Checking date: 30/06/2021

Course: 2023/2024

Master in Computer Science and Technology (Plan: 462 - Estudio: 71)

Coordinating teacher: GARCIA GUZMAN, JAVIER

Department assigned to the subject: Computer Science and Engineering Department

Type: Electives
ECTS Credits: 6.0 ECTS


Description of contents: programme
1.- Introduction to Software Engineering For IoT 1.1.- Application Areas and practical Applications using IoT 1.2.- Principles of Software Systems Design for IoT 1.3.- Reference Architectures in IoT 2.- Key technologies for IoT 2.1.- Internet of Things Devices, End to End 2.2.- Communications in IoT 2.3.- Securization in IoT 2.4.- Data Architecture for IoT 3.- Development and deployment process for IoT 3.1.- Frameworks 3.2.- Development process for IoT 3.3.- Deployment for IoT 3.4.- Integration and Continuous Delivery
Learning activities and methodology
FORMATIVE ACTIVITIES AF1 - Theoretical class [23.33 hours, 100% attendance, 0,77 ECTS] AF2 - Practical classes [25 hours, 100% attendance, 0,83 ECTS] AF5 - Tutorials [2 hours, 25% attendance, 0,06 ECTS] AF6 - Group work [50 hours, 0% attendance, 1,66 ECTS] AF7 - Individual student work [79 hours, 0% attendance, 2,63 ECTS] AF8 - Midterm and final exams [1.67 hours, 100% attendance, 0,05 ECTS*] TEACHING METHODOLOGIES MD1 - Lectures in the teacher's class with the support of computer and audiovisual media, in which the main concepts of the subject are developed and the bibliography is provided to complement the students' learning. MD2 - Critical reading of texts recommended by the professor of the subject: Press articles, reports, manuals and / or academic articles, either for later discussion in class, or to expand and consolidate the knowledge of the subject. MD3 - Resolution of practical cases, problems, etc ... raised by the teacher individually or in groups MD4 - Presentation and discussion in class, under the moderation of the teacher, on topics related to the content of the subject, as well as practical cases MD5 - Preparation of works and reports individually or in groups
Assessment System
  • % end-of-term-examination 30
  • % of continuous assessment (assigments, laboratory, practicals...) 70
Calendar of Continuous assessment
Basic Bibliography
  • Amita Kapoor. Hands-On Artificial Intelligence for IoT: Expert machine learning and deep learning techniques for developing smarter IoT systems. Packt Publishing. 2019
  • Dirk Slama, Frank Puhlmann, Jim Morrish, Rishi M Bhatnagar. Enterprise IoT: Strategies and Best Practices for Connected Products and Services. O'Reilly Media. 2015
  • Giacomo Veneri. Hands-On Industrial Internet of Things: Create a powerful Industrial IoT infrastructure using Industry 4.0. Packt Publishing. 2018
  • Perry Lea. Internet of Things for Architects: Architecting IoT solutions by implementing sensors, communication infrastructure, edge computing, analytics, and security. Packt Publishing. 2018
  • Qusay F. Hassan. Internet of Things A to Z: Technologies and Applications. Wiley-IEEE Press. 2018

The course syllabus may change due academic events or other reasons.