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2018 年度 実施状況報告書

Wear-I: A Multi-Wearable Organic System for Smarter Individual Services

研究課題

研究課題/領域番号 18K11408
研究機関法政大学

研究代表者

Jianhua Ma  法政大学, 情報科学部, 教授 (70295426)

研究分担者 Huang Runhe  法政大学, 情報科学部, 教授 (00254102)
研究期間 (年度) 2018-04-01 – 2021-03-31
キーワードWearable / Platform / Modeling
研究実績の概要

In 2018 fiscal year, our main research was focused on development of a multi-wearable platform and representative applications in using various wearable devices.
A fog-cloud integrated framework has been adopted to develop the multi-wearable platform manage diverse devices, their states and their data. The platform uses DynamoDB of Amazon Web Service (AWS) in the cloud for universal data management and local server as fog to manage data from various devices smart watch and myo for fast response. We also conducted a preliminary study to use the blockchain technique to protect data privacy.
We have studied the data quality from multiple wearable devices and possible impact to human activity recognition with considering devices’ misplacement and temporal differences. Multi wearables have also been exploited for users’ behavioral modeling such as preference, and human psychological state analyses such as emotion features and personality computing.
These research results have been published in two internal journals and presented in three IEEE international conferences, respectively.

現在までの達成度 (区分)
現在までの達成度 (区分)

2: おおむね順調に進展している

理由

The research was smoothly carried out as we planned. Since our laboratory had already possessed many wearables, the design and development on the multi-platform were able to start in the beginning. Although data from wearables are kept permanently in the remote cloud of Amazon Web Service (AWS) with DyanmoDB, we also have used a Linux CentOS based server inside our laboratory. The server is functioned as a fog with MongoDB for quicker response to nearby wearables. A series experiments were conducted to test the performance, speed and scalability using various wearables and sensors.
One basic characteristic of this research is to use multi devices for many different applications, which were fallen into two categories. One is to combine smartphone, smart watch and Myo to achieve higher recognition rate of physical activity such as walking and sitting. The other is to use biological wearables including Muse and Spire to recognize emotional states. When using multi wearables, it is necessary to synchronize multi data streams from different devices. Therefore, we made many experiments to study the data quality including temporal differences and their impact to activity recognition.

今後の研究の推進方策

The research in FY 2019 will be carried out from the following three aspects.
A data security scheme will be added to the multi-wearable platform. We are going to use the blockchain technology to control data access and update so as to achieve data operation traceability. All information about users and their multi wearables devices will be protect as well.
The approaches and techniques to effectively use multi devices and their data will be one of important research focuses in 2019. A relatively simple or atomic activities that will be recognized using a single wearable, and a complex or high-level activity can be further recognized by combining and fusing a set of the simple activities. A proper hierarchical mode with hybrid recognition algorithms will be explored and tested.
Human psychologic state recognition and personal character computing will be studied with using various wearable sensors including inertia, physiology and brainwave. The combinational uses of these wearables is for higher recognition accuracy by data fusion and reasoning.

次年度使用額が生じた理由

One main reason is that we just used once for traveling to present our research achievement in an international conference. Personnel expenditure and miscellaneous expenses were used less as planned.

In year 2019, we will be able to have more research output, which will be published and presented. So, it is expected to spend more budget in publishing our papers in journals and present our research in attending conferences. We shall have more research exchange with other research by mutual visit and discussion.

  • 研究成果

    (5件)

すべて 2019 2018

すべて 雑誌論文 (2件) (うち査読あり 2件、 オープンアクセス 1件) 学会発表 (3件) (うち国際学会 3件)

  • [雑誌論文] Associative Memory and Recall Model with KID Model for Human Activity Recognition2019

    • 著者名/発表者名
      Runhe Huang, Peter Kimani Mungai, Jianhua Ma, Kevin I-Kai Wang
    • 雑誌名

      Future Generation Computer Systems

      巻: 92 ページ: 312-323

    • DOI

      doi.org/10.1016/j.future.2018.09.007

    • 査読あり
  • [雑誌論文] Archetype-Based Modeling of Persona for Comprehensive Personality Computing from Personal Big Data2018

    • 著者名/発表者名
      Ao Guo, Jianhua Ma
    • 雑誌名

      Sensors

      巻: 18 ページ: 684.1-684.25

    • DOI

      10.3390/s18030684

    • 査読あり / オープンアクセス
  • [学会発表] Wear-I: A Multi-Wearable Organic System for Smarter Individual Services2018

    • 著者名/発表者名
      Jianhua Ma
    • 学会等名
      IEEE Conference on Internet of People
    • 国際学会
  • [学会発表] Correlation Analyses Between Personality Traits and Personal Behaviors Under Specific Emotion States Using Physiological Data from Wearable Devices2018

    • 著者名/発表者名
      Ruiying Cai, Ao Guo, Jianhua Ma, Runhe Huang, Ruiyun Yu, Chen Yang
    • 学会等名
      IEEE Cyber Science and Technology Congress
    • 国際学会
  • [学会発表] From User Models to the Cyber-I Model: Approaches, Progresses and Issues2018

    • 著者名/発表者名
      Ao Guo, Jianhua Ma, Kevin I-Kai Wang
    • 学会等名
      IEEE Cyber Science and Technology Congress
    • 国際学会

URL: 

公開日: 2019-12-27  

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