Smart Highways Begin with Smart Data: How U.S. and Canadian DOTs Can Transform Geotechnical Reports

The Challenge of Legacy Geotechnical Reports

Highways across the United States and Canada depend on thousands of geotechnical investigations, from borehole logs to CPTs and lab tests. Departments of Transportation (DOTs) manage this critical information, yet most of it still sits locked in PDF archives, Excel sheets, and consultant reports. The result is a wealth of knowledge that is difficult to access, compare, or re-use across projects, creating inefficiencies, repeated investigations, and limiting the ability to build cumulative expertise over time. DAARWIN doesn’t replace these archives — it transforms them into a decision-ready database, unlocking their value for both day-to-day projects and long-term asset management.

From PDFs to Structured Ground Models

With DAARWIN’s digitization engine, boreholes, CPTs, and lab reports are converted from PDFs and Excels into digital formats at ~96% accuracy, automatically extracting soil parameters such as friction angle, cohesion, unit weight, and modulus. What once took weeks of re-typing can now be achieved in hours, allowing engineers to focus on interpretation rather than manual entry. Here you can see how the digitalization process works in practice. Once digitized, the records are stored in a centralized geotechnical database, which ensures consistency across contractors and consultants, makes past investigations reusable for new projects, and allows comparable ground models to be built across entire regions.

Living Models Instead of Static Assumptions

DAARWIN goes further by connecting monitoring data such as settlement plates, piezometers, or inclinometers directly to design assumptions, running sensitivity and back-analysis to recalibrate soil parameters dynamically. This transforms static design checks into living models, where governing parameters are identified early, predictions are updated as new data arrives, and deviations are caught before they escalate into risks. With the addition of machine learning, the platform also learns from historical datasets. For example, DAARWIN’s algorithms can learn from past embankment settlement data in Gulf Coast clays to forecast time-to-stabilization more accurately than conventional methods, giving DOTs more confidence in preload durations and construction schedules.

A Model for Centralized Ground Information

An additional strength of DAARWIN is its Public Ground Information Platform (GRIS), where thousands of borehole and investigation points are available in regions such as Nebraska, Chicago, Washington, New York, California, Vancouver, and Toronto. . For DOTs, the relevance of GRIS is not in accessing external points, but in seeing the value of centralization. Just as GRIS demonstrates how scattered public datasets can be structured and shared, the same approach can be applied internally, transforming decades of state-level archives into a unified and searchable resource. This model gives DOTs the ability to consolidate their own records, import consultant data into one format, and ensure that every future project begins with a robust, cumulative ground model rather than isolated reports.

The Impact for DOTs in the U.S. and Canada

The impact of adopting DAARWIN goes beyond efficiency — it addresses the very challenges that DOTs struggle with every day. Budgets are drained by repeated site investigations because legacy data is inaccessible or unusable; with DAARWIN, archives are digitized and standardized, cutting millions in unnecessary fieldwork. Design cycles are slowed by manual re-typing of logs and lab sheets, while DAARWIN automates this process, delivering structured datasets in hours instead of weeks. Safety risks often emerge when field monitoring diverges from design assumptions without being detected in time; DAARWIN links monitoring directly to the ground model, running back-analysis and sensitivity checks to flag risks before they escalate. And as DOTs move toward digital twin initiatives, the absence of a reliable geotechnical layer is a critical gap — one that DAARWIN fills by providing continuously updated, decision-ready ground models.

And as DOTs move toward digital twin initiatives, the absence of a reliable geotechnical layer is a critical gap, one that DAARWIN fills by providing continuously updated, decision-ready ground models. This has clear regional relevance:

• In the Gulf Coast (Texas, Louisiana), where soft clays challenge highway embankments, DAARWIN accelerates preload and wick drain assessments.

• In the Midwest and Canada, where glacial tills dominate, DAARWIN helps recalibrate stiffness assumptions in deep foundation design.

• In urban centers like New York, Toronto, and Vancouver, where reclaimed soils and fills complicate excavation and tunneling, DAARWIN ensures monitoring data is continuously linked back to design.

For DOTs in the U.S. and Canada, this means shifting from reactive firefighting, dealing with overruns, redesigns, and unexpected ground behavior, to proactive infrastructure management, where every decision is backed by structured data, predictive analysis, and a single source of truth.

Smart Highways

Smart highways cannot be built on inaccessible or fragmented records. By adopting DAARWIN, DOTs can transform decades of geotechnical data into a decision-ready resource, enriched by both their own datasets and a model inspired by centralized platforms such as GRIS. The road ahead is digital, and in geotechnics, it begins with DAARWIN.

Discover how DOT’s legacy records can be digitalized with DAARWIN’s Digitalization Engine and see how a centralized approach, like GRIS Public Ground Information Platform, can be applied to your own archives.