I) To understand the role of computer systems based on the Cloud and on the Internet of Things in the process of data modelling and transformation in capturing (or collecting) data and in its storage and mining.
II) To know the multiple applications of the Internet of Things in daily life.
III) To realize the impact of IoT on societies’ daily lives and how it influences the development of sustainable solutions.
IV) To know how to choose a cloud-based solution for collecting, storing and mining information collected from the Internet of Things
1. Internet of Things concept and features
2. Application design template
3. Application development tools
4. IoT and Data Science applications
5. Platforms (in the cloud) for IoT data collection, pre-processing, mining and visualization
6. Challenges in the design and implementation of Internet of Things and Data Science-based systems
Lectures are expository, presenting the fundamental concepts of the Internet of Things using examples and applications in the Data Science domain.
The theoretical-practical classes work in conjunction with lectures and are filled by the exposure and analysis of case studies, of small and medium scale, related to the IoT and Data Science, exploring their challenges and how to implement such solutions.
Students develop a project that is the element that brings together the content learned throughout the course, which allows them to experiment the knowledge and methodologies learned in a case study closer to reality and acquire skills of teamwork in a larger project.
The UAc e-Learning Moodle platform (at http://moodle.uac.pt) is used as a repository of educational and didactic material to support learning, as well as a platform for scheduling, disseminating and promoting complementary activities and management of assessment elements.
Students will be assessed on the completion, presentation and discussion of two projects (PI_CD and PI_IoT) with a weight of 45% and 35% respectively, and on the assessment of project discussions and classroom performance (20%). In the assessment by exam (AE), this has a weight of 40% and the average of the projects has a weight of 60%.
Hersent, O., Boswarthick, D. (2012). The Internet of Things: Key Applications and Protocols: Wiley
Hwang, K. (2017). Cloud and Cognitive Computing: A Machine Learning Approach (Cloud Computing for Machine Learning and Cognitive Applications): MIT Press.
Marinescu, D. C. (2013). Cloud Computing: Theory and Practice: Morgan Kaufmann.
Rajkumar, B. & Dastjerdi, A. V. (2016). Internet of Things: Principles and Paradigms: Morgan Kaufmann.
Ruparelia, N. B. (2016). Cloud Computing: MIT Press
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