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The way tofully automatic Building site

Artificial intelligence is seen as the key technology for the future for the construction industry as well as for many other industries. Open Experience positions itself as a pioneer in this area.

Artificial intelligence is seen as the key technology for the future for the construction industry as well as for many other industries. Open Experience positions itself as a pioneer in this area.


ESKIMO Artificial Intelligence Recognition of people or faces

Recognition of people or faces

  • The service construction-photos
  • Object detection from images
  • two modes: persons- or face recognition
  • Pixelation of personal data
  • GDPR-compliant image documentation
EKIMO Artificial Intelligence Recognition of faces

Detection of objects

  • The service construction-photos
  • Object detection of relevant objects
  • Laser distance measuring device, cell phone etc.
  • Exclusion of the areas from the pixelation
ESKIMO Artificial Intelligence Automatic picture classification

Automatic image classification

  • The service construction-photos
  • Object detection of doors, windows etc.
  • Filtering according to automatically recognized categories

Research formorning


Development of system modules of artificial intelligence for a digital mobile value chain for construction


The aim of the ESKIMO project is to develop methods of artificial intelligence(AI) to implement a far more efficient construction management. Three sub-goals are pursued here:

  • The image data captured during execution from smartphones, tablets, helmet camera systems, etc. are processed by AI-Interpreted algorithms. Construction objects and their characteristics can be recognized automatically. Optical defects such as scratches or cracks can be identified directly and digitally processed.

  • The recognized building objects are with the topology of the BIM-Model so that a virtual, continuously updated image of the current construction status including machines and materials is created. Based on this, it will be possible to determine the performance progress and potential anomalies. This increases the degree of automation of the technical and commercial construction supervision by leaps and bounds.

  • Based on the image-based object recognition and the topological comparison with BIM, real-time-Position determination on the construction site using AI-Methods and sensor data fusion developed, which is built into intelligent systems to optimize construction processes. So who-the modern collaborative construction-Methods such as networked construction site, Just-in-Time-Delivery, intel-Ligent construction logistics, synchronized working methods as well as lean construction find a practical application. This assumes that data on the current and planned state are available on the new-are available digitally.


Technical quality assurance

On the one hand, the module for technical quality assurance detects optical deviations from the target-Condition, i.e. surface features such as damage, stains, discoloration, etc. and, on the other hand, structural differences to BIM-Model, such as missing or incorrectly installed components, and automatically records these defects.

Commercial quality assurance

The commercial quality assurance takes on the challenge of a performance comparison based on the BIM-Model and reality. Look regular is-Recordings, the time of installation of the individual components can be determined and compared with the planning based on models.

Intelligent construction logistics

Intelligent construction logistics focuses on internal logistics processes- and outside the construction site, so that the available resources such as possible storage spaces and procedural routes can be used as optimally as possible.


Key data

  • begin: April 01, 2020
  • Duration 24 months
  • total cost: € 2.4 million
  • Funded by the Federal Ministry of Education and Research(BMBF) ![Funded-from the-Federal Ministry-for-education-and-research(BMBF).png](/images/subjects/Artificial-intelligence/Funded-from the-Federal Ministry-for-education-and-research(BMBF).png)

Research formorning


Development of a modular and adaptable system for the automatic acquisition of digital information in construction

![Demonstration-Video](/images/subjects/Helmet attachment-digiBau-to the-Capture-from-360-pictures/Research project-digiBau/Research project-digiBau-concept-of-HelmKamerasystems.png)

The aim of the "digiBau" project is a modular and adaptable hard drive-software-To develop a system that enables the automatic acquisition of digital information in the construction industry. Thanks to a module-based structure, this system should be able to be used on various “carrier systems”. The desired technical solution should conceptually and technically consist of the following Soft- and hardware-There are components that each fulfill a specific task and must be developed independently of one another.

  • The sensor-The module consists of a mechanically flexible construction to accommodate various sensors, which are attached to the construction helmets. Using integrated software-Components, the data from a wide variety of sensors are read in via a generic interface and used for further evaluations by the digiBau system unit-System provides.

  • The camera-Module is a mechanically flexible component that is attached to a construction helmet depending on the examination procedure and, at the same time, software-Interface for importing different picture- and includes video data that can be used for further evaluations in the analysis-Module of the system unit are provided.

  • Hard-and-Software innovations used to enable sensor data processing, image processing, navigation and defect analysis. It essentially consists of a database within which the sensor- as well as picture- and video data in one analysis-Module can be merged. With the help of special algorithms the picture-/Video data of the examined object(Room, building facade, system, etc.) merged together with the recorded sensor data in real time, which requires a powerful computing unit. This then creates a realistic overall image of the examination object with specific data on the various object dimensions and examination measurements.

  • The smart-Inspection-Cockpit is a mobile application for the field service that enables real-time communication between the system unit and a mobile device(Smartphone or tablet) enables. Here, the employee who carries out the examination is shown the images merged in the system unit- and sensor data are displayed graphically and via the analysis module of the system unit(see M3) Identified defects are visualized directly with the respective position information. In this way, if necessary, further investigations can be carried out on identified defects, which are initiated directly from the cockpit, e.g. zooming in on a construction defect using the camera on the construction helmet for photo documentation and adding digital annotations at the same time/ Texts/ Voice memos.

The backbone of the system is the inspection server. This accompanies all investigations- and analysis processes and offers data management functions as well as further analysis algorithms for offline processing of the data. For example, historical and new data from the current object examination are to be compared for comparison in order to identify dependencies and anomalies using computer-learning algorithms. Examples are the recognition of patterns and dependencies on defects that have occurred in relation to materials, usage behavior or interactions with the environment. The information obtained from this should be saved as(Optimization-)Knowledge can be made available for future construction projects, which is why a further step is the internal processing of the information via the inspection server.

Open Experience is responsible for the implementation of the software in the project-Building blocks.


Key data

  • begin: 01 July 2017
  • Duration 24 months
  • Funded by the Federal Ministry for Economic Affairs and Energy(BMWi) ![Funded by the BMWi)](/images/subjects/Helmet attachment-digiBau-to the-Capture-from-360-pictures/Research project-digiBau/BMWi_Logo.svg)



Press event with Open Experience, Darmstadt University of Applied Sciences and Gemünden


Starting shot of ESKIMO on April 28th, 2020


DigiBau helmet camera attachment for 360 °-pictures

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