A social issue that leads to the safety and security of people is the network that monitors the safety of people living alone in remote areas. Various research and developments of indoor human activity recognition using IoT sensor nodes have been conducted in recent years. In this research, we focus on turning on and off indoor lighting and propose an activity recognition system at home using an illuminance sensor. An IoT sensor node with a built-in illuminance sensor is attached to the wall near the indoor lighting equipment. The living activities of people in the room are estimated from changes in the illuminance. We assume a significant change in the illuminance of the indoor lighting is observed at least once a day at the sampling interval of the IoT sensor node. In that case, it is possible to estimate the operation of the indoor lighting due to daily activities and to confirm the safety of people living alone in remote areas. The activity recognition system was evaluated for a total of 380 days, excluding the missing period. The estimation of indoor lighting manipulation by daily activities was accurate for 376 days. Precision, Recall, and F-measure score values, which are evaluation indices for activity estimation, were 94.9%, 98.2%, and 96.5%, respectively.

中文翻译：

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基于照度传感器的家庭活动识别系统

关系到人们安全的一个社会问题是监控偏远地区独居者安全的网络。近年来，已经进行了使用物联网传感器节点的室内人体活动识别的各种研究和开发。在这项研究中，我们专注于打开和关闭室内照明，并提出了一种使用照度传感器的家庭活动识别系统。带有内置照度传感器的物联网传感器节点安装在室内照明设备附近的墙壁上。根据照度的变化来估计房间内人们的生活活动。我们假设在物联网传感器节点的采样间隔内，每天至少观察到一次室内照明照度的显着变化。在这种情况下，可以根据日常活动估计室内照明的运行情况，并确认偏远地区独居者的安全。活动识别系统的评估时间总计为 380 天，不包括缺失的时间段。日常活动对室内照明操纵的估计在 376 天中是准确的。作为活动估计的评价指标的精确度、召回率和F-measure得分值分别为94.9%、98.2%和96.5%。