Educational guide 2024_25 Escola de Enxeñaría de Telecomunicación

Máster Universitario en Internet das Cousas- IoT

Training and Learning Results

Choose A

Code

Training and Learning Results

Choose B	Code	Knowledge
	B1	CNC1: Identify the different types of services and deployment models for IoT cloud computing systems. deployment models of cloud computing systems for IoT.
	B2	CNC2: Recognise the characteristics of new (e.g., decentralised, distributed) IoT architectures.
	B3	CNC3: Identify the basic concepts of cybersecurity for IoT.
	B4	CNC4: Determine the sensor and actuator devices needed for IoT applications.
	B5	CNC5: Recognise the structure of embedded IoT systems.
	B6	CNC6: Recognise the operation of the different network and application
	B7	CNC7: Identify the characteristics of different types of networks and IoT network technologies.
	B8	CNC8: Identify different types of innovation and entrepreneurship and their entrepreneurship, and their application to IoT-based based on IoT.
	B9	CNC9: Knowing and understanding the basic aspects of intellectual and industrial intellectual and industrial protection.
	B10	CNC10: Know and understand the basic notions of the Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP). Online Analytical Processing (OLAP).
	B11	CNC11: To know and understand the fundamental concepts on machine learning for IoT.
	B12	CNC12: Acquire advanced knowledge and demonstrate, in a scientific and technological or highly scientific and technological research or highly specialised research context, a detailed and grounded understanding of theoretical and practical theoretical and practical aspects and methodology of work in one or more fields of study. or more fields of study.
	B13	S-CN1: Know and understand the basic fundamentals of IoT communication, traceability and wearable technologies for self-quantified, participatory and intelligent health.
	B14	S-CN2: To know and understand the basic fundamentals of sensorics and automation for smart cities.
	B15	S-CN3: Identify the technological trends for the management and construction of smart cities.
	B16	S-CN4: To know and understand the basic concepts of domotics and inmotics including sensorization, architectures and services.
	B17	S-CN5: Knowing and understanding the main energy models and the concept of smart grid from the point of view of buildings and homes. point of view of smart buildings and smart homes.
	B18	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 data processing, as well as the main statistical techniques and storage/management techniques.
	B19	S-CN7: Know and understand the basic operation of video cameras and motion detectors in the field of applications for Society 5.0.
	B20	S-CN8: Know and understand the concepts and systems related to the deployment of networks in the field of applications for Society 5.0.
	B21	I-CN1: To know and understand the main Big Data architectures for IIoT and their data processing mechanisms, as well as the main statistical and storage/management techniques.
	B22	I-CN2: Know and understand the essential concepts about. Green IoT and the main energy optimization strategies.
	B23	I-CN3: To know and understand the different architectures for the deployment, monitoring and management of continuous robotic systems.
	B24	I-CN4: Know and understand the basic operation of video cameras and motion detectors in the IIoT environment, as well as the applications of video analytics in that domain.
	B25	I-CN5: Know and understand the basic concepts about IIoT system integration.
	B26	I-CN6: To know and understand the basics of data preprocessing for industrial plants.
	B27	V-CN1: Know and understand the main Big Data architectures for connected vehicle applications and their data processing processing mechanisms, as well as the main statistical and storage/management techniques.
	B28	V-CN2: Know and understand the basic fundamentals of the Intelligent Transportation Systems.
	B29	V-CN3: To know and understand the essential concepts and the enabling technologies in the field of UAVs for IoT.
	B30	V-CN4: Know and understand the architecture of the connected and autonomous vehicle and its main elements.
	B31	V-CN5: Know and understand the basic operation of the. video cameras and motion detectors in the field of connected vehicle, as well as the applications of the of video analytics in this field.
	B32	V-CN6: Knowing and understanding the basic concepts related with the deployment of networks in the connected vehicle environment.

Choose C	Code	Skill
	C1	HBL1: Select the most appropriate IoT cloud platform for each scenario.
	C2	HBL2: Select the most suitable distributed or decentralized architecture and system for each IoT scenario.
	C3	HBL3: Analyze the cybersecurity risks of an IoT system.
	C4	HBL4: Develop low-power IoT systems.
	C5	HBL5: Develop embedded systems for IoT applications.
	C6	HBL6: Manage the storage and distribution of spatial and temporal data.
	C7	HBL7: Select network topologies and routing and application protocols suitable for IoT scenarios.
	C8	HBL8: Plan connectivity scenarios for IoT networks.
	C9	HBL9: Establish funding sources for an innovative business plan based on developments on IoT technologies.
	C10	HBL10: Manage spatial data and time-stamped data sets. time stamps.
	C11	HBL11: Implement supervised/unsupervised machine learning algorithms with classical and deep neural networks. deep.
	C12	HBL12: Apply the acquired knowledge and solve problems in new or unfamiliar environments within broader, multidisciplinary contexts, being able to integrate knowledge.
	C13	HBL13: Communicate (orally and in written form) the conclusions-and the ultimate knowledge and reasons that support them - to specialized and non-specialized audiences in a clear and unambiguous way.
	C14	HBL14: Predict and monitor the evolution of complex situations by developing new and innovative work methodologies adapted to the scientific/investigation, technological or professional field, generally multidisciplinary, in which their activity is in which their activity is carried out.
	C15	S-HB1: Program and deploy IoT wearables for health.
	C16	S-HB2: Apply statistical techniques to large-scale IoT datasets and for Society 5.0 applications.
	C17	S-HB3: Apply video analytics techniques for Society 5.0 applications.
	C18	I-HB1: Apply statistical techniques to large-scale IIoT datasets. scale.
	C19	I-HB2: Program Single-Board Computers (SBCs) for deployment and management of IIoT sensor and actuator nodes.
	C20	I-HB3: Integrate telemetry data into commercial IIoT platforms. IIoT.
	C21	I-HB4: Implement specific protocols for industrial control of robotic systems.
	C22	I-HB5: Employ techniques to perform IIoT data cleaning and preprocessing for machine learning algorithms.
	C23	I-HB6: Apply techniques to track objects in IIoT domains through image analysis.
	C24	V-HB1: Apply statistical techniques to large-scale data in connected vehicle IoT applications
	C25	V-HB2: Apply image analysis techniques in the connected vehicle domain.

Choose D	Code	Competences
	D1	CMP1: Design IoT devices by selecting the most appropriate sensors/actuators for each use.
	D2	CMP2: Develop the necessary architecture to ensure device interoperability.
	D3	CMP3: Build networks and define protocols to enable communication between IoT devices.
	D4	CMP4: Evaluate the performance of IoT embedded electronic systems.
	D5	CMP5: Determine mechanisms for real-time data collection.
	D6	CMP6: Integrate technologies such as Machine Learning, massive data processing, Distributed Logging Technologies (DLT), edge computing, among others, for the development of more intelligent and efficient IoT systems.
	D7	CMP7: Ensure the security of information generated by IoT devices.
	D8	CMP8: Develop a business plan for a business project based on IoT.
	D9	CMP9: Design databases for storing and managing large amounts of IoT data.
	D10	CMP10: Acquire experience in the design, implementation, deployment and maintenance of IoT systems within a real working environment.
	D11	CMP11: Develop sufficient autonomy to participate in research projects and scientific or technological collaborations within their thematic area, in interdisciplinary contexts and, where appropriate, with a high component of knowledge transfer.
	D12	CMP12: To integrate knowledge and to face the complexity of formulate judgments based on information that, being incomplete or limited, includes reflections on the social and ethical responsibilities linked to the application of knowledge and judgments.
	D13	CMP13: Assume responsibility for one's own professional development and specialization in one or more fields of study, in a continuous, self-directed and autonomous way.
	D14	S-CP1: Design and deploy networks of IoT devices in the field of Smart Cities and Buildings.
	D15	S-CP2: Implement video processing and analysis algorithms for Society 5.0 applications.
	D16	S-CP3: Design and use IoT systems for asset location in healthcare environments.
	D17	S-CP4: Design and deploy large-scale IoT data processing systems for Society 5.0 applications.
	D18	I-CP1: Design and deploy large-scale IIoT data processing systems.
	D19	I-CP2: Design, deploy and optimize Green IoT systems.
	D20	I-CP3: Analyze and interpret IIoT data flows in an industrial enterprise.
	D21	I-CP4: Design an industrial robotic twin.
	D22	I-CP5: Design and implement video analysis and processing algorithms for IIoT environments
	D23	V-CP1: Design and deploy device networks in the connected car domain.
	D24	V-CP2: Implement video analysis and processing algorithms in the connected car domain.
	D25	V-CP3: Design and deploy large-scale IoT data processing systems for connected car applications.
	D26	V-CP4: Design and deploy IoT systems for ITS.
	D27	V-CP5: Deploy and utilize IoT systems for UAVs.
	D28	V-CP6: Design and deploy services for the connected vehicle.