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Connected Environments MSc

Connected Environments MSc

University College London

Location

United Kingdom

Qualification

Post Graduate(PG)

Fees

£37,500

Duration

1 year

Next intake

Autumn

Entry score

English language requirements

UCL Centre for Advanced Spatial Analysis has a long history of thinking about the science of cities and how data can help us understand our complex environments. Our goal for the Connected Environments programme is to extend this activity further and focus on the research challenges that relate to the infrastructure required to instrument and understand our built and natural environments from an end to end perspective – i.e from understanding what to sense, through to developing tools to support decision making. As such the course builds on the need for a skill set in programming, data capture and visualisation, and prototyping with stakeholders to support the analysis of complex systems.

The course will be delivered at the brand new UCL East campus on the Queen Elizabeth Olympic Park in Stratford, East London. This is the biggest development in our 200-year history, and our accessible, state-of-the-art facilities will have shared labs and workshop spaces open to all, to facilitate collaboration across different disciplines. Research staff in the Connected Environments Lab have been working with stakeholders in the park for the past 10 years and have established a living lab environment in both the buildings and the surrounding landscape.

The programme has been co-developed with industry as a result of a 5 year industry academic research collaboration between UCL and Intel. A number of key learning objectives motivated the programme:

  • Understanding of current state of art IoT best practice in an urban context.
  • Enable skills to prototype IoT systems
  • Develop skills in embedded AI techniques
  • Develop mobile and web applications to collect and store time-series data
  • Work with stakeholders to gain insight into the politics and economics of IoT
  • Scientifically acquire and analyse data
  • Use data analytics skills
  • Communicate effectively through academic writing and oral presentations
  • Carry out independent research

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