Measuring Tree Properties and Responses Using Low-Cost Accelerometers

Enhancing TreeMMoSys with a high-precision strain gauge to measure the wind-induced response of trees down to the ground

Measuring tree response to wind loads is fundamental for the process-based analysis of wind-tree interactions. Comprehensive knowledge of wind-tree interactions enables the further development of decision support tools available for estimating the probability of wind damage to trees. The assessment of critical wind loads that lead to damage is particularly important. This paper describes the inexpensive Tree Strain Sensor (TSS) suitable for precisely measuring the response of tree parts to external loads such as pulling tests and natural wind loading. It is an addition to the recently developed Tree Motion Monitoring System (TreeMMoSys) but can also be used as a standalone device, allowing measurements necessary to estimate effective wind loads on trees.

Toward a Unified TreeTalker Data Curation Process

The Internet of Things (IoT) development is revolutionizing environmental monitoring and research in macroecology. This technology allows for the deployment of sizeable diffuse sensing networks capable of continuous monitoring. Because of this property, the data collected from IoT networks can provide a testbed for scientific hypotheses across large spatial and temporal scales. Nevertheless, data curation is a necessary step to make large and heterogeneous datasets exploitable for synthesis analyses. This process includes data retrieval, quality assurance, standardized formatting, storage, and documentation. TreeTalkers are an excellent example of IoT applied to ecology. These are smart devices for synchronously measuring trees’ physiological and environmental parameters. A set of devices can be organized in a mesh and permit data collection from a single tree to plot or transect scale. The deployment of such devices over large-scale networks needs a standardized approach for data curation. For this reason, we developed a unified processing workflow according to the user manual. In this paper, we first introduce the concept of a unified TreeTalker data curation process. The idea was formalized into an R-package, and it is freely available as open software. Secondly, we present the different functions available in “ttalkR”, and, lastly, we illustrate the application with a demonstration dataset. With such a unified processing approach, we propose a necessary data curation step to establish a new environmental cyberinfrastructure and allow for synthesis activities across environmental monitoring networks. Our data curation concept is the first step for supporting the TreeTalker data life cycle by improving accessibility and thus creating unprecedented opportunities for TreeTalker-based macroecological analyses.

Self-Calibration Technique with Lightweight Algorithm for Thermal Drift Compensation in MEMS Accelerometers

Capacitive MEMS accelerometers have a high thermal sensitivity that drifts the output when subjected to changes in temperature. To improve their performance in applications with thermal variations, it is necessary to compensate for these effects. These drifts can be compensated using a lightweight algorithm by knowing the characteristic thermal parameters of the accelerometer (Temperature Drift of Bias and Temperature Drift of Scale Factor). These parameters vary in each accelerometer and axis, making an individual calibration necessary. In this work, a simple and fast calibration method that allows the characteristic parameters of the three axes to be obtained simultaneously through a single test is proposed. This method is based on the study of two specific orientations, each at two temperatures. By means of the suitable selection of the orientations and the temperature points, the data obtained can be extrapolated to the entire working range of the accelerometer. Only a mechanical anchor and a heat source are required to perform the calibration. This technique can be scaled to calibrate multiple accelerometers simultaneously. A lightweight algorithm is used to analyze the test data and obtain the compensation parameters. This algorithm stores only the most relevant data, reducing memory and computing power requirements. This allows it to be run in real time on a low-cost microcontroller during testing to obtain compensation parameters immediately. This method is aimed at mass factory calibration, where individual calibration with traditional methods may not be an adequate option. The proposed method has been compared with a traditional calibration using a six tests in orthogonal directions and a thermal chamber with a relative error difference of 0.3%.

The Tracking and Frequency Measurement of the Sway of Leafless Deciduous Trees by Adaptive Tracking Window Based on MOSSE

The tree sway frequency is an important part of the dynamic properties of trees. In order to obtain trees sway frequency in wind, a method of tracking and measuring the sway frequency of leafless deciduous trees by adaptive tracking window based on MOSSE was proposed. Firstly, an adaptive tracking window is constructed for the observed target. Secondly, the tracking method based on Minimum Output Sum Of Squared Error Filter (MOSSE) is used to track tree sway. Thirdly, Fast Fourier transform was used to analyze the horizontal sway velocity of the target area on the trees, and the sway frequency was determined. Finally, comparing the power spectral densities (PSDs) of the x axis acceleration measured by the accelerometer and PSDs of the x axis velocity measured by the video, the fundamental sway frequency measured by the accelerometer is equal to the fundamental sway frequency measured by video. The results show that the video-based method can be used successfully for measuring the sway frequency of leafless deciduous trees.

Lightweight Thermal Compensation Technique for MEMS Capacitive Accelerometer Oriented to Quasi-Static Measurements

The application of MEMS capacitive accelerometers is limited by its thermal dependence, and each accelerometer must be individually calibrated to improve its performance. In this work, a light calibration method based on theoretical studies is proposed to obtain two characteristic parameters of the sensor’s operation: the temperature drift of bias and the temperature drift of scale factor. This method requires less data to obtain the characteristic parameters, allowing a faster calibration. Furthermore, using an equation with fewer parameters reduces the computational cost of compensation. After studying six accelerometers, model LIS3DSH, their characteristic parameters are obtained in a temperature range between 15 °C and 55 °C. It is observed that the Temperature Drift of Bias (TDB) is the parameter with the greatest influence on thermal drift, reaching 1.3 mg/°C. The Temperature Drift of Scale Factor (TDSF) is always negative and ranges between 0 and −400 ppm/°C. With these parameters, the thermal drifts are compensated in tests with 20 °C of thermal variation. An average improvement of 47% was observed. In the axes where the thermal drift was greater than 1 mg/°C, the improvement was greater than 80%. Other sensor behaviors have also been analyzed, such as temporal drift (up to 1 mg/h for three hours) and self-heating (2–3 °C in the first hours with the corresponding drift). Thermal compensation has been found to reduce the effect of the latter in the first hours after power-up of the sensor by 43%.

Experimental and Numerical Study on Dynamics of Two Footbridges with Different Shapes of Girders

The paper presents the experimental and numerical results of the dynamic system identification and verification of the behavior of two footbridges in Poland. The experimental part of the study involved vibration testing under different scenarios of human-induced load, impulse load, and excitations induced by vibration exciter. Based on the results obtained, the identification of dynamic parameters of the footbridges was performed using the peak-picking method. With the impulse load applied to both structures, determination of their natural vibration frequencies was possible. Then, based on the design drawings, detailed finite element method (FEM) models were developed, and the numerical analyses were carried out. The comparison between experimental and numerical results obtained from the modal analysis showed a good agreement. The results also indicated that both structures under investigation have the first natural bending frequency of the deck in the range of human-induced excitation. Therefore, the risk of excessive structural vibrations caused by pedestrian loading was then analysed for both structures. The vibration comfort criteria for both footbridges were checked according to Sétra guidelines. In the case of the first footbridge, the results showed that the comfort criteria are fulfilled, regardless of the type of load. For the second footbridge, it was emphasized that the structure meets the assumptions of the guidelines for vibration severability in normal use; nevertheless, it is susceptible to excitations induced by synchronized users, even in the case of a small group of pedestrians.

A Low-Cost Chamber Prototype for Automatic Thermal Analysis of MEMS IMU Sensors in Tilt Measurements Perspective

In this work, a low-cost, open-source and replicable system prototype for thermal analysis of low-cost Micro Electro-Mechanical Systems (MEMS) Inertial Measurement Unit (IMU) sensors in tilt measurement perspective is presented and tested. The system is formed of a 3D printed frame, a thermal cell consisting in a Peltier element mounted over a heat sink, and a control and power system. The frame is designed to allow the independent biaxial tilting of the thermal cell through two servomotors. The control board is formed by an Arduino^® and a self-made board including a power drive for controlling the thermal unit and servomotors. We tested the chamber analyzing the behavior of multiple MEMS IMU onboard accelerometers suitable for measuring tilt. Our results underline the variability of the thermal behavior of the sensors, also for different sensor boards of the same model, and consequently the need for the adoption of a thermal compensation strategy based on thermal analysis results. These data suggesting the need for the analysis of the thermal behavior of MEMS-based sensors, indicate the potential of our system in making low-cost sensors suitable in medium-to-high precision monitoring applications.

An architectural understanding of natural sway frequencies in trees

The relationship between form and function in trees is the subject of a longstanding debate in forest ecology and provides the basis for theories concerning forest ecosystem structure and metabolism. Trees interact with the wind in a dynamic manner and exhibit natural sway frequencies and damping processes that are important in understanding wind damage. Tree-wind dynamics are related to tree architecture, but this relationship is not well understood. We present a comprehensive view of natural sway frequencies in trees by compiling a dataset of field measurement spanning conifers and broadleaves, tropical and temperate forests. The field data show that a cantilever beam approximation adequately predicts the fundamental frequency of conifers, but not that of broadleaf trees. We also use structurally detailed tree dynamics simulations to test fundamental assumptions underpinning models of natural frequencies in trees. We model the dynamic properties of greater than 1000 trees using a finite-element approach based on accurate three-dimensional model trees derived from terrestrial laser scanning data. We show that (1) residual variation, the variation not explained by the cantilever beam approximation, in fundamental frequencies of broadleaf trees is driven by their architecture; (2) slender trees behave like a simple pendulum, with a single natural frequency dominating their motion, which makes them vulnerable to wind damage and (3) the presence of leaves decreases both the fundamental frequency and the damping ratio. These findings demonstrate the value of new three-dimensional measurements for understanding wind impacts on trees and suggest new directions for improving our understanding of tree dynamics from conifer plantations to natural forests.

In-Vivo Vibroacoustic Surveillance of Trees in the Context of the IoT

This work introduces a device for long term systematic monitoring of trees against borers. A widely applied way to detect wood-boring insects is to insert a piezoelectric probe with an uncoated waveguide in the tree trunk and listen for locomotion or feeding sounds through headphones. This approach has several shortcomings: (a) frequent manual inspection of trees is costly and impractical to scale to hundreds or thousands of trees, (b) the larvae could be present but inactive during the inspection time and, (c) when the trees are in urban environments the background noise can be significant and can mask the feeble sounds of wood-boring insects even with the use of specialized headphones. We introduce a remotely controlled device that records and wirelessly transmits on a scheduled basis short recordings of the internal vibrations of a tree to a server. The user can listen remotely or process the recording automatically to infer the infestation state of the tree with wood-boring insects that feed or move inside the tree. When integrated within the IoT framework this device can scale up to automatically monitoring the trees of the entire city. The proposed approach led to detection results in field trials of the pests Xylotrechus chinensis (Chevrolat) (Cerambycidae) and Rhynchophorus ferrugineus Olivier (Coleoptera: Curculionidae).

Thermal Compensation of Low-Cost MEMS Accelerometers for Tilt Measurements

Low-cost MEMS accelerometers have the potential to be used in a number of tilt-based monitoring applications but have the disadvantage of being very sensitive to temperature variation (thermal drift). In this paper, we analyze the thermal behavior of a low-cost sensor in the range -10 to +45 °C in order to provide a simple compensation strategy to mitigate this problem. For sensor analysis, we have developed a miniaturized thermal chamber, which was mounted on a tilting device to account for tilt angle variation. The obtained raw data were used to construct low degree polynomial equations that by relating the measurement error induced by thermal drift (i.e., acceleration residuals) to temperature and inclination (of each specific axis), can be used for thermal compensation. To validate our compensation strategy, we performed a field monitoring test and evaluated the compensation performance by calculating RMS errors before and after correction. After compensation, the RMS errors calculated for both the X and Y axes decreased by 96%, indicating the potential of using a simple set of equations to solve common drawbacks that currently make low-cost MEMS sensors unsuitable for tilt-based monitoring applications.