In recent years, due to the continuous increase in infrastructure construction such as road, airport and railway construction in global, the quality requirements for compaction operations have been continuously improved. At the same time, with the rapid development of electronic information, automatic control and computer technology, the road roller has gradually developed towards automation and intelligence. The intelligent vibratory roller with adjustable mode has become the leading direction of the development of compaction equipment, which can obtain the state of the pressed material in time in the compaction operation. Then control the working parameters and the excitation mode of the whole machine according to the condition of the pressed material. Thus, the intelligent vibratory roller can better meet today’s requirements for compaction. This paper proposes an intelligent compaction operation monitoring system for intelligent vibratory roller based on internet of things. Firstly, the acceleration change characteristics of the vibrating wheel are first analyzed, by constructing the dynamic model of the vibratory roller and the compacted material under different working conditions. Secondly, a hardware system for real-time compaction monitoring is established, including design selection of sensor module, signal conditioning module and wireless transmission module. Thirdly, a method for real-time compaction monitoring data evaluation and analysis of intelligent compaction is proposed, and a detailed analysis process of compaction data is designed. Finally, an intelligent vibratory roller operation monitoring prototype system based on the Internet of Things technology is constructed.

Vibrational micro-spectroscopies have been applied to investigate gingival crevicular fluid (GCF) for monitoring the orthodontic treatment with fixed appliances [1-3]. In particular, GCF samples have been investigated using Fourier transform infrared, Raman, and Surface-Enhanced Raman micro-spectroscopies. GCF samples were collected from patients aged between 12 and 22 years before bracket bonding and after 2, 7, and 14 days of treatment at the buccal side of the incisors. The GCF spectra collected at different times of orthodontic tooth movement have been used for characterizing biochemical changes occurring during the treatment. The examined spectra show that Amide I band due to protein contents give relevant information.

In the present work, we examined the Amide I band region with particular attention by using deconvolution analysis using Gaussian-Lorentzian curves for infrared spectra and Lorentzian curves for Raman spectra. The performance of the procedure was evaluated using the χ² parameter.

The deconvolution analysis allowed us to evidence the contribution of the different subcomponents of the Amide I band and the changes occurring during orthodontic treatment. These changes can be ascribed to modifications in the secondary structure of protein content and can contribute to make vibrational spectroscopies a useful tool for monitoring the individual patient’s response to the orthodontic force application.

References

[1] F. d’ Apuzzo, L. Perillo, I. Delfino, M. Portaccio, M. Lepore, C. Camerlingo Monitoring early phases of orthodontic treatment by means of Raman spectroscopies Journal of Biomedical Optics 22(11), 115001 (2017), DOI: 10.1117/1.JBO.22.11.115001.

[2] M. Portaccio, F. d’ Apuzzo, L. Perillo, V. Grassia, S. Errico, M. Lepore Infrared microspectroscopy characterization of gingival crevicular fluid during orthodontic treatment Journal of Molecular Structure 1176 (2019) 847-854

[3] F. d' Apuzzo, L. Nucci, I. Delfino, M. Portaccio, G. Minervini, G. Isola, I. Serino, C. Camerlingo, M. Lepore “Application of vibrational spectroscopies in the qualitative analysis of gingival crevicular fluid and periodontal ligament during orthodontic tooth movement” J. Clin. Med. 2021, 10, 1405. https://doi.org/10.3390/jcm10071405

The noise caused by airports and its impact on human health, together with train, road traffic, leisure and wind nose has been widely analyzed, even in the reports published in 2019 by the WHO. Noise effect ​has also been studied in the literature on other species, such as birds and amphibians. In this work, we focus on a natural environment of special singularity ​due to its location: the natural space of the Delta del Llobregat, next to the city of Barcelona. Placed in an area close to the Port of Barcelona, and right on the way out of the planes taking off at Barcelona airport. In this paper, we present a first analysis of the typology of the sounds found in the natural environment of the Delta del Llobregat after conducting a simultaneous recording campaign at three separate spots of biological interest, determined by the park's curators. We measure the intermittency of interfering sounds, as well as the intensity of wildlife sounds in relation to the noises caused by the airport activity. The recordings and posterior analysis were made on March 5, 2021, when airport activity was still greatly diminished by the lockdown. This first analysis shows clear acoustic impact on the environment, especially during the operational peak hours of the airport. Results encourage us to deepen the study, even with more data recordings and metrics definitions in the future, to consider the Delta del Llobregat airport activity in the new conditions after the COVID-19 pandemic.

Vibration energy harvesting (VEH) have emerged as one of the most promising sources of sustainable energy to power low-powered electronics and structural health monitoring. However, research that involves powering larger devices have also been explored. Among the different approaches to convert mechanical vibrations into electricity, the two most common applied methods are piezoelectric transducers and electromagnetic induction. While piezoelectric VEH generally dominates in the micro-volume scale, electromagnetic VEH tends to perform better at larger volumes. Triangular cantilever beam are often desired in piezoelectric vibration energy harvesting applications as they result in a better performance due to a higher and more uniform stress. However, the application of this cantilever geometry has not yet been explored for other transduction methods. In this study, the application of a triangular cantilever beam for a cantilevered electromagnetic vibration energy harvester was examined by analyzing its material damping and comparing it to a regular rectangular beam. The material damping of the harvester was predicted through finite element analysis using the critically damped stress method. Under the same beam volume or beam length, the triangular cantilever beam exhibited an approximately 7.1% lower material damping when compared to a rectangular cantilever beam. Further analysis shows that the triangular beam can also deliver a 21.7% higher power output than the rectangular beam.

Urban acoustic environment is composed of a great variety of sounds, whose effects citizen are mainly unaware of, despite medical studies showing that urban noise affects quality of life and health, causing from sleep disturbances to cardiovascular. The development and deployment of Wireless Acoustic Sensor Networks (WASNs) presents new ways to face the urban acoustic challenges in the context of a smart city. The improvement of the quality of life of the citizens cannot be limited to measuring the equivalent levels of noise in the streets, but should also identify the type of noise source and its impact on the overall noise measurement. For this purpose, the collection of noise sources information requires the application of many techniques, including the recording and labeling of noise events. The latter are tasks that are mostly performed manually by experts, being very time-consuming. To improve this task and taking advantage of the rise of new technologies, in this work we propose the design of a game using a mobile application to encourage citizens' participation in research, raising awareness of the problems generated by noise and helping experts in the work of pre-labeling sounds for later analysis. We detail the envisioned mechanics of the proposed game, its dynamics, and its design.

Human gait analysis is a growing field of research interest in medical treatment, diagnosis, sports training, and structural health monitoring. It is the study of graphical representation of human motion through observation method (video or image-based) in a clinical setup or placing sensor method at different parts of the body, to understand the condition of human muscles, mechanics, and fitness. Out of the two methods, the role of wearable sensors in such clinical applications is crucial because of their low cost, simple implementation, and time to time monitoring. In our study, we propose an insole design for wearable sensors based on lead zirconate titanate piezoelectric discs (PZT) and inertial measurement unit (IMU) BMI270 to acquire the human gait. A PZT and an IMU aligned on the same axis are placed in a metallic structure. Such structures are placed at three points of a shoe sole: toe, metatarsal, and heel. The human gait obtained from this insole layout is significantly affected by plantar pressure distribution and alignment of the feet. The PZT sensors give an insight into the pressure map under the feet in the form of voltage. The accelerometer in the IMU gives the change of position of the feet to examine the gait analysis. The gyroscope in IMU is used for the understanding of the motion and posture of feet by measuring its angular rate. The acquired data from these sensors shows that each individual has a different gait pattern at the three points in the sole. It also shows intra-individual variations where the gait of the same person varies in daily situations.

Ultrasonic oscillating temperature sensors (UOTSes) allow sensing temperatures of the medium of interest across the complete ultrasonic pathway and quickly react to the temperature changes. These features are advantageous comparing to the conventional temperature sensors, which need to come to the thermal equilibrium to the environment in order to report the correct temperature, and sense temperature at a particular point only. To date UOTSes were used for temperature measurements in liquids only.

In its simplest form an UOTS requires a pair of ultrasonic transducers and an amplifier, that feeds the signal from the receiver to the transmitter. Positive feedback leads to sustained oscillations with the frequency, which is dependent on the temperature distribution between the transducers as it determines the ultrasound velocity thus the ultrasound propagation delay.

For the reporting protype we used a pair of narrowband 40 kHz ultrasonic transducers and an electronic driver built around a dual operating amplifier (opamp) LM358. The transducers were mounted on an aluminium 2020 slot 5 profile using two rubber lined Munsen rings with backplates and positioned at desirable distances with the help of four roll-in T-nuts. One opamp provided the mid supply reference point, and the other operated as an inverting amplifier with the gain ranging within 10..50. Increasing the distance between the transducers required increasing the gain to sustain the oscillations. When the distance changed, resulting in the change in the propagation delay, the output frequency of the UOTS changed too, confirming the feasibility of measuring air temperature using UOTSes. The frequency changed substantially when the air between the transducers was heated using a hairdryer.

We present details of the mechanical and electronic design of the working prototype and discuss the obtained experimental results.

Temperature sensors are used for a wide variety of industrial, scientific, medical and domestic purposes, and differ by their design and/or operating principles to better suit a particular application. Measuring temperature distribution requires use of many sensors, and their selection should balance cost, accuracy and convenience of networking. Most accurate are resistance temperature detectors (RTDs), of which most commonly used are Pt100 and Pt1000 platinum RTDs. These sensors are expensive, require a separate electronic driver for each RTD and complicated networking. Thermistors are the least expensive on their own but ensuring accurate measurement requires their individual calibration, provisions to shield them from noise and complicated networking. Semiconductor temperature sensors frequently integrate an appropriate electronic driver and provide a standardised interface, which eases of their networking, at a medium price point. However, their accuracy is usually specified rather conservatively by the manufacturers.

In this study we compared readings, collected every 19 seconds from Pt100 and DS18B20 temperature sensors, placed in a cardboard box close to each other in a typical dwelling, over several months’ period. For periods of time both sensors were placed inside the same plastic bag, or were wrapped around with packaging materials for thermal insulation, or were left exposed to the environment on their own.

The vast majority of collected data show that the DS18B20 provided substantially better accuracy than the one specified by the manufacturer (+-0.5°C) when the sensors were close to each other and well insulated. Their readings were well correlated over time even when the absolute readings were notably biased. These and some other past and present observations, to be presented at the conference, led us to the conclusion that DS18B20 sensors, after some suitable calibration, can reduce complexity and cost of the temperature distribution measurement networks.

The advantage of Graphene oxide (GO) is its hydrophilicity in contrast to Graphene’s hydrophobicity, and aqueous dispersions of GO are stable due to the absorption of water. This property makes GO ideal for producing strain and force sensors. To monitor the production of a graphene sensor, we painted 2 silver electrodes on a wooden substrate, connected these electrodes to a voltage divider with a reference resistor, and continuously measured the drop voltage across the reference resistor. The signal of the open circuit was recorded at 2 Hz before painting the GO solution across the electrodes, thereby closing the circuit. As GO is an insulator, ionic impurities of the aqueous solution and possibly the negatively charged Graphene oxide sheets provided the initial conductivity. Closing the circuit increased the conductance from 0 to 5-20 microS. Heating the fluid GO dispersion with an air gun increased the conductance by a further 2-5 microS until the water started to evaporate, and the conductivity dropped to 0 when a dry layer of GO was left. This process of painting, heating and drying was repeated twice, and after painting the third time, the GO was left to air-dry for approximately 2 h. Subsequently, the temperature of the heat gun was pre-set to 350°C , and GO was reduced to graphene (rGO). During the reduction process, the conductivity spiked to 0.8-1 S within 0.5 s, but dropped immediately through a power decay with an exponent of –0.24. After 15 minutes, the signal stabilised at 90 microS, and we subjected the wooden substrate to a three-point bending test with the sensor on the compression side. A force with a triangular wave profile was applied with a frequency of 0.03 Hz, and the loading, unloading, and dwell (zero force) segments of 11, 10, and 12 s, respectively, with maximum force of 200 N. The measured voltage sampling frequency across the reference resistor was increased to 20 Hz. The calculated conductance of the sensor and the force were aligned and plotted against each other. A 4^th order polynomial was fitted to the data to obtain a calibration curve (R² = 0.9974). The force was recalculated from the calibration curve, resulting in a good match of the original force and the recalculated one, resulting in an RMSE of 3.4 N. The RMSE% was < 10% at forces > 50 N, and < 5% at forces > 75 N. Alternatively, instead of the force accuracy, the time accuracy can be calculated. Although the hysteresis was negligible, the calculated force lagged the original by 0.25 s at small forces, decreasing linearly to 0 s at the peak force (0.25 s corresponds to 1.2% of the loading-unloading cycle, and 0.76% of the total cycle including the dwell segment). The force and time accuracy data proved that the sensor is sufficiently accurate. The calibration of the sensor served for evaluation of the quality of the electrical signal, in terms of the signal (drift, noise) and the calibration curve (range of conductance, hysteresis, degree of non-linearity, ease of curve fitting), thereby providing vital information on the sensitivity and measurement range (accuracy, saturation point). From these data, the purpose and the application of the sensor will be selected.

Sensors are devices that measures a change in physical stimulus by converting it into an electronic signal which can be read by a designated instrument. Notable sensing application include among others vibration sensing, pressure sensing, temperature sensing, Humidity sensing, strain sensing, biosensing and structural health monitoring (SHM). Structural health monitoring relies on the automatic detection of anomalous behavior of structures. Any localized damage in a structure reduces the stiffness thereby increases damping in the structure. Reduced stiffness and or increased damping causes a decrease in the natural frequencies and hence a modification of the vibration modes of the structure. Effective study of this dynamic characteristic is very important as a robust method for quantifying assurance of their integrity and mechanical health because an unpredicted failure may be devastating on economic, social, and human life. Powering SHM devices/sensors remotely and autonomously in a passive, efficient, ecofriendly, and minimum retrofitting cost has been a major desire over the past decades. A device that meets such specification is the vibration energy harvester. This work focuses on the electromagnetic transduction harvester whose harvested voltage/power is formulated from Faraday law of electromagnetic induction. Electromagnetic parameter that determines the degree of transduction is called the coupling constant The value of coupling constant must accurately set during harvester design because it directly determines harvester damping ratio and the power available for the sensor. All parameters used to compute the coupling except the flux density is constant. In this work, we focus on formulating set analytical equation that could effectively determine the harvester’s optimum magnetic flux parameter to be used in computing the optimum coupling constant. This work concludes that the degree of coupling for the determined optimum flux density increases with an increased load resistance and hence larger harvested power is available to power the sensor.