Digital Twins Tech | Reinvents Dike Safety

Digital twin based monitoring turns traditional dikes into intelligent, self-reporting flood guardians — boosting infrastructure resilience!

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Published July 24, 2025 By EngiSphere Research Editors

In Brief

A recent research presents a digital-twin-based structural health monitoring system for dikes that integrates real-time sensor data into a 3D BIM environment to enable predictive maintenance and enhance flood protection resilience.


In Depth

Smart Dikes Are Here!

Imagine a world where dikes — those long mounds of earth protecting cities from floods — could talk. What if they could sense danger, predict problems, and call for help before anything breaks? That’s no longer science fiction. Thanks to digital twins and smart sensors, we’re building flood barriers that can think. New research brings structural health monitoring (SHM) of dikes into the digital age!

Why Do We Need Smarter Dikes?

Traditional flood protection dikes are built to last decades, but they face a silent enemy: invisible internal damage. Cracks, seepage, and shifting materials don’t always show up until it’s too late.

Currently, most dike maintenance relies on:

  • Periodic manual inspections
  • Visual checks for visible damage
  • Reactive repairs after something has already gone wrong

That’s risky business, especially in the face of climate change, rising sea levels, and more intense storms. We need a better way — enter the Digital Twin.

What Is a Digital Twin (DT)?

It's a virtual replica of a real-world object — in this case, a dike — that evolves in real time using live data. It’s more than just a 3D model. It:

  • Mirrors the real dike’s geometry and materials
  • Updates continuously with sensor data
  • Predicts future damage using simulations
  • Helps engineers make faster, better decisions

So think of it as the dike’s smart, digital self.

The Research: Building a Digital Twin of a Dike

The research team designed a full Digital Twin-Based Structural Health Monitoring (SHM) system using a real lab-built dike. Here’s how they did it:

Step 1: Build the Dike
  • Constructed in a controlled lab environment at RWTH Aachen University, Germany
  • Integrated 9 pressure sensors to measure water levels inside the dike
  • Included realistic materials: sand core, filter layers, geotextiles, and a seal
Step 2: Create the Digital Twin

Using BIM (Building Information Modeling) tools, they created a detailed 3D model of the dike. The model:

  • Includes every layer, material, and sensor location
  • Uses IFC 4.1, a standard format to ensure compatibility with other tools
  • Can be enriched with external data like satellite images or inspection records
Step 3: Connect the Real Dike to Its Digital Twin

Here’s where it gets exciting:

  • Sensor data is sent to an online server using OGC SensorThings API (a universal language for IoT devices)
  • The digital twin software (DESITE md) fetches this data every few minutes
  • Engineers can view live seepage levels, trends, and even set up warning systems

All communication follows international IoT standards, making it scalable and future-proof.

Real-Time Insights = Predictive Power

What makes this system truly valuable is real-time monitoring and contextualization. For example:

  • Sensor U6 shows rising pressure? The twin highlights the exact spot in the model
  • Historical data shows increasing seepage trend? Engineers get an early warning before cracks appear
  • A predefined threshold is exceeded? The system flags it with a red alert

This is predictive maintenance in action — fixing issues before they escalate.

Validation: Does It Work?

Yes, and impressively so.

  • The system handled live data from multiple sensors without performance lags.
  • Engineers could access detailed measurements on-demand or set automated refresh intervals.
  • Visual dashboards showed sensor data over time, helping spot anomalies instantly.
  • Linking real sensors to virtual dike elements enabled location-based analysis — a major upgrade over generic reports!
Future Prospects: What’s Next?

This digital twin system is just the beginning. The potential is massive:

Real-World Deployment

The concept needs to scale from lab dikes to real ones by rivers and coasts. Pilot projects could:

  • Combine smart geotextiles with digital twins
  • Include satellite and drone data for visual inspection
  • Integrate with early warning systems for flood response
AI + Big Data

As more data flows in, AI could:

  • Spot failure patterns across multiple dikes
  • Predict collapse scenarios based on environmental conditions
  • Optimize inspection schedules and resource allocation
Interconnected Infrastructure

Imagine a network of digital twins — not just dikes, but:

  • Bridges
  • Water treatment plants
  • Pump stations

All talking to each other, sharing risks, and responding as one. That’s the smart city of the future!

Key Takeaways
  • Traditional inspections alone can’t catch hidden dike problems
  • Digital twins provide live, localized, and predictive insights
  • The system is built with international standards and real-world tools
  • It’s flexible, scalable, and ready for real-world rollout
  • With more data and smarter tech, we’re looking at a future of resilient infrastructure
Final Thoughts: A Smarter Defense Against Rising Waters

Floods are becoming more frequent and intense. But with digital twins, we can move from reacting to predicting. Dikes can become smart, self-aware guardians that warn us before things go wrong.

This research is a huge step in that direction — combining engineering wisdom with digital innovation. Engineers, policymakers, and technologists must now work together to make digital twin powered infrastructure the new normal.


In Terms

Digital Twin - A digital twin is a virtual, real-time copy of a physical structure (like a dike), constantly updated with live data to monitor and predict how it's doing — think of it as a "smart clone" that helps engineers keep an eye on the real thing. - More about this concept in the article "Building Trust in Smart Factories | How Engineers Are Embedding Ethics into AI".

Dike - A dike is a long wall or embankment made of earth or other materials, built to hold back water and prevent flooding in low-lying areas — it’s like a giant barrier between land and water.

Structural Health Monitoring (SHM) - SHM is the use of sensors and data to constantly check the condition of a structure, like a dike or a bridge, helping detect damage or wear before it becomes a serious problem — basically a 24/7 health check-up for infrastructure. - More about this concept in the article "Cracking the Code of Skyscraper Safety | How AI Is Revolutionizing Structural Damage Detection!".

Sensor Network - A sensor network is a group of small electronic devices that gather real-time information (like water pressure or movement) from a structure and send it to computers for analysis.

Building Information Modeling (BIM) - BIM is a smart 3D model of a structure (like a dike) that holds not just the shape but also info about materials, sensors, and history — it’s a digital blueprint with brains! - More about this concept in the article "Building a Greener Future: Exploring the Driving Forces Behind China's Low-Carbon Construction Revolution".

IoT (Internet of Things) - IoT is a system where physical devices like sensors are connected to the internet, letting them send data and talk to software — it’s what makes a dike “smart.” - More about this concept in the article "From Farm to Future | How a New Tool is Transforming Sensor Data Fusion in Agriculture and Animal Welfare".

Seepage Level - The seepage level is the amount of water that moves through or under a dike, which can be dangerous if it gets too high — monitoring this helps predict possible leaks or failures.

Predictive Maintenance - Predictive maintenance means fixing problems before they happen, using data and trends — much smarter (and cheaper) than waiting for things to break! - More about this concept in the article "Agentic AI in Industry 5.0 | How Talking to Your Factory Is Becoming the New Normal".

OGC SensorThings API - A standard language that lets sensors and software talk to each other easily — it ensures that all data can be shared and understood, no matter who made the devices.


Source

Bornholdt, M.; Herbrand, M.; Smarsly, K.; Zehetmaier, G. Digital-Twin-Based Structural Health Monitoring of Dikes. CivilEng 2025, 6, 39. https://doi.org/10.3390/civileng6030039

From: WTM Engineers GmbH; Hamburg University of Technology.

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