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Smart Sensing



#50917 / #2

Seit WS 2021/22

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
2350425 43348 Smart Sensing

Learning Outcomes

After taking this course, students will be able to outline and discuss the latest advances on digital measurement techniques in the broad field of critical urban infrastructure. These include 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). The students will learn what the current research challenges in the field of digital metering are, in different scientific settings. Students will also be able to apply qualitative and quantitative techniques of systematically analysing, summarizing and presenting scientific data and articles. They will then be able to approach the practical implementation of solutions to currently relevant problems in the field of digitalisation of critical urban infrastructure in the “Smart City Hackathon”.


The course content is divided into three thematic clusters: 1) Urban Context and associated opportunities and challenges 2) Conceptual and practical tools of innovation 3) Scientific communication and methodology Across these three areas, the block course “Smart Sensing” deals with the area of sensors, data gathering and processing in different urban critical infrastructure sectors. Moreover, it will give fundamental knowledge about data harvesting and processing (e.g., with new digital sensors and IoT technologies). In this course, the digitalization of urban critical infrastructure will be analysed, with a particular focus on its sensor components and applications. Assessment will include a presentation, the creation of a wiki page and an online quiz. The course 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 7.0 8.0h 56.0h
Pre- / Post Processing 2.0 40.0h 80.0h
Team Project Assignment 1.0 44.0h 44.0h
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 course is taught in lectures, workshops and through group assignments or team project work. These will be held in both synchronous and asynchronous digital formats. This course, together with the “Smart Cities” course is leading up to the “Smart City Hackathon” and takes a problem- and project-based learning approach where groups of students work on real-life urban challenges in partnership with external organisations (city stakeholders). Group assignments are organised as a research, design and/or development project, undertaken by student teams mentored jointly by academic staff and external organisation representatives (field mentors). The courses are going to be fully virtual, while the hackathon will take place in presence as long as pandemic circumstances permit. 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 in two two-day intensive teaching sessions plus a digital pre- and post-processing part which 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. Please note that students can only enrol in EITHER the ‘Smart Sensing’ OR ‘Smart Cities’ module but will receive access to content of both courses. Participants of both modules will be required to participate in the ‘Smart Cities Hackathon’ to be awarded the course ECTS.

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
Presentation (Hackathon Solution) 35 oral No information
Quiz 15 written No information
Wiki Page (Hackathon Solution) 50 written 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; - a Wiki page on the developed solution - a quiz on the preparation material and material covered during the course

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 40.

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 moduleversion is used in the following modulelists:


No information