{"title":"印尼手语API (OpenSIBI API)作为Myo Armband的网关服务","authors":"M. Zikky, R. Hakkun, Buchori Rafsanjani","doi":"10.25139/ijair.v1i1.2026","DOIUrl":null,"url":null,"abstract":"We create an API (Application Programming Interface) for Indonesian Sign Language (Sistem Isyarat Bahasa Indonesia/SIBI) which is called OpenSIBI. In this case study, we use the Myo Armband device to capture hand gesture data movement. It uses five sensors: Accelerometer, Gyroscope, Orientation, Orientation-Euler, and EMG. First, we record, convert and save those data into JSON dataset in the server as data learning. Then, every data request (trial data) from the client will compare them using k-NN Normalization process. OpenSIBI API works as the middleware which integrated to RabbitMQ as the queue request arranger. Every service request from the client will automatically spread to the server with the queue process. As the media observation, we create a client data request by SIBI Words and Alphabeth Game, which allows the user to answer several stages of puzzle-game with Indonesian Sign Language hand gesture. Game-player must use the Myo armband as an interactive device that reads the hand movement and its fingers for answering the questions given. Thus, the data will be classified and normalized by the k-NN algorithm, which will be processed on the server. In this process, data will pass OpenAPI SIBI (which connected to RabbitMQ) to queue every incoming data-request. So, the obtained data will be processed one by one and sent it back to the client as the answer.","PeriodicalId":365842,"journal":{"name":"International Journal of Artificial Intelligence & Robotics (IJAIR)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Indonesian Sign Language API (OpenSIBI API) as The Gateway Services for Myo Armband\",\"authors\":\"M. Zikky, R. Hakkun, Buchori Rafsanjani\",\"doi\":\"10.25139/ijair.v1i1.2026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We create an API (Application Programming Interface) for Indonesian Sign Language (Sistem Isyarat Bahasa Indonesia/SIBI) which is called OpenSIBI. In this case study, we use the Myo Armband device to capture hand gesture data movement. It uses five sensors: Accelerometer, Gyroscope, Orientation, Orientation-Euler, and EMG. First, we record, convert and save those data into JSON dataset in the server as data learning. Then, every data request (trial data) from the client will compare them using k-NN Normalization process. OpenSIBI API works as the middleware which integrated to RabbitMQ as the queue request arranger. Every service request from the client will automatically spread to the server with the queue process. As the media observation, we create a client data request by SIBI Words and Alphabeth Game, which allows the user to answer several stages of puzzle-game with Indonesian Sign Language hand gesture. Game-player must use the Myo armband as an interactive device that reads the hand movement and its fingers for answering the questions given. Thus, the data will be classified and normalized by the k-NN algorithm, which will be processed on the server. In this process, data will pass OpenAPI SIBI (which connected to RabbitMQ) to queue every incoming data-request. So, the obtained data will be processed one by one and sent it back to the client as the answer.\",\"PeriodicalId\":365842,\"journal\":{\"name\":\"International Journal of Artificial Intelligence & Robotics (IJAIR)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Artificial Intelligence & Robotics (IJAIR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25139/ijair.v1i1.2026\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Artificial Intelligence & Robotics (IJAIR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25139/ijair.v1i1.2026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
我们为印尼手语(SIBI)创建了一个API(应用程序编程接口),称为OpenSIBI。在本案例研究中,我们使用Myo Armband设备来捕获手势数据运动。它使用五个传感器:加速度计、陀螺仪、方向、方向-欧拉和肌电图。首先,我们将这些数据记录、转换并保存到服务器端的JSON数据集中作为数据学习。然后,来自客户端的每个数据请求(试验数据)将使用k-NN归一化过程对它们进行比较。OpenSIBI API作为中间件集成到RabbitMQ中作为队列请求安排器。来自客户机的每个服务请求都将通过队列进程自动传播到服务器。作为媒体观察,我们通过SIBI Words and Alphabeth Game创建了一个客户数据请求,允许用户用印度尼西亚手语手势回答几个阶段的益智游戏。游戏玩家必须使用Myo臂环作为一个互动设备,读取手的运动和手指来回答给定的问题。因此,数据将通过k-NN算法进行分类和归一化,并在服务器上进行处理。在这个过程中,数据将通过OpenAPI SIBI(连接到RabbitMQ)来对每个传入的数据请求进行排队。因此,获得的数据将被逐一处理并作为答案发送回客户端。
Indonesian Sign Language API (OpenSIBI API) as The Gateway Services for Myo Armband
We create an API (Application Programming Interface) for Indonesian Sign Language (Sistem Isyarat Bahasa Indonesia/SIBI) which is called OpenSIBI. In this case study, we use the Myo Armband device to capture hand gesture data movement. It uses five sensors: Accelerometer, Gyroscope, Orientation, Orientation-Euler, and EMG. First, we record, convert and save those data into JSON dataset in the server as data learning. Then, every data request (trial data) from the client will compare them using k-NN Normalization process. OpenSIBI API works as the middleware which integrated to RabbitMQ as the queue request arranger. Every service request from the client will automatically spread to the server with the queue process. As the media observation, we create a client data request by SIBI Words and Alphabeth Game, which allows the user to answer several stages of puzzle-game with Indonesian Sign Language hand gesture. Game-player must use the Myo armband as an interactive device that reads the hand movement and its fingers for answering the questions given. Thus, the data will be classified and normalized by the k-NN algorithm, which will be processed on the server. In this process, data will pass OpenAPI SIBI (which connected to RabbitMQ) to queue every incoming data-request. So, the obtained data will be processed one by one and sent it back to the client as the answer.