Course - Hydroinformatics for Smart Water Systems - TVM4174
TVM4174 - Hydroinformatics for Smart Water Systems
About
Examination arrangement
Examination arrangement: Oral examination and Work
Grade: Letters
| Evaluation form | Weighting | Duration | Examination aids | Grade deviation |
|---|---|---|---|---|
| work | 20/100 | |||
| work | 20/100 | |||
| Oral examination | 60/100 | E |
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, fuzzy logic, 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. Two semester assignments, one related to analytics (software) and one related to smart systems (hardware) will be submitted by each student. A final written exam will consist of multiple choice and open form questions. A final oral presentation will focus on briefly presenting one of the two semester assignments followed by questions.
Compulsory assignments
- Obligatory excercises
Further on evaluation
Oral exam accounts for 60% of the grade, another 2 term assignments account for 20% each. Each part of the total assessment is given a letter grade. Both parts of the assessment must be awarded a passing grade in order to be awarded a passing grade for the course as a whole. For a re-take of an examination, all assessments during the course must be re-taken.
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.
Oral exam including a presentation of the term assignments.
Specific conditions
Exam registration requires that class registration is approved in the same semester. Compulsory activities from previous semester may be approved by the department.
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: SPRING 2021
No.of lecture hours: 3
Lab hours: 2
No.of specialization hours: 7
Language of instruction: English
Location: Trondheim
- Technological subjects
Department with academic responsibility
Department of Civil and Environmental Engineering
Phone:
Examination
Examination arrangement: Oral examination and Work
- Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
- Spring ORD work 20/100 INSPERA
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Room Building Number of candidates - Spring ORD work 20/100 INSPERA
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Room Building Number of candidates - Spring ORD Oral examination 60/100 E
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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"