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IoT Lab and Projects

Code: 45654
Credits: 5
2026/2027
Degree programme Type Course
Telecommunication Engineering OP 2

Contact lecturer

Name :
Ferran Paredes Marco
Email :
ferran.paredes@uab.cat

Teaching staff

Paris Velez Rasero

Group languages

You can consult this information at the end of the document.

Prerequisites

Having passed the master's course A9: "RF/Microwave Instrumentation and Sensors for IoT and Industry 4.0".

Objectives

The main objective of the course is to train students to design, characterize, and experimentally implement Internet of Things (IoT) systems based on radio frequency (RF) and microwave sensors, ranging from the theoretical conception of the sensor to the validation of a functional prototype applicable in real-world environments.

Learning outcomes

  • CA32 (Propose an IoT system based on RF/microwave sensors for a specific application, assessing the needs of the environment and technical requirements.) Propose an IoT system based on RF/microwave sensors for a specific application, assessing the needs of the environment and technical requirements.
  • CA33 (Develop custom RF/microwave sensors to be integrated into an IoT system, adjusted to the characteristics and demands of a particular application.) Develop custom RF/microwave sensors to be integrated into an IoT system, adjusted to the characteristics and demands of a particular application.
  • CA34 (Develop a project in the laboratory in an autonomous, continuous and self-directed way, demonstrating planning, execution and problem-solving skills.) Develop a project in the laboratory in an autonomous, continuous and self-directed way, demonstrating planning, execution and problem-solving skills.
  • CA35 (Integrate IoT technologies and RF/microwave sensors in cross-cutting environments, considering the interoperability and impact of these solutions in various systems.) Integrate IoT technologies and RF/microwave sensors in cross-cutting environments, considering the interoperability and impact of these solutions in various systems.
  • KA32 (Identify the applicable regulations for an IoT project based on a high-frequency sensor system.) Identify the applicable regulations for an IoT project based on a high-frequency sensor system.
  • SA46 (Design RF/microwave sensors for IoT applications) Design RF/microwave sensors for IoT applications
  • SA47 (Present the result of the IoT project and appropriately justify the results.) Present the result of the IoT project and appropriately justify the results.
  • SA48 (Design an IoT system in a laboratory applying the appropriate regulations.) Design an IoT system in a laboratory applying the appropriate regulations.

Contents

  • Project development phases: System block design and characterization. Implementation and validation.
  • Introduction to the laboratory: Introduction to the IoT laboratory and to manufacturing and characterization tools.
  • Infrastructure monitoring: System for structural damage monitoring in urban and civil infrastructures based on permittivity and pressure sensors.
  • RF Technology: RF systems for identification and data capture (temperature, humidity, etc.).
  • Agri-food applications: Smart system for performance improvement and product quality control in the agri-food industry, based on fluidic sensors.
  • Industrial control: System for motion control in industrial systems based on electromagnetic encoders.

Learning activities and methodology

Title Hours ECTS Learning outcomes
Office hours 12.5 0.5 CA32, CA35, KA32, SA48
Problems seminars 12.5 0.5 CA32, SA46, SA47
Master Class 20 0.8 CA33, KA32, SA46
Preparation of the course content (reports, study, problem-solving) 42.5 1.7 CA32, CA33, CA34, CA35, SA48
Laboratory sessions 12.5 0.5 CA32, CA33, SA46

Directed activities:

  • Lectures: Oral presentation given by the professor with the aim of transmitting knowledge about the subject.
  • Problem seminars: The professor will solve problems or, in some cases, the students themselves will do so in small groups.


Supervised activities:

  • Laboratory sessions: Before the session, the student must prepare (reports or preliminary exercises) and, once finished, must submit a report with the material worked on.


Autonomous activities:

  • The student must solve class exercises, problems, and laboratory sessions, as well as study the subject syllabus autonomously.
  • Tutorials outside of class hours.


Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Assessment

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Partial Exam (first) 37,5% 2 0.08 CA32, CA33, KA32, SA46
Partial Exam (second) 37,5% 2 0.08 CA32, CA35, KA32, SA46
Laboratory (Report and Presentation) 25% 21 0.84 CA32, CA34, CA35, SA47, SA48

The assessment will be based on two written partial exams, each with a weight of 37.5%, and on the results of the practical reports, with a weight of 25%.

The partial exams will be averaged together provided a minimum grade of 3 has been obtained in each one. If the average grade of the partial exams is higher than 4, it will be averaged with the course practicals to obtain the final grade. Furthermore, to pass any exam, a minimum grade of 3 out of 10 must be obtained in the theory section.

In the event of failing the subject, the part corresponding to the partial exams may be retaken in a single final exam in which all the course contents will be assessed. To participate in the retake exam, the student must have been previously evaluated in activities representing at least 2/3 of the final grade of the subject.


Failure to attend any of the practical sessions or lacking a grade in the partial or final exams will result in the student being declared "non-assessable" (not evaluated).


Awarding an honors grade (Matrícula de Honor) is the decision of the teaching staff responsible for the subject. UAB regulations stipulate that honors grades may only be awarded to students who have obtained a final grade equal to or higher than 9.00. Up to 5% of honors grades may be granted based on the total number of enrolled students.

Without prejudice to other disciplinary measures deemed appropriate, irregularities committed by the student that may lead to a variation in the grade of an evaluation activity will be graded with a zero. Therefore, copying, plagiarizing, cheating, allowing others to copy, etc., in any of the evaluation activities will result in failing that activity with a zero. Evaluation activities graded in this manner and by this procedure will not be recoverable. If passing any of these evaluation activities is required to pass the subject, the subject will be directly failed, without the possibility of retaking it in the same academic year.

If the subject is repeated, the same assessment system will be followed as for the rest of the students.

This subject does not provide for the single assessment system.

For this subject, the use of artificial intelligence (AI) technologies is permitted exclusively for support tasks, such as bibliographic or information searches, text correction, or translations. The student must clearly identify which parts have been generated with this technology, specify the tools used, and include a critical reflection on how these tools have influenced the process and the final result of the activity. A lack of transparency in the use of AI in this assessable activity will be considered a violation of academic honesty and may lead to a partial or total penalty in the activity's grade, or more severe sanctions in serious cases.

Bibliography

D. M. Pozar, Microwave Engineering,Wiley (4th edition), 2011. ISBN: 9780470631553

F. Martín, P. Vélez, J. Muñoz-Enano, L Su, Planar Microwave Sensors. : Wiley-IEEE Press, 2022. ISBN: 978-1-119-81105-3

Software

Keysight ADS-Momentum,

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE