Machine Learning You can use ML in different areas in construction management such as image recognition, problem-solving, digital assistants, workflow and schedule optimization. In the first step, you need to collect data in a construction project. Main data sources of a project include Design, Machinery, Employee, Contracts, Planning Tools, ERP, Specifications, and Handbooks. Of course, the number of these sources may change depending on the project.
about construction activity, resource quantity, weather conditions, schedule information easily can be used to make ML-based predictions or warnings. You can see a diagram for ML powered prediction system for piling works.
After collecting data in a central database, you can crunch this data for several purposes. If you ask proper questions, ML algorithms can find data-driven answers to those questions.
Another example is issue management. As you know, there a lot of issues are recorded in the construction site using different tools. ML algorithms can learn this process to evaluate the priority of these issues and make suggestions about possible solutions. You can increase the number of that kind of examples. The key is to have data to feed ML algorithms and asking the right question about your project.
You can use ML algorithms in different construction workflows such as scheduling, quality check, safety management, issue tracking, resource and design management. For example, data
In 2019 we will see more tool using ML algorithms in construction project management and this help to increase productivity in a construction site.
THE EUROPEAN WOMEN IN CONSTRUCTION & ENGINEERING AWARDS >> MAY 2019
2019 WICE awards and summit summary.