Using Sequence Mining in Cloud Service to Design the Warning System for Construction Safety
Chun-Ling Ho1, Tung-Chiung Chang2
1Chun-Ling Ho, Department of Information Management, Kao Yuan University, Taiwan.
2Tung-Chiung Chang, Department of Civil Engineering, Kao Yuan University, Taiwan.
Manuscript received on 25 May 2019 | Revised Manuscript received on 03 June 2019 | Manuscript Published on 22 June 2019 | PP: 376-379 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C10780283S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the era of knowledge economy, to establish adaptive management and warning system can enhance performance depends on the foundation with using technology for decision makers and management team. In view of the fact that the labor force of the middle-aged and elderly people in Taiwan is increasing year by year, the manpower of the construction industry is gradually becoming middle-aged, which will be associated with the aging of the body of the phenomenon. The elderly workers in the construction safety education and its relative safety experience in warning services should be taken seriously. Therefore, this study takes the construction safety as the core and focuses on the warning design of the dynamic working safety for the warning index and pattern by the cloud service. In order to enhance the safety of pre-working and working safety, the study will collect the initial data of safety training history in the iWork cloud service, and carry out real-time data analysis and sequence mining to find out the warning mode of affecting safety behavior. Sequence mining will use the concept of the phenomenon in monitoring, and extract the events in order to establish the relationship between the time sequence and then establish the exact rule of sequence calculation. It is in order to adapt to the middle-aged workers in the construction warning service with security model.
Keywords: Sequence Mining, Safety Warning, Working Training in Construction, Cloud Service, Mobile Service.
Scope of the Article: Construction Engineering