SMUA4500 Smart Cities Course description

One of the biggest challenges we are facing globally is climate change. Given that our world is becoming more computable opens up the opportunity for applying new technologies to achieve smart cities to fulfil sustainability goals. The current Smart City paradigm has evolved from a technology-only driven approach to a human-centred approach, in which a variety of technological tools help to improve quality of life for people. The main aim of the smart city is to enhance the existing built environment. Nowadays smart cities are geared towards facing future multifaced environmental, social, economic and political challenges of societies. Residents are coming to the forefront in the co-creating of cities, expressing their needs with increasing interest and influencing the design of livable, sustainable cities. An integrated understanding has an enormous impact in planning of smart cities and policy recommendations to achieve livability in urban areas, quality of life for residents and equity in cities. This course is utilizing acquired knowledge from previous and parallel running courses such as advanced methods course, ethics in research, data analysis in GIS, and urban policies, and adds to it the component of smart cities and the human factor.

Language of instruction: English

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Upon completing the course, the student should have the following outcomes:

Knowledge:

Upon successful completion of the course, the student

• understands key concepts of Smart Cities, including IoT, digital twins, urban sensing, open data, AI for cities, and citizen-centric design principles
• can explain and critically reflect on the different paradigms of the smart city
• has knowledge of systems thinking approaches to urban environments, including how mobility, energy, buildings, public space, environment, and governance form interconnected socio-technical systems.
• is familiar with leading international frameworks for smart and sustainable cities (UN SDGs, EU Cities Mission, NEB, ISO 37120/40, ITU-U4SSC).
• knows how data governance, ethics, privacy (GDPR), and algorithmic accountability shape digital innovation in cities.

Skills:

Upon successful completion of the course, the student

• can apply systems thinking tools to analyse complex urban challenges and identify cross-sectoral linkages.
• can use digital and spatial analysis tools (GIS, dashboards, data visualisation) to evaluate city performance indicators and urban form.
• can critically assess smart-city solutions in terms of social, environmental, and governance impacts.
• can compare and evaluate technologies such as IoT sensors, digital twins, and AI-based analytics for planning and operational use.
• can interpret mobility, environmental, or socio-spatial datasets and translate them into planning and design recommendations.

General competence:

Upon successful completion of the course, the student

• can reflect critically on technology-driven urban development and its implications for equity, sustainability, ethics, and democratic governance.
• can communicate smart-city analyses, scenarios, and strategies to diverse stakeholders (municipalities, citizens, researchers, private sector).
• is able to participate in interdisciplinary project teams working on digital-urban innovation.
• is aware of the risks, limitations, and unintended consequences of digital transformations in cities and can argue for responsible and human-centred applications.

The course is delivered through lectures, seminars, practicals, excursions to provide theoretical content, methods and hands-on experience. The students will be given a group or individual project during the semester.

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Part-exam consisting of:

(Part 1) Group or individual project assignment: Project report prepared individually or in groups of 2 students (or more), 3,000-5,000 words incl. figures and references, weighted 70%.

(Part 2) Oral group (or individual if project is written alone) presentation of the project, weighted 30%

Grading is individual, which means that grades may differ within each group. Both oral and written examinations can be presented/written in teams. To ensure that individual grading should be possible, each group of students will provide a written and signed statement in where each individual's contribution is clearly stated and explained.

All assessment parts must be awarded a pass grade (E or better) to pass the course.

Assessment parts: 1) can be appealed and 2) cannot be appealed.

1) All aids are permitted, as long as the rules for source referencing are met.

2) No aid are permitted.

Graded scale A-F.

1) Two internal examiners,

2) Two internal examiners

External examiners are used regularly.

Claudia van der Laag; email: claudia.vanderlaag@oslomet.no