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DTSTART;TZID=America/New_York:20220215T123000
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SUMMARY:Context Driven Analytics and AI for Infrastructure and Facility Management
DESCRIPTION:Engineers and managers involved in facility/infrastructure operations need situational awareness and accurate assessment of as-is conditions when making daily decisions and developing short- and long-term plans. Currently\, however\, the situational awareness of engineers is often limited by a lack of actionable information relevant to the specific facilities and infrastructure systems in their purview. Advances in sensing and reality capture technologies\, such as 3D imaging via stationary platforms or drones and in-situ sensing\, streamline capturing of data depicting as-is conditions. Data collected from these technologies\, integrated with building information models\, enable context-driven analyses of as-is conditions\, generation of actionable information related to specific facilities/infrastructure systems\, and development of algorithms that help support proactive and predictive operations. Professor Burcu Akinci will provide an overview of the opportunities and research approaches associated with integration of sensor data with building/infrastructure information models and with development of context-driven algorithms. She’ll demonstrate applications of these approaches through specific deployments in several facilities and other infrastructure systems\, and highlight specific research projects being conducted at Carnegie Mellon University with a vision towards self-aware autonomous facilities and infrastructure systems.\n  \nDr. Burcu Akinci is Paul Christiano Professor of Civil & Environmental Engineering at Carnegie Mellon University and a member of the National Academies of Construction. She earned an MBA from Bilkent University (Ankara\, Turkey)\, and master’s and PhD degrees in civil and environmental engineering from Stanford University. Dr. Akinci’s research focuses on investigating utilization and integration of building information models with data capture technologies to create digital twins of construction projects and infrastructure operations and develop approaches to support proactive and predictive operations and management. Recipient of myriad awards\, including 4 best paper awards from top journals and PI of more than $6M grants\, she co-founded and is Chief Innovation Officer at LeanFM Technologies\, recipient of the 2017 Pittsburgh Business Times Innovation Award.
URL:https://c2smart.engineering.nyu.edu/event/improving-contraflow-left-turn-lane-design-at-signalized-intersections-to-decrease-traffic/
LOCATION:C2SMART Center Viz Lab\, 6 Metrotech Center\, Room 460\, Brooklyn\, 11201
CATEGORIES:Big Data & Planning for Smart Cities
ORGANIZER;CN="C2SMART":MAILTO:c2smart@nyu.edu
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