Correcting the Course of Failed Climate-conscious Planning with AI

Climate-conscious construction starts before construction begins. AI-driven underground exploration that provides more accurate underground maps de-risks the discovery process and ensures safer, more sustainable builds that reduce a project’s environmental footprint, states Jeremy Suard, co-founder and CEO of Exodigo.

Climate-conscious construction is a hot topic, but there is often a fixation on embodied carbon, materials offering low-carbon alternatives and recycled construction. However, the where, what, and how of a build are only part of the equation. The steps taken before a build – the early planning, or discovery, stages – need to be considered when advocating for more sustainable construction initiatives.  

While exorbitant sums of money will be invested in overhauling aging infrastructure and new builds in the years to come, innovation in artificial intelligence (AI), robotics and automation will dramatically enhance planning quality–reducing faults, leaks, and potentially catastrophic accidents in new construction efforts. The first step of climate-conscious construction that needs to be addressed is fully understanding what lies beneath any build site. 

What Lies Beneath: When Dangers Go Undiscovered 

Sustainable, safer building practices can no longer afford to ignore the critical first step – knowing exactly what lies beneath the surface at a build site before construction ever begins. Inaccurate, incomplete underground maps create tremendous risks for infrastructure projects. From immediate dangers like electric lines and natural gas pipes to abandoned lines and ground layers, the inability to “see” underground is a problem affecting countless industries, including construction, utilities, transportation and mining. 

The need for precise knowledge of subterranean assets is well-documented, but traditional methods of underground exploration and utility mapping rely on incomplete, inaccurate data. At best, relying on a partial picture of buried material causes schedule delays and skyrocketing costs from unforeseen utility strikes and leaks; at worst, it leads to devastating environmental damage, detrimental explosions and loss of lives. While there have been other AI breakthroughs in Image Processing and high-quality time series (like text-to-speech), no one has been able to crack the code to effectively leverage AI for low-SNR signals in noisy environments. While most would think the underground might be quiet, it is the noisiest, and therefore one of the most complicated, frontiers for imaging. All signals that are affected by the underground suffer from a major dynamic range, highly noisy environments and completely different normalizations. 

Traditional underground discovery techniques are costly, cumbersome and insufficient for today’s underground mapping needs. Conventional solutions can only find, let alone accurately map, approximately 85% of potential risks, like buried utility lines underground. A 15% window of inaccuracy leads to an unclear picture of what lies beneath, and as a result, unnecessary excavation and drilling (to the tune of $100B) are performed each year. This spend doesn’t avoid all of the avoidable, either: cut lines, spills, explosions and other accidents still occur, and the equipment used to perform this exploration leads to unnecessary greenhouse gas emissions. The best way to rectify this is using a crystal clear, all-encompassing map at the onset of projects.

Can you imagine using a printed MapQuest map today to navigate your driving route? In a Waze-powered world, you wouldn’t. Technology now exists to help map the best driving route based on real-time traffic conditions, the location of police, roadwork, detours and more. Not only does MapQuest not recalculate when you’ve gone off course, but it also doesn’t tell you what is presently on the road – the most important thing you need to know before driving. The same is true before planning a build, picking up a shovel or rolling in the heavy construction machinery—knowing what potential pitfalls for your planned “route” are currently below the surface is critical. Non-intrusive, multi-sensing underground mapping platforms bring the power of Waze to the underground and should become the go-to solution to de-risk the underground discovery process. 

See More: Is Responsible AI a Technology Issue or a Business Issue?

De-Risking the Discovery Process: Creating Safer and More Sustainable Builds

Safety risks, project delays, ballooning budgets and excessive environmental damage go hand in hand. Infrastructure projects are notorious for running years behind schedule and millions, if not billions, of dollars over budget. Recent research found that the average delay caused by a widespread event would put a project 20-30% over budget. The transit industry serves as a prime example – Honolulu’s rail project (11 years delayed, $7.3 billions over budget), Maryland’s Purple Line (4.5 years delayed, $1.4 billion over budget), and San Francisco’s Van Ness Bus Rapid Transit (delivered three years behind schedule and $37 million over budget) are just a few examples of how expensive overruns can become. Every moment that a project continues, the higher its carbon footprint is. In these cases and many others, unexpected utilities are a common thread for derailing transit projects.

An accurate, precise understanding of subsurface hazards and buried assets accelerates project delivery – saving time and money and dramatically reducing the carbon footprint of construction. Starting large capital projects with the best underground data from the start delivers unprecedented sustainability benefits. Imagine finishing a project 10%, 25%, 50% more quickly – and reducing greenhouse gas emissions of construction proportionately as well. AI-driven underground exploration delivers a new way to derisk the discovery process, ensuring safer, more sustainable builds. Philippe Schwartz, managing partner at SquarePeg, said it well, “Opening up visibility to what’s underground is a new superpower that will help organizations save billions, while also significantly reducing environmental damage.” 

When you dig only where it’s safe and only when needed, when you avoid cascading redesigns from unexpected hazards that delay construction – you cut the length of the project, and the environmental impact rapidly adds up. And new technology enables non-intrusive subsurface discovery to maximize accuracy and precision and minimize disruptions on the ground. 

Like the combined power of integrating MRI, CT scan, and ultrasound technology, 

AI-powered subsurface imaging technology creates a “master map” that allows an entire organization to work off of a centralized data source – identifying  more buried assets than previous surveying methods. As one example, Exodigo can find 20-50% more utilities than alternatives, according to analysis from the Common Ground Alliance (CGA) Technology Advancements and Gaps in Underground Safety 2022 report. Successfully combining all those signals into one single matrix has never been done before, but that is exactly what the Exodigo team is doing. 

A Spotlight on Real-World Results: Eliminating Industry Risks and Costs 

AI has the power to dramatically improve the planning and execution of infrastructure and construction projects. Leaders across the transportation, utility, and construction industries are already realizing the benefits of AI-driven underground exploration. 

To provide one quick success story of the power of this technology: a project for utility infrastructure engineering and construction company, Charge, helped identify 3x more underground lines than its standard toolset, therefore avoiding future hits on the project and helped reduce their potholing costs by 30%. Erich Metzger, Sr. Director, Strategic Development shared that this eliminated a lot of the risks that the construction industry considers “norms” on job sites as Exodigo’s underground maps provided a level of precision above and beyond traditional scans.

Looking at a partial or outdated picture can lead to catastrophic results in the infrastructure and construction world. Using technology to create a “single source of truth,” is the way forward. With advanced, AI-powered underground mapping, you can ensure that investments of time, money, labor, and equipment are made as efficiently, safely and sustainably as possible. 

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