Smart Self-Isolation System to Monitor the Condition of Covid-19 Patients at Home

Aries Pratiarso, Muhammad Hafidz Hismawan, Inna Ladayna Mazida, M. Z. S. Hadi, Mike Yuliana
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Abstract

Self-isolation is step or effort to stop the spread of the Covid-19 virus that can carried out by individuals infected with the corona virus. However, they do not show enough symptoms seriously. This is one method to push amount Covid-19 cases. People who do self-isolation must stay at home around 7 days until they are free from Covid-19. To help monitoring by effective condition patient in self-isolation at home and reduce risk the symptoms of Covid-19 experienced, it requires a support system. In this research, it makes a system that can help inhabitant of village to monitor condition patients in the room during self-isolation through camera-based detection object and some sensors to monitor their health such as temperature, heart rate, and oxygen saturation. Camera can classify condition patient based on real-time video recording. If patient is detected lie down or fall on the floor, it will be assumed need help and message emergency sent to the telegram bot. However, if the patient is in a position like stand up, it will be assumed that patient in health condition. By using Mobilenet V2 320x320 SSD object model the average of accuracy is obtained by 86.8%. The results in this system could be monitored through web page.
智能自我隔离系统在家中监测Covid-19患者的状况
自我隔离是阻止Covid-19病毒传播的步骤或努力,可由感染冠状病毒的个体进行。然而,他们并没有表现出足够严重的症状。这是推动新冠肺炎病例数量的一种方法。自我隔离的人必须呆在家里7天左右,直到他们从Covid-19中解脱出来。为了帮助监测在家自我隔离的有效病情患者,并减少出现Covid-19症状的风险,需要一个支持系统。在本研究中,通过基于摄像头的检测对象和一些传感器来监测病人的健康状况,如体温、心率、血氧饱和度等,制作了一个系统,可以帮助村庄居民在自我隔离期间监测房间内的病情。摄像机可以根据实时视频记录对患者进行病情分类。如果检测到病人躺下或摔倒在地板上,则认为需要帮助,并向电报机器人发送紧急信息。但是,如果患者处于站立的姿势,则会认为患者处于健康状态。采用Mobilenet V2 320x320 SSD对象模型,平均准确率为86.8%。该系统的测试结果可以通过网页进行监控。
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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