Leveraging AI to Actualize Next-Gen Construction Projects

Artificial intelligence has entered the construction industry, and early adopters say the efficiencies will transform this sector of the global economy for the better. Companies that are ready to take advantage of all the benefits AI has to offer will have the opportunity to not only stand out from a crowded playing field, but also keep costs under control and better manage their labor force. In this article, we will take a look at some of the most compelling ways companies are using AI to actualize their latest projects and data annotation required.

Monitor the Progress of the Construction

Since construction projects involve many moving parts, it is important to stay on top of how well the project is moving along to make and update all the stakeholders. One of the interesting new ways companies are doing this is by capturing site data. This is done through a helmet mounted with 360-degree cameras, which automatically analyze using proprietary AI algorithms. The platform provides the project management team with true-to-life progress reports supported by visuals. This leads to significantly improved efficiency in terms of costs, labor and management time, and resources.

This technology could offer a lot of value since the latest research shows that, on average, 54% of construction sites remain idle, meaning that over half of our work fronts are not being worked every single week. Keeping a greater amount of focus on construction sites and the progress they are making can lead to significant cost savings and also increased efficiency.

Incorporating ChatGPT

While we don’t usually associate the construction sector with generative AI, like ChatGPT, there are many interesting ways construction companies can take advantage of it. For example, let’s consider something like producing proposals for new projects.

The final step in the sales and marketing process for construction firms is frequently creating fascinating, captivating, and convincing proposals. A high-quality proposal’s development and writing might take time and be difficult. ChatGPT may come up with suggestions for proposal material and even finish particular sections of a proposal. ChatGPT may generate language that is specific to the proposal by taking into account the project, the client, and other pertinent factors. ChatGPT can assist with the proposal’s general organization. ChatGPT may assist in making the proposal simple to read and comprehend by offering ideas for headers, subheadings, summaries, and bullet points. This can be a useful tool that will help writers of proposals save a lot of time and effort.

Another interesting way to use ChatGPT is to conduct research into prospective vendors. There are many red flags companies need to look out for when searching for a vendor. For example, there are companies that owe back taxes or have material regulatory infractions. Currently, it is nearly impossible for public employees to manually go through available companies and owners to identify those entities that should be barred, including those operating under new related family or company names.

Generative AI like ChatGPT, if given access to data from departments like finance, building, permitting, sanitation, and transportation, can identify these bad actors trying to hide under layers of false names, shell ownership, or frequent company changes.

What Types of Data Annotation are Needed to Train Advanced AI Technologies?

If we look at AI technology to monitor the pace of construction, we see that it uses computer vision cameras to identify various aspects of construction. This means that data annotation methods ranging from 2D/3D bounding boxes to more advanced types, like semantic segmentation, will need to be used. The latter delineates boundaries between similar objects and labels them under the same identification. This method is used when you want to understand the presence, location, and sometimes, the size and shape of objects.

When we look at generative AI, like ChatGPT, it needs to have the ability to be capable of optical character recognition (OCR). Here, entity annotation will need to be done, which recognizes key phrases, named entities, or parts of speech in the sentences. Entity annotation helps drive attention to the crucial details of the long text. Entity linking will also be necessary, which is the location and annotation of certain entities within a text. Entity linking is the process of connecting those entities to larger repositories of data about them.

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