M
Manu Venugopal
Researcher at Georgia Institute of Technology
Publications - 20
Citations - 1534
Manu Venugopal is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Industry Foundation Classes & Interoperability. The author has an hindex of 13, co-authored 20 publications receiving 1329 citations. Previous affiliations of Manu Venugopal include Autodesk.
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Building Information Modeling (BIM) and Safety: Automatic Safety Checking of Construction Models and Schedules
TL;DR: The developed automated safety checking platform informs construction engineers and managers by reporting, why, where, when, and what safety measures are needed for preventing fall-related accidents before construction starts, the safety area reviewed is fall protection.
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Performance evaluation of ultra wideband technology for construction resource location tracking in harsh environments
TL;DR: In this paper, the authors evaluate a commercially available Ultra Wideband (UWB) system for real-time, mobile resource location tracking in harsh construction environments and demonstrate the applicability of UWB for the design of construction management support tools.
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Semantics of model views for information exchanges using the industry foundation class schema
TL;DR: It is concluded that although the IFC product model schema is richly expressive, it lacks formal definition of its entities, attributes, and relationships, which is expected to impact the overall interoperability of applications in the building information modeling realm.
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Ultrawideband for Automated Real-Time Three-Dimensional Location Sensing for Workforce, Equipment, and Material Positioning and Tracking
TL;DR: In this paper, an emerging sensing technology called ultrawideband (UWB) is introduced that is capable of determining three-dimensional resource location information in object-cluttered construction environments in real time (up to 60 Hz).
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An ontology-based analysis of the industry foundation class schema for building information model exchanges
TL;DR: This research examines Industry Foundation Classes from a perspective of an ontological framework, which can make the IFC definitions more formal, consistent and unambiguous and proposes reforms such that data exchanges would be more semantically robust.