Technology has improved efficiency, safety, and accuracy in the construction industry. For instance, takeoff software has simplified project cost estimations while increasing precision and reducing the chances of human error.
These tools have also become more specialized. Software for contractors provides features specific to their needs. Meanwhile, applications for quantity surveyors offer different, specific features to make their jobs easier, helping with issues like improving sustainability.
In addition, construction software companies are creating tools using artificial intelligence (AI). For instance, computer vision programs can collect and analyze visual data. They can help read blueprints and collate symbols, abbreviations, and measurements in much less time than a human. With this help, contractors, architects, and engineers are free to work on higher-level tasks.
What Is Computer Vision?
Computer vision is a wing of AI focused on getting data from images. It uses algorithms that can be applied to photos, illustrations, drawings, videos, and other types of visuals.
Computer vision programs “learn” by processing images of specific items until they can find distinguishing characteristics. For instance, a program to check the quality of roofing shingles would look at millions of pictures of shingles until it can differentiate between flawed and perfect shingles.
Because these programs can analyze images pixel by pixel, they can be more accurate than human quality inspectors. Currently, computer vision programs can monitor construction site images and video feeds for safety. The programs look for anomalies that signal an increased risk of falling materials or misused equipment.
Programs can also detect objects and workers at the job site to track progress and manage workflow. Specialized programs can inspect work and check for quality and compliance with project protocols.
The Impact of Computer Vision on Construction
AI tools like computer vision bring two important advantages. First, they monitor constantly without suffering from fatigue or inattention. Second, the programs see minute details invisible to the most attentive inspector. For instance, a program can pick out identical images on blueprints to streamline design and estimation processes.
AI can be implemented to augment and improve estimation processes for concrete work, framing, flooring, masonry, and many other areas of construction work.
Here is a closer look at the three benefits construction companies can enjoy when using computer vision tools.
Enhancing Project Safety
Computer vision programs can scour video feeds and images from job sites. The software looks for anomalies, such as spills or equipment that should have been removed.
Computer vision programs can monitor video streams for safety compliance around a job site in real time. It sends alerts after detecting hazards, allowing for rapid response.
For instance, OSHA requires head protection for construction areas with possible head impact. AI tools can find workers not complying with this rule.
Improving Quality Control
Programmers can train computer vision software to inspect workmanship. For instance, the software can learn what quality welding work looks like and inspect images of welds on job sites for quality.
AI can also extract dimension data from blueprints and use it to assess the dimensions on the actual work site. This software is meant to ensure measurement accuracy. Correct measurements are essential for materials and cost estimates, which impact the profitability of each construction project.
Improving Sustainability
Green building is another area where AI tools can be of use for improving and streamlining processes.
AI can also help construction firms implement more sustainable building methods, optimizing cost and quality for contractors using greener construction materials.
Streamlining Project Management
Construction project management is a complex undertaking. Computer vision enables constant, real-time updates on progress at construction sites. Programs can compare actual progress to 3D models of the construction site. As a project manager, you can use these insights to update stakeholders.
In addition to monitoring progress, computer vision can count laborers and materials on the site. This verifies workers and resources are there on schedule. If workers are absent, for example, managers get an early warning and contact or replace employees to avoid delays.
How To Integrate Computer Vision into Construction Projects
Computer vision is effective for specific purposes. It may lack the understanding of the context and real-world experience of human workers. It won’t work for tasks requiring creativity or dynamic solutions.
Also, it takes time and data to train AI for specific tasks. Companies need to integrate computer vision carefully. They have to choose the right applications for the software and train using high-quality image data.
Here is a look at four factors to consider when making computer vision a part of your construction process.
Assess Your Needs
The first step in choosing computer vision applications is defining project needs and goals. Then, select software that supports these goals. Also, consider the biggest challenges. For example, if safety compliance is a problem, opt for hazard and compliance detection tools.
Once you purchase computer vision applications, programmers need to develop and train AI models to meet your specific needs. Then, you’ll need to place the cameras or other imaging equipment around the job site. Placement is important because you need to provide the correct views for the program so that it can collect the necessary image data.
Choose the Right Computer Vision Solutions
As a project manager, you need to match computer vision solutions with your needs. You also need to ensure that the programs have specific qualities.
First, the solutions need to be scalable. The scale of each construction project is different. The programs need to function the same whether dealing with large or small amounts of data. They also need to work in different settings and conditions.
Reliability is also essential. Programs trained on poor-quality data may miss important data points. They will send false alarms or miss key details related to project completion or work quality.
For these reasons, you need programs with strong developer support. Developers should be willing to work with you to debug software and continue AI model training. For instance, if the program misses certain data points in video feeds, programmers may need to feed it more training images to improve its accuracy.
Also, they should be able to ensure computer vision programs function with other tools. For instance, computer vision and barcode-based inventory can work together to verify the quantity and quality of the materials onsite.
Train Your Team
Construction workers need to understand how to work with computer vision tools. For example, safety managers should learn how to use their AI programs' user interface and manage alerts. Train tradespeople to interpret the results of quality assessment software and make corrections to their work.
In all cases, hands-on training is most effective when adopting new technology. This ensures workers learn skills they can apply on the job. It also helps them understand how the program is making their job easier. With this knowledge, they may buy into the idea of using technology rather than worry about it slowing them down.
Monitor Effectiveness
Continue to monitor the performance of computer vision software. You can use key performance indicators (KPIs) to quantify the tools’ results. For instance, measure adherence to the project timeline, materials costs, number of safety issues, or response time to safety problems.
Whatever KPIs you choose, the results should be better after you implement computer vision.
Also, you can assess the performance of the programs after each project. Find areas for improvement and establish KPIs to measure any improvements for the next project. This approach helps continuously improve AI integration in your construction business.
With careful planning, computer vision can streamline construction operations and increase quality and safety. The right choices and high-quality software can improve operations and bring the benefits of AI to every aspect of construction jobs.
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