Navigation To modulepage
Display language

Smart Sensing



#50917 / #1

WiSe 2020/21 - SoSe 2021

Fakultät V


Institut für Strömungsmechanik und Technische Akustik

35311100 FG Fluidsystemdynamik-Strömungstechnik der Maschinen und Anlagen

Cominola, Andrea

Fischer, Markus

POS-Nummer PORD-Nummer Modultitel
Keine Verknüpfungen...

Learning Outcomes

During this course, the students will acquire knowledge about the latest advances on digital measurement techniques in the broad field of critical urban infrastructure, including water flow/pressure metering, IoT (Internet of Things) sensors for water and energy applications, simulation of virtual sensors and sensor networks architectures, and processing of sensor data. The technical content on new digital technologies will be coupled with content on the relevance of smart sensing techniques for better monitoring and resilience of interconnected critical urban infrastructure (e.g., water networks, electricity grid, sensor networks), with theory, methods, and applications. The students will learn what the current research challenges in the field of digital metering are, in different scientific settings. They will approach the practical implementation of solutions to currently relevant problems in the field of digitalisation of critical urban infrastructure. They will learn how to concisely present a research work and pitch a project idea and proposed solution.


The block course “Smart Sensing” deals with the area of sensors and data gathering and processing in different urban critical infrastructure sectors (e.g., measurement of flow in a water pipe). Moreover, it will give fundamental knowledge about data harvesting and processing (e.g., with new digital sensors and Internet of Things technologies). In this course, the phenomenon of digitalization of urban critical infrastructure will be analysed, with a particular focus on its sensor components and applications. During the "hackathon" activity, the students will be actively fostered to develop own solutions to relevant problems related to the course content, with a focus on sensor technologies and processing of sensor data. Assessment includes a final presentation of the solution developed in teams to the hackathon challenges. The lectures will be given in English.

Module Components


All Courses are mandatory.

Course Name Type Number Cycle Language SWS VZ
Smart Sensing IV 3531 L 10967 WS English 4

Workload and Credit Points

Smart Sensing (IV):

Workload description Multiplier Hours Total
Attendance 15.0 4.0h 60.0h
Pre/post processing 15.0 8.0h 120.0h
180.0h(~6 LP)
The Workload of the module sums up to 180.0 Hours. Therefore the module contains 6 Credits.

Description of Teaching and Learning Methods

The lectures will be mainly in a frontal presentations format and held virtually via Zoom. Slides will be made available to students. The project (hackathon) includes tutoring sessions to guide the student through the solution development process and give them feedback. A short (max 7 pages) final report will be delivered at the end of the course as a deliverable of small hackathons with teams of participating students. The course is going to be fully virtual and everything is going to be managed online. Further instructions will be communicated to registered students on how to get access to the online lectures and hackathon materials for the school. The course will be conducted as a five-days intensive teaching week plus a digital pre- and post-processing part with includes team activities.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

Preferred competences (not compulsory): basic concepts of mathematical modelling or statistics, basic programming knowledge with Matlab or Python, and basic knowledge of one among water/energy/sensor networks fundamentals and modelling.

Mandatory requirements for the module test application:

No information

Module completion



Type of exam

Portfolio examination

Type of portfolio examination

100 points in total



Test elements

Name Points Categorie Duration/Extent
Group Assignement - project report 50 written No information
Group Presentation - hackathon solution 50 oral No information

Grading scale

Test description (Module completion)

Assessment includes: - a final oral exam, including the presentation of the solutions developed by student teams to the hackathon challenge and a Q&A session; - and a short project report (approx. 7 pages).

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:

Maximum Number of Participants

The maximum capacity of students is 25.

Registration Procedures

Students have to register via the ide3a project website:; the exam registration will take place via Prüfungsamt at TU Berlin.

Recommended reading, Lecture notes

Lecture notes

Availability:  unavailable

Electronical lecture notes

Availability:  unavailable


Recommended literature
No recommended literature given.

Assigned Degree Programs

This module is not used in any degree program.


No information