MABY5350 Sensor Networks and Model Based Decisions Support Emneplan

This course aims to provide students with an understanding of the complexities involved with infrastructure projects and the tools required for delivering the project and its wider benefits originally envisaged - on time, on budget, and within scope. It also covers a wide range of skill sets and knowledge areas needed during the life cycle of infrastructure projects in order to ensure successful delivery and at the same time enable them to make decisions and take actions based on the best interest of society, public safety, and the environment.

Grade scale A-F

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student will have

•  broad knowledge about the various sensor types used within the different fields of urban water;
• deep knowledge about the most common properties, deficiencies and uncertainties for the various sensor types;
• insight into the current state-of-the-art of sensor and model usage in current urban water management;
• good understanding of the different requirements for models for design, diagnostics and forecasting.

Skills

The student

• can design and implement simple hydrological/hydraulic models;
• can interpret data using a model;
• can use a model to critically assess sensor data and balance conflicting data against each other for systemwide diagnostics.

General competences

The student will know how to

• integrate knowledge into practice in the water industry to apply this to a range of scenarios, to critically analyse, evaluate, interpret and report on information from a range of sources and to solve complex problems systematically and creatively;
• critically assess sensor data.

The teaching will consist of a combination of:

Lectures & discussions

Independent studies including video recordings and online exercises

Coursework assignments

Guest lectures

Practical use of tools and software.

Two individual multiple-choice of 30 minutes each must be passed.

The students must have individual reflection notes (approx. 4-5 pages per note) approved and linked to 80% of the total guest lectures. Students who fail to meet the coursework requirements can be given up to one opportunity to resubmit reflection notes before the exam.

All aids permitted.

A grade scale with grades from A to E for pass (with A being the highest grade and E being the lowest pass grade) and F for fail is used in connection with the final assessment. 

All types of materials and equipment are allowed.