Prototyping Structural Health Monitoring with Arduino UNO

Prototyping SHM with Arduino

A while ago, we needed to quickly validate a structural health monitoring (SHM) concept for a client. Instead of jumping straight to industrial hardware, we started with Tier 1 IoT components - specifically, an Arduino UNO R4. As discussed in our earlier blog “Four Tiers of IoT Hardware: What to Choose and When,” the classic Arduino is a timeless entry point for sensor-based IoT projects. Using just an Arduino UNO R4, a strain gauge sensor and, a MEMS accelerometer mounted on a 3D-printed factory model, we measured beam bending and vibrations in real time. This let us demo the SHM concept quickly and affordably, showcasing Arduino’s accessibility and rapid iteration cycle - the very strengths that make it ideal for Tier-1 prototyping

Why Arduino for SHM?

The Arduino UNO (now in its R4 version) is a perfect Tier-1 prototyping platform. Its ease of use (friendly IDE, huge library ecosystem, and plug-and-play sensor libraries) lets engineers get code running in minutes. The new Arduino UNO R4 is a leap forward - it uses a 32-bit Renesas RA4M1 ARM Cortex M4 processor with much more speed, memory, and peripherals than older UNOs. Yet it retains the classic UNO layout (5V logic, shield headers, USB-C, etc.). The UNO R4 combines familiarity with performance.

• Entry-level friendly: An Arduino board doesn’t require custom PCB design or complex toolchains. Anyone on the team (even non-hardware specialists) can wire up a sensor and write a quick sketch. The Arduino UNO is “a timeless entry point for hardware projects”.

• Affordable & supported: UNO boards are cheap (~$20-$30) and have a vast maker community. There’s always example code or tutorials for any sensor. This low barrier means we could commit time to the SHM concept, not spend weeks sourcing parts.

• Rapid iteration: Arduino’s simplicity enabled fast testing cycles. We could upload new firmware over USB in seconds, adjust parameters on the fly, or swap out sensors with zero friction. That agility was essential as we refined sensor placements and behavior on the 3D-printed model.

In short, choosing an Arduino UNO R4 (a Tier-1 device) let us focus on the SHM problem itself. We avoided the upfront cost and complexity of higher-end boards, while still getting a powerful microcontroller for quick code iterations.

The Prototype Setup

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We built a minimal hardware stack on a small-scale model. Key components included:

• Arduino UNO R4 board: The brain of the prototype. It read all sensors and ran the control sketch.

• Strain gauge: Glued onto a support beam to measure bending strain. In SHM, strain sensors monitor loads, compression, tension, bending, and torsion in a structure. Our tensiometer produced a small voltage proportional to beam deflection, which the UNO’s analog input captured.

• 3-axis accelerometer: A small breakout (e.g. a common MEMS accel) mounted on the model to detect vibrations.

• 3D-printed factory model: A simplified industrial structure with beams and supports. This provided a tangible testbed for applying loads or vibrations and seeing the prototype respond.

• Miscellaneous:  A universal double-sided board, to which we have soldered a small display, button, and LEDs.

We quickly wired the sensors to the UNO R4 (strain gauge analog output into an A/D pin, accelerometer via I²C pins) and uploaded a short Arduino sketch. The code simply sampled the sensor values and streamed them out over USB serial in real time. With this setup, we could physically press on the model or even shake it. The logic behind raw data was presented on a small display and various LEDs to indicate if the structure is in an alarming state. Within a few hours we had a working system that visibly demonstrated structural bending and vibration measurements.

What We Learned

Building this prototype taught us several key lessons:

• Fast proof-of-concept: Thanks to Arduino’s simplicity, the SHM demo came together in a matter of days, not weeks. We iterated on sensor placement and code parameters by just tweaking our sketch and rerunning. This “fast prototyping” workflow is exactly what Tier-1 platforms are for.

• Client clarity: The physical model plus live data made the concept concrete. Instead of abstract diagrams, the client could see the Arduino board and sensors on the model and watch real-time strain/vibration plots. This hands-on demo built immediate understanding and confidence. Often, clients understand a problem more quickly when they see actual numbers or a moving graph, rather than just a verbal pitch.

• Sensor performance: Both sensors behaved as expected. For example, when we applied a steady load to the beam, the tensiometer’s output (read by the UNO) shifted proportionally – exactly as strain gauges should. Likewise, gentle taps produced clear spikes in the accelerometer’s readings. Overall, the prototype sufficed to prove feasibility.

• Scope & limits: Of course, an Arduino-based prototype is not the final solution. Its ADC resolution and build quality have limits, and it wasn’t ruggedized. But by proving the core idea first, we saved resources.  

In summary, the Tier-1 Arduino prototype achieved its goal. It validated our SHM approach cheaply and swiftly, and provided concrete feedback that we couldn’t have gotten from slides alone. The experience confirmed a best practice: start with the simplest hardware that can possibly work, then scale up. If you're interested in reading about the other tiers, check out the comparison blog: Four Tiers of IoT Hardware: What to Choose and When.

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