AI Tools Speed Construction, Enhance Safety

Robots won’t be building skyscrapers anytime soon, but developers increasingly are embracing artificial intelligence-driven tools to speed construction, cut costs and enhance safety at job sites.

Builders are deploying a legion of drones, cameras, mobile apps—and yes, some robots—to track and improve real-time performance on large construction sites.

Helmet-mounted cameras that capture footage of a site are being used to schedule new shifts or direct the shipment of materials, while precise sensors detect whether building components align with blueprints or need to be adjusted, according to a recent report in the New York Times.

The use of artificial intelligence algorithms to analyze construction data in real-time is being embraced by the construction industry to improve speed, accuracy and efficiency in construction projects, as well as safety.

Machine learning models that ingest huge amounts of data to discern patterns are being used to improve project performance, the report said.

Boston-based construction firm Suffolk has a team of 30 data analysts collecting and scrutinizing information from job sites. At a construction site for the South Station Tower in Boston, cranes have cameras that document and label steel being used on the building’s frame.

The need to reduce risk—and thereby reduce the cost of insurance, which can be as much as 10% for a single project—is driving use of AI-driven solutions for safety management on construction sites.

Hoboken, NJ-based Otoos offers a platform billed as an end-to-end solution for safety management. Otoos is a daughter company of Tel Aviv-based SafeGuard, which uses machine learning to predict and prevent accidents at construction sites.

The SafeGuard system collects data simultaneously from multiple sources such as cameras, sensors, drones, statistical analysis, open data and “big data” to automate on-site decision-making.

Algorithms are deployed to identify on-site “human error patterns,” using AI to predict the probability of an accident occurring. The predictive data is then converted into proactive measures that “enforce good decision-making beforehand.”

According to the company, SafeGuard machine learning capabilities can identify and stop a construction worker in real time on the verge of making a mistake and it can prevent an accident by locking the worker out of the hazardous area.

“Construction shouldn’t be the most dangerous in America. Unfortunately, our field is focused on digitizing compliance rather than innovating decision-support tools, but the reality is that compliance does not assure safety,” said Izhak Paz, CEO and founder of SafeGuard.

“Only an end-to-end solution that removes the human factor from the equation can prevent accidents and construction site shutdowns. The same is true for industries like manufacturing, maritime or agriculture that suffer from similar issues,” Paz said. 

The Otoos platform offers seamless integration with the Procore Sync and BIM 369 Sync platforms. Otoos also provides seamless integration with the NYC DOB SST program, allowing SSC cards to integrate automatically to the Otoos system.