Teaching Guide 2024/25 Faculty of Computer Science

AR1

CMP01 - To design IoT devices by selecting the most suitable sensors/actuators for each use. TYPE: Competencies

AR2

CMP02 - To develop the necessary architecture to ensure the interoperability of the devices. TYPE: Competencies

AR3

CMP03 - To build networks and to define protocols that enable communications among IoT devices. TYPE: Competencies

AR4

CMP04 - To evaluate the performance of embedded IoT electronic systems. TYPE: Competencies

AR5

CMP05 - To determine mechanisms for real-time data collection. TYPE: Competencies

AR6

CMP06 - To ontegrate technologies such as Machine Learning, Big Data processing, Distributed Ledger Technologies (DLT), Edge Computing, among others, for the development of smarter and more efficient IoT systems. TYPE: Competencies

AR7

CMP07 - To ensure the security of information generated by IoT devices. TYPE: Competencies

AR8

CMP08 - To develop a business plan for an entrepreneurial project based on IoT. TYPE: Competencies

AR9

CMP09 - To design databases for the storage and management of large amounts of IoT data. TYPE: Competencies

AR10

CMP10 - To gain experience in the design, implementation, deployment and maintenance of IoT systems within a real working environment. TYPE: Competencies

AR11

CMP11 - To develop sufficient autonomy to participate in research projects and scientific or technological collaborations within their thematic area, in interdisciplinary contexts, and potentially with a high component of knowledge transfer. TYPE: Competencies

AR12

CMP12 - To integrate knowledge and to deal with the complexity of formulating judgments based on information that, while incomplete or limited, includes reflections on the social and ethical responsibilities related to the application of knowledge and judgments. TYPE: Competencies

AR13

CMP13 - To take responsibility for one's own professional development and specialization in one or more fields of study, continuously, self-directed and autonomously. TYPE: Competencies

AR14

CNC01 - To identify the different types of services and deployment models of Cloud Computing systems for IoT. TYPE: Knowledge or content

AR15

CNC02 - To recognize the characteristics of new IoT architectures (e.g., decentralized, distributed). TYPE: Knowledge or content

AR16

CNC03 - To identify the basic concepts of cybersecurity for IoT. TYPE: Knowledge or content

AR17

CNC04 - To determine the necessary sensor and actuator devices for IoT applications. TYPE: Knowledge or content

AR18

CNC05 - To recognize the structure of embedded IoT systems. TYPE: Knowledge or content

AR19

CNC06 - To recognize the operation of different network and application IoT protocols. TYPE: Knowledge or content

AR20

CNC07 - To identify the characteristics of the different types of networks and network technologies for IoT. TYPE: Knowledge or content

AR21

CNC08 - To identify the different types of innovation and entrepreneurship, and their application to entrepreneurial projects based on IoT. TYPE: Knowledge or content

AR22

CNC09 - To know and to understand the basic aspects of intellectual and industrial protection. TYPE: Knowledge or content

AR23

CNC10 - To know and to understand the basic concepts of Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP). TYPE: Knowledge or content

AR24

CNC11 - To know and to understand the fundamental concepts of Machine Learning for IoT. TYPE: Knowledge or content

AR25

CNC12 - To acquire advanced knowledge and to demonstrate, in a context of scientific and technological research or highly specialized fields, a detailed and grounded understanding of the theoretical and practical aspects and methodology of work in one or more fields of study. TYPE: Knowledge or content

AR26

HBL01 - To select the most suitable cloud IoT platform for each scenario. TYPE: Skills

AR27

HBL02 - To select the most suitable architecture and distributed or decentralized system for each IoT scenario. TYPE: Skills

AR28

HBL03 - To analyze the cybersecurity risks of an IoT system. TYPE: Skills

AR29

HBL04 - To develop low-power IoT systems. TYPE: Skills

AR30

HBL05 - To develop embedded systems for IoT applications. TYPE: Skills

AR31

HBL06 - To manage the storage and distribution of spatial and temporal data. TYPE: Skills

AR32

HBL07 - To select appropriate network topologies and routing protocols for IoT scenarios. TYPE: Skills

AR33

HBL08 - To plan connectivity scenarios for IoT networks. TYPE: Skills

AR34

HBL09 - To establish funding sources for an innovative business plan based on IoT technology developments. TYPE: Skills

AR35

HBL10 - To manage spatial data and time-series data. TYPE: Skills

AR36

HBL11 - To implement supervised/unsupervised Machine Learning algorithms with classical and Deep Neural Networks. TYPE: Skills

AR37

HBL12 - To apply the acquired knowledge and to solve problems in new or unfamiliar environments within broader and multidisciplinary contexts, integrating knowledge effectively. TYPE: Skills

AR38

HBL13 - To communicate (both orally and in writing) clearly and unambiguously conclusions, along with the knowledge and underlying reasons supporting them, to specialized and non-specialized audiences. TYPE: Skills

AR39

HBL14 - To predict and to control the evolution of complex situations by developing new and innovative methodologies adapted to specific scientific/research, technological or professional domains, generally multidisciplinary, in which their activity is conducted. TYPE: Skills

AR40

S-CP1: To design and to deploy IoT device networks in the field of Smart Cities and Smart Buildings.

AR41

S-CP2: To implement video analysis and processing algorithms for Society 5.0 applications.

AR42

S-CP3: To design and to use IoT systems for asset tracking in healthcare environments.

AR43

S-CP4: To design and to deploy large-scale IoT data processing systems for Society 5.0 applications.

AR44

I-CP1: To design and to deploy large-scale IIoT data processing systems.

AR45

I-CP2: To Design, to deploy and to optimize Green IoT systems.

AR46

I-CP3: To analyze and to interpret IIoT data streams in an industrial company.

AR47

I-CP4: To design an industrial robotic twin.

AR48

I-CP5: To design and to implement video analysis and processing algorithms for IIoT environments.

AR49

V-CP1: To design and to deploy device networks in the connected car domain.

AR50

V-CP2: To implement video analysis and processing algorithms in the connected vehicle domain.

AR51

V-CP3: To design and to deploy large-scale IoT data processing systems for connected vehicle applications.

AR52

V-CP4: To design and to deploy IoT systems for Intelligent Transportation Systems (ITS).

AR53

V-CP5: To deploy and to use IoT systems for UAVs (Unmanned Aerial Vehicles).

AR54

V-CP6: To design and to deploy services for the connected vehicle.

AR55

S-CN1: To know and to understand the basic principles of IoT technologies for communication, traceability and wearables for self-quantified, participatory and smart health.

AR56

S-CN2: To know and to understand the basic principles of sensors and automation for smart cities.

AR57

S-CN3: To identify technological trends for the management and construction of smart cities.

AR58

S-CN4: To know and to understand the basic concepts of home automation and building automation, including sensing, architectures and services.

AR59

S-CN5: To know and to understand the main energy models and the concept of smart grid from the perspective of smart buildings and homes.

AR60

S-CN6: To identify the main Big Data architectures for IoT for Society 5.0 applications and their data processing mechanisms, as well as the main statistical techniques and storage/management methods.

AR61

S-CN7: To know and to understand the basic operation of video cameras and motion detectors in the context of applications for Society 5.0.

AR62

S-CN8: To know and to understand the concepts and systems related to network deployment in the context of applications for Society 5.0.

AR63

I-CN1: To know and to understand the main Big Data architectures for IIoT and their data processing mechanisms, as well as the main statistical techniques and storage/management methods.

AR64

I-CN2: To know and to understand the essential concepts of Green IoT and the main strategies for energy optimization.

AR65

I-CN3: To know and to understand the different existing architectures for the deployment, monitoring and management of continuous robotic systems.

AR66

I-CN4: To know and to understand the basic operation of video cameras and motion detectors in the IIoT domain, as well as the applications of video analysis in such a field.

AR67

I-CN5: To know and to understand the basic concepts of IIoT system integration.

AR68

I-CN6: To know and to understand the fundamentals of data preprocessing for industrial plants.

AR69

V-CN1: To know and to understand the main Big Data architectures for connected vehicle applications and their data processing mechanisms, as well as the main statistical techniques and storage/management methods.

AR70

V-CN2: To know and to understand the basic principles of Intelligent Transportation Systems (ITS).

AR71

V-CN3: To know and to understand the essential concepts and enabling technologies in the field of UAVs for IoT.

AR72

V-CN4: To know and to understand the architecture of the connected and autonomous vehicle and its main elements.

AR73

V-CN5: To know and to understand the basic operation of video cameras and motion detectors in the context of connected vehicles, as well as the applications of video analysis in such a domain.

AR74

V-CN6: To know and to understand the basic concepts related to network deployment in the context of connected vehicles.

AR75

S-HB1: To program and to deploy IoT wearables for healthcare.

AR76

S-HB2: Aplicar técnicas estadísticas a conjuntos de datos IoT a gran escala y para aplicaciones de la Sociedad 5.0.

AR77

S-HB3: Aplicar técnicas de análisis de vídeo para aplicaciones de la Sociedad 5.0.

AR78

I-HB1: Aplicar técnicas estadísticas a conjuntos de datos IIoT a gran escala.

AR79

I-HB2: To program Single-Board Computers (SBCs) for the deployment and management of IIoT sensor and actuator nodes.

AR80

I-HB3: To integrate telemetry data into commercial IIoT platforms.

AR81

I-HB4: To implement specific protocols for industrial control of robotic systems.

AR82

I-HB5: To employ techniques for cleaning and preprocessing IIoT data for Machine Learning algorithms.

AR83

I-HB6: To apply techniques to track objects in IIoT environments through image analysis.

AR84

V-HB1: To apply statistical techniques to large-scale data in connected vehicle IoT applications.

AR85

V-HB2: To apply image analysis techniques in the domain of connected vehicles.

TypeA	Code
		Research guided
	AR1	CMP01 - To design IoT devices by selecting the most suitable sensors/actuators for each use. TYPE: Competencies
	AR2	CMP02 - To develop the necessary architecture to ensure the interoperability of the devices. TYPE: Competencies
	AR3	CMP03 - To build networks and to define protocols that enable communications among IoT devices. TYPE: Competencies
	AR4	CMP04 - To evaluate the performance of embedded IoT electronic systems. TYPE: Competencies
	AR5	CMP05 - To determine mechanisms for real-time data collection. TYPE: Competencies
	AR6	CMP06 - To ontegrate technologies such as Machine Learning, Big Data processing, Distributed Ledger Technologies (DLT), Edge Computing, among others, for the development of smarter and more efficient IoT systems. TYPE: Competencies
	AR7	CMP07 - To ensure the security of information generated by IoT devices. TYPE: Competencies
	AR8	CMP08 - To develop a business plan for an entrepreneurial project based on IoT. TYPE: Competencies
	AR9	CMP09 - To design databases for the storage and management of large amounts of IoT data. TYPE: Competencies
	AR10	CMP10 - To gain experience in the design, implementation, deployment and maintenance of IoT systems within a real working environment. TYPE: Competencies
	AR11	CMP11 - To develop sufficient autonomy to participate in research projects and scientific or technological collaborations within their thematic area, in interdisciplinary contexts, and potentially with a high component of knowledge transfer. TYPE: Competencies
	AR12	CMP12 - To integrate knowledge and to deal with the complexity of formulating judgments based on information that, while incomplete or limited, includes reflections on the social and ethical responsibilities related to the application of knowledge and judgments. TYPE: Competencies
	AR13	CMP13 - To take responsibility for one's own professional development and specialization in one or more fields of study, continuously, self-directed and autonomously. TYPE: Competencies
	AR14	CNC01 - To identify the different types of services and deployment models of Cloud Computing systems for IoT. TYPE: Knowledge or content
	AR15	CNC02 - To recognize the characteristics of new IoT architectures (e.g., decentralized, distributed). TYPE: Knowledge or content
	AR16	CNC03 - To identify the basic concepts of cybersecurity for IoT. TYPE: Knowledge or content
	AR17	CNC04 - To determine the necessary sensor and actuator devices for IoT applications. TYPE: Knowledge or content
	AR18	CNC05 - To recognize the structure of embedded IoT systems. TYPE: Knowledge or content
	AR19	CNC06 - To recognize the operation of different network and application IoT protocols. TYPE: Knowledge or content
	AR20	CNC07 - To identify the characteristics of the different types of networks and network technologies for IoT. TYPE: Knowledge or content
	AR21	CNC08 - To identify the different types of innovation and entrepreneurship, and their application to entrepreneurial projects based on IoT. TYPE: Knowledge or content
	AR22	CNC09 - To know and to understand the basic aspects of intellectual and industrial protection. TYPE: Knowledge or content
	AR23	CNC10 - To know and to understand the basic concepts of Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP). TYPE: Knowledge or content
	AR24	CNC11 - To know and to understand the fundamental concepts of Machine Learning for IoT. TYPE: Knowledge or content
	AR25	CNC12 - To acquire advanced knowledge and to demonstrate, in a context of scientific and technological research or highly specialized fields, a detailed and grounded understanding of the theoretical and practical aspects and methodology of work in one or more fields of study. TYPE: Knowledge or content
	AR26	HBL01 - To select the most suitable cloud IoT platform for each scenario. TYPE: Skills
	AR27	HBL02 - To select the most suitable architecture and distributed or decentralized system for each IoT scenario. TYPE: Skills
	AR28	HBL03 - To analyze the cybersecurity risks of an IoT system. TYPE: Skills
	AR29	HBL04 - To develop low-power IoT systems. TYPE: Skills
	AR30	HBL05 - To develop embedded systems for IoT applications. TYPE: Skills
	AR31	HBL06 - To manage the storage and distribution of spatial and temporal data. TYPE: Skills
	AR32	HBL07 - To select appropriate network topologies and routing protocols for IoT scenarios. TYPE: Skills
	AR33	HBL08 - To plan connectivity scenarios for IoT networks. TYPE: Skills
	AR34	HBL09 - To establish funding sources for an innovative business plan based on IoT technology developments. TYPE: Skills
	AR35	HBL10 - To manage spatial data and time-series data. TYPE: Skills
	AR36	HBL11 - To implement supervised/unsupervised Machine Learning algorithms with classical and Deep Neural Networks. TYPE: Skills
	AR37	HBL12 - To apply the acquired knowledge and to solve problems in new or unfamiliar environments within broader and multidisciplinary contexts, integrating knowledge effectively. TYPE: Skills
	AR38	HBL13 - To communicate (both orally and in writing) clearly and unambiguously conclusions, along with the knowledge and underlying reasons supporting them, to specialized and non-specialized audiences. TYPE: Skills
	AR39	HBL14 - To predict and to control the evolution of complex situations by developing new and innovative methodologies adapted to specific scientific/research, technological or professional domains, generally multidisciplinary, in which their activity is conducted. TYPE: Skills
	AR40	S-CP1: To design and to deploy IoT device networks in the field of Smart Cities and Smart Buildings.
	AR41	S-CP2: To implement video analysis and processing algorithms for Society 5.0 applications.
	AR42	S-CP3: To design and to use IoT systems for asset tracking in healthcare environments.
	AR43	S-CP4: To design and to deploy large-scale IoT data processing systems for Society 5.0 applications.
	AR44	I-CP1: To design and to deploy large-scale IIoT data processing systems.
	AR45	I-CP2: To Design, to deploy and to optimize Green IoT systems.
	AR46	I-CP3: To analyze and to interpret IIoT data streams in an industrial company.
	AR47	I-CP4: To design an industrial robotic twin.
	AR48	I-CP5: To design and to implement video analysis and processing algorithms for IIoT environments.
	AR49	V-CP1: To design and to deploy device networks in the connected car domain.
	AR50	V-CP2: To implement video analysis and processing algorithms in the connected vehicle domain.
	AR51	V-CP3: To design and to deploy large-scale IoT data processing systems for connected vehicle applications.
	AR52	V-CP4: To design and to deploy IoT systems for Intelligent Transportation Systems (ITS).
	AR53	V-CP5: To deploy and to use IoT systems for UAVs (Unmanned Aerial Vehicles).
	AR54	V-CP6: To design and to deploy services for the connected vehicle.
	AR55	S-CN1: To know and to understand the basic principles of IoT technologies for communication, traceability and wearables for self-quantified, participatory and smart health.
	AR56	S-CN2: To know and to understand the basic principles of sensors and automation for smart cities.
	AR57	S-CN3: To identify technological trends for the management and construction of smart cities.
	AR58	S-CN4: To know and to understand the basic concepts of home automation and building automation, including sensing, architectures and services.
	AR59	S-CN5: To know and to understand the main energy models and the concept of smart grid from the perspective of smart buildings and homes.
	AR60	S-CN6: To identify the main Big Data architectures for IoT for Society 5.0 applications and their data processing mechanisms, as well as the main statistical techniques and storage/management methods.
	AR61	S-CN7: To know and to understand the basic operation of video cameras and motion detectors in the context of applications for Society 5.0.
	AR62	S-CN8: To know and to understand the concepts and systems related to network deployment in the context of applications for Society 5.0.
	AR63	I-CN1: To know and to understand the main Big Data architectures for IIoT and their data processing mechanisms, as well as the main statistical techniques and storage/management methods.
	AR64	I-CN2: To know and to understand the essential concepts of Green IoT and the main strategies for energy optimization.
	AR65	I-CN3: To know and to understand the different existing architectures for the deployment, monitoring and management of continuous robotic systems.
	AR66	I-CN4: To know and to understand the basic operation of video cameras and motion detectors in the IIoT domain, as well as the applications of video analysis in such a field.
	AR67	I-CN5: To know and to understand the basic concepts of IIoT system integration.
	AR68	I-CN6: To know and to understand the fundamentals of data preprocessing for industrial plants.
	AR69	V-CN1: To know and to understand the main Big Data architectures for connected vehicle applications and their data processing mechanisms, as well as the main statistical techniques and storage/management methods.
	AR70	V-CN2: To know and to understand the basic principles of Intelligent Transportation Systems (ITS).
	AR71	V-CN3: To know and to understand the essential concepts and enabling technologies in the field of UAVs for IoT.
	AR72	V-CN4: To know and to understand the architecture of the connected and autonomous vehicle and its main elements.
	AR73	V-CN5: To know and to understand the basic operation of video cameras and motion detectors in the context of connected vehicles, as well as the applications of video analysis in such a domain.
	AR74	V-CN6: To know and to understand the basic concepts related to network deployment in the context of connected vehicles.
	AR75	S-HB1: To program and to deploy IoT wearables for healthcare.
	AR76	S-HB2: Aplicar técnicas estadísticas a conjuntos de datos IoT a gran escala y para aplicaciones de la Sociedad 5.0.
	AR77	S-HB3: Aplicar técnicas de análisis de vídeo para aplicaciones de la Sociedad 5.0.
	AR78	I-HB1: Aplicar técnicas estadísticas a conjuntos de datos IIoT a gran escala.
	AR79	I-HB2: To program Single-Board Computers (SBCs) for the deployment and management of IIoT sensor and actuator nodes.
	AR80	I-HB3: To integrate telemetry data into commercial IIoT platforms.
	AR81	I-HB4: To implement specific protocols for industrial control of robotic systems.
	AR82	I-HB5: To employ techniques for cleaning and preprocessing IIoT data for Machine Learning algorithms.
	AR83	I-HB6: To apply techniques to track objects in IIoT environments through image analysis.
	AR84	V-HB1: To apply statistical techniques to large-scale data in connected vehicle IoT applications.
	AR85	V-HB2: To apply image analysis techniques in the domain of connected vehicles.
TypeB	Code
TypeC	Code