Undergraduate Course: Principles and Design of IoT Systems (INFR11150)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Year 4 Undergraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | The course is concerned with the emerging discipline of digitising the physical world with networks of wireless sensors, analysing the sensor data using machine learning techniques to extract concise actionable information, and influencing the physical world via actuators, with an optional human in the loop.
The course imparts foundational concepts in IoT through personal research distilled in the form of one survey papers on foundational topics in IoT, and students working in pairs gain hands-on experience by realising a healthcare application idea as a demonstrable IoT system using wearable sensors by the end of the semester. |
| Course description |
The course aims to deliver a sound understanding of the design and analysis of Internet of Things systems through personal research and practice. The research in selected topics in IoT provides the foundational knowledge distilled in the form of a 3000-word survey paper.
The students conduct a major piece of coursework working in pairs to develop an IoT application using wearable sensors. Students will experience all the stages in the design and implementation of a complex system, from its specification to the demonstration of a working prototype. They will be exposed to aspects of embedded systems programming, sensor data analytics using machine learning methods, user interface design, system integration and testing. Each pair will demonstrate a working prototype at the end of Semester 1 and deliver a written report at the start of Semester 2.
Each student pair is given a couple of Inertial Measurement Unit (IMU) with 3-axis accelerometer and 3-axis gyroscope sensors, and Android app for sensor data collection. The task will be to design, implement and demonstrate a system for human activity recognition in real-time using the wearable sensor which interfaces to an Android App.
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Course Delivery Information
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| Academic year 2024/25, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Supervised Practical/Workshop/Studio Hours 10,
Feedback/Feedforward Hours 1,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
185 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
100% coursework
CW1: Data Collection (10%)
CW2: Research Paper (20%)
CW3: Implementation and final report (70%
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| 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:
- Perform the end-to-end design, implementation and demonstration of a typical Internet of Things system.
- Demonstrate skills in data collection, cleaning, pre-processing, feature extraction and classification of noisy time-series sensor data, using machine learning techniques.
- Develop Android apps and communicate with Bluetooth low-energy devices.
- Gather information from primary sources, such as research papers, for a review paper on a given IoT topic.
- Work productively in a team, where members have complimentary skill sets, and demonstrate competence in project management, requirements capture, negotiations, and oral and written presentations.
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Additional Information
| Course URL |
https://opencourse.inf.ed.ac.uk/pdiot |
| 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.
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| Keywords | PDIoT,Internet of Things |
Contacts
| Course organiser | Prof D K Arvind
Tel: (0131 6)50 5176
Email: d.k.arvind@ed.ac.uk |
Course secretary | Miss Yesica Marco Azorin
Tel: (0131 6)50 5194
Email: ymarcoa@ed.ac.uk |
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