Field measurement of structural displacement and inclination is hindered by drift in double integration, stringent filtering needs, and the limited compute/bandwidth of low-cost microcontrollers. This work presents node based on an ADXL345 tri-axial accelerometer with on-board processing that estimates dynamic tilt and symmetry in real time without double integration. Three real-time filters, Butterworth IIR (BWF), finite impulse response (FIR), and moving average (MAF, uniform-tap FIR), were implemented on the device and benchmarked against an offline Savitzky–Golay reference. A rigid-body rotation model links off-centre acceleration to inclination and defines a dimensionless rotation index for symmetry assessment. Calibration against analytical motion identified a linear-phase FIR as optimal, yielding the lowest RMSE over 0.5–8 Hz while preserving waveform shape. Computational profiling on an 11.0592 MHz microcontroller measured average per-sample execution of 2.5 µs (MAF), 6 µs (FIR), and 12 µs (BWF), enabling 800 Hz local sampling with ≥ 100 Hz wireless streaming and an 8 × reduction via on-device decimation (no compression). Under cyclic tension, lateral acceleration quantified asymmetry: non-cracked and two-sided-cracked specimens showed comparable lateral levels, whereas one-sided-cracked specimens exhibited markedly higher values consistent with crack-induced rotation. Vertical acceleration agreed with acceleration reconstructed from displacement, with peak deviations of ∼ 9–14%; accuracy decreased at the lowest acceleration levels, consistent with stronger low-frequency spectral content. Tilt from acceleration tracked displacement-based tilt with minor underestimation at the smallest amplitudes. Overall, the node delivers embedded, phase-faithful filtering and tilt/symmetry estimation with quantified computational cost, making acceleration-based monitoring practical on resource-constrained hardware while avoiding big-data burdens.

Field measurement of structural displacement and inclination is hindered by drift in double integration, stringent filtering needs, and the limited compute/bandwidth of low-cost microcontrollers. This work presents node based on an ADXL345 tri-axial accelerometer with on-board processing that estimates dynamic tilt and symmetry in real time without double integration. Three real-time filters, Butterworth IIR (BWF), finite impulse response (FIR), and moving average (MAF, uniform-tap FIR), were implemented on the device and benchmarked against an offline Savitzky–Golay reference. A rigid-body rotation model links off-centre acceleration to inclination and defines a dimensionless rotation index for symmetry assessment. Calibration against analytical motion identified a linear-phase FIR as optimal, yielding the lowest RMSE over 0.5–8 Hz while preserving waveform shape. Computational profiling on an 11.0592 MHz microcontroller measured average per-sample execution of 2.5 µs (MAF), 6 µs (FIR), and 12 µs (BWF), enabling 800 Hz local sampling with ≥ 100 Hz wireless streaming and an 8 × reduction via on-device decimation (no compression). Under cyclic tension, lateral acceleration quantified asymmetry: non-cracked and two-sided-cracked specimens showed comparable lateral levels, whereas one-sided-cracked specimens exhibited markedly higher values consistent with crack-induced rotation. Vertical acceleration agreed with acceleration reconstructed from displacement, with peak deviations of ∼ 9–14%; accuracy decreased at the lowest acceleration levels, consistent with stronger low-frequency spectral content. Tilt from acceleration tracked displacement-based tilt with minor underestimation at the smallest amplitudes. Overall, the node delivers embedded, phase-faithful filtering and tilt/symmetry estimation with quantified computational cost, making acceleration-based monitoring practical on resource-constrained hardware while avoiding big-data burdens.

Engineering structures, such as bridges, wind turbines, airplanes, ships, buildings, and offshore platforms, often experience uncertain dynamic loadings due to environmental factors and operational conditions. The lack of knowledge about the load spectrum for these structures poses challenges in terms of design and can lead to either over-engineering or catastrophic failure. This research introduces a robust and innovative device, analogous to a "Fitbit" for structures, capable of measuring complex loading conditions throughout the structure's lifespan. The proposed approach involves developing a middleware, referred to as an "extension," which facilitates the transfer of mechanical deformation to a piezoelectric sensor. This approach overcomes challenges associated with directly attaching piezoelectric sensors to the structure's surface such as rupture possibility in higher strain and attaching on rough surfaces. The feasibility study primarily focuses on validating the performance of the extension and monitoring variation trends. The ultimate objective is to develop an Internet of Things (IoT) sensor node capable of measuring applied cyclic loads. To achieve this goal, an electronic system and embedded software will be developed to capture the complex load spectrum and convert it into a fatigue damage index for predicting the structure's fatigue life. The collected data will be transmitted to the user through a wireless communication platform. The proposed sensor design is versatile, allowing for both attachment and embedding and is demonstrated here for monitoring fatigue in engineering structures.

Fatigue Life Monitoring is crucial to ensuring the safety and durability of engineering structures. This paper presents an innovative approach for fatigue life monitoring using a PZT (Lead Zirconate Titanate) piezoelectric sensor operating in buckling mode to measure applied cyclic strains. A significant focus is placed on the utilization of a 3D-printed 'Extension' platform upon which the PZT sensor is installed, allowing it to operate in buckling mode while subjected to cyclic strains. An analytical framework is developed to establish a direct relationship between dynamic strain values and the sensor's output, considering critical strain attributes such as amplitude and strain rate. The analytical solutions are validated through a series of experimental tests conducted under various dynamic loading conditions. Integrating the piezoelectric sensor with the 3D-printed extension demonstrates high sensitivity and serves as a passive dynamic strain measurement sensor, with promising potential for application as sensor nodes in fatigue life monitoring of engineering structures.

The high deformation capacity of auxetic cementitious cellular composites (ACCCs) makes them promising for strain-based energy harvesting applications in infrastructure. In this study, a novel piezoelectric energy harvester (PEH) with ACCCs and surface-mounted PVDF film based on strain-induced piezoelectric mechanisms has been designed, fabricated, and experimentally tested. Furthermore, a numerical model for simulating the energy harvesting of ACCC-PVDF system undergoing repeated mechanical loading has been established and validated against the experimental data. The mechanical behavior of ACCCs was simulated by the concrete damage plasticity model during the preloading stage, which was converted to the second-elasticity model during cyclic loading stage. Based on the mechanical responses, analytical formulas for piezoelectric effects were developed to calculate the output voltage of the PVDF film. The output voltages of the ACCCs-PVDF system under different loading amplitudes and loading frequencies were assessed. The experimental results and models of the ACCCs-PVDF energy harvester lay a solid foundation for utilizing architected cementitious composites in energy harvesting applications to supply self-power electronics in infrastructure.

The growing demand towards life cycle sustainability has created a tremendous interest in non-destructive evaluation (NDE) to minimize manufacturing defects and waste, and to improve maintenance and extend service life. Applications of Magnetic Sensors (MSs) in NDE of civil Construction Materials to detect damage and deficiencies have become of great interest in recent years. This is due to their low cost, non-contact data collection, and high sensitivity under the influence of external stimuli such as strain, temperature and humidity. There have been several advancements in MSs over the years for strain evaluation, corrosion monitoring, etc. based on the magnetic property changes. However, these MSs are at their nascent stages of development, and thus, there are several challenges that exist. This paper summarizes the recent advancements in MSs and their applications in civil engineering. Principle functions of different types of MSs are discussed, and their comparative characteristics are presented. The research challenges are highlighted and the main applications and advantages of different MSs are critically reviewed.

The growing demand towards life cycle sustainability has created a tremendous interest in non-destructive evaluation (NDE) to minimize manufacturing defects and waste, and to improve maintenance and extend service life. Applications of Magnetic Sensors (MSs) in NDE of civil engineering structures have become of great interest in recent years due to their non-contact data collection, and their high sensitivity under the influence of external stimuli such as strain, temperature, and humidity, to detect damage and deficiencies. There have been several advancements in MSs over the years for strain evaluation, corrosion monitoring, etc. based on the magnetic property changes. However, these MSs are at their nascent stages of development, and thus, there are several challenges that exist. This paper summarizes the recent advancements in MSs and their applications in civil engineering. Principle functions of different MSs are discussed, and their comparative characteristics are presented. The research challenges are highlighted and the roadmap towards high technology readiness level is discussed.