Aisyatul Karima, Afandi Nur Aziz Thohari, F. Abdollah, Sirli Fahriah, Parsumo Rahardjo, Wahyu Sulistiyo, S. Sukamto
{"title":"使用结构相似指数测量的智能病人监测系统","authors":"Aisyatul Karima, Afandi Nur Aziz Thohari, F. Abdollah, Sirli Fahriah, Parsumo Rahardjo, Wahyu Sulistiyo, S. Sukamto","doi":"10.24002/ijis.v5i2.6791","DOIUrl":null,"url":null,"abstract":"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. \n \nKeywords: Security, Internet of Thing, Hospital, SSIM, Rasberry Pi","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"30 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"SPAM (Smart Patient Monitoring System) using Structural Similarity Index Measurement\",\"authors\":\"Aisyatul Karima, Afandi Nur Aziz Thohari, F. Abdollah, Sirli Fahriah, Parsumo Rahardjo, Wahyu Sulistiyo, S. Sukamto\",\"doi\":\"10.24002/ijis.v5i2.6791\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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. \\n \\nKeywords: Security, Internet of Thing, Hospital, SSIM, Rasberry Pi\",\"PeriodicalId\":34118,\"journal\":{\"name\":\"Indonesian Journal of Information Systems\",\"volume\":\"30 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Indonesian Journal of Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24002/ijis.v5i2.6791\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Indonesian Journal of Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24002/ijis.v5i2.6791","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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