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Unit information: Smart Cities 4 in 2017/18

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Smart Cities 4
Unit code CENGM0052
Credit points 10
Level of study M/7
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
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 aims of this unit are for the students to:

  • Develop deep insight of a variety of Information and Communication Technologies (ICT) and urban data that facilitate the delivery of integrated infrastructure (e.g. smart buildings, intelligent transport systems);
  • Be able to identify and propose how to use latest developments of ICT and urban data sets within field sectors of Civil and Industrial Engineering (e.g. in design, construction, manufacturing etc.);
  • 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.).

The unit will explore issues of IT within the infrastructure sector and more specifically how technologies such as sensor networks and the Internet of Things, smart meters, data fusion, information modelling, neural networks, 3D modelling etc. are used to deliver integrated services such as smart transport, sustainable planning, structural health monitoring, intelligent 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 new media for stakeholder engagement 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 information technologies that facilitate the delivery of integrated infrastructure, incl. wireless sensor networks, radio frequency identification, artificial neural networks, building information modelling etc.,

2. be able to analyse in depth and specify formally the informational 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.).

Teaching Information

Lectures (~20 hrs), invited talks and/or seminars (~2 hrs), demos and/or computer labs (~2 hrs).

Assessment Information

The unit will be assessed via a combination of individual (40%) and group coursework (60%), involving two discrete but interconnected elements: a critical analysis of contemporary topics in smart cities (individual essay, ULO 1&2), urban app design and/or prototyping including requirements capture, data analysis and visualisation or coding where applicable (group project, ULO 2&3).

Reading and References

Ratti, C (2016), The City of Tomorrow: Sensors, Networks, Hackers, and the Future of Urban Life, Yale University Press (CORE)

Townsend, A (2013), Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, W. W. Norton & Company (CORE)

Various authors (2014), DESIGNING THE URBAN FUTURE: Smart Cities, Letters to the Editor, Scientific American

Foth, M. (Ed.) (2009). Handbook of Research on Urban Informatics: The Practice and Promise of the Real-Time City. Hershey, PA: Information Science Reference, IGI Global.

Kymmell, W. (2008). Building Information Modeling: Planning and Managing Construction Projects with 4D CAD and Simulations. McGraw-Hill Construction Series.

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