78.0pt74.0pt70.0pt66.0pt62.0pt58.0pt54.0pt50.0pt

Prüfungsbeschreibung (Abschluss des Moduls)

Assessment includes a final presentation combined with a short oral exam, and a short project report (approx. 5-7 pages).

Dauer des Moduls

Für Belegung und Abschluss des Moduls ist folgende Semesteranzahl veranschlagt:
1 Semester.

Dieses Modul kann in folgenden Semestern begonnen werden:
Sommersemester.

Maximale teilnehmende Personen

Die maximale Teilnehmerzahl beträgt 40.

Anmeldeformalitäten

Course registration via Prüfungsamt.

Literaturhinweise, Skripte

Skript in Papierform

Verfügbarkeit:  nicht verfügbar

 

Skript in elektronischer Form

Verfügbarkeit:  verfügbar

 

Literatur

Empfohlene Literatur
Keine empfohlene Literatur angegeben

Zugeordnete Studiengänge


Diese Modulversion wird in folgenden Studiengängen verwendet:

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
Dieses Modul findet in keinem Studiengang Verwendung.

Studierende anderer Studiengänge können dieses Modul ohne Kapazitätsprüfung belegen.

Sonstiges

Keine Angabe