使用结构相似指数测量的智能病人监测系统

Aisyatul Karima, Afandi Nur Aziz Thohari, F. Abdollah, Sirli Fahriah, Parsumo Rahardjo, Wahyu Sulistiyo, S. Sukamto
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引用次数: 0

摘要

摘要2019冠状病毒病大流行期间住院患者数量显著增加,由于人力资源的限制,无法得到最优的服务。此外,他们需要工具来检测病人房间里的人,监控人们的活动。物联网能够正确控制房间。针对这些问题,本研究的目的是开发SPAM(智能患者监测系统),该系统利用Rasberry Pi实现物联网(IoT)来控制医院中的患者。这些数据是实时的,通过电报通知完成。因此,如果有紧急情况,他们可以很容易地观察。我们使用结构相似指数测量(SSIM)技术通过比较不同的图像在几个连续帧的视频由拉斯贝里派。研究方法为仪器准备、系统设计、数据处理、测试与评价。实验证明,该系统已经有效地识别了15次以上准确捕捉到的人体物体。虽然有5到40秒的延迟,但通知也被正确传输。当评估50 cm至300 cm距离的光强水平时,系统以勒克斯bbb100正确识别光线何时明亮。关键词:安全,物联网,医院,SSIM,树莓派
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SPAM (Smart Patient Monitoring System) using Structural Similarity Index Measurement
Abstract. The number of patients in Hospital during pandemic covid-19 has increasing significantly which cause do not get the optimal service because limitation of human resource. Furthermore, they need tools to detect human in patient’s room and monitor the movement of people. IoT capable to control the room properly. Regarding to these problems, the aim of this research is to develop SPAM (Smart Patient Monitoring System) which implement Internet of Thing (IoT) to control the patient in hospital using Rasberry Pi. Those data are real-time and completed by notification via telegram. Consequently, if there are emergency they can observe easily. We use Scructural Similarity Index Measurement (SSIM) technique by comparing different images on several consecutive frames of video by Rasberry Pi. The research methodology is instrument preparation, design system, data processing, testing and evaluation. The experiment prove that the system has effectively spotted human things accurately captured on camera more than 15 trials. Although there is a delay of between 5 and 40 seconds, notifications are also correctly transmitted. The system correctly recognizes when the light is bright with lux > 100 when evaluating the level of light intensity at a distance of 50 cm to 300 cm.                 Keywords: Security, Internet of Thing, Hospital, SSIM, Rasberry Pi
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