基于Android传感器的应用生成方法

Tarik Ponciano, D. Tabosa, Windson Viana, P. A. S. Duarte, Rafael Carmo
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引用次数: 1

摘要

随着智能手机的普及,移动设备成为我们这个时代至关重要的技术元素。除了终端用户平台,智能手机还有几个传感器来捕捉和描述用户的环境。当前的上下文感知移动(CAM)应用程序使用这些数据来过滤数据、服务,甚至调整用户的行为,从而改善用户体验。由于移动硬件生态系统的多样性和传感器api的复杂性,CAM应用程序的开发对移动开发人员来说是具有挑战性的。本文介绍了EasyContext,一个用于设计和生成移动设备上下文规则的可视化工具,使用Google Awareness API作为其上下文信息提供者。移动开发人员在可视化工具中指定捕获什么以及何时对上下文变化做出反应,这些上下文规则被导出到Android项目中。我们与开发人员一起评估了我们的方法,这些开发人员被选中参加了一个类似的实验。该实验包括使用EasyContext和Google Awareness API开发两个移动应用程序。初步结果表明,与Google Awareness API相比,用更少的代码行构建应用程序是可能的。根据开发人员的说法,该方法具有更好的可读性,并且更容易设计上下文规则。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Generative Approach for Android Sensor-based Applications
As smartphones increased in popularity, mobile devices became a crucial technological element of our time. Beyond the end-user platform, smartphones have several sensors to capture and characterise the user's context. Current Context-Aware Mobile (CAM) applications use this data to improve user experience by filtering data, services, and, even, adapting their behaviour. The development of CAM applications can be challenging for mobile developers, due to the diversity of mobile hardware ecosystem and sensor APIs' complexity. This paper presents EasyContext, a visual tool for designing and generating contextual rules for mobile devices, using the Google Awareness API as its contextual information provider. Mobile developers specify what to capture and when to react to context-changes in the visual tool and these contextual rules are exported to Android projects. We evaluated our approach with developers, which were selected to participate in a quasi-experiment. The experiment involves developing two mobile applications using both EasyContext and Google Awareness API. Preliminary results show that it is possible to build applications with fewer lines of code compared to the Google Awareness API. According to the developers, the proposed approach has better readability and makes it easier to design contextual rules.
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