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| 1.
| Be able to understand the concepts and applications of IoT, and understand the core problems (e.g., networking, sensing) for building IoT systems |
| 2.
| Be able to understand and manage the knowledge of models and principles and compare the performance of key techniques for IoT data analytics. |
| 3.
| Be able to identify and implement practical IoT applications with data analytics techniques |
Mapping from Course Learning Outcomes to Programme Learning Outcomes
| | PLO a | PLO b | PLO c | PLO d | PLO e | PLO f | PLO g | PLO h | PLO i | PLO j |
| CLO 1 | T | T | | | | | | T | | |
| CLO 2 | | T | T | | | | | | | |
| CLO 3 | | | T | T | | | | | | T |
T - Teach, P - Practice
For BEng(CompSc) Programme Learning Outcomes, please refer to
here.
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Calendar Entry:
This course introduces basic concepts, technologies, and applications of the Internet of Things (IoT), with a focus on data analytics. The course covers a range of enabling techniques in sensing, computing, analytics, learning for IoT and connects them to exciting applications in smart homes, healthcare, security, etc. The lectures cover the pipeline of data generation, data acquisition, data transportation, data analysis and learning, and data applications, with various topics from the fundamentals (e.g., signal processing, statistical analysis, machine learning) to real-world systems. Billions of things are connected today, and this course helps students to understand how IoT will evolve into AIoT (Artificial Intelligence of Things).
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Detailed Description:
| Course Content |
Mapped to CLOs
|
| Introduction to IoT | 1, 3 |
| IoT Connectivity | 1, 2 |
| Location Analytics | 2, 3 |
| Mobile Analytics | 2, 3 |
| Radio Analytics | 2, 3 |
| IoT Sensing and Learning | 2, 3 |
| Analytics Systems in IoT | 2, 3 |
| Advanced Topics and Emerging Technologies | 2, 3 |
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