Jochen Teizer

Internet of Things (IoT) for Integrating Environmental and Localization Data in Building Information Modeling (BIM)

Digital transformation is an ongoing challenge in construction. Whereas central storage and planning with Building Information Modeling (BIM) can be considered state-of-the-art, the integration of realtime data like environmental and localization data of workers in indoor work environments can provide further benefits for operations management in construction and facility management. This paper introduces the concept of permanent availability of up-to-date actual performance data sets through an Internet-of-Things (IoT) approach that integrates environmental and localization data in a cloud-based BIM platform. In this paper, we reflect on the usage of Internet of Things (IoT) technology and the lean and injury-free (LIFE) construction management approach, create a concept to implement the topics in existing systems, design and create a prototypical application, validate the prototype in field-typical work settings, and critically review the results.

Mobile Point Cloud Assessment for Trench Safety Audits

Fatalities resulting from cave-in hazards during excavation work in the United States account for 48% of the trench fatalities in construction every year per Occupational Safety and Health Administration (OSHA) data. Recent trends indicate that fatalities from trench and excavation hazards in the US are increasing. Often the experience of safety inspectors and/or the designated competent person (CP) for trenching and excavation is vital when assessing sloping measurements with approved engineering survey tools. The degree of accidents, however, allows the conclusion that proper assessment and/or protection of excavation sites is not performed sufficiently in the field, or safety coordinators and/or adequately trained CPs are not on hand when needed. While existing assessment processes and protection methods are reviewed for potential improvement, this paper proposes a new compliance assistance prototype that incorporates state-of-the-art technology. The proposed prototype creates: (1) mobile field data acquisition with lowcost photo cameras to capture point cloud surveys of the as-built conditions of trenches, and (2) computational data processing to automatically extract trench height, width, and slope values. Early results to field-realistic experiments promise useful applications of the developed prototype for safety coordinators or adequately trained CPs.

Quantitative Analysis of Close Call Events

Construction safety is a big problem according to official statistics. In many of the developed countries about 15–25% of all fatal construction workplace accidents relate to too close proximity of pedestrian workers to construction equipment or hazardous materials. Extracting knowledge from data to near hits (aka. close calls) might warrant better understanding on the root causes that lead to such incidents and eliminate them. While a close call is a subtle event where workers are in close proximity to a hazard, its frequency depends – amongst other factors – on poor site layout, a worker’s willingness to take risks, limited safety education, and pure coincidence. Some pioneering organizations have recognized the potential on gathering and analyzing leading indicator data on close calls. However, mostly manual approaches are infrequently performed, subjective due to situational assessment, imprecise in level of detail, and importantly, reactive or inconsistent in effective or timely follow-ups by management. While existing predictive analytics research targets change at strategic levels in the hierarchy of organizations, personalized feedback to strengthen an individual worker’s hazard recognition and avoidance skill set is yet missing. This study tackles the bottom of Heinrich’s safety pyramid by providing an in-depth quantitative analysis of close calls. Modern positioning technology records the trajectory data of personnel, equipment, and materials. Computational algorithms then automatically generate previously unavailable details to close call events. The derived information is embedded in simplified geometric information models that users on a construction site can retrieve, easily understand, and adapt in existing preventative hazard recognition and control processes. Results from scientific and field experiments demonstrate that the developed system works successfully under the constraints of currently available positioning technology.

BIM for 3D Printing in Construction

Three-dimensional printing – often known as additive manufacturing or the layered production of 3D objects – has been the focus of attention in the media at present and a subject that arouses great expectations in the construction industry. While the topic is rapidly emerging, 3D printing has the potential of simplifying key processes in the facility lifecycle, for example, by following design to production principles and reducing waste while increasing the quality of the final product. A pivotal piece in the success of 3D printing in construction is the Building Information Modeling (BIM) method. Since BIM already serves as a rich source of geometric information for commercially-existing, large scale, and automated 3D printing machines, 3D printing robots co-existing with human workers on construction sites will eventually need scheduling and assembly sequence information as well to maintain safety and productivity. As suitable 3D printing techniques and materials are still parts of wider research efforts, applications by early adopters in the construction industry demonstrate how 3D printing may benefit and at some point in the future complement existing construction methods like prefabrication or modularization.

BIM at STRABAG

Modern construction projects can be designed, built and operated more efficiently and to a higher quality when knowledge is shared quickly and transparently. With BIM.5D®, STRABAG SE has been advancing the vision of a “digital construction site” since the late 1990s. The “5D” stands for the 3D model + time (4D) + process data (5D), thus adding all relevant process information to the product-oriented building information model. BIM.5D® involves the client and all project participants from the start of a project and facilitates the interdisciplinary gathering and analysis of data to generate valuable information. One of the many benefits BIM.5D® offers is the transfer of knowledge that increases the quality and the efficiency of the final product. Since project data is digitally captured, combined, and linked over the entire lifecycle of a construction project, the result is a comprehensible, transparent and resilient information network for everyone involved in a project.

BIM bei STRABAG SE

STRABAG SE ist ein groser europaischer Technologiekonzern fur Baudienstleistungen, der samtliche Bereiche und die gesamte Bauwertschopfungskette der Bauindustrie abgedeckt. Fruhzeitig wurde das Potenzial von Building Information Modeling (BIM) fur den Konzern STRABAG SE erkannt und die Notwendigkeit, dieses Potenzial mit allen Baubeteiligten zu realisieren. Seit 2006 beschaftigt sich die Abteilung 5D-Planung innerhalb der Zentralen Technik exklusiv mit der Entwicklung, Anwendung und Umsetzung von BIM innerhalb des Konzerns. In der 5D-Abteilung sind die wichtigen technischen BIM-Kompetenzen des Konzerns gebundelt. An den Standorten Stuttgart und Wien werden Vorlagen und Richtlinien fur die Anwendung von BIM durch operative Einheiten der STRABAG SE erstellt, BIM-Ausfuhrungsprojekte weltweit unterstutzt, BIM-Manager fur Projekte ausgebildet und BIM-Schulungen durchgefuhrt. Dieses Kapitel erlautert die Ziele der 5D-Planung im Bauprozess sowie die Umsetzung von 5D anhand einer 5D-Roadmap und verdeutlicht anhand aktueller Anwendungsthemen einige erfolgreiche Beispiele aus der Praxis.