BUILD-CYCLE

Integrated analysis and visualization for advanced construction planning and controls

 Coordinatore Ozyegin University 

 Organization address address: NISANTEPE MAH ORMAN SOK 13
city: ALEMDAG CEKMEKOY ISTANBUL
postcode: 34794

contact info
Titolo: Mrs.
Nome: Nilay
Cognome: Papila
Email: send email
Telefono: +90 216 564 95 68
Fax: +90 216 564 90 57

 Nazionalità Coordinatore Turkey [TR]
 Totale costo 100˙000 €
 EC contributo 100˙000 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call FP7-PEOPLE-2012-CIG
 Funding Scheme MC-CIG
 Anno di inizio 2012
 Periodo (anno-mese-giorno) 2012-08-01   -   2016-07-31

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    Ozyegin University

 Organization address address: NISANTEPE MAH ORMAN SOK 13
city: ALEMDAG CEKMEKOY ISTANBUL
postcode: 34794

contact info
Titolo: Mrs.
Nome: Nilay
Cognome: Papila
Email: send email
Telefono: +90 216 564 95 68
Fax: +90 216 564 90 57

TR (ALEMDAG CEKMEKOY ISTANBUL) coordinator 100˙000.00

Mappa


 Word cloud

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techniques    automation    environment    building    construction    crew    planning    energy    modeling    simulation    describe    data   

 Obiettivo del progetto (Objective)

'This project offers a novel integrated 3D planning and control environment for construction projects. While recent Building Information Modeling (BIM) and construction automation techniques have potential to significantly improve construction management, the benefits are yet to be realized for construction planning and controls. This proposed project will describe an integrated 3D platform for analysis and visualization of construction process data and energy use. Building on the geometry-based process modeling and simulation approach (GPM), it will describe a group of methods to achieve automation for planning-control cycle for detailed construction operations through combination of optimization of construction crew behavior and automated data collection within an integrated system. Construction crew actions will be optimized using reinforcement learning techniques on the simulation model. Sensor data will be integrated in the same environment to perform data fusion and improve progress feedback. Through collaborations with experts at leading universities at USA and European Research Area, this project is expected to make a large impact on computational modeling of construction systems. Moreover, it will contribute to the European excellence for the goals of virtual factory and energy efficient building.'

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