TypeA
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Code |
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Research guided |
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AR1 |
CMP01 - To design IoT devices by selecting the most suitable sensors/actuators for each use. TYPE: Competencies |
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AR2 |
CMP02 - To develop the necessary architecture to ensure the interoperability of the devices. TYPE: Competencies |
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AR3 |
CMP03 - To build networks and to define protocols that enable communications among IoT devices. TYPE: Competencies |
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AR4 |
CMP04 - To evaluate the performance of embedded IoT electronic systems. TYPE: Competencies |
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AR5 |
CMP05 - To determine mechanisms for real-time data collection. TYPE: Competencies |
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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 |
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AR7 |
CMP07 - To ensure the security of information generated by IoT devices. TYPE: Competencies |
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AR8 |
CMP08 - To develop a business plan for an entrepreneurial project based on IoT. TYPE: Competencies |
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AR9 |
CMP09 - To design databases for the storage and management of large amounts of IoT data. TYPE: Competencies |
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AR10 |
CMP10 - To gain experience in the design, implementation, deployment and maintenance of IoT systems within a real working environment. TYPE: Competencies |
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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 |
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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 |
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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 |
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AR14 |
CNC01 - To identify the different types of services and deployment models of Cloud Computing systems for IoT. TYPE: Knowledge or content |
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AR15 |
CNC02 - To recognize the characteristics of new IoT architectures (e.g., decentralized, distributed). TYPE: Knowledge or content |
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AR16 |
CNC03 - To identify the basic concepts of cybersecurity for IoT. TYPE: Knowledge or content |
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AR17 |
CNC04 - To determine the necessary sensor and actuator devices for IoT applications. TYPE: Knowledge or content |
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AR18 |
CNC05 - To recognize the structure of embedded IoT systems. TYPE: Knowledge or content |
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AR19 |
CNC06 - To recognize the operation of different network and application IoT protocols. TYPE: Knowledge or content |
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AR20 |
CNC07 - To identify the characteristics of the different types of networks and network technologies for IoT. TYPE: Knowledge or content |
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AR21 |
CNC08 - To identify the different types of innovation and entrepreneurship, and their application to entrepreneurial projects based on IoT. TYPE: Knowledge or content |
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AR22 |
CNC09 - To know and to understand the basic aspects of intellectual and industrial protection. TYPE: Knowledge or content |
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AR23 |
CNC10 - To know and to understand the basic concepts of Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP). TYPE: Knowledge or content |
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AR24 |
CNC11 - To know and to understand the fundamental concepts of Machine Learning for IoT. TYPE: Knowledge or content |
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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 |
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AR26 |
HBL01 - To select the most suitable cloud IoT platform for each scenario. TYPE: Skills |
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AR27 |
HBL02 - To select the most suitable architecture and distributed or decentralized system for each IoT scenario. TYPE: Skills |
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AR28 |
HBL03 - To analyze the cybersecurity risks of an IoT system. TYPE: Skills |
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AR29 |
HBL04 - To develop low-power IoT systems. TYPE: Skills |
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AR30 |
HBL05 - To develop embedded systems for IoT applications. TYPE: Skills |
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AR31 |
HBL06 - To manage the storage and distribution of spatial and temporal data. TYPE: Skills |
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AR32 |
HBL07 - To select appropriate network topologies and routing protocols for IoT scenarios. TYPE: Skills |
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AR33 |
HBL08 - To plan connectivity scenarios for IoT networks. TYPE: Skills |
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AR34 |
HBL09 - To establish funding sources for an innovative business plan based on IoT technology developments. TYPE: Skills |
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AR35 |
HBL10 - To manage spatial data and time-series data. TYPE: Skills |
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AR36 |
HBL11 - To implement supervised/unsupervised Machine Learning algorithms with classical and Deep Neural Networks. TYPE: Skills |
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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 |
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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 |
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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 |
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AR40 |
S-CP1: To design and to deploy IoT device networks in the field of Smart Cities and Smart Buildings. |
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AR41 |
S-CP2: To implement video analysis and processing algorithms for Society 5.0 applications. |
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AR42 |
S-CP3: To design and to use IoT systems for asset tracking in healthcare environments. |
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AR43 |
S-CP4: To design and to deploy large-scale IoT data processing systems for Society 5.0 applications. |
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AR44 |
I-CP1: To design and to deploy large-scale IIoT data processing systems. |
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AR45 |
I-CP2: To Design, to deploy and to optimize Green IoT systems. |
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AR46 |
I-CP3: To analyze and to interpret IIoT data streams in an industrial company. |
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AR47 |
I-CP4: To design an industrial robotic twin. |
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AR48 |
I-CP5: To design and to implement video analysis and processing algorithms for IIoT environments. |
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AR49 |
V-CP1: To design and to deploy device networks in the connected car domain. |
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AR50 |
V-CP2: To implement video analysis and processing algorithms in the connected vehicle domain. |
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AR51 |
V-CP3: To design and to deploy large-scale IoT data processing systems for connected vehicle applications. |
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AR52 |
V-CP4: To design and to deploy IoT systems for Intelligent Transportation Systems (ITS). |
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AR53 |
V-CP5: To deploy and to use IoT systems for UAVs (Unmanned Aerial Vehicles). |
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AR54 |
V-CP6: To design and to deploy services for the connected vehicle. |
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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. |
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AR56 |
S-CN2: To know and to understand the basic principles of sensors and automation for smart cities. |
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AR57 |
S-CN3: To identify technological trends for the management and construction of smart cities. |
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AR58 |
S-CN4: To know and to understand the basic concepts of home automation and building automation, including sensing, architectures and services. |
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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. |
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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. |
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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. |
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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. |
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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. |
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AR64 |
I-CN2: To know and to understand the essential concepts of Green IoT and the main strategies for energy optimization. |
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AR65 |
I-CN3: To know and to understand the different existing architectures for the deployment, monitoring and management of continuous robotic systems. |
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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. |
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AR67 |
I-CN5: To know and to understand the basic concepts of IIoT system integration. |
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AR68 |
I-CN6: To know and to understand the fundamentals of data preprocessing for industrial plants. |
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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. |
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AR70 |
V-CN2: To know and to understand the basic principles of Intelligent Transportation Systems (ITS). |
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AR71 |
V-CN3: To know and to understand the essential concepts and enabling technologies in the field of UAVs for IoT. |
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AR72 |
V-CN4: To know and to understand the architecture of the connected and autonomous vehicle and its main elements. |
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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. |
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AR74 |
V-CN6: To know and to understand the basic concepts related to network deployment in the context of connected vehicles. |
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AR75 |
S-HB1: To program and to deploy IoT wearables for healthcare. |
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AR76 |
S-HB2: Aplicar técnicas estadísticas a conjuntos de datos IoT a gran escala y para aplicaciones de la Sociedad 5.0. |
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AR77 |
S-HB3: Aplicar técnicas de análisis de vídeo para aplicaciones de la Sociedad 5.0. |
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AR78 |
I-HB1: Aplicar técnicas estadísticas a conjuntos de datos IIoT a gran escala. |
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AR79 |
I-HB2: To program Single-Board Computers (SBCs) for the deployment and management of IIoT sensor and actuator nodes. |
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AR80 |
I-HB3: To integrate telemetry data into commercial IIoT platforms. |
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AR81 |
I-HB4: To implement specific protocols for industrial control of robotic systems. |
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AR82 |
I-HB5: To employ techniques for cleaning and preprocessing IIoT data for Machine Learning algorithms. |
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AR83 |
I-HB6: To apply techniques to track objects in IIoT environments through image analysis. |
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AR84 |
V-HB1: To apply statistical techniques to large-scale data in connected vehicle IoT applications. |
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AR85 |
V-HB2: To apply image analysis techniques in the domain of connected vehicles. |
TypeB
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Code |
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TypeC
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Code |
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