Analysis of Fire-Accident Factors Using Big-Data Analysis Method for Construction Areas

被引:4
|
作者
Kim, Joon-Soo [1 ]
Kim, Byung-Soo [1 ]
机构
[1] Kyungpook Natl Univ, Dept Civil Engn, Daegu 41566, South Korea
基金
新加坡国家研究基金会;
关键词
big-data; negligent accident; web crawling; text mining; data mining; principal component analysis;
D O I
10.1007/s12205-017-0767-7
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The Ministry of Employment and Labor releases its annual report on the present conditions of industrial disasters by aggregating and summarizing negligent accidents that occur at construction sites. Industry-specific accident and fatality rates, and disaster classification and statistics are aggregated in this report, but its effectiveness is low. This is due to the fact that it does not sufficiently present the direct causes of accidents or related information on their causal relation. However, this study utilizes a big-data method that has recently gained significant attention throughout all industrial and academic areas to collect Internet articles on fire-accidents that have occurred at construction sites over the last decade. In addition, principal component analysis was conducted to deduce season-specific factors according to time, location, inducer, and accident pattern. Based on this analysis, as for common factors, direct spark and oil mist were deduced. As work-related factors, negligent supervision and violations of the safety regulations were shown to cause fire-accidents, illustrating the man-made nature of such accidents. It was also found that secondary accidents such as collapses, burials, explosions, and suffocation have occurred when fires have broken out. The big-data analysis method utilized in this study is considered to be very effective and can be successfully utilized in the future for deducing high volumes of text data.
引用
收藏
页码:1535 / 1543
页数:9
相关论文
共 50 条
  • [41] Analysis of influencing factors of severity in acute pancreatitis using big data mining
    Fei, Yang
    Liu, Xiao-qiang
    Gao, Kun
    Xue, Cheng-bin
    Tang, Liang
    Tu, Jian-feng
    Wang, Wei
    Li, Wei-qin
    REVISTA DA ASSOCIACAO MEDICA BRASILEIRA, 2018, 64 (05): : 454 - 461
  • [42] Real-time business activity monitoring and analysis of process performance on big-data domains
    Vera-Baquero, Alejandro
    Colomo-Palacios, Ricardo
    Molloy, Owen
    TELEMATICS AND INFORMATICS, 2016, 33 (03) : 793 - 807
  • [43] A big-data analysis of political rhetoric relating the developments of the United States, China, and global powers
    Carter, Patrick
    Wang, Jeffrie
    Chau, Davis
    PUBLIC ADMINISTRATION AND POLICY-AN ASIA-PACIFIC JOURNAL, 2020, 23 (03): : 227 - 243
  • [44] Three faces of the online leftists: An exploratory study based on case observations and big-data analysis
    Gui, Yong
    Huang, Ronggui
    Ding, Yi
    CHINESE JOURNAL OF SOCIOLOGY, 2020, 6 (01) : 67 - 101
  • [45] The construction of a localized teaching model of the Orff music teaching method based on big data analysis
    Qin T.
    Appl. Math. Nonlinear Sci., 2024, 1
  • [46] Performance Meta-analysis for Big-Data Univariate Auto-Imputation in the Building Sector
    Stefanopoulou, Aliki
    Michailidis, Iakovos
    Dimara, Asimina
    Krinidis, Stelios
    Kosmatopoulos, Elias B.
    Anagnostopoulos, Christos-Nikolaos
    Tzovaras, Dimitrios
    ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS. AIAI 2022 IFIP WG 12.5 INTERNATIONAL WORKSHOPS, 2022, 652 : 276 - 288
  • [47] An Analysis of the Korea National DNS Using Big Data Technology
    Jung, Euihyun
    Lim, Joonhyung
    Kim, Juyoung
    FRONTIER AND INNOVATION IN FUTURE COMPUTING AND COMMUNICATIONS, 2014, 301 : 605 - 613
  • [48] Analysis of India Ecosystem for Startup with Using Data Mining: Settlement of Big Data
    Zhuparova, Aziza
    Sagiyeva, Rimma
    Zhaisanova, Dinara
    VISION 2020: SUSTAINABLE ECONOMIC DEVELOPMENT AND APPLICATION OF INNOVATION MANAGEMENT, 2018, : 2176 - 2183
  • [49] Measure for the Improvement of Constructio Work Accident Informaiton Service Contents in CPMS Focused on Analysis of Construction Work Accidents Big Data
    Yang, Sung-Hoon
    Kim, Jin-Uk
    Kim, Young-Jin
    Ok, Hyun
    2015 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI), 2015, : 340 - 343
  • [50] A generalizable sentiment analysis method for creating a hotel dictionary: using big data on TripAdvisor hotel reviews
    Bagherzadeh, Sayeh
    Shokouhyar, Sajjad
    Jahani, Hamed
    Sigala, Marianna
    JOURNAL OF HOSPITALITY AND TOURISM TECHNOLOGY, 2021, 12 (02) : 210 - 238