Historic Preservation Leveraging Imaging Technology

Preservationist are combining lidar, thermal and infrared to most effectively archive the past.  Archivists will soon store reality models holding geometry, RGB, temperature and coordinate values to accurately summon previous lifecyle states.   LiDAR is most commonly used for historic renovations for virtual design and construction coordination.

History is lost each day due to war, theft, careless development and neglect.  Digitizing our past should be a priority in case we need it in the future.   Furthermore; unless our past and present is digitized, automated building practices and artificial intellegence type algorithms will not work. Billions of objects in cultural institutions worldwide remain undigitized. Of the estimated 130 million books published in modernity, Google has scanned only about 25 million.

Our focus is on automation and commercial application, where a ton of data has to be collected, archived and analyzed.  Architectural as-builts, industrial inspections, main street and mine scanning, bridge scanning, oil refineries, transmission towers, roofing – hard to reach areas, very difficult to reach.  The surveys conducted with stringline measurements and single beam leasers take longer and are less detailed than lidar, infrared and thermal cameras.

Preserving the Great Wall of China

Stretching over 20,000 kilometers, the Great Wall of China presents a challenge to architects and historians working on its preservation.  Certain areas are difficult to reach, and a manual examination of the Wall would be very tedious. Intel recently teamed up with the China Foundation for Cultural Heritage Conservation to use the latest drone technology to gather thousands of photos and then analyze the data with AI to pinpoint exact areas in the Wall that need restoration.

“With precise information about where repairs are needed and what is required, the work can be done much more quickly, efficiently and cost-effectively”, explains Alyson Griffin, Intel’s Vice President, global brand and thought leadership marketing.

“Computers are not good at open-ended creative solutions; that’s still reserved for humans. But through automation, we’re able to save time doing repetitive tasks, and we can reinvest that time in design,” says Mike Mendelson instructor and curriculum designer at the Nvidia Deep Learning Institute.