Accessibility and smart data: the case study of mPASS

Catia Prandi
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引用次数: 5

Abstract

The growing availability of data gathered by people via personal sensing and crowdsourcing is changing the way data are collected, provided and perceived. Information is becoming too much to actually make sense and this leads to an increasing demand of Smart Data. We can intend Smart Data as information obtained by large data and extracted by intelligent algorithms to meet people needs. This concept easily matches with well-known accessibility issues, solutions and techniques. Moreover, Smart Data is an emerging solution to prevent the large amount of data from becoming a new challenge in the e-accessibility field. In this context, my research is devoted to apply Smart Data to improve e-accessibility in a mobile crowdsourcing and sensing application designed to support users with disabilities in avoiding urban accessibility barriers.
可访问性和智能数据:以mPASS为例
人们通过个人感知和众包收集的数据越来越多,正在改变数据收集、提供和感知的方式。信息变得太多,实际上没有意义,这导致对智能数据的需求不断增加。我们可以将Smart Data定义为通过大数据获取的信息,通过智能算法提取出来,满足人们的需求。这个概念很容易与众所周知的可访问性问题、解决方案和技术相匹配。此外,智能数据是一种新兴的解决方案,以防止大量数据成为电子无障碍领域的新挑战。在此背景下,我的研究致力于应用智能数据来改善移动众包和传感应用程序中的电子可访问性,旨在支持残疾用户避免城市无障碍障碍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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