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IŞIN, Gürşans Güven

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Gürşans Güven

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    ArticlePublicationMetadata only
    Formalization of occupant feedback and integration with BIM in office buildings
    (ASCE, 2021-01-01) Ergen, E.; Kula, B.; Işın, Gürşans Güven; Artan, D.; Civil Engineering; IŞIN, Gürşans Güven
    Occupant feedback is not effectively used in the facility management (FM) phase for operations and maintenance activities as well as retrofit and refurbishment investment decisions. One of the reasons is related to incomplete or mostly unstructured occupant feedback data. The goal of this paper is (1) to formalize occupant feedback in office buildings by developing a semantic data model, and (2) to implement the semantic data model in a prototype to demonstrate that capturing and storing occupant feedback and integrating it with building information modeling (BIM) improves the experience of both occupants and FM personnel. Interviews were conducted with office occupants and facility managers, and use cases were created to develop the semantic data model. This data model was implemented in the Industry Foundation Classes (IFC) schema and a case study was conducted, in which a prototype for collecting occupant feedback integrated with BIM was developed to test the proposed approach. The applicability, practicability, and usability of the system were measured via usability tests that were applied to the occupants and FM team members. The findings showed that the proposed semantic data model can be utilized to store occupant feedback in a structured manner and to integrate this information with BIM-enabled FM systems. This approach facilitates (1) continuous collection of occupant feedback along with the vital contextual information including geometric data, and (2) effective utilization of this information in FM operations by providing visualization and analysis capabilities.
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    BIM-based automated safety review for fall prevention
    (Springer, 2020) Tekbaş, Gökhan; Işın, Gürşans Güven; Civil Engineering; IŞIN, Gürşans Güven; Tekbaş, Gökhan
    The construction industry is globally known as one of the most hazardous industries. Safety in construction is affected by many factors such as the behavior of workers, site conditions, the design and the implementation of the safety measures. Falls from height and hits by moving or falling objects are the most common types of accidents at construction sites and lead to serious injuries and fatalities. Researchers have been looking for solutions to reduce fall incidents at construction sites. Health and safety (H&S) experts usually follow traditional methods to plan and employ safety measures at sites. These safety planning methods are mainly based on reviewing 2D drawings to identify the risks and associated hazards and have some important deficiencies. First of all, the efficiency of safety planning depends on the experience of H&S experts. More importantly, it is difficult to identify the potential hazards from a 2D drawing while the project is progressing. Building Information Modeling (BIM) can overcome the challenges observed with the traditional safety planning processes. Hazards in a project and the related safety measures should be continuously identified throughout the construction. Since BIM is a 3D model-based process that assists the stakeholders not only to construct and manage but also to plan and design structures; BIM can provide an efficient solution to plan and design the safety measures of a construction project both during the design and construction phases. In addition, the safety review of buildings can be more effectively performed with a 3D building information model. In this study, “Automatic Fall Safety Review (AFSR)” rule checking tool is developed by using Dynamo, the open-source visual programming add-in for Autodesk Revit. This tool analyzes a 3D building model in Revit, and automatically identifies the hazardous places in a building and shows the related safety measures for preventing falls from height in particular. This paper presents the details of the AFSR tool and demonstrates its application for an 8-storey residential building.
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    A rule-based methodology for automated progress monitoring of construction activities: A case for masonry work
    (International Council for Research and Innovation in Building and Construction, 2019) Işın, Gürşans Güven; Ergen, E.; Civil Engineering; IŞIN, Gürşans Güven
    The conventional approach that is used to monitor construction projects is to collect progress data from the construction site through visual investigation. This results in deficient and sometimes erroneous data, and leads to inefficiencies in project control, delays and cost overruns. To address these problems in building construction projects, an approach was developed to automatically monitor activity progress by tracking major construction equipment and bulk materials using sensor-based technologies that are cost-effective and easy to deploy. In this approach data obtained from sensors (e.g., load sensor) and/or other sensor-based technologies (i.e., Radio Frequency Identification (RFID)), which were deployed on major construction resources, were fused using rule-based algorithms to determine the activity progress. This progress data was compared with human-generated site related data (e.g., schedules, site reports) to determine the activity performance. This paper presents the developed data fusion approach and rule-based data fusion algorithms that incorporate the domain-specific heuristic information for determining the activity's overall progress. To validate the proposed approach, a proof-of-concept prototype was deployed and tested at a construction site for monitoring the progress of masonry work. The results show that the developed approach achieved 95% average accuracy in identifying the progress of the masonry work that was monitored during the field tests. The main contributions of this study are the rule-based data fusion approach and the rules that were developed for processing data from equipment and bulk materials. These rules can be used to determine the progress of other activities that use similar resources.
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    ArticlePublicationOpen Access
    Rateworkspace: BIM integrated post-occupancy evaluation system for office buildings
    (International Council for Research and Innovation in Building and Construction, 2022-04) Artan, D.; Ergen, E.; Kula, B.; Işın, Gürşans Güven; Civil Engineering; IŞIN, Gürşans Güven
    The feedback obtained from occupants regarding their comfort needs and performance of buildings is critical for assessing occupant satisfaction, identifying the operation and maintenance (O&M) issues in time and for improving resource efficiency in buildings. Current facility management (FM) systems and occupant feedback collection practices, however, have limitations in supporting effective decision-making in FM, as they lack the necessary contextual data related to the occupant feedback (e.g., building geometry, systems, elements). Building Information Modeling (BIM)-enabled FM systems are used for combining different types of FM information with building models; however, occupant feedback is still not effectively utilized in FM since it is not integrated with BIM. In this study, a BIM integrated post-occupancy evaluation system prototype is developed for: (1) collecting occupant feedback along with the contextual information related to the feedback items in a structured way, and (2) presenting this information as integrated with BIM to the facility managers. This enables conducting spatio-temporal queries and supports effective decision-making by visualizing the collected feedback. The prototype was designed by using qualitative shadowing with FM teams to identify information needs and use case analysis to determine how contextual data integrated with BIM could be collected from office occupants who are non-technical persons with limited information on building models. This paper identifies the FM query categories that are required to process the occupant feedback and describes the RateWorkSpace prototype developed for office buildings. The deployment of the prototype in a real-world office demonstrates that the proposed system is applicable, practical, usable, and that real-time building performance data can be both collected and analysed with the developed system. This has the potential to increase the effectiveness of the FM and O&M processes, and help to create office spaces with optimized energy use and occupant comfort that also supports occupant well-being and productivity.
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    ArticlePublicationMetadata only
    Tracking major resources for automated progress monitoring of construction activities: masonry work case
    (Emerald, 2021-10-21) Işın, Gürşans Güven; Ergen, E.; Civil Engineering; IŞIN, Gürşans Güven
    Purpose: The purpose of this study is to monitor the progress of construction activities in an automated way by using sensor-based technologies for tracking multiple resources that are used in building construction. Design/methodology/approach: An automated on-site progress monitoring approach was proposed and a proof-of-concept prototype was developed, followed by a field experimentation study at a high-rise building construction site. The developed approach was used to integrate sensor data collected from multiple resources used in different steps of an activity. It incorporated the domain-specific heuristics that were related to the site layout conditions and method of activity. Findings: The prototype estimated the overall progress with 95% accuracy. More accurate and up-to-date progress measurement was achieved compared to the manual approach, and the need for visual inspections and manual data collection from the field was eliminated. Overall, the field experiments demonstrated that low-cost implementation is possible, if readily available or embedded sensors on equipment are used. Originality/value: Previous studies either monitored one particular piece of equipment or the developed approaches were only applicable to limited activity types. This study demonstrated that it is technically feasible to determine progress at the site by fusing sensor data that are collected from multiple resources during the construction of building superstructure. The rule-based reasoning algorithms, which were developed based on a typical work practice of cranes and hoists, can be adapted to other activities that involve transferring bulk materials and use cranes and/or hoists for material handling.