Even the strongest structures will eventually fail. When such failures might occur is hard to predict, so it takes regular inspection to ensure buildings and public infrastructure are in good condition. Now, researchers think artificial intelligence (AI)-powered robots could handle these checkups.

Concrete crack detection has come a long way over time, but researchers believe it can go further. Automating the process through AI and robotics could transform the industry for the better.

How Do AI Robot Building Inspections Work?

Scientists at Drexel University created a solution that uses a convolutional neural network to recognize structural damage in concrete. Upon seeing a crack, the machine vision system measures it with a laser scanner while using lidar to scan the surrounding area.

Using the lidar scan and 3D laser measurements, the robot then builds a digital twin of the damaged structure. This virtual replica makes it easier to assess the condition of the crack, including whether it’s cause for alarm yet or how it may worsen in the future. Building and architectural professionals can use such insights to inform their next steps.

Organizations may need to address the crack immediately to prevent larger failures. In cases with no immediate threat, they may re-scan the area over time to compare digital twins and track the damage’s growth. Whatever the case, the robotic solution provides a far better look at the structure than conventional means.

Benefits of AI Robot Inspections

Inspecting aging infrastructure with AI and robotics offers several advantages over manual alternatives. Such automation could improve safety, accuracy, labor availability and long-term strategies.

1. Increased Safety

The most obvious benefit of AI robot inspections is that they remove humans from hazards. Safety is a common upside to automation — humans cause most accidents, so minimizing the human element means fewer incidents. Errors aside, it’s harder for inspectors to get hurt when they do not need to enter tight spaces or approach hazardous structures.

Automated building checkups would also improve safety for the people who live or work inside. The Drexler experiment found that their AI robot outperformed even state-of-the-art manual methods. It could discover cracks humans may miss or offer a better understanding of the structure’s condition, letting stakeholders respond appropriately before a larger accident occurs.

In practice, such a solution wouldn’t replace humans entirely. Rather, it would inform expert opinions. Even so, the extra data and insights enable earlier, safer choices.

2. Improved Accuracy

Measurements from AI-driven inspections are often more precise than conventional ones. That applies to both initial crack recognition and the following detailed modeling of the damaged structure.

The machine vision system is detailed enough to detect cracks a hundredth of a millimeter wide better than fiber-optic sensors and leading cameras. Such early detection buys professionals more time to determine how to respond to the scenario. Stakeholders may be unable to make a thoughtful decision when they must fix the situation immediately.

Digital twins of the concrete offer even greater assurance and insight. Inspectors can simulate various scenarios to see how the cracked structure would hold up to expected stresses, taking the guesswork out of performance predictions.

3. Mitigated Labor Constraints

In addition to being more accurate and safe than manual alternatives, AI robots could help the industry overcome labor challenges. Like many blue-collar industries, construction and building inspectors are struggling with a declining workforce. Automation could fill the gap.

The U.S. Bureau of Labor Statistics predicts there will be 15,000 open inspector positions each year through 2033 despite minimal industry growth. At the same time, the need for checking on the nation’s aging infrastructure won’t go away as workers retire. Automating much of the process would relieve the constraint by letting fewer people maintain the same productivity.

Human experts are still necessary to make the final call. However, robots could handle almost all of the time-consuming fieldwork. As technology advances and these systems become increasingly common and accessible, the industry could complete even more inspections with a diminished workforce.

4. Predictive Insights

AI robots provide an additional layer to the building checkup process. The digital twins they create offer deeper insight into where issues originate and how they progress. This data provides an ideal foundation for predictive analytics to reveal which fixes may yield better performance in future architectural projects.

Major improvements in construction can come from seemingly small adjustments. For example, concrete vibrating takes just five to 15 seconds but can increase compressive strength to prevent early cracking. An analysis of digital twins of several damaged supports could reveal if teams need to optimize their vibration workflows to ensure resilient infrastructure in the future.

As teams use these tools more frequently, they will compile larger sample sizes for predictive analytics engines to analyze. The resulting insights will become increasingly detailed and reliable over time.

5. Remaining Concerns Over Robotic Inspections

While Drexler’s AI-powered robot shows significant promise, it’s still an imperfect solution. Deploying an advanced system may require technical skills and expertise many organizations lack. The U.S. needs roughly one million additional STEM workers in the next decade to remain a tech leader, and that gap may hinder the adoption of inspection robotics.

Overconfidence in technology is another concern. Even though AI is more reliable than alternative measurements, errors are still possible. However, professionals may become complacent and take data at face value, leading to larger mistakes they would have caught if they had applied more scrutiny.

Given the severity of infrastructure collapses, regulations will need to evolve, too. Government regulators must update their standards to ensure the safe usage of robotic inspections. Better oversight will empower organizations to use AI confidently for high-value projects. 

These challenges may cause concern for some businesses, but none of them are impossible obstacles. Many will fade over time with additional technological advancements and the development of relevant best practices. This field is still new, so some hiccups are inevitable along the way.

Robots and AI Could Make Buildings Safer

The nation needs better building inspections as its infrastructure ages. Robotics and AI could be the optimal vehicle for a safer future. While the technology may not be ready for large-scale implementation yet, it’s promising.

Early studies show how AI-powered robots can address many of the challenges currently facing building inspections. Further development in this area could pave the way for substantial improvements within the industry.