TRACKING AKTIVITAS BELAJAR SISWA DALAM E-LEARNING

Abstrak : E-learning merupakan pembelajaran berbantuan teknologi informasi dan komunikasi. Wujudnya mencakup sejumlah aplikasi dan proses, termasuk pembelajaran berbasis komputer, pembelajaran berbasis web, virtual classrooms dan digital collaboration. Implementasinya dapat berwujud web-based, web-distributed atau web-capable untuk tujuan pendidikan. Guna meningkatkan efektivitas belajar para siswa pengguna e-learning maka perlu dilakukan tracking aktivitas belajar mereka. Tracking dalam e-learning dapat menggunakan cookie. Dengan tracking dapat diketahui berapa banyak para siswa login dan berapa lama mereka mengakses untuk belajar serta materi apa saja yang dipelajari. Informasi ini diperlukan untuk meningkatkan performa sistem e-learning dalam mendukung pencapaian prestasi belajar siswa. Kata kunci : E-learning, tracking, cookie, aktivitas belaja

Contribution to the advancement of data engineering for smart spaces through data usage control and context-aware systems

Currently, one of the most promising application fields of context-aware systems is that of IoT-based (Internet of Things) smart spaces. A smart space is a physical space that relies on technology to connect "things" to the virtual world, increasing the level of awareness of what is occurring in physical environments. Besides IoT devices, IoT-based smart spaces include software platforms and services, artificial intelligence (AI), machine learning (ML), big data, cloud computing, heterogeneous connectivity, virtual/mixed realities, and a huge range of technologies to improve people’s quality of life, to decrease environmental impact, and to optimize the use of physical resources. Most previous works provide a generic high-level structure of how a context-aware system can be operationalized, but do not offer clues on how to implement it. On the other hand, there are many implementations of context-aware systems applied to specific IoT-based smart environments that are context-specific: it is not clear how they can be extended to other use cases. Additionally, in recent years, a new business paradigm has emerged which revolves around effectively extracting value from data. In this scope, providing a secure ecosystem for data sharing that ensures data governance and traceability is of paramount importance as it holds the potential to create new applications and services. Protecting data goes beyond restricting who can access what resource (covered by identity and Access Control): it becomes necessary to control how data are treated once accessed, which is known as data usage control. Data usage control provides a common and trustful security framework to guarantee the compliance with data governance rules and responsible use of organizations’ data by third-party entities, easing and ensuring secure data sharing in ecosystems such as Smart Cities and Industry 4.0. This thesis encompasses the design, implementation, and validation of two architectures for enabling context-aware data analytics and data usage control in smart spaces. Both architectures have been implemented relying on the building blocks of the FIWARE ecosystem, presenting agnostic end-to-end solutions that take into consideration the complete data lifecycle, filling the existing gap in the literature. On the one hand, on the topic of context-aware systems, I provide an architecture and a reference implementation that can be readily operationalized in any IoT-based smart environment regardless of its field of application, providing a context-aware data analytics solution that is not context-specific. I provide two sample application scenarios that showcase how the reference implementation can be used in a variety of fields, covering from data acquisition and modeling, to data reasoning and dissemination. On the other hand, regarding data usage control, I present an architecture proposal and its subsequent implementation that achieves access and usage control in shared data ecosystems among multiple organizations. The proposed architecture is based on the UCON (Usage Control) model and an extended XACML (eXtensible Access Control Markup Language) Reference Architecture, relying on key aspects of the IDS (International Data Spaces) Reference Architecture Model. The implementation presented has been validated with a use case in the food industry, presenting a series of metrics of the response time of policy compliance verification and punishment enforcement. Finally, the results reported in this thesis contributes to the advancement of data engineering not only by enabling data analytics capabilities in context-aware systems but also by providing a trustworthy mechanism to ensure that the data generated by those systems can be continuously controlled and monitored using the proposed data usage control framework. ----------RESUMEN---------- Actualmente, uno de los campos de aplicación más prometedores de los sistemas conscientes del contexto es el de los espacios inteligentes basados en el IoT (Internet de las cosas). Un espacio inteligente es un espacio físico que se apoya en la tecnología para conectar las "cosas" con el mundo virtual, aumentando el nivel de conciencia de lo que ocurre en los entornos físicos. Además de los propios dispositivos IoT, los espacios inteligentes basados en IoT incluyen plataformas y servicios de software, inteligencia artificial (IA), aprendizaje automático (ML), big data, computación en la nube, conectividad heterogénea, realidades virtuales/mixtas y una enorme gama de tecnologías para mejorar la calidad de vida de las personas, disminuir el impacto medioambiental y optimizar el uso de los recursos físicos. La mayoría de los trabajos anteriores proporcionan una estructura genérica de alto nivel sobre cómo puede funcionar un sistema consciente del contexto, pero no ofrecen pistas sobre cómo implementarlo. Por otra parte, hay muchas implementaciones de sistemas conscientes del contexto aplicadas a entornos inteligentes específicos basados en IoT que son específicos del campo de aplicación: no está claro cómo pueden extenderse a otros casos de uso. Además, en los últimos años ha surgido un nuevo paradigma empresarial que gira en torno a la extracción efectiva de valor de los datos. En este ámbito, proporcionar un ecosistema seguro para el intercambio de datos que garantice la gobernanza y la trazabilidad de los mismos es de vital importancia, ya que encierra el potencial de crear nuevas aplicaciones y servicios. La protección de los datos va más allá de la restricción de quién puede acceder a qué recurso (cubierta por el control de identidad y acceso): se hace necesario controlar cómo se tratan los datos una vez que se accede a ellos, lo que se conoce como control de uso de los datos. El control de uso de los datos proporciona un marco de seguridad común y de confianza para garantizar el cumplimiento de las normas de gobernanza de datos y el uso responsable de los datos de las organizaciones por parte de terceras entidades, facilitando y garantizando el intercambio seguro de datos en ecosistemas como las Ciudades Inteligentes y la Industria 4.0. Esta tesis abarca el diseño, la implementación y la validación de dos arquitecturas para permitir el análisis de datos conscientes del contexto y el control del uso de datos en espacios inteligentes. Ambas arquitecturas se han implementado basándose en los bloques del ecosistema FIWARE, presentando soluciones agnósticas de extremo a extremo que tienen en cuenta el ciclo de vida completo de los datos, llenando el vacío existente en la literatura. Por un lado, en lo relacionado con el tema de los sistemas conscientes del contexto, proporciono una arquitectura y una implementación de referencia que puede ser fácilmente operacionalizada en cualquier entorno inteligente basado en IoT, independientemente de su campo de aplicación, proporcionando una solución de análisis de datos consciente del contexto que no es específica del mismo. Proporciono dos escenarios de aplicación de ejemplo que muestran cómo la implementación de referencia puede ser utilizada en una variedad de campos, cubriendo desde la adquisición de datos y el modelado, hasta el razonamiento de datos y la difusión. Por otro lado, en lo que respecta al control del uso de los datos, presento una propuesta de arquitectura y su posterior implementación que logra el control de acceso y uso de datos en ecosistemas de datos compartidos entre múltiples organizaciones. La arquitectura propuesta se basa en el modelo UCON (Usage Control) y en una arquitectura de referencia XACML (eXtensible Access Control Markup Language) ampliada, apoyándose en aspectos clave del modelo de arquitectura de referencia IDS (International Data Spaces). La implementación presentada ha sido validada con un caso de uso en la industria alimentaria, presentando una serie de métricas del tiempo de respuesta de la verificación del cumplimiento de las políticas y de la aplicación de las sanciones. Finalmente, los resultados reportados en esta tesis contribuyen al avance de la ingeniería de datos, no sólo al habilitar las capacidades de análisis de datos en los sistemas conscientes del contexto, sino también al proporcionar un mecanismo confiable para asegurar que los datos generados por esos sistemas puedan ser controlados y monitoreados continuamente usando el marco de control de uso de datos propuesto en esta tesis

Diseño e implementación de un sistema de riego inteligente basado en sensores y módulos de radiofrecuencia para transmisión y sistema de control y módulos de radiofrecuencia para transmisión y sistema de control

Un Sistema de Riego Inteligente (S.R.I) es un sistema que se enfoca en el ahorro de agua y energía, surtiendo a la planta del agua que necesita y no de la que el hombre cree necesaria. Para alcanzar este objetivo se deben de recolectar constantemente los parámetros que influyen en el regadío como son, la humedad relativa del suelo y la temperatura ambiental. Nuestro S.R.I ha sido diseñado pensando en las necesidades del agricultor ecuatoriano, que muchas veces no puede acceder a la tecnología para mejorar su proceso de producción agrícola puesto que la tecnología va de la mano, la mayoría de las veces de una gran inversión económica que hace inalcanzable la idea de implementar Sistemas de Riego Inteligente que existen en el mercado.Smart Irrigation System (S.I.S) is a system that focuses on saving water and energy, providing water that the plant needs and not what the farmer thinks necessary. To achieve this target must constantly collect the parameters that influence such as irrigation, soil relative humidity and ambient temperature. Our S.I.S has been designed thinking in the needs of the Ecuadorian farmers, who often can not access to technology to improve agricultural production process due to that the technology goes hand in hand, most of the time of a financial investment that makes unattainable the idea of implementing Smart Irrigation Systems on the market

A case study : ingestion analysis of WSN data in databases using docker

In this paper, we present an analysis of the different database systems for storing the information gather by a wireless sensor network. In this work we present different test scenarios in order to evaluate the Fetch Time and the use of Mebibyte in Relational (MySQL, PostgreSQL) and No-SQL (MongoDB, Couch, Ne04J) databases. For achieving this goal, the database instances are deployed in Docker containers for providing the same deploy, host platform and, also present a performance analysis of the resources for each database. Moreover, we conduct a case of study focus in the storage of the asynchronous information collected by a WSN in a reactive evacuation system, this is information is handled by a Kafka cluster and Zookeeper topics. Finally the tests made in this work provide the information needed for making the correct elections of the database in this type of systems

Relation between BMI and exit time of a building in an emergency situation: Earthquake

This paper states a research on what is the relation established between the Body Mass Index (BMI) and the exit time of people inside of the building when an earthquake takes place. To accomplish this goal in this article is presented a case of study in where is develop a simulation that uses as physical infrastructure a graph representation of a university building in Ecuador. The sensor nodes and the evacuation routes are also represented in this simulation. On the other hand, the study is developed using metrics as the earthquake magnitude, the body mass index, nature of soil, footwear and clothing, all of this variation combined between them allow to determine the relation of BMI and exit time in an emergency situation. As a result of this work solid conclusions are obtained, displaying the statements as the BMI is related to the exit time independently of the speed of the people, the clothing that one person is using at the moment of an emergency affect the time that they need to evacuate and it is increased with the type of shoes when walking. Another important topic that influence at the exit time is the type of soil, because it generates a considerable reduction of the speed of the person to go to an exit door. Finally, all of the experiments and the result of that are introduced in the body of this document and additional information in the appendix section

A case study : ingestion analysis of WSN data in databases using docker

In this paper, we present an analysis of the different database systems for storing the information gather by a wireless sensor network. In this work we present different test scenarios in order to evaluate the Fetch Time and the use of Mebibyte in Relational (MySQL, PostgreSQL) and No-SQL (MongoDB, Couch, Ne04J) databases. For achieving this goal, the database instances are deployed in Docker containers for providing the same deploy, host platform and, also present a performance analysis of the resources for each database. Moreover, we conduct a case of study focus in the storage of the asynchronous information collected by a WSN in a reactive evacuation system, this is information is handled by a Kafka cluster and Zookeeper topics. Finally the tests made in this work provide the information needed for making the correct elections of the database in this type of systems

Wildfire propagation simulation tool using cellular automata and GIS

This paper states the research done in building a Wildfire Propagation Simulation tool able to present graphically, how the fire will be propagated in case of a wildfire. The core of this tool was developed using Cellular Automata (CA) relayed on mathematical foundations for modeling the propagation and the transition rules of the CA. Also, the mathematical model was combined with a geographical information system provided by Google Maps API, allowing to conduct a simulation that considers the kind and density of vegetation in a specific zone of interest. Finally, we define and perform a full simulation providing information for managing and predicting wildfires and, the future works derived from this research

An architecture for providing data usage, access control in data sharing ecosystems

We are experiencing a new digital revolution in which data are becoming a key pillar for business and industry. Promoting data sharing, without compromising data sovereignty and traceability, is fundamental since it provides a heterogeneous ecosystem with the potential to enrich the variety of applications and services that take part in this digital revolution. In this scope, the use of secure and trusted platforms for sharing and processing personal and industrial data is crucial for the creation of a data market and a data economy. Protecting data goes beyond restricting who can access what resource (covered by identity and access control respectively): it becomes necessary to control how data are treated, which is known as data usage control. Data usage control provides a common and trustful security framework to guarantee the sovereignty and the responsible use of organizations’ data by third-party entities, easing and ensuring data sharing in ecosystems such as industry or smart cities. In this article, we present an architecture proposal for achieving access and usage control in shared data ecosystems among multiple organizations. The proposed architecture is based on the UCON (Usage Control) model and an extended XACML (eXtensible Access Control Markup Language) Reference Architecture, relying on key aspects of the IDS (International Data Spaces) Reference Architecture Model. Its modular design and technology-agnostic nature provide an integral solution while maintaining flexibility of implementation