Study of Vital Data Analysis Platform Using Wearable Sensor

社団法人 電子情報通信学会 THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS 信学技報 TECHNICAL REPORT OF IEICE. SC2016-34 (2017-03) ウェアラブルセンサーを用いたバイタルデータ分析プラットフォームの 検討 山登 庸次† † NTT ソフトウェアイノベーションセンタ 東京都武蔵野市緑町3-9-11 E-mail: †yamato.yoji@lab.ntt.co.jp あらまし 本稿では，バイタルデータを活用しリアルタイムなアクションに繋げるための，ウェアラブルセンサーデー タを用いた分析プラットフォームを提案する．近年IoT 技術が進展しているが，ヘルスケア分野では，分析したバイ タルデータを元に，リアルタイムなアクションを行うアプリケーションは十分検討されていない．その原因としては， ストリーム処理/マイクロバッチ処理の適切な使い分け，ネットワークコストの検討が不十分であるからと考える．既 存の課題を解決するため，私達はバイタルデータ分析プラットフォームを提案する．提案は，ウェアラブルバイタル センサーを一つの例に用いて，着用者の心電や加速度のバイタルデータを取得して，スマートホン及びクラウドで姿 勢，疲労度，緊張度等の分析を行い，危険な姿勢や疲労度推移等を取得可能とする．プラットフォームを実装し，ト ライアルの準備を行っている． キーワード IoT, ウェアラブルセンサー，クラウド, Spark Streaming, リアルタイム処理, Study of Vital Data Analysis Platform Using Wearable Sensor Yoji YAMATO† † Software Innovation Center, NTT Corporation 3-9-11, Midori-cho, Musashino-shi, Tokyo 1808585 Japan E-mail: †yamato.yoji@lab.ntt.co.jp Abstract In this paper, we propose a vital data analysis platform which resolves existing problems to utilize vital data for real-time actions. Recently, IoT technologies have been progressed but in the healthcare area, real-time actions based on analyzed vital data are not considered sufficiently yet. The causes are proper use of analyzing methods of stream / micro batch processing and network cost. To resolve existing problems, we propose our vital data analysis platform. Our platform collects vital data of Electrocardiograph and acceleration using an example of wearable vital sensor and analyzes them to extract posture, fatigue and relaxation in smart phones or cloud. Our platform can show analyzed dangerous posture or fatigue level change. We implemented the platform and we are now preparing a field test. Key words IoT, Wearable Sensor, Cloud Computing, Spark Streaming, Real-Time Processing, 1. Introduction Recently, IoT (Internet of Things) technologies have been progressed. IoT is the technology to attach communication functions to physical things, connect things to networks, ana- lyze things data to enable automatic control. IoT application areas are wide such as manufacturing, supply chain [1] [2], maintenance which Industrie4.0 [3] and Industrial Internet [4] target and also health care, agriculture, energy. To utilize IoT data, IoT platforms also appeared to de- velop and operate IoT applications effectively. AWS IoT [5] is a platform to analyze IoT data on a cloud by inte- grating several Amazon Web Services. For example, Ama- zon Kinesis collects and delivers IoT data by MQTT(MQ Telemetry Transport) [6] protocol to a cloud and Amazon Machine Learning analyzes those data by machine learning algorithms. To integrate IoT data and other services, there are some service coordination technologies such as [7]- [13]. — 1 — In manufacturing or maintenance area, there are appli- cations of appropriate timing maintenance actions based on monitored business machine statuses (e.g., KOMTRAX [14]), but in the healthcare area, real-time actions based on ana- lyzed vital data are not considered sufficiently yet. Of course, there are applications to show daily statistical information such as calorie consumption using wearable sensor data such as amount of movement acquired by list band sensor, how- ever it has not been able to utilize vital data to real-time actions. There are two main causes. The first is proper use of an- alyzing methods. To utilize vital data in real-time, not only batch processing but also stream processing for continuous data and micro batch processing for bulk data of short pe- riod are needed, but it is not considered to apply health care industry sufficiently. The second is network cost. Because vital data is continuously generated, bandwidth to transfer them to a cloud is large. Based on these backgrounds, in this paper, we propose a vital data analysis platform which resolves existing two problems based on open source HortonWorks Data Platform (HDP) [15] architecture to utilize vital data. Our platform collects workers’ vital data of Electrocardiograph and accel- eration using wearable vital sensor (e.g., [16]) and analyzes them to extract posture, fatigue and relaxation in smart phones or cloud. Our platform can show analyzed dangerous posture or fatigue level change. The rest of this paper is organized as follows. In Section 2, we review existing IoT technologies. In Section 3, we propose and design a vital data utilization platform which resolves existing problems. We summarize the paper in Section 4. 2. Overview of IoT data technologies Because IoT technologies include a lot of topics such as sensor, actuator, big data, platform, communication proto- col and so on, this section only introduces existing platform technologies and wearable sensor for IoT vital data analyzing applications. To utilize IoT data collected by sensing technologies, AWS IoT [5] is a major platform. Amazon IoT can integrate each service of Amazon Web Services for IoT processing flow. Amazon Kinesis [17] can deliver IoT data to Am

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