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Norwegian AI Directory

Digital Building Twins for Construction Site (DiCoSiMa)


Digital twin for real time monitoring of building production: state and quality assessment supporting dynamic re-planing enabling reduced production cost with improved production quality. 1. The production planning is always a challenge while environmental have a big influence. Monitoring of the construction progress on the construction site with autonomous vehicles equipped with cameras. A drone inspects, for instance, the fire seals in building modules and the water sealing of roof elements to protect the building against rain already in the early assembly phase. The construction progress will be monitored with image recognition together with water sensors (e.g. create models based on images and derive progress information) and will be compared with the initially agreed planning. 2. The monitoring of the location of each single worker and of smaller and larger equipment would help to optimize the resource efficiency with forecasting and deep learning algorithms. That would mean: · Lower idle time of trucks and reduce the time that building modules stay idle on the construction site. Use of satellite data for the localization of the modules. ·Safer work condition while workers get warning signals when cranes move loads in their working area ·Monitor the health of smaller equipment (e.g. envelops for building modules) and use a forecasting when envelops need to be replaced. 3. Very often it the real costs status of a construction building is not clear for all parties involved. The creation of more cost sensitivity would help to reduce the construction costs. This will lead to a better information base for decisions and to well informed actors in the factory and on the construction site. Transparent costs presentation helps to reduce the cost of construction projects..

Project leader: Jochen Haenisch

Started: 2019

Ends: 2020

Category: Næringsliv

Sector: Næringsliv

Budget: 70000


Address: Oslo