User talk:Vincent Fung

=Web-based Data Fusion and Visualization in Smart Environments=

Abstract
Recently, a huge volume of data referring to human life and surrounding circumstance could be collected and stored by advanced technologies and applications. However, such data become useless to lay users without any background in data analysis if they are not presented in a model which implements intuitive interaction to reveal the patterns and principles, thus transforming the sheer amount of data into valuable information.

Introduction
In recent years, ubiquitous computing and communication techniques have promoted the development of applications across a wide range of domains in terms of transportation, wellbeing and entertainment. This research will present FuseViz, a framework for the processing of Web-based data fusion and visualization in smart environments. In FuseViz-based model, an open-source document-oriented database called Apache CouchDB is used to store the data collected from multiple sources. Joint data streams are fused by MapReduce, which is a framework for processing parallelizable problems across large datasets. Joint data streams are visualized on scalable vector graphics (SVG), which is an XML-based vector image format supported by major modern web browsers.

Findings
There are three requirements of the FuseViz framework for analysis-oriented visualization by lay users in smart environments: support for different devices’ Web access; modular and extensible data source and visualizations; interactive, embedded, and responsive visualization. There are several front-end languages, such as HTML, JavaScript, and CSS, they are standards and are available on a wide array of devices. D3 is a JavaScript library for visualizing data using web standards. D3 allows for editing the subset of Document Object Model (DOM) elements, so that only those elements are affected when user-generated events are updated. Similarly, elements could be removed from or added to the visualization of live data streams without rendering other elements again. Moreover, the agnostic technique of D3 does not limit visualizations to one technology (e.g., SVG). Visualization includes not only scalar data, but also incorporates multimedia ones, thus expanding the applicability of FuseViz to other fields in ubiquitous computing. Finally, the selection mechanism of D3 greatly simplifies the implementation of zooming, panning, and brush-and-linking, those functions make it easy to transform raw data into valuable information to lay users. Due to the support of JSON by CouchDB, visualization applications could also be embedded in other Web pages.

Conclusion
Stimulated by rapidly expanding datasets from sensors, simulations, and other digital sources, visualization is gaining interest to leverage powerful computation resources to drive engineers and scientists to make sense of the massive datasets. This research presents a novel framework called FuseViz, for the implementation of Web-based data fusion and visualization applications in smart environments. The FuseViz could help people to save energy and cost. For instance, people could be shown how to change their behaviour to improve home energy efficiency by using visualization application for smart home. There are still many problems that affect the performance of visualization, such as bandwidth and network latency. These will be the subsequent subject of future’s research.