Lorenzo Parri

This study presents a flexible IoT monitoring system suitable for gas sensing, applicable to the pervasive experimental assessments of CO₂ concentrations, particularly in relation to plant respiration and chlorophyll photosynthesis. Beyond CO₂ measurement, the system incorporates the monitoring of other parameters meaningful for photosynthesis and possible plants stress factors, such as solar radiation intensity, temperature and water vapor concentration. Concerning the solar radiation monitoring, two low-cost sensing techniques are proposed based on the measurement of the short circuit current of a monocrystalline silicon photovoltaic panel and on CdS light dependent resistors. A preliminary experimental campaign for the measurement of global and diffuse radiation is performed outdoors and the outcomes are compared with the acquisitions of a commercial pyranometer. Then, tests are performed in the laboratory with an experimental setup envisaging a closed accumulation chamber housing some plants exposed to diffuse radiation, with the final goal of monitoring the CO₂, temperature and water vapor changes inside the chamber and of providing a rough assessment of the mean daily CO₂ uptake of the plants under test.

The estimation of the CO2 concentration variations due to plants photosynthesis has become a topic of outstanding interest in view of evaluating the carbon footprint of greenhouses and farms. In this framework, distributed sensing solutions can be an alternative to expensive and power-consuming gas analyzers. In this paper, a low-cost sensor node thought for the accurate monitoring of photosynthesis-related quantities (i.e., temperature, pressure, water vapor concentration and CO ₂ concentration) is presented. The system is validated through measurement campaigns involving plants enclosed in an accumulation chamber in the presence of artificial light with controlled intensity, photoperiod and spectral composition. A simplified preliminary model is also proposed to interpret the obtained results from the point of view of the kinetics of the gas exchanges, achieving the estimation of the CO ₂ uptake and release rates ascribable to the plants activity.

In this paper a low-cost, low-complexity photoacoustic sensing system for the simultaneous detection of CO ₂ and NO ₂ in exhaust gas is presented. The proposed system is designed as part of a Continuous Emissions Monitoring System for gas turbine emissions. The system exploits the amplification of the photoacoustic signal provided by an acoustic ring resonator, which is characterized by a simple and robust structure and is suitable for in-field measurements. The dual gas detection is obtained by exploiting two measurement principles, the first one, dedicated to the detection of NO ₂ which is present in the target mixture in the ppm range, is the classical PA effect. In fact, the optical source is a light emitting diode with a center wavelength of 405 nm matched on an adsorption peak of NO ₂ . This allows for deriving the NO ₂ concentration measurement directly from the amplitude of the photoacoustic signal. The other mechanism is used to measure the concentration of one of the major components of the exhaust gas, with a concentration in the range of some percents. The quantity of CO ₂ is sensed exploiting its effect on the sound speed, and consequently on the resonance frequency of the resonator. To measure the CO ₂ concentration the system automatically tracks the acoustic resonance shift. The detection of the two gases is realized simultaneously by a unique sensor with real time measurements. A laboratory characterization of the proposed systems showed its feasibility. Experimental results show the possibility to detect NO ₂ with a resolution lower than 1 ppm whereas CO ₂ resolution is about 0.2%.

The safety of an operator working in a hazardous environment is a recurring topic in the technical literature of recent years, especially for high-risk environments such as oil and gas plants, refineries, gas depots, or chemical industries. One of the highest risk factors is constituted by the presence of gaseous substances such as toxic compounds such as carbon monoxide and nitric oxides, particulate matter or indoors, in closed spaces, low oxygen concentration atmospheres, and high concentrations of CO₂ that can represent a risk for human health. In this context, there exist many monitoring systems for lots of specific applications where gas detection is required. In this paper, the authors present a distributed sensing system based on commercial sensors aimed at monitoring the presence of toxic compounds generated by a melting furnace with the aim of reliably detecting the insurgence of dangerous conditions for workers. The system is composed of two different sensor nodes and a gas analyzer, and it exploits commercial low-cost commercially available sensors.

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.

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.

In this article, we propose a reliable and low-latency Long Range Wide Area Network (LoRaWAN) solution for environmental monitoring in factories at major accident risk (FMAR). In particular, a low power wearable device for sensing the toxic inflammable gases inside an industrial plant is designed with the purpose of avoiding peculiar risks and unwanted accidents to occur. Moreover, the detected data have to be urgently and reliably delivered to remote server to trigger preventive immediate actions so as to improve the machine operation. In these settings, LoRaWAN has been identified as the most proper communications technology to the needs owing to the availability of off the shelf devices and software. Hence, we assess the technological limits of LoRaWAN in terms of latency and reliability and we propose a fully LoRaWAN compliant solution to overcome these limits. The proposed solution envisages coordinated end device (ED) transmissions through the use of Downlink Control Packets (DCPs). Experimental results validate the proposed method in terms of service requirements for the considered FMAR scenario.

Within the big picture of the Internet of Things (IoT) a brand new paradigm has risen since few years ago in the context of industrial scenarios: the Industrial Internet of Things (IIoT), whose aim is to transplant all of the features, characteristics and scopes of the IoT into industrial settings. The latter ones might be subject to a wide range of environmental conditions from the point of view of both temperature and relative humidity, along with harmful gases exposure and vibration due to, for instance, machineries. Therefore, whenever their monitoring is performed by means of devoted infrastructures, such extreme working conditions must be born in mind during the pertaining design phases. Mostly, industrial monitoring is put into effect by resorting to wireless sensor networks enabled by Low Power Wide Area Network (LPWAN) techonologies. This set of facilities includes an ample heterogeneity of standards and techniques. However, the Long Range (LoRa) modulation and the LoRa Wide Area Network (LoRaWAN) protocol extensively proved to be reliable and robust alternatives. Thus, in this paper the variations of hardware performances of a LoRaWAN sensor node, in terms of transmission capabilities, due to the changes of temperature and relative humidity, vibration and gaseous atmospheres like CO, NO and NO2, which are typical of industrial processes, are investigated. In so doing, an ageing process due to the aforementioned phenomena was induced. To this end, a measurement campaign within controlled environments (i.e., a climatic chamber, a fume extraction plant and an adhoc vibration test bench) was sorted out, whose results show a physiological performances drop that neither undermine the network reliability, nor damage the sensor node electronics.

This paper aims to thoroughly investigate the potential of ion current measurements in the context of combustion process monitoring in gas turbines. The study is targeted at characterizing the dynamic behavior of a typical ion-current measurement system based on a spark-plug. Starting from the preliminary study published in a previous work, the authors propose a refined model of the electrode (spark plug), based on the Langmuir probe theory, that incorporates the physical surface effects and proposes an optimized design of the conditioning electronics, which exploits a low frequency AC square wave biasing of the electrodes and allows for compensating some relevant parasitic effects. The authors present experimental results obtained in the laboratory, which allow for the evaluation of the validity of the model and the interpreting of the characteristics of the measurement signal. Finally, measurements carried out in the field on an industrial combustor are presented. The results confirm that the charged chemical species density sensed by the proposed measurement system and related to the mean value of the output signal is an indicator of the ‘average’ combustion process conditions in terms e.g., of air/fuel ratio, whereas the high frequency spectral component of the measured signal can give information related to the turbulent regime and to the presence of pressure pulsations. Results obtained with a prototype system demonstrated an achievable resolution of about 5 Pa on the estimated amplitude, even under small biasing voltage (22.5 V) and an estimated bandwidth of 10 kHz.

In this paper, the efficiency of the carbonic anhydrase (CA) enzyme in accelerating the hydration of CO₂ is evaluated using a measurement system which consists of a vessel in which a gaseous flow of mixtures of nitrogen and CO₂ is bubbled into water or water solutions containing a known quantity of CA enzyme. The pH value of the solution and the CO₂ concentration at the measurement system gas exhaust are continuously monitored. The measured CO₂ level allows for assessing the quantity of CO₂, which, subtracted from the gaseous phase, is dissolved into the liquid phase and/or hydrated to bicarbonate. The measurement procedure consists of inducing a transient and observing and modelling the different kinetics involved in the steady-state recovery with and without CA. The main contribution of this work is exploiting dynamical system theory and chemical kinetics modelling for interpreting measurement results for characterising the activity of CA enzymes. The data for model fitting are obtained from a standard bioreactor, in principle equal to standard two-phase bioreactors described in the literature, in which two different techniques can be used to move the process itself away from the steady-state, inducing transients.