Modeling Pervasive Context-Aware Mobile Phone Application

Fekade Getahun Taddesse, B. Abebe
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引用次数: 1

Abstract

Recently, the IT industry has shown great advancement in building various technological resources. Smart phones with better processing power that almost matches with personal computers are built. Although mobile phones have achieved their original purpose (i.e. interconnecting people, facilitating business, recreation, intelligence and emergency communication), they become main source of distraction for humans in doing their job. One of the main problems of modern day smart phones is battery capacity that has not shown similar exponential growth as processing power, memory or storage devices. Nowadays people are dependent on mobile phone to conduct their day to day activities. Battery consumption is also increasing with our increasing dependency on those devices and it has to be managed. In this study, we have proposed and developed a model for a pervasive context-aware mobile phone. Context information is collected from different sources and preprocessed to have a standard metrics. Ontology based context modeling approach has been used to serialize, store and process the context information in the mobile phones. Appropriate context reasoning approaches have been studied and prediction of the user's activity from the context information collected in context acquisition has been done. A prototype application has been developed tested for the home domain. The prototype application has been tested indifferent circumstances using different devices and it exhibits an average accuracy of 78%.
建模普遍的上下文感知移动电话应用程序
近年来,信息技术产业在建立各种技术资源方面取得了长足的进步。智能手机拥有更好的处理能力,几乎可以与个人电脑相媲美。虽然手机已经达到了最初的目的(即连接人们,方便商务,娱乐,情报和应急通信),但它们成为人们在工作中分散注意力的主要来源。现代智能手机的主要问题之一是电池容量没有像处理能力、内存或存储设备那样呈指数级增长。现在人们依赖手机来进行日常活动。随着我们越来越依赖这些设备,电池消耗也在增加,这必须得到管理。在这项研究中,我们提出并开发了一个无处不在的上下文感知手机模型。从不同的来源收集上下文信息,并对其进行预处理以获得标准度量。采用基于本体的上下文建模方法对手机中的上下文信息进行序列化、存储和处理。研究了适当的语境推理方法,并根据语境获取中收集的语境信息对用户的活动进行了预测。已经开发了一个原型应用程序,并对其进行了测试。原型应用程序已经在不同的环境下使用不同的设备进行了测试,其平均准确率为78%。
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