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MSc Systems Engineering for the Internet of Things Project (COMP0234)

Key information

Faculty
Faculty of Engineering Sciences
Teaching department
Computer Science
Credit value
60
Restrictions
Module delivery for PGT (FHEQ Level 7) available on MSc Systems Engineering for the Internet of Things.
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

In this module students will pull together all the skills they have learned within their degree and carry out a substantive piece of work that will result in a comprehensive written report along with demonstrable protypes, processes, or products. The module 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. There is a broad range of topics and questions that might be considered, and students will work closely with their supervisor in selecting and carrying out the project. Project work will normally be carried out on a full-time basis over a three-month period during the summer term.

Aims:

Students will be required to submit a dissertation as a major element of the work towards their MSc degree. The dissertation should present the findings of a programme of original research, the topic of which is chosen by the student in consultation with a supervisor and the course director. The dissertation is an opportunity to demonstrate the ability to formulate and investigate a question of relevance to the programme of study, and to apply problem solving and subject specific skills to analyse and present the findings of that investigation as an original piece of writing.

This allows 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, while acquiring complementary skills required (e.g., research skills, transferable skills) required to successfully deliver a project from conceptualization to deployment and exploitation.

Intended learning outcomes:

On successful completion of the module, a student will be able to:

Research skills:

  1. Critically examine a research problem within the Sensor Engineering and IoT area using scientific arguments around claims, reasons and evidence.
  2. Discover and define research issues and questions.
  3. Develop algorithms, systems or applications which are then used to report in a clear manner the contribution to the field that their project has achieved.

Subject specific skills:

  1. Develop detailed working knowledge of a chosen subject within the broad topic of sensor systems.
  2. Develop their own ideas and understanding of a topic.
  3. Use this knowledge to create a unique contribution to the design, implementation or exploitation of sensor systems.

Transferable skills:

  1. Develop critical thinking and self-reflection.
  2. Communicate in and to a cross-disciplinary team.
  3. Develop problem-solving skills.

Indicative content:

The following are indicative of the topics the module will typically cover:

Students will choose a project from a list or proposals put forward by supervisors. They will work with input from their supervisor to develop a proposal and then work intensely on these during term 3 before submitting a final dissertation. Students will be supported by regular contact with their supervisor and through a series of skill-based seminars to complement their skills. Core to the student’s development of the dissertation and linking in with the other course modules will be a literature review of the chosen topic and its wider research context.

The dissertation process is outlined here:

  • Initial proposals (beginning Term 2): project proposals from potential supervisors released to students.
  • Agreed proposals (mid Term 2): students may meet with potential supervisors to express interest and/or tailor specific projects. The course director then assigns students to projects and sends a notification to this effect to the project supervisor stating the title of the project and the student. Students should have early project meetings with supervisors to decide on the scope and weighting of various aspects of their contributions.
  • Project pitch (May): Short project presentations providing a brief to the project (problem statement, approach and methodology).
  • Formative Skill-based Seminars (May – June): students should complete the 6 online or in-person skill-based seminars (see below.)
  • Progress report (end June): students will prepare an interim progress report articulating clearly, their claims, reasons and evidence.
  • Development (June – August): students to meet with supervisors ~ 10 times over the 12 weeks of full-time project work.
  • Project submission (September).

The delivery of the module will be augmented by a series of online or in-person skill-based seminars and workshops which will prepare the students to write and deliver on a well-structured dissertation with a clear contribution and evidence-based arguments. Some examples of skill-based seminars and training for students include:

  • The Craft of Research.
  • Responsible Research and Innovation.
  • How to conduct a literature review.
  • Planning, writing and unpicking a Dissertation.
  • Pre-mortem analysis of your project.
  • Referencing & plagiarism.

Requisites:

To be eligible to select this module as an optional or elective, a student must be registered on a programme and year of study for which it is formally available.

Module deliveries for 2024/25 academic year

Intended teaching term: Terms 2 and 3 ÌýÌýÌý Postgraduate (FHEQ Level 7)

Teaching and assessment

Mode of study
In person
Methods of assessment
90% Dissertations, extended projects and projects
10% Viva or oral presentation
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
27
Module leader
Dr Akin Delibasi
Who to contact for more information
cs.pgt-students@ucl.ac.uk

Last updated

This module description was last updated on 8th April 2024.

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