A Hybrid Event-Processing Architecture based on the Model-driven Approach for High Performance Monitoring

2007 ◽  
Author(s):  
Yosuke Ozawa ◽  
Teruo Koyanagi ◽  
Mari Abe ◽  
Liangzhao Zeng
Keyword(s):  
High Performance ◽  
Performance Monitoring ◽  
Event Processing ◽  
Model Driven ◽  
Model Driven Approach ◽  
Processing Architecture ◽  
Hybrid Event

A model-driven approach to develop high performance web applications

2013 ◽  
Vol 86 (12) ◽  
pp. 3013-3023 ◽  
Author(s):  
José Luis Herrero Agustin ◽  
Pablo Carmona del Barco
Keyword(s):  
High Performance ◽  
Web Applications ◽  
Model Driven ◽  
Model Driven Approach

Model-driven Per-panel Solar Anomaly Detection for Residential Arrays

2021 ◽  
Vol 5 (4) ◽  
pp. 1-20
Author(s):  
Menghong Feng ◽  
Noman Bashir ◽  
Prashant Shenoy ◽  
David Irwin ◽  
Beka Kosanovic
Keyword(s):  
Fault Detection ◽  
Snow Cover ◽  
Performance Monitoring ◽  
Percentage Error ◽  
Model Driven ◽  
Solar Arrays ◽  
Anomaly Classification ◽  
New Sensors ◽  
Model Driven Approach ◽  
Utility Scale

There has been significant growth in both utility-scale and residential-scale solar installations in recent years, driven by rapid technology improvements and falling prices. Unlike utility-scale solar farms that are professionally managed and maintained, smaller residential-scale installations often lack sensing and instrumentation for performance monitoring and fault detection. As a result, faults may go undetected for long periods of time, resulting in generation and revenue losses for the homeowner. In this article, we present SunDown, a sensorless approach designed to detect per-panel faults in residential solar arrays. SunDown does not require any new sensors for its fault detection and instead uses a model-driven approach that leverages correlations between the power produced by adjacent panels to detect deviations from expected behavior. SunDown can handle concurrent faults in multiple panels and perform anomaly classification to determine probable causes. Using two years of solar generation data from a real home and a manually generated dataset of multiple solar faults, we show that SunDown has a Mean Absolute Percentage Error of 2.98% when predicting per-panel output. Our results show that SunDown is able to detect and classify faults, including from snow cover, leaves and debris, and electrical failures with 99.13% accuracy, and can detect multiple concurrent faults with 97.2% accuracy.

scholarly journals Compliance with Environmental Regulations through Complex Geo-Event Processing

2017 ◽  
Vol 20 (2) ◽  
Author(s):  
Federico Herrera ◽  
Laura González ◽  
Daniel Calegari ◽  
Bruno Rienzi
Keyword(s):  
Geographic Location ◽  
Regulatory Compliance ◽  
Event Processing ◽  
Environmental Laws ◽  
Model Driven ◽  
Compliance Requirements ◽  
Environmental Requirements ◽  
Model Driven Approach ◽  
Different Sources

In a context of e-government, there are usually regulatory compliance requirements that support systems must monitor, control and enforce. These requirements may come from environmental laws and regulations that aim to protect the natural environment and mitigate the effects of pollution on human health and ecosystems. Monitoring compliance with these requirements involves processing a large volume of data from different sources, which is a major challenge. This volume is also increased with data coming from autonomous sensors (e.g. reporting carbon emission in protected areas) and from citizens providing information (e.g. illegal dumping) in a voluntary way. Complex Event Processing (CEP) technologies allow processing large amount of event data and detecting patterns from them. However, they do not provide native support for the geographic dimension of events which is essential for monitoring requirements which apply to specific geographic areas. This paper proposes a geospatial extension for CEP that allows monitoring environmental requirements considering the geographic location of the processed data. We extend an existing platform-independent, model-driven approach for CEP adding the geographic location to events and specifying patterns using geographic operators. The use and technical feasibility of the proposal is shown through the development of a case study and the implementation of a prototype.

A model-driven approach to cross-platform development of accessible business apps

2020 ◽  
Author(s):  
Christoph Rieger ◽  
Daniel Lucrédio ◽  
Renata Pontin M. Fortes ◽  
Herbert Kuchen ◽  
Felipe Dias ◽  
...  
Keyword(s):  
Model Driven ◽  
Cross Platform ◽  
Platform Development ◽  
Model Driven Approach

scholarly journals Learn-CIAM: A Model-Driven Approach for the Development of Collaborative Learning Tools

2021 ◽  
Vol 11 (6) ◽  
pp. 2554
Author(s):  
Yoel Arroyo ◽  
Ana I. Molina ◽  
Miguel A. Redondo ◽  
Jesús Gallardo
Keyword(s):  
Collaborative Learning ◽  
Methodological Approach ◽  
Automatic Generation ◽  
Learning Activities ◽  
Learning Tools ◽  
Model Driven ◽  
Collaborative Tools ◽  
Learning Tasks ◽  
Collaborative Learning Tools ◽  
Model Driven Approach

This paper introduces Learn-CIAM, a new model-based methodological approach for the design of flows and for the semi-automatic generation of tools in order to support collaborative learning tasks. The main objective of this work is to help professors by establishing a series of steps for the specification of their learning courses and the obtaining of collaborative tools to support certain learning activities (in particular, for in-group editing, searching and modeling). This paper presents a complete methodological framework, how it is supported conceptually and technologically, and an application example. So to guarantee the validity of the proposal, we also present some validation processes with potential designers and users from different profiles such as Education and Computer Science. The results seem to demonstrate a positive reception and acceptance, concluding that its application would facilitate the design of learning courses and the generation of collaborative learning tools for professionals of both profiles.

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