By Daedalus Howell
PALO ALTO, Calif. 鈥� For some, the concept of autonomous devices (or, to invoke common parlance, 鈥渄rones鈥�) bring to mind footage of our kids鈥� quadcopter-cam barnstorming the family barbecue. Palo Alto-based Doxel, developers of an an artificial intelligence and computer vision-based system for large-scale commercial construction projects, wants you to consider autonomous devices in an entirely different听 light 鈥斕齛nd not squinting into the sun at a jobsite. Instead, they suggest you view them from the bottom line.
Doxel uses autonomous devices to visually monitor every inch of a project 鈥斕齦iterally, roving or flying around the physical space 鈥斕齮hen feeds this data to its proprietary deep-learning algorithms. The algorithms then inspect the quality of installed work and measure the work in real time, which enables project managers to immediately react to inefficiencies.
鈥淔or an industry that is notorious for cost overruns and delays, we see Doxel as the canary in the coalmine for construction projects,鈥� said Lars Dalgaard, general partner at Andreessen Horowitz, a venture capital firm that invests in cutting-edge technologies, including Doxel.
This could be good news to purveyors of large-scale construction projects such as university campuses. According to McKinsey & Company, a global management consulting firm, 98 percent of large-scale construction projects are delivered, on average, 80 percent over budget and 20 months behind schedule. The Construction Industry Institute echoes the observation citing that 10 percent of construction time is often spent fixing mistakes. Technologies like Doxel鈥檚 seek to head-off such overages.
鈥淵ou can鈥檛 improve what you can鈥檛 measure. Without real-time visibility into quality and progress, managers simply can鈥檛 boost productivity,鈥� said Doxel CEO and Co-Founder Saurabh Ladha.
The technology uses LIDAR (a surveying method by way of a pulsed laser that is named after a portmanteau of 鈥渓ight鈥� and 鈥渞adar鈥�) and high-definition (HD) cameras mounted to an autonomous device to inspect a construction site鈥檚 interiors and exteriors. A proprietary artificial intelligence algorithm then processes this visual data and can deduce whether the work is up to snuff.
鈥淐onstruction projects involve millions of similar-looking components, packed tightly together in a dark environment. It鈥檚 a Molotov cocktail of challenges for computer vision software,鈥� said Doxel鈥檚 CTO and Co-Founder Robin Singh.
To wit, advances in computer vision software allow the artificial intelligence engine to perceive the world not just in two dimensions (like a flat photograph) but in three dimensions (like the human eye). Thereafter, algorithms can recognize and contextualize objects not just based on color, but also based on their shape, location and size. This information is also processed by a cloud-based dashboard then provides project managers with real-time, granular feedback on productivity and how it compares to actual expenditures of time and money. Moreover, errors can be detected immediately.
The result is that project managers can get real-time data on earned value for hundreds of thousands of line items in a project budget whilst reacting to issues in minutes rather than months.