A few people have been asking about the curriculum we plan to teach on the MSc in Connected Environments. The design went through a classic double diamond approach where the initial exploration expanded into something requiring a 3 or 4 year undergrad programme! The past six months have been spent narrowing this down into a connected curricula that could be approved by UCL. We are now in the second phase of the diamond as we actually start writing the course materials and again have to work out what we include and leave as additional resources.

Our goal for Connected Environments has always been to focus on the research challenges that relate to the infrastructure required to instrument our built and natural environments from an end to end perspective – ie from understanding what to sense, through to developing tools to support decision making. As such it builds on the need for a skill set in programming, data capture and visualization, and prototyping with stakeholders to support the analysis of complex systems.

A number of key learning objectives have motivated the programme:

  • Understanding of current state of art IoT best practice in an urban context.
  • 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 / crits
  • Carry out independent research

Our teaching and learning strategy is focused on:

  • Learning by doing, making and prototyping (>80% modules practical)
  • Delivering practice-based teaching with living labs that support longitudinal monitoring of the environment
  • Working with stakeholders in the QEOP / London to understand commercial and community needs
  • Facilitating learning interaction across Future Living Institute partners through shared data, sensing and visualisation infrastructure
  • Teaching in 1:1 tutorials, small group and seminar format and incorporating input from industry practitioners.

We anticipate students will leave the course and head in one of three directions:

  • Business: the knowledge to become digital practitioners / leaders in the smart city sector
  • Research: developing cross disciplinary researchers and PhD candidates with a knowledge of Urban IoT technologies
  • Start-ups: the knowledge to bring a novel IoT product or service to the smart city / civictech community

For launch we have 8 modules which are introduced below:


An introduction to building the internet of things for people and the environment. In this module students will be introduced to concepts and technologies underpinning connected environments and the role technology can play in trying to measure and understand the built and natural world. Through a series of 10 practical workshop sessions students will be introduced to IoT prototyping tools, existing sensor systems in UCL East and the Queen Elizabeth Olympic Park and will build a simple sensor system to monitor the environment for the duration of their course.

The aim of this introductory module is to:
Introduce the “learn, build, critique” approach to be used throughout the course
Expose the students to the building blocks of creating a connected environment
Establish a shared ‘connected environment’ they will curate throughout the programme.


Within this module students will be introduced to the theory, context and challenges of user centric design within mobile systems as well as the design, implementation and testing of cross platform applications with respect to sensing the world around us. Students will be exposed to full stack of development tools as well as the process of designing and prototyping mobile applications to interact with IoT devices. Through a series of practical’s students, in groups, will create a mobile application to fulfil a client brief and within each practical will unlock new skills to further develop their application throughout the course.

Aim: To give the student an exposure and understanding of what makes a good mobile application, and developing the skill set to design and build a mobile interfaces and applications.


Learn how to build and deploy the things that sense and monitor the world around us. Through a series of lectures and group projects students will be introduced to the hardware and software of the internet of things that enables us to sense and interact with a connected environment. The module will cover an introduction to the senses, analogue and digital sensors, energy harvesting and powering connected devices, physical prototyping, enclosures and architecture, and mounting / installing sensors.

Aim: To give the student an exposure and understanding of what makes a good connected device, and developing the skill set to design and build an object that can be used to sense or actuate in the built or natural environment.


This module investigated the technical architecture underlying the Web, its subsequent evolution to deal with problems of scale and real-time interaction, the research that has informed its development and expanding to the future of the platform beyond the classic use of sharing and disseminating data. The student will learn how to create website to interact with devices and create interactive visualisations to analyse various datasets. Students will explore the different frameworks (WebBluetooth, WebRTC, for example) as well as learn to leverage advanced machine learning libraries within the browser.

Aim: To give the student an exposure and understanding of what makes a good web application, and developing a skill set to design and build a web interfaces and applications that interact with the physical as well as the digital interfaces.


Students will learn the main concepts of deep learning, understand how to apply deep learning to data streams from cameras and other IoT sensors, and learn how to structure successful deep learning projects. Students will learn about deep learning architectures such as fully connected networks, convolutional networks and RNNs. Students will apply these ideas to sensor data in order to do forecasting, anomaly detection, image recognition, and object tracking. Students will master not only the basic theory, but also learn how to diagnose errors and prioritise directions in deep learning projects. Students will practice all these ideas in Python and TensorFlow.

Aim: To give the students the understanding and practical experience of applying deep learning to sensor data (video, timeseries), and develop the skill set to design and implement deep learning systems for IoT devices.


The module introduces the foundations of visualising sensor data relating to the built environment. It covers core topics such as Geographic Information Systems, Building Information Modelling and links them to the wider ability to consume, analyse and communicate data. The module provides key practical examples in Augmented, Virtual and Mixed Reality of Internet of Things data, leading to the concept of Digital Twins.

Aim: The aims of the module are to provide core background concepts, leading to an understanding of data visualisation methods and leading to a practical build in Augmented / Virtual and / or Mixed Reality with real-time data.


In this module students explore the socio, economic and political factors that influence connected environment projects. Through a series of lectures and guest seminars from practitioners outside of academia, students will gain insight on how IoT is delivered in commercial, environment, community and public office applications. Topics will include stakeholder and community engagement, service design, ethics, GDPR and sustainability. In two separate practical activities students will develop case studies of past projects and assess an IoT product or service using an evaluation framework to explore market readiness of existing services and the challenges of real world IoT deployments.

Aim: To expose students to the commercial landscape for deploying connected devices and to develop an understanding of the strategies required to successfully deliver connected environment services.


In this module project groups will form to identify and develop a connected environments product or service. Through a series of lectures and design reviews these mini projects will be developed from idea to prototype culminating in a pitching session to internal and external experts. Topics will cover idea generation, service design, prototyping, business modelling, starting a business, presentation and pitching an idea.

The aims of the group project are:
– to expose students to the experience of creating a minimal viable prototype for a connected environment product or service in a short space of time,
– to develop the skills and strategic approaches to pitch an idea to an expert panel to get support for further investment.


In this module students will pull together all the skills they have learned within their degree and write an original piece of writing around their final project. The dissertation is an opportunity to demonstrate the ability to formulate and investigate a question of relevance to the programme of study, and to analyse and present the findings of that investigation.

Aims: The dissertation gives the students a chance to pursue research themes that they have chosen and find particularly interesting. It is also a chance to put into practice the skills learned or refined through work for the taught course elements of the Master’s degree.

In addition to the above modules we are exploring different pathways to deliver this content such as integration with our CASA Smart Cities activities and an ecological computing pathway with our colleagues in CBER and CS.

We can also run versions of these modules in short course format for industry – get in touch if interested.

As mentioned last week we have a couple of open posts at the moment for lecturers on the case and we would love to hear from potential PhD candidates who are interested in research in this area.