The construction industry is beset by problems such as inadequate budgets, lack of planning, and management issues. It sometimes has to cope with labor issues like strikes, go-slows, and wage negotiations. These problems run the gamut of all sectors, not only construction. Many of these setbacks, e.g., cost overruns, can be prevented or improved by making proper use of data. While data will not stop worker discord, it can ensure that projects are kept on track and stay within budget. It can provide sufficient, accurate information and trends to permit confidence in making decisions. Below we take a look at how civil engineers use data.
Too Much Data?
Are we overrun by excessive volumes of data that are too unwieldy to draw conclusions from? How do we decide which data matters and what can safely be ignored? Fortunately, one of the greatest technological advances we have witnessed and that is now being utilized across sectors is Big Data.
Big Data has more sources of data (variety), being delivered at greater speeds (velocity), and in bigger amounts (volume), hence it is referred to as the three Vs. We can thank artificial intelligence and machine learning for our ability to use this data more effectively than we did with much smaller quantities so that we can solve new problems that we had no solutions for before.
On occasion, you may see a manual traffic counter sitting next to an intersection with a clipboard and counting the number of cars passing through. This process is called field data collection. This may be fine to ascertain how many cars use an entrance or exit from a townhouse complex and whether the volume justifies a separate traffic light for these vehicles. But with larger projects, it is just not viable. For example, how accurate would the counts be for a massive interchange with five lanes of traffic, with many of them overtaking other vehicles? You could not rely on manual counts from this example to make informed decisions.
Digitalization enables civil engineers to obtain 100% accuracy on even the largest project. The time taken to do this is also far swifter than a manual process and is more cost-effective. Once you have your digital data, then infrastructure analytics allows you to make sense of it and determine the best course of action.
Simulations of the construction process can be run. These simulations provide a realistic portrayal of conditions on the ground at a particular site that is under review. Costly mistakes can be avoided by first using this software before committing building materials and labor to construction.
Data science is a field that is employed by many industries. It maximizes the uses of data to ensure better planning and delivery. Thus, statistics play a role in every phase of construction. Civil engineers use data science for many applications in the industry. For example, data science can assist with the blended calculations needed to make predictions. This is a great boon when scales are huge but can be used just as effectively on smaller projects. Data science is also useful for conducting a risk analysis of a project.
These are just a few of the ways that civil engineers manage and interpret data.