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PurposeThis paper introduces a novel method to improve building safety management by leveraging building information modeling (BIM) and adaptive information retrieval techniques. The integration aims to overcome the limitations of traditional safety management methods in connecting construction processes with risk management efficiently.Design/methodology/approachThe proposed method involves developing industry foundation classes (IFC) ontologies and integrating them with a safety document ontology to form a comprehensive BIM-based safety context framework. Custom reasoning rules and an inference engine are constructed to enable automatic context-aware safety information retrieval. The methodology is demonstrated through an adaptive information retrieval system using job hazard analysis (JHA) documents.FindingsThe implementation of the BIM-based adaptive information retrieval system shows significant improvements in identifying and managing construction risks. By mapping job-specific risks to corresponding safety measures, the system enhances risk detection and management tailored to particular construction tasks. The results indicate a marked improvement in the precision and accuracy of safety assessments and recommendations, aligning them closely with planned construction activities and conditions.Originality/valueThis paper offers an innovative approach to construction safety management through the development of a BIM-facilitated context-aware information retrieval system. This approach provides a more intelligent and automated framework for identifying and managing risks in construction projects. By focusing on specific job steps and related risks, the system enhances the effectiveness and accuracy of safety measures, contributing to better overall building safety management.
PurposeThis paper introduces a novel method to improve building safety management by leveraging building information modeling (BIM) and adaptive information retrieval techniques. The integration aims to overcome the limitations of traditional safety management methods in connecting construction processes with risk management efficiently.Design/methodology/approachThe proposed method involves developing industry foundation classes (IFC) ontologies and integrating them with a safety document ontology to form a comprehensive BIM-based safety context framework. Custom reasoning rules and an inference engine are constructed to enable automatic context-aware safety information retrieval. The methodology is demonstrated through an adaptive information retrieval system using job hazard analysis (JHA) documents.FindingsThe implementation of the BIM-based adaptive information retrieval system shows significant improvements in identifying and managing construction risks. By mapping job-specific risks to corresponding safety measures, the system enhances risk detection and management tailored to particular construction tasks. The results indicate a marked improvement in the precision and accuracy of safety assessments and recommendations, aligning them closely with planned construction activities and conditions.Originality/valueThis paper offers an innovative approach to construction safety management through the development of a BIM-facilitated context-aware information retrieval system. This approach provides a more intelligent and automated framework for identifying and managing risks in construction projects. By focusing on specific job steps and related risks, the system enhances the effectiveness and accuracy of safety measures, contributing to better overall building safety management.
The study assesses the coastal evolution of Southeastern Crete and the vulnerability of archeological sites of the area to coastal erosion. Shoreline dynamics for the period since the 1940s was investigated based on the interpretation of high-resolution aerial photos and satellite images. The set of climatic variables derived from the Copernicus databases, as well as data on geomorphological and geological factors obtained from fieldworks, images interpretation, archives, and open sources, were analyzed. The impact of these variables on coastal dynamics was evaluated through regression analysis, correlating their spatial distribution with rates of shoreline retreat/advance. Based on this analysis, variables for the Coastal Vulnerability Index (CVI) calculation were selected, and the weights for the weighted CVI were determined. Both approaches, the CVI and the weighted CVI, identified the most vulnerable areas as being situated in the north, east, and southeast of Koufonisi island, as well as in the north and east of the Chrisi island. The least vulnerable are the wide beaches in the closed bays in the areas of Gra Lygia, Ierapetra, and Ferma, along with the rocky capes at the east of the Ierapetra area. Two of five archeological sites of the area (Lefki Roman Town and Stomio Roman Villa) are located within the zone of high or very high coastal vulnerability. This study provides the first in-depth analysis of coastal dynamics and coastal vulnerability of the area of Southeastern Crete, which has significant cultural heritage assets but has previously remained under-researched.
This research analyses beach vulnerability to erosion along the coast of Valencia province, Spain. The Coastal Vulnerability Index (CVI) is used to assess vulnerability, considering the following variables: beach width, beach erosion/accretion rate, dune width, wave height, relative coastal flood level, submerged vegetation, upper depth limit of submerged vegetation, and percentage of vegetated dune. The results show that vulnerability varies significantly along the coast. The vulnerability assessment revealed that 26.9% of the coastal sections were classified as having very low susceptibility to erosion, 34.5% as low, 22.3% as moderate, 12% as high, and 4.3% as very high. Urbanized areas with reduced dunes are more vulnerable than natural areas with wide beaches and well-developed dunes. The study highlights and discusses limitations of the CVI method and suggests using the mean instead of the square root to calculate the overall vulnerability index due to the influence of one single variable in this formula. It is concluded that natural areas characterized by the presence of dunes exhibit a diminished vulnerability to erosion when compared to highly urbanized regions devoid of dunes and marine vegetation.
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