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Unit information: Smart Cities and Infrastructure in 2021/22

Unit name Smart Cities and Infrastructure
Unit code CENGM0081
Credit points 20
Level of study M/7
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Professor. Theo Tryfonas
Open unit status Not open
Pre-requisites

None

Co-requisites

None

School/department Department of Civil Engineering
Faculty Faculty of Engineering

Description including Unit Aims

The unit will explore issues of digitisation of the infrastructure sector and more specifically how high technologies such as sensor networks and the Internet of Things, smart meters, data fusion, information modelling, neural networks, 3D design etc. are used to deliver integrated services such as intelligent transport, sustainable planning, structural health monitoring, smart buildings, stakeholder engagement platforms etc.

The unit contents will cover at a broad level the following topics: wireless sensor networks and their applications, smart metering, radio-frequency identification applications, building information modelling, neural computation and artificial neural networks modelling, knowledge representation and management, 3D modelling and CAD with integrated simulation, use of social media for stakeholder engagement etc.

The aims of this unit are for the students to:

1. Develop a critical perspective of future infrastructure technologies and understanding their impact and role in urban planning, architectural design and construction projects;
2. Develop deep insight of a variety of digital technologies and urban data that facilitate the delivery of integrated infrastructure (e.g. smart buildings, intelligent transport systems);
3. Be able to identify and propose how to use latest developments of high technology products and urban data sets within the sectors of Civil Engineering and Construction (e.g. in planning, design, construction, manufacturing etc.);
4. Be able to use confidently computer-based tools and techniques for the analysis and visualisation of built environment and urban data (e.g. Building Information Modelling, transport data analytics etc.).

Intended Learning Outcomes

By the end of the course, successful students will:

1. Develop an appreciation for, and have a sound understanding of, a variety of digital technologies that facilitate the delivery of integrated infrastructure, including wireless sensor networks, radio frequency identification, artificial neural networks, machine learning, building information modelling etc.;
2. Be able to analyse in depth, and specify formally, the information needs of civil and industrial engineering projects;
3. Be able to define, at system-level, information architectures that meet the needs of the delivery of integrated infrastructure (smart buildings, intelligent transport systems etc.); and
4. Be able to select and use advanced tools for the planning and the delivery of infrastructure projects such as infrastructure data analytics, BIM design standards etc.

Teaching Information

Teaching will be delivered through a combination of synchronous and asynchronous sessions, which may include lectures, practical activities supported by drop-in sessions, problem sheets and self-directed exercises.

Assessment Information

The unit will be assessed via a combination of individual and group coursework, involving two discrete but interconnected elements:

1. a critical analysis of contemporary topics in smart cities and infrastructure (individual essay, ILO 1,2, 40%);

2. urban app design and prototyping including requirements capture, data analysis and visualisation and coding where applicable (group project, ILO 3,4, 60%).

Resources

If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. CENGM0081).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the Faculty workload statement relating to this unit for more information.

Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.

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