Performance Evaluation of an IoT Sensor Node for Health Monitoring of Artwork and Ancient Wooden Structures

In this paper, an IoT sensor node, based on smart Bluetooth low energy (BLE), for the health monitoring of artworks and large wooden structures is presented. The measurements from sensors on board the node are collected in real-time and sent to a remote gateway. The sensor node allows for the monitoring of environmental parameters, in particular, temperature and humidity, with accurate and robust integrated sensors. The developed node also embeds an accelerometer, which also allows other mechanical quantities (such as tilt) to be derived. This feature can be exploited to perform structural monitoring, exploiting the processing of data history to detect permanent displacements or deformations. The node is triggered by acceleration transients; therefore, it can also generate alarms related to shocks. This feature is crucial, for instance, in the case of transportation. The developed device is low-cost and has very good performance in terms of power consumption and compactness. A reliability assessment showed excellent durability, and experimental tests proved very satisfactory robustness against working condition variations. The presented results confirm that the developed device allows for the realization of pervasive monitoring systems, in the context of the IoT paradigm, with sensor nodes devoted to the monitoring of each artwork present in a museum or in a church

Optimization of perovskite gas sensor performance: characterization, measurement and experimental design

Eight different types of nanostructured perovskites based on YCoO3 with different chemical compositions are prepared as gas sensor materials, and they are studied with two target gases NO2 and CO. Moreover, a statistical approach is adopted to optimize their performance. The innovative contribution is carried out through a split-plot design planning and modeling, also involving random effects, for studying Metal Oxide Semiconductors (MOX) sensors in a robust design context. The statistical results prove the validity of the proposed approach; in fact, for each material type, the variation of the electrical resistance achieves a satisfactory optimized value conditional to the working temperature and by controlling for the gas concentration variability. Just to mention some results, the sensing material YCo0.9Pd0.1O3 (Mt1) achieved excellent solutions during the optimization procedure. In particular, Mt1 resulted in being useful and feasible for the detection of both gases, with optimal response equal to +10.23% and working temperature at 312°C for CO (284 ppm, from design) and response equal to −14.17% at 185°C for NO2 (16 ppm, from design). Analogously, for NO2 (16 ppm, from design), the material type YCo0.9O2.85 + 1%Pd (Mt8) allows for optimizing the response value at −15.39% with a working temperature at 181.0°C, whereas for YCo0.95Pd0.05O3 (Mt3), the best response value is achieved at −15.40% with the temperature equal to 204°C

On the safety design of radar based railway level crossing surveillance systems

Recent accidents experienced at railway level crossings are pushing researchers to design surveillance systems able to grant safety of passengers and structural integrity of trains at level crossings. The challenge is represented by granting at the same time an appropriate reliability, availability and maintainability degree despite the high safety requirements imposed by the application. The approach proposed in this paper takes into consideration the most common suggested standards used in designing this kind of systems and introduces new general concepts which demystify the use of such standards in actual applications. This paper illustrates the roadmap to be followed in general when designing level crossing monitoring systems, to minimize the risk due to object misdetection occurring on barrier closure when exploiting radar technology

A Hazardous Area Personal Monitoring System for Operators in Gas Depots and Storage Tanks

This work describes a smart monitoring system for the detection of flammable gas residues, toxic gases, and reduced oxygen concentrations. The proposed system aims at reducing the risk of fires and explosions, thus increasing the safety of workers engaged in maintenance or inspection of gas storages. The monitoring system is based on compact battery-powered wearable sensor nodes containing sensors for LPG flammable compounds, toxic gases, and oxygen. The designed system can also increase plants safety by incorporating an intrusion detection system, which prevents unauthorized access to safety-critical areas to prevent accidents. The sensor nodes transmit data through a LoRa low power radio channel to a remote server whereas they allow for the identification of the operators for the access to restricted areas exploiting a Bluetooth Low Energy (BLE) proximity technique

Autonomous IoT Monitoring Matching Spectral Artificial Light Manipulation for Horticulture

This paper aims at demonstrating the energy self-sufficiency of a LoRaWAN-based sensor node for monitoring environmental parameters exploiting energy harvesting directly coming from the artificial light used in indoor horticulture. A portable polycrystalline silicon module is used to charge a Li-Po battery, employed as the power reserve of a wireless sensor node able to accurately monitor, with a 1-h period, both the physical quantities most relevant for the application, i.e., humidity, temperature and pressure, and the chemical quantities, i.e., O(2) and CO(2) concentrations. To this aim, the node also hosts a power-hungry NDIR sensor. Two programmable light sources were used to emulate the actual lighting conditions of greenhouses, and to prove the effectiveness of the designed autonomous system: a LED-based custom designed solar simulator and a commercial LED light especially thought for plant cultivation purposes in greenhouses. Different lighting conditions used in indoor horticulture to enhance different plant growth phases, obtained as combinations of blue, red, far-red and white spectra, were tested by field tests of the sensor node. The energy self-sufficiency of the system was demonstrated by monitoring the charging/discharging trend of the Li-Po battery. Best results are obtained when white artificial light is mixed with the far-red component, closest to the polycrystalline silicon spectral response peak

Highly Reliable Multicomponent MEMS Sensor for Predictive Maintenance Management of Rolling Bearings

In the field of vibration monitoring and control, the use of low-cost multicomponent MEMS-based accelerometer sensors is nowadays increasingly widespread. Such sensors allow implementing lightweight monitoring systems with low management costs, low power consumption and a small size. However, for the monitoring systems to provide trustworthy and meaningful data, the high accuracy and reliability of sensors are essential requirements. Consequently, a metrological approach to the calibration of multi-component accelerometer sensors, including appropriate uncertainty evaluations, are necessary to guarantee traceability and reliability in the frequency domain of data provided, which nowadays is not fully available. In addition, recently developed metrological characterizations at the microscale level allow to provide detailed and accurate quantification of the enhanced technical performance and the responsiveness of these sensors. In this paper, a dynamic calibration procedure is applied to provide the sensitivity parameters of a low-cost, multicomponent MEMS sensor accelerometer prototype (MDUT), designed, developed and realized at the University of Siena, conceived for rolling bearings vibration monitoring in a broad frequency domain (from 10 Hz up to 25 kHz). The calibration and the metrological characterization of the MDUT are carried out by comparison to a reference standard transducer, at the Primary Vibration Laboratory of the National Institute of Metrological Research (INRiM)

Mobile opportunity against stress: Open study protocol on the effectiveness of a mobile platform for stress self-management in the post-pandemic era

Mobile health platforms have shown promise in the management of various mental health conditions (including stress, anxiety, and depression) and cognitive behavioral strategies emerged as a popular and effective option offered by the platforms. This paper presents the protocol of a study aimed to test the effectiveness of a mobile platform that uses cognitive-behavioral strategies for stress self-management in the Tuscany region (Italy). The mobile app is adapted to the specific needs of each vulnerable population for which it is designed: young and older people, healthcare professionals, entrepreneurs. The app will be evaluated on the following outcomes: (i) perceived susceptibility and severity of the pandemic situation, perceived benefits, and costs of preventive health behaviors, (ii) knowledge about Covid-19 preventive behaviors and negative consequences of social distancing, (iii) stress and psychopathological symptoms (i.e., anxiety, depression, and post-traumatic stress symptoms) and cognitive distortions. If successful, we expect that the platform could give various groups clinical benefits by providing symptom self-monitoring and early intervention, consolidating the number of mental health programs available, and decreasing barriers to treatment-seeking. This population-level approach has the potential to improve mental health outcomes in pandemic periods for many people

An Adaptive Measurement System for the Simultaneous Evaluation of Frequency Shift and Series Resistance of QCM in Liquid

In this paper, a novel measurement system based on Quartz Crystal Microbalances is presented. The proposed solution was conceived specifically to overcome the measurement problems related to Quartz Crystal Microbalance (QCM) applications in dielectric liquids where the Q-factor of the resonant system is severely reduced with respect to in-gas applications. The QCM is placed in a Meacham oscillator embedding an amplifier with adjustable gain, an automatic strategy for gain tuning allows for maintaining the oscillator frequency close to the series resonance frequency of the quartz, which is related in a simple way with the physical parameters of interest. The proposed system can be used to monitor simultaneously both the series resonant frequency and the equivalent electromechanical resistance of the quartz. The feasibility and the performance of the proposed method are proven by means of measurements obtained with a prototype based on a 10-MHz AT-cut quartz

QCM Measurements of RH with Nanostructured Carbon-Based Materials: Part 2-Experimental Characterization

In this series of two papers, the humidity sensing of a carbon nanotube (CNT) network-based material is transduced and studied through quartz crystal microbalance (QCM) measurements. To this aim, quartzes functionalized with different amounts of sensing material were realized, exposed to different humidity levels, and characterized. In this second paper, the experimental results are presented and discussed. The sensing mechanisms are elucidated exploiting the theory presented in the first paper of this series. The presented results show that the investigated material functionalization induces a large response of QCM to humidity in terms of resonant frequency even at low RH levels, with a sensitivity of about 12 Hz/%RH (at RH < 30% and room temperature and 10 ug of deposited SWCNT solution) and an increase in sensitivity in the high RH range typical of nanostructured film. Regarding the response in terms of motional resistance, a large response is obtained only at intermediate and high humidity levels, confirming that condensation of water in the film plays an important role in the sensing mechanism of nanostructured materials