首页> 外国专利> UTILIZING A MACHINE LEARNING MODEL TO IDENTIFY ACTIVITIES AND DEVIATIONS FROM THE ACTIVITIES BY AN INDIVIDUAL

UTILIZING A MACHINE LEARNING MODEL TO IDENTIFY ACTIVITIES AND DEVIATIONS FROM THE ACTIVITIES BY AN INDIVIDUAL

机译:使用机器学习模型从个人识别活动和活动中的偏差

摘要

#$%^&*AU2020203106A120200528.pdf#####ABSTRACT A method, including receiving, by a device, configuration information associated with configuring an application for monitoring an individual, wherein the configuration information includes at least one of: information identifying physical characteristics of the individual, information identifying medications taken by the individual, personal information of the individual, or information associated with a caregiver of the individual, receiving, by the device, historical information associated with the individual, wherein the historical information includes at least one of: information associated with a health history of the individual, information associated with health histories of other individuals, information associated with activities of the individual, or information associated with activities of the other individuals, creating, by the device, a training set using the configuration information and the historical information, training, by the device and using the training set, a machine learning model to generate a trained machine learning model, receiving, by the device and via the application, monitored information associated with the individual from one or more client devices associated with the individual, the one or more client devices including at least one of an image sensor or an audio sensor, the monitored information including first monitored information including at least one of: a first video captured by the image sensor, or first audio captured by the audio sensor, and the monitored information including second monitored information representing information captured at a time subsequent to capture of the first monitored information and including at least one of: a second video captured by the image sensor, or second audio captured by the audio sensor, processing, by the device, the first monitored information, with the trained machine learning model, to identify one or more first activities of the individual, determining, by the device, a routine associated with the individual based on identifying the one or more first activities of the individual, processing, by the device, the second monitored information, with the trained machine learning model, to identify one or more second activities of the individual and one or more deviations from the routine by the individual, the one or more deviations determined based upon analyzing the second video or the second audio and analyzing the first video or the first audio, and performing, by the device, one or more actions based on identifying the one or more second activities of the individual and the one or more deviations, the one or more actions includingone or more of: causing a robot to provide medication to the individual based on a first deviation of the one or more deviations, or causing an autonomous emergency vehicle to traverse a route to the individual based on a second deviation of the one or more deviations.1/12 Cao E 0 1 00 , 0 0)a0 LP = c 0) 00 C)l ca aa 0 ca) 0 a) 00 cm 0 00 CDC .20 a)a .2 C ' Eca 0 02 a 0 ca) 'o E 0 l C _2 o I ca 0 0- U) ) a) 0 ~ E ca) 0~0 co 0 '91 L 3 0a a 0m
机译:#$%^&* AU2020203106A120200528.pdf #####抽象一种方法,包括由设备接收与以下内容相关联的配置信息:配置用于监视个人的应用程序,其中,配置信息包括以下至少一项:识别个人身体特征的信息,识别个人服用药物的信息,个人或与个人照顾者相关的信息,由设备,与个人相关联的历史信息,其中,历史信息包括以下至少一项:与个人健康史相关的信息;与其他人的健康史相关的信息个人的活动或与其他个人的活动相关的信息,设备使用配置信息和历史记录创建训练集设备提供的信息,培训,使用培训集的机器学习模型生成训练有素的机器学习模型,并通过设备和应用程序进行接收,来自一个或多个客户端设备的与个人相关的受监视信息与个人相关联,一个或多个客户端设备包括以下至少之一:图像传感器或音频传感器,监视的信息包括第一次监视信息,包括以下至少一项:图像传感器捕获的第一视频或第一音频由音频传感器捕获,并且监视的信息包括第二监视的表示在捕获第一个之后的某个时间捕获的信息的信息监视的信息,包括以下至少一项:图像捕获的第二视频传感器,或由音频传感器捕获的第二音频,由设备处理第一受监控的信息,以及经过训练的机器学习模型,可以首先识别一个或多个个人的活动,通过设备确定与基于识别个人的一个或多个第一活动,处理,通过设备,第二条监视的信息,以及经过训练的机器学习模型,识别个人的一项或多项第二活动以及与之的一项或多项偏离个人的常规,基于分析确定的一个或多个偏差第二视频或第二音频并分析第一视频或第一音频,以及该设备基于识别一个或多个秒来执行一个或多个动作个人的活动和一项或多项偏差,一项或多项行动包括以下一项或多项:使机器人根据第一项向个人提供药物一个或多个偏差的偏差,或导致自动驾驶应急车辆基于一个或多个偏差中的第二个偏差,遍历通往个人的路线。1/12oË0 100,00)a0LP =c 0)00C)ca aa0ca)0 a)00厘米00> 0CDC.20a)a.2 C'Eca0 020ca)'o E0升C _2 o> I约00- U))> a)0〜E ca)0〜0 co 0'<913号0a0米

著录项

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号