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Using AI to manage project risk at scale

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What Vinnie “Sees”

Vinnie has been trained to find--and count--a number of indicators of project risk in the areas of safety, productivity and quality. Here are examples of what Vinnie can see in each of these areas:

Safety
  • Leading indicators of risk like presence of slip, trip and fall hazards like standing water, housekeeping and ladders (by specific type)
  • Personal protective equipment compliance detection and measurement for equipment like gloves, hard hats, glasses and high vis clothing
Productivity
  • Site activity metrics like how many workers are seen by time, including arrival and departure times
  • Phase of construction can also be identified, including excavation, foundations, structural steel, finishes/fitout and more
Quality
  • Specific types of defects like cracks in tunnel walls can be detected and quantified automatically

Why the Name Vinnie?

The name Vinnie originated from the CIO of a large contractor in the New York City area. At one time he was explaining how they had recently “found” some photo and video content that was critical to a claim. When asked how they knew where to find that content, he matter-of-factly replied, “Vinnie remembered.” Vinnie, in this case, was a superintendent located in New Jersey who had a great memory for where specific site imagery was stored. So we’ve built construction-tuned AI into our product so that now every company can have a “Vinnie”. In addition to knowing where to find your photos and videos, he is always looking for, finding and creating indicators of project risk. Read more about Vinnie’s background.

Privacy First

Vinnie is sensitive to the privacy of the workers seen in images he analyzes.  No workers are attempted to be identified (there is no facial recognition and never will be) and all data is governed by our privacy policy.  As evidence of our commitment to privacy, Vinnie has been certified to be compliant with the strict privacy requirements specified by the European GDPR standard as a part of our compliance with the Privacy Shield standard. 

“Smartvid.io complemented our human-based observations with a third-party AI perspective. Both are necessary for understanding risk and deciding where to focus our attention. For example, when Vinnie found a high rate of housekeeping issues on an otherwise well performing project, we immediately reviewed examples and found the project had begun demolition, creating piles of debris and standing water. We provided additional resources to the site, including a tool box talk, as the project had now entered this higher risk phase. Without Vinnie, we never would have known to give the project some added support.”

- Shaun Carvalho, Vice President of Safety, Shawmut