Course - Hydroinformatics for Smart Water Systems - TVM4174
TVM4174 - Hydroinformatics for Smart Water Systems
About
Examination arrangement
Examination arrangement: Aggregate score
Grade: Letter grades
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| Assignment 1 | 30/100 | |||
| School exam | 40/100 | 4 hours | D | |
| Assignment 2 | 30/100 |
Course content
The course provides an overview of the main applications of hydroinformatics for smart water systems, focusing on state of art in systems analysis, simulation and optimization techniques, with an emphasis on water management problems, at both urban and catchment scales. The course provides an overview of current state of art in smart water systems, focusing on challenges and opportunities. It then focuses on providing a good understanding of key data driven, artificial intelligence techniques such as neural networks, surrogate models and data mining that form the "brains" of smart applications.
The course also provides the basis for understanding and managing the challenge of calibration, decision making and quantification of uncertainty using probabilistic optimization techniques such as evolutionary optimization, genetic algorithms and hybrid approaches. Last but not least, the course provides an overview of the field from the other side: that of novel sources of data for smart water systems, including novel sensors and IoT applications for main elements of the water system (pipes, pumps, actuators etc.).
Learning outcome
Knowledge and competence
The topic shall give the students in-depth understanding of the state of art, challenges and opportunities of smart water systems. They shall understand the principles of data driven methods and evolutionary optimization that underpin most of the "intelligence" behind smart water systems as well as the basics of the opportunities and challenges afforded by new ubiquitous sensing and remote-control technologies.
Skills
The students shall be able to use data driven approaches and probabilistic optimization tools to solve relevant problems in water management in the context of smart water systems.
General competence
Students will develop a systems viewpoint to smart water and its link to emerging AI technologies and enhance their ability to critically evaluate problems and solutions in the context of smart water systems.
Learning methods and activities
Lectures will be given on regular basis and supplied with a limited number of hands-on exercises connected to problems from practice. Six hands-on programming assignments related to the course content will be submitted by each student. An oral presentation will focus on briefly presenting a specific project work by each student or student group. A final written exam will consist of multiple choice and open form questions.
Further on evaluation
The course is assessed by a written exam (40 %) and two term papers (30 % + 30 %).
Data Driven Techniques Term Paper will critically review a topic in data driven techniques (analytics) with a clear water application. The paper must be typed, single spaced, at least 5 pages in length, and contain at least references to 10 journal articles and scientific reports.
Smart Water Systems Term Paper will critically review a topic in smart water systems (data from the field, sensors, smart meters, actuators) with a clear water application. The paper must be typed, single spaced, at least 5 pages in length, and contain at least references to 10 journal articles and scientific reports.
The written exam will consist of multiple choice and open form questions.
In case of a re sit exam the exam may be changed from written to oral.
Required previous knowledge
TVM4125 - Water Supply and Wastewater Engineering, Basic Course or similar
Course materials
Notes of lectures, selection of journal articles.
No
Version: 1
Credits:
7.5 SP
Study level: Second degree level
Term no.: 1
Teaching semester: AUTUMN 2024
Language of instruction: English
Location: Trondheim
- Technological subjects
Department with academic responsibility
Department of Civil and Environmental Engineering
Examination
Examination arrangement: Aggregate score
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Autumn ORD School exam 40/100 D 2024-12-17 15:00 INSPERA
-
Room Building Number of candidates SL510 Sluppenvegen 14 1 -
Autumn
ORD
Assignment 1
30/100
Submission
2024-10-31
INSPERA
14:00 -
Room Building Number of candidates -
Autumn
ORD
Assignment 2
30/100
Submission
2024-11-15
INSPERA
14:00 -
Room Building Number of candidates - Summer UTS School exam 40/100 D INSPERA
-
Room Building Number of candidates
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"