Checking date: 07/06/2024


Course: 2024/2025

Sensor networks and embedded systems communication
(12427)
Master in Electronic Systems Engineering (Plan: 327 - Estudio: 304)
EPI


Coordinating teacher: LOPEZ ONGIL, CELIA

Department assigned to the subject: Electronic Technology Department

Type: Electives
ECTS Credits: 3.0 ECTS

Course:
Semester:




Requirements (Subjects that are assumed to be known)
Microprocessores (VERY RECOMMENDABLE) Digital and Analogue Electronics (basic) (RECOMMENDABLE)
Objectives
SKILLS Students should be able to apply their knowledge and shoulod have the ability to solve problems in new or unfamiliar environments within broader (or multidisciplinary ) contexts related to their field of study . Students should be able to integrate knowledge and handle complexity, and formulate judgments based on information that, being incomplete or limited, includes thoughts about social and ethical responsibilities linked to the application of their knowledge and judgments. Developing concise, clear and justified documentation and specifing the work to be done for the development, integration and implementation of complex and high added value electronic systems. Ability to conceive, design , implement and maintain an electronic system in a specific application. Ability to work within a design team integratin multidisciplinary focuses Adopting the scientific method as a fundamental working tool in both professional and research carreers. Ability to design electronic systems at the behavioral level, from a set of certain specifications, such as at system level, using modeling and simulation tools , such as at subsystem level, using hardware description languages. Ability to handle tools, techniques and methodologies for designing advanced electronic systems or subsystems Ability to design a device, system or application that meets a given specification , using a systemtic and multidisciplinary approach and integrating modules and advanced tools that are specific to the field of Electronic Engineering . Ability to solve practical problems derived from interaction within an electronic system and external elements, with effects such as signal interferences, EMI or thermic management, in design, prototyping and redesign stages. Ability to search efficiently for information as well as to identify the state of the art of a technological problem in the electronic systems scope and its possible application to new systems LEARNING OUTCOMES The students passing this course should be able to: - From a set of specifications and requirements of the diffrenet blocks involved in an electronic system, for a given professional application or research activity, to know the tools required for designing and developing every block and for planning system integration - To know the differences between a reconfigurable digital system and microprocessor-based digital system, and to assess their usage for every application or even their integration witing an embedded system. - To know the elements involved in a data communication system and the different abstraction levels, with a block specification focus (considering required elements for an electronic system working in a network) -To know the different networks topologies applied to the design and specification of electronic systems, including sensor networks.
Skills and learning outcomes
Description of contents: programme
1. Introduction to Sensor Networks 1.a. Communication networks, Sensor networks, OSI model 1.b. Sensor networks built with Embedded Systems 1.c. Computing on-the-edge 2. Nodes Hardware 2.a Nodes Architecture. 2.b Dealing Sensor Data 2.c Sensors 2.d Sensor-Node Interfaces (SPI, I2C, 1wire, etc.) 2.e Energy harvesting, power consumption and sustainability 3. Networks and Communications 3.a. Introduction to communications 3.b. Network fundamentals 3.b. Communications protocols 3.c. Design and implementation 3.d. Artificial intelligence with on-the-edge computation 3.f. Application and case studies. 4. Seminar taught by an expert in the generation of solutions for the challenges of Society, pursuing the achievement of Sustainable Development Goals. 5. Practice - Real WSN implementation - Research Study on WSN, Master's students should implement a system, including software and hardware, considering the generation of solutions including Artificial Intelligent to solve a given problem, as well as sustainability, data protection, cybersecurity and ethical aspects. In this design, the bias in data for training the AI algorithms, as well as the blocks for data acquisition and preprocessing will have an important relevance.
Learning activities and methodology
LEARNING ACTIVITIES Lectures Theoretical and practical classes Practical classes Oral presentation from the students Individual support when required by student (online and face-to-face) Team work TEACHING METHODOLOGIES Teacher explanations supported with audiovisual media and information technology, in which the main concepts of the subject are developed and the reference literature is provided to supplement student learning. Demonstration of practical cases, problems, etc.. The cases are posed by the teacher and solved individually or in groups with support of IDE tools
Assessment System
  • % end-of-term-examination 50
  • % of continuous assessment (assigments, laboratory, practicals...) 50

Calendar of Continuous assessment


Basic Bibliography
  • Mohammad Ilyas, Imad Mahgoub. Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems. ISBN: 9780849319686. CRC Press. 2004
  • W. Dargie, C. Poellabauer. "Fundamentals of Wireless Sensor Networks Theory and Practice" ISBN: 978-0-470-99765-9. Willey Series on Wireless Communication and Computing. 2010
Additional Bibliography
  • J. Fraden. Handbook of Modern Sensors, Physics Design and Applications. Springer. 2004
  • Peter Marwedel. Embedded System Design. Springer Science. 2011. 2nd Edition

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