12 research outputs found
Paving the Way for a Real-Time Context-Aware Predictive Architecture
Internet of Things society generates and needs to consume huge amounts of data in a demanding context-aware scenario. Such exponentially growing data sources require the use of novel processing methodologies, technologies and tools to facilitate data processing in order to detect and prevent situations of interest for the users in their particular context. To solve this issue, we propose an architecture which making use of emerging technologies and cloud platforms can process huge amounts of heterogeneous data and promptly alert users of relevant situations for a particular domain according to their context. Last, but not least, we will provide a graphical tool for domain experts to easily model, automatically generate code and deploy the situations to be detected and the actions to be taken in consequence. The proposal will be evaluated through a real case study related to air quality monitoring and lung diseases in collaboration with a doctor specialist on lung diseases of a public hospital
Dataset for a Microservice Architecture for Real-time IoT Data Processing: a Reusable Web of Things Approach for Smart Ports
This dataset provides the JAR files for the Smart Port microservices together with the EPL schema and patterns for the case study, the EPL schema and patterns used for the performance evaluation and the data collected from such evaluation for the paper entitled "A Microservice Architecture for Real-time IoT Data Processing: a Reusable Web of Things Approach for Smart Ports": - Smart Port microservices: it includes the JAR files for the three microservices (SmartPortTransformers, SmartPortCEP and SmartPortActions), the instructions for their deployment (readme.md) and the schema and patterns defined for the case study (SmartPortSchemaAndPatterns.txt).- Performance EPL schema and patterns: it includes the Esper EPL schema and patterns defined both for the short performance tests as well as for the long ones.- Performance evaluation results: it includes the spreadsheets response time values obtained from every performance test both for the short performance tests as well as for the long ones.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
Dataset for Atmosphere: Context and Situational-Aware Collaborative IoT Architecture for Edge-Fog-Cloud Computing
This dataset provides the event patterns for the case study of respiratory disease surveillance in hospitals proposed in the paper "Atmosphere: Context and Situational-Aware Collaborative IoT Architecture for Edge-Fog-Cloud Computing". These patterns were graphically modeled and automatically implemented through the MEdit4CEP tool (https://ucase.uca.es/medit4cep/). Additionally, it provides the results obtained during the performance evaluation
Dataset for paper MEdit4CEP-Gam: A Model-driven Approach for User-friendly Gamification Design, Monitoring and Code Generation in CEP-based Systems
The video shows step-by-step how to use MEdit4CEP-Gam
Dataset for CEPchain: A graphical model-driven solution for integrating complex event processing and blockchain
This dataset contains the files used and obtained in the vaccine delivery case study, which was conducted to test our CEPchain model-driven solution
Dataset for the Paper MEdit4CEP-CPN: An Approach for Complex Event Processing Modeling by Prioritized Colored Petri Nets
These files should be considered as additional material for the paper "MEdit4CEP-CPN: An Approach for Complex Event Processing Modeling by Prioritized Colored Petri Nets". Its aim is to show how our MEdit4CEP-CPN approach works
Dataset for the Paper MEdit4CEP-CPN: An Approach for Complex Event Processing Modeling by Prioritized Colored Petri Nets
These files should be considered as additional material for the paper "MEdit4CEP-CPN: An Approach for Complex Event Processing Modeling by Prioritized Colored Petri Nets". Its aim is to show how our MEdit4CEP-CPN approach works
Dataset for paper: Real-time automatic analysis of temporal information in sensor networks
The event pattern implementation and the results of the whole sensor network described in the paper "Real-time automatic analysis of temporal information in sensor networks
Dataset for Paper: Un Editor Textual para el Modelado y la Generaci贸n de C贸digo de Patrones de Eventos
El procesamiento de eventos complejos (CEP) es una tecnolog铆a que permite analizar y correlacionar grandes cantidades de datos con el prop贸sito de detectar situaciones de inter茅s en tiempo real. Para ello se requiere implementar patrones de eventos, especificando las condiciones que deben cumplirse para detectar dichas situaciones, con los lenguajes de procesamiento de eventos (EPL). A pesar de que los usuarios suelen tener un vasto conocimiento en el dominio para el que se necesitan definir ciertos patrones de eventos, suelen ser inexpertos tanto en EPL como en el lenguaje requerido para implementar las acciones a llevar a cabo tras la detecci贸n de los patrones. En este art铆culo presentamos un editor textual para el modelado y la generaci贸n de c贸digo de los patrones de eventos que se necesiten detectar en un dominio de aplicaci贸n. Gracias a este editor, el usuario solo tendr谩 que conocer un lenguaje textual para definir patrones de eventos, que podr谩n ser posteriormente transformados autom谩ticamente al EPL soportado por el motor CEP en cuesti贸n. Este editor complementa a MEdit4CEP, un editor que permite la definici贸n gr谩fica e intuitiva de patrones sin necesidad de conocer ning煤n lenguaje de programaci贸n en particular