A Living Lab Infrastructure for Investigating Activity Monitoring Needs in Service Robot Applications

Manolis Vasileiadis, Dimitrios Giakoumis, K. Votis, D. Tzovaras
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引用次数: 4

Abstract

This paper presents a framework that has been developed for automatic activity recognition and domestic behavior monitoring, towards supporting elderly MCI patients in their daily domestic life. Our framework's infrastructure consists of a network of smart-home sensors and RGB-D cameras that can be adapted and be unobtrusively installed in a variety of indoor living areas, collecting data relative to the human's movement and the state of the home environment. User activities and behavior are then assessed through machine learning algorithms applied on these data. The developed framework has been applied in real house settings and extensive analysis has been performed, so as to investigate how human activity and behavior monitoring needs, in the scope of ICT solutions for supporting active and healthy ageing of MCI patients, can be covered in the scope of corresponding service robot applications.
研究服务机器人应用中活动监控需求的生活实验室基础设施
本文提出了一个用于自动活动识别和家庭行为监测的框架,以支持老年轻度认知障碍患者的日常家庭生活。我们的框架基础设施由智能家居传感器和RGB-D摄像头组成,这些传感器和摄像头可以不显眼地安装在各种室内生活区域,收集与人类运动和家庭环境状态相关的数据。然后通过应用于这些数据的机器学习算法评估用户活动和行为。所开发的框架已应用于真实的家庭环境,并进行了广泛的分析,以调查如何在ICT解决方案范围内支持MCI患者积极健康老龄化的人类活动和行为监测需求可以涵盖相应的服务机器人应用范围。
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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