An Israeli startup that uses machine learning to predict and prevent accidents in construction sites has raised $8 million.
SafeGuard has developed algorithms that identify human error patterns, predict the probability of an accident occurring, and take preventative measures.
It can, for example, identify a worker in real time who is on the verge of making a mistake, and prevent an accident by locking them out of a hazardous area.
It collects data simultaneously from cameras, sensors, drones, and statistical analysis to automate decision-making.
Nearly all construction accidents (90 percent) take place because of human error. In the US alone, three workers die in the construction industry every day, and a worker is injured every three minutes.
“Construction shouldn’t be the most dangerous job 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.”
SafeGuard claims it has saved over 2,745 lives since its launch in 2016, and says its technology reduces accidents in industries like construction, ports, and more.
The investment was raised by hi-tech investors Ron Zuckerman and Hillel Kobrinsky, as well as other real estate investors.
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