The power of Tensorflight’s AI and machine learning algorithm makes it simple to evaluate any building in the world.
But what about buildings that aren’t really part of this world?
To show the effectiveness of our product, we decided to analyze Barcliff Building A of Emory University, better known as the Hawkins National Laboratory, a real, yet fictional place from the Netflix show Stranger Things.
The building has been the filming location for many feature films over the years, owing to it’s intimidating presence and unique use of materials. Is such a unique design difficult for Tensorflight to analyze?
Not at all.
All that was needed was an address to gather hundreds of data points on the building in mere seconds. All this information was captured remotely, without having to have anything or anyone in the vicinity of the building.
Hawkins National Laboratory Data & Valuation
Here’s some of the data that Tensorflight pulled from the building:
Number of stories: 5 (+basement)
Footprint area (ft^2): 55018
Estimated floor area (ft^2): 174543
Building occupancy type: Hospital
Occupancy types: Health Care Services
RMS occupancy type: 8000
Construction type: Reinforced concrete
RMS construction type: 3A
Year built: 1965
Roof pitch: Flat
Roof geometry: Flat
Roof material: Bituminous waterproofing
Facade material: Concrete
Roof condition: Fair
Has basement: Yes
Quality of finishes: Medium
Number of trees within 25 meters from the building: 22
Flood zone: X
Distance to coast [mi]: 223.0
Estimated building replacement cost: $82,357,000
Within the Tensorflight suite, a detailed image is shown, with a breakdown of areas, materials and construction types. The suite also presents the age of the building, construction types and occupancy types.
The information generated by Tensorflight is then used by insurers, underwriters and other analysts to create more accurate and relevant insurance policies with real risk factors taken into account.
The Hawkins Laboratory, while looking ominous and foreboding, is easily analyzed by our tool. If you’d like to put Tensorflight to work for any other address, reach out to us and see how we can make this technology work for you.