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Multi-Agent System for Detecting Elderly People Falls through Mobile Devices

机译:通过移动设备检测老人跌倒的多智能体系统

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Falls in the elderly and disabled people represent a major health prob lem in terms of primary care costs facing the public and private systems. This pa per presents a multi-agent system capable of detecting falls through sensors in a mobile device and act accordingly at runtime. The new system incorporates a fall detection algorithm based on machine learning and data classification using decision trees. The base of the system are three types of interrelated agents that coordinate to know the position of a user from data obtained through a mobile terminal, and GPS position, which in case of fall may be sent via SMS or by an automatic call. The proposed system is self-adaptive, since as new fall date is in corporated, the decision mechanisms are automatically updated and personalized taking into account the user profile.
机译:就公共和私人系统面临的初级保健费用而言,老年人和残疾人的跌倒是主要的健康问题。该论文提出了一种多代理系统,该系统能够检测通过移动设备中的传感器的跌倒并在运行时相应地采取行动。新系统结合了基于机器学习和使用决策树进行数据分类的跌倒检测算法。该系统的基础是三种类型的相互关联的代理,它们相互协作以从通过移动终端获得的数据中了解用户的位置,以及GPS位置(在坠落的情况下可以通过SMS或通过自动呼叫发送)。所提议的系统是自适应的,因为随着新的下降日期的加入,决策机制会自动更新并考虑到用户配置文件进行个性化设置。

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