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RESEARCH FOR EXPERIMENTING VARIOUS POSSIBILITIES GRAPSING NEAR MISS INCIDENTS AND PHYSICAL FATIGUE USING SMART WATCH IN CONSTRUCTION FIELDS
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- IMAI Ryuichi
- 東京都市大学 工学部
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- KAMIYA Daisuke
- 琉球大学 工学部
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- INOUE Haruka
- 関西大学 先端科学技術推進機構
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- TANAKA Shigenori
- 関西大学 総合情報学部
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- SAKURAI Jun
- 青山学院大学 情報メディアセンター
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- FUJII Takuya
- 株式会社ケー・シー・エス
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- HONMA Nobuya
- 株式会社長大
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- ITO Makoto
- 東急建設株式会社
Bibliographic Information
- Other Title
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- 建設現場への適用に向けたスマートウォッチによるヒヤリハット及び疲労度把握の可能性実験
Description
At the construction fields, the aging of skill engineers and the lack of successors are growing into a serious problem. And the increase in the number of labor accidents due to crushing labor is becoming a growing concern. Therefore, the thorough safety control of the workers is the urgent action assignment. To decrease the number of labor accidents, it is essential to detect the near miss incidents which can be directly linked to accidents, also to understand the physical fatigue condition of individuals at all time. Looking at existing cases, there are researches aimed for the decrease of the road traffic accidents. One is to detect near miss incidents of the drivers using the vehicle behavioral data such as an acceleration rate. Another research is to estimate the physical fatigue of the driver using the biological information such as the heart rate. However, these cases are intended for persons in sitting position, which cannot be applied to the workers at the construction fields.<br> Therefore, in this research, we validated the various possibilities concerning the near miss incidents and the physical fatigue using smart watch, which can easily measure the biological information at a reasonable price, under the environmental conditions considering the construction fields.
Journal
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- Journal of Japan Society of Civil Engineers, Ser. F3 (Civil Engineering Informatics)
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Journal of Japan Society of Civil Engineers, Ser. F3 (Civil Engineering Informatics) 74 (2), I_167-I_177, 2018
Japan Society of Civil Engineers
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Details 詳細情報について
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- CRID
- 1390001288143274752
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- NII Article ID
- 130007627333
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- ISSN
- 21856591
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed