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R&D PROJECT

Construction projects have a long and complicated chain of dependencies, in which failure to meet even one of the assumptions can often result in a significant increase in project costs, and lack of project profitability. This is usually caused by so-called ‘’domino effect’’.

The problem is even more difficult to solve, as the construction industry is currently one of the least digitized in the world. Algorithms predicting specific events or detecting their causes early need a large amount of input data of a certain accuracy and appropriate nature (e.g. geoposition, time, metadata).

We decided to find an answer. Our work resulted in creating a system that would be capable of controlling all workflow in the company. Now, we’re working on enabling it to forecast possible delays on a job site.

Thanks to the planned design of a centralized sensory data warehouse related to construction workers and a wide range of data functioning in the Archdesk system, as well as data from external sources (e.g. metadata) it will be possible to warn in advance about various delays in construction projects.

 

By analyzing this data to detect patterns, using artificial intelligence algorithms, we will be able to ultimately providing value to the end user in the form of an early warning system for adverse events, mitigating their risk, and supporting key decision making. This will directly translate into optimization of economic aspects of construction projects and their timeliness (anticipating and counteracting delays).

Predictive processes will use innovative methods to detect dependencies and patterns in high-volume data sets. Archdesk, thanks to the new technology developed as a result of the project, will be able to automatically detect the risk of delay or increase in project costs, and will also allow the employee to specify the nature of a specific delay or problem, which will positively increase the precision of predicting adverse events in the future.

The project will involve the development of new data analysis technology, such as the availability of resources, work schedules, GPS positioning data and data from sensors such as gyroscope, accelerometer, as well as external data such as weather forecast, traffic intensity, accidents etc. By analyzing this data to detect patterns, using artificial intelligence algorithms, we will be able to ultimately providing value to the end user in the form of an early warning system for adverse events, mitigating their risk, and supporting key decision making. This will directly translate into optimization of economic aspects of construction projects and their timeliness (anticipating and counteracting delays).

 

Find a solution tailored for your business.

 
 
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