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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2022/2023

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DRPS : Course Catalogue : School of Informatics : Informatics

Undergraduate Course: Principles and Design of IoT Systems (UG) (INFR11239)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Year 4 Undergraduate) AvailabilityNot available to visiting students
SCQF Credits20 ECTS Credits10
SummaryThis course follows the delivery and assessment of Principles and Design of IoT Systems (INFR11150) exactly. Undergraduate students must register for this course, while MSc students must register for INFR11150 instead.
Course description This course follows the delivery and assessment of Principles and Design of IoT Systems (INFR11150) exactly. Undergraduate students must register for this course, while MSc students must register for INFR11150 instead.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites Students MUST also take: Applied Machine Learning (INFR11211) OR Machine Learning (INFR10086) OR Machine Learning and Pattern Recognition (INFR11130) OR Data Analysis and Machine Learning 4 (ELEE10031)
Prohibited Combinations Students MUST NOT also be taking Principles and Design of IoT Systems (INFR11150)
Other requirements This course follows the delivery and assessment of Principles and Design of IoT Systems (INFR11150) exactly. Undergraduate students must register for this course, while MSc students must register for INFR11150 instead.

Students should be proficient in Java / Python programming.
Course Delivery Information
Academic year 2022/23, Not available to visiting students (SS1) Quota:  None
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 10, Supervised Practical/Workshop/Studio Hours 10, Feedback/Feedforward Hours 0.5, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 175 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) 100% coursework

Practical coursework (70% of the overall marks)
Two survey papers (30%) on foundational topics (max 5000 words) in the area of Internet of Things
Feedback There will be a course feedback opportunity for the students mid-way and at the end of the course. There will be a formative feedback on the coursework provided to the students in Week 6 and Week 10.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Experience the end-to-end design, implementation and demonstration of a typical Internet of Things system, and gaining skills in embedded programming for the collection and processing of sensor data, processing and analysis using machine learning methods, and, displaying the results in an Android mobile application
  2. Gain knowledge in a selection of methods for pre-processing, feature extraction and classification of time-series sensor data, and their efficacy when applied to noisy sensor data
  3. Gain experience using tools such as compilers for IoT development board using inertial sensors, system-level simulators, and Android mobile applications development
  4. Earn the process of gathering information from primary sources such as research papers and reports for comparative study in selected foundational topics in IoT which are distilled in two survey papers
  5. Gain experience working with another team member with complimentary skill sets; develop skills in project management, requirements capture, negotiations, and oral and written presentations
Reading List
None
Additional Information
Graduate Attributes and Skills Develop communication skills (oral/written) for capturing the requirements and specification of complex systems.
Develop inter-personal skills when working with another team member in dividing the work up and dealing with delays, setbacks and other issues.
Develop skills in project management, requirements capture and negotiations.
KeywordsPDIoT,internet of things
Contacts
Course organiserProf D K Arvind
Tel: (0131 6)50 5176
Email: d.k.arvind@ed.ac.uk
Course secretaryMrs Helen Tweedale
Tel: (0131 6)50 3827
Email: Helen.Tweedale@ed.ac.uk
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