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Hierarchical structured data logging system for effective lifelog management in ubiquitous environment

机译:分层结构化数据记录系统,可在无处不在的环境中进行有效的生命日志管理

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The researches for collecting personal daily behaviors and providing lifelog services with them have been recently increasing. Recent advances in mobile devices and sensor technologies have motivated to collect a huge amount of personal lifelog data in real time. With the rapid growth of the need for the research, there is a coming need for the effective lifelog management system which collects time-series big lifelog data sent from sensing devices and extracts major activities through processing them. For the effective lifelog management, the lifelog data can be processed in separated computing resources depending on the size and level of data. In this paper, we propose hierarchical structured data logging to support lifelog based personal services and to reduce the processing complexity and storage cost. First, we present the architecture of personal lifelog management system. With the system we present hierarchical lifelog data logging to optimally utilize computing and storage resources. Then we describe cost analysis and performance comparison for demonstrating the efficacy of our proposed system. Finally, as an initial step for experiments in our research, we describe experimental results of recognizing physical activities and extracting lifelog data which indicate major activities from them.
机译:收集个人日常行为并提供生活日志服务的研究近来正在增加。移动设备和传感器技术的最新进展促使人们实时收集大量的个人生活日志数据。随着研究需求的快速增长,迫切需要一种有效的生命日志管理系统,该系统收集从传感设备发送的按时间顺序排列的大型生命日志数据,并通过对其进行处理来提取主要活动。为了进行有效的生命日志管理,可以根据数据的大小和级别在单独的计算资源中处理生命日志数据。在本文中,我们提出了分层结构化数据记录,以支持基于生命日志的个人服务并降低处理复杂性和存储成本。首先,我们介绍个人生活日志管理系统的体系结构。使用该系统,我们可以提供分层的生活日志数据记录,以最佳利用计算和存储资源。然后,我们描述成本分析和性能比较,以证明我们提出的系统的功效。最后,作为我们研究实验的第一步,我们描述了识别身体活动并提取表明其主要活动的生活日志数据的实验结果。

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