The atmospheric particulate matter is considered one of the most dangerous pollutants because of its effects on the climate and human health. Particulate concentration changes largely with spatial position and time, and thus, a distributed real-time monitoring would be mandatory, especially in densely populated areas. The proposed optical sampling system has a negligible cost with respect to the already available instruments and can be used for deploying a capillary particulate monitoring network thanks to its wireless capability based on the LoRa protocol. The proposed solution employs an optical method for the atmospheric particulate detection and the estimation of its concentration and size distribution. The air is sampled by a small pump which forces a known flux through a commercial glass-fiber filter, where the particulate is captured. A low-cost digital camera coupled with a multi-wavelength lighting system takes periodical photographs of the filter surface, and a small PC-on-single-board processes the acquired images in order to identify the particles and to estimate their size. The system can work unattended for a long time and transmit remotely measurement data with a typical range of few kilometers.

Digitalization techniques, such as photogrammetry (PG), are attracting the interest of experts in the cultural heritage field, as they enable the creation of three-dimensional virtual replicas of historical artifacts with 2D digital images. Indeed, PG allows for acquiring data regarding the overall appearance of an artifact, its geometry, and its texture. Furthermore, among several image-based techniques exploited for the conservation of works of art, multispectral imaging (MSI) finds great application in the study of the materials of historical items, taking advantage of the different responses of materials when exposed to specific wavelengths. Despite their great usefulness, PG and MSI are often used as separate tools. Integrating radiometric and geometrical data can notably expand the information carried by a 3D model. Therefore, this paper presents a novel research methodology that enables the acquisition of multispectral 3D models, combining the outcomes of PG and MSI (Visible (VIS), Ultraviolet-induced Visible Luminescence (UVL), Ultraviolet-Reflected (UVR), and Ultraviolet-Reflected False Color (UVR-FC) imaging) in a single coordinate system, using an affordable tunable set-up and open-source software. The approach has been employed for the study of two wooden artifacts from the Museo Egizio di Torino to investigate the materials present on the surface and provide information that could support the design of suitable conservation treatments.

This paper describes a simple though extremely effective sensor for acetone monitoring in the breath. The sensor is capable of monitoring the presence of acetone at ppm concentrations therefore being suitable for diabetes diagnosis. It has a dimension of 3 mm×6 mm and a cost of less than one dollar. The small dimensions allow one to greatly limit the power required to increase its temperature, and its high selectivity with respect to other gases present in the breath reduces the risk of false positive responses. The sensor is based on a thin alumina substrate on which platinum strips are deposited on both faces. A thin Nb2O5 layer with nano-metric thickness provide the required sensitivity and selectivity. Sensor prototypes have been characterized by FESEM and XPS, and proved an inherent linear response up to few part per million of acetone.

This paper describes a viable and self-contained imaging system able to assess and quantify the effects of microbial corrosion on metals surface. The proposed image processing uses Scanning Electron Microscope micrographs to analyze bacteria attachment on sample surface and to estimate the degradation degree of the material. After a preliminary brightness and contrast normalization, which refines the image taken by the operator, the software is able to identify dark spots on the clear metal surface. These are then attributed to singly attached bacteria or to larger clusters, which are the most dangerous ones, as they could overlay corrosion pits. After that, the degradation of the material is evaluated through the quantification of microbial attachment on the surface and through dimensional distribution of bacteria clusters.

Mechanical and insulation defects can lead to severe faults in power equipment, making it essential to conduct a comprehensive and accurate fusion diagnosis. Vibration and acoustic emission (AE) are two effective ways to detect the above two defects. This paper proposes and develops a reliable smart vibration and AE combined wireless sensor network (WSN), featuring both low cost and power consumption, which is suitable to detect and monitor the power equipment’s mechanical and insulation conditions. Firstly, the combined sensor is designed and the feasibility is validated by simulation, then the circuit system is designed in order to sample and process analog signals, perform edge computing, self-calibrate impedance and transmit wireless data. The calibartion and consumption tests are carried out to verify the combined measurement performance and reliable smart sensing. Then, a combined vibration and AE WSN is designed and established, enabling efficient sensor control. Fixed and mobile clients are proposed to support monitoring for various applications. Additionally, laboratory experiments demonstrate the sensor’s ability to synchronously measure vibration and partial discharge (PD), a novel vibration-AE amplitude graph is presented to reflect the correlation between vibration and PD. The proposed WSN has been deployed in an actual GIS substation, it is able to detect an apparent abnormal vibration on phase-B of the voltage transformer chamber due to a poor electrical contact defect. This paper presents a reliable and effective wireless sensing approach for the distributed fusion detection and diagnosis of both mechanical and insulation conditions of power equipment, offering a feasible solution for industrial automated measurement.