A Low Cost UWB Based Solution for Direct Georeferencing UAV Photogrammetry

Thanks to their flexibility and availability at reduced costs, Unmanned Aerial Vehicles (UAVs) have been recently used on a wide range of applications and conditions. Among these, they can play an important role in monitoring critical events (e.g., disaster monitoring) when the presence of humans close to the scene shall be avoided for safety reasons, in precision farming and surveying. Despite the very large number of possible applications, their usage is mainly limited by the availability of the Global Navigation Satellite System (GNSS) in the considered environment: indeed, GNSS is of fundamental importance in order to reduce positioning error derived by the drift of (low-cost) Micro-Electro-Mechanical Systems (MEMS) internal sensors. In order to make the usage of UAVs possible even in critical environments (when GNSS is not available or not reliable, e.g., close to mountains or in city centers, close to high buildings), this paper considers the use of a low cost Ultra Wide-Band (UWB) system as the positioning method. Furthermore, assuming the use of a calibrated camera, UWB positioning is exploited to achieve metric reconstruction on a local coordinate system. Once the georeferenced position of at least three points (e.g., positions of three UWB devices) is known, then georeferencing can be obtained, as well. The proposed approach is validated on a specific case study, the reconstruction of the façade of a university building. Average error on 90 check points distributed over the building façade, obtained by georeferencing by means of the georeferenced positions of four UWB devices at fixed positions, is 0.29 m. For comparison, the average error obtained by using four ground control points is 0.18 m

Implementation and assessment of two density-based outlier detection methods over large spatial point clouds

Several technologies provide datasets consisting of a large number of spatial points, commonly referred to as point-clouds. These point datasets provide spatial information regarding the phenomenon that is to be investigated, adding value through knowledge of forms and spatial relationships. Accurate methods for automatic outlier detection is a key step. In this note we use a completely open-source workflow to assess two outlier detection methods, statistical outlier removal (SOR) filter and local outlier factor (LOF) filter. The latter was implemented ex-novo for this work using the Point Cloud Library (PCL) environment. Source code is available in a GitHub repository for inclusion in PCL builds. Two very different spatial point datasets are used for accuracy assessment. One is obtained from dense image matching of a photogrammetric survey (SfM) and the other from floating car data (FCD) coming from a smart-city mobility framework providing a position every second of two public transportation bus tracks. Outliers were simulated in the SfM dataset, and manually detected and selected in the FCD dataset. Simulation in SfM was carried out in order to create a controlled set with two classes of outliers: clustered points (up to 30 points per cluster) and isolated points, in both cases at random distances from the other points. Optimal number of nearest neighbours (KNN) and optimal thresholds of SOR and LOF values were defined using area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Absolute differences from median values of LOF and SOR (defined as LOF2 and SOR2) were also tested as metrics for detecting outliers, and optimal thresholds defined through AUC of ROC curves. Results show a strong dependency on the point distribution in the dataset and in the local density fluctuations. In SfM dataset the LOF2 and SOR2 methods performed best, with an optimal KNN value of 60; LOF2 approach gave a slightly better result if considering clustered outliers (true positive rate: LOF2\u2009=\u200959.7% SOR2\u2009=\u200953%). For FCD, SOR with low KNN values performed better for one of the two bus tracks, and LOF with high KNN values for the other; these differences are due to very different local point density. We conclude that choice of outlier detection algorithm very much depends on characteristic of the dataset\u2019s point distribution, no one-solution-fits-all. Conclusions provide some information of what characteristics of the datasets can help to choose the optimal method and KNN values

A Low-Cost Monitoring System and Operating Database for Quality Control in Small Food Processing Industry

The use of completely automated systems for collecting sensor data with the aim of monitoring and controlling the quality of small-scale food processes is not widespread. Small and micro-enterprises usually do not carry out their own precompetitive research or prototype development as regards to automation technologies. This study proposes a web-based, low-cost monitoring and supervisory control and data acquisition (SCADA) system whose kernel is available for free, as a possible solution that could be adopted by these food producers. It is mainly based on open SW/HW so as its configuration is adaptable to the application and type of plant. It presents a modular architecture and its main functionalities encompass the acquisition, management, aggregation and visualization of process data, providing an operating database. It also provides food tracking and process quality control: The time series are browsable due to QR-Code generation and different early warning detection strategies are implemented. A tool for solving migration problems based on Fick\u2019s equation is offered as a packaging decision support system

Application of Essential Oils to Control the Biodeteriogenic Microorganisms in Archives and Libraries

Microbial contamination control in indoor environments, such as libraries and archives, represents a challenge. Essential oils (EOs), well-known for their antimicrobial properties, have been applied in pharmaceutical and food industry from many years. In the present study, Thymus vulgaris and Origanum vulgare EO antimicrobial efficacy on paper-born microorganisms, Staphylococcus epidermidis, Rhodotorula mucilaginosa and Alternaria alternata, was investigated to protect water-damaged paper documents and to control indoor air quality for operator’s health safety. T. vulgaris EO was the most effective: Minimum Inhibitory Concentration (MIC) values obtained for S. epidermidis and R. mucilaginosa, with a broth macro-dilution method, were 7.5 microgram/mL and 5.63 microgram/mL, respectively. T. vulgaris EO (0.75% v/v), nebulized immediately after the inoculation on agar plates or paper sheets, showed a high inhibition effect against the three biodeteriogenic microorganisms, also when lyophilized on paper sheets; in this last case, the EO has a higher efficacy when applied immediately after the freeze drying. Regarding the EO effect against A. alternata, the inhibition percentage of the mycelial growth, MGI, (81.4%), observed for nonsporulated mycelium, was higher than that for the sporulated one (51.4%). Finally, T. vulgaris EO (0.75% v/v) was effectively applied on a real contaminated book cover by means of EO impregnated contact sheets. Obtained results demonstrated that tested EOs were able to delay or completely inhibit paper-born microorganism growth for both flood-independent or -dependent contamination

Microbial contamination of libraries and archives: risk assessment and contamination control

Freezing of the paper material is a way to control the growth of microorganisms and the possibility of “acute” biodeterioration and illness, after accidental events, e.g. flooding. But as the paper-born microorganisms can survive after lyophilisation, they must be controlled also after the drying process. The decision-making about the adoption of prevention and protection measures for the exposed operators’ safety, among which the possibility to control the biodeteriogenic and toxigenic microflora growth by the application of Thymus vulgaris oil, was supported not only by the experimental results but also through a dedicated risk assessment procedure

Performance Evaluation of Two Indoor Mapping Systems: Low-Cost UWB-Aided Photogrammetry and Backpack Laser Scanning

During the past dozen years, several mobile mapping systems based on the use of imaging and positioning sensors mounted on terrestrial (and aerial) vehicles have been developed. Recently, systems characterized by an increased portability have been proposed in order to enable mobile mapping in environments that are difficult to access for vehicles, in particular for indoor environments. In this work the performance of a low-cost mobile mapping system is compared with that of: (i) a state-of-the-art terrestrial laser scanning (TLS), considered as the control; (ii) a mobile mapping backpack system (Leica Pegasus), which can be considered as the state-of-the-art of commercial mobile mapping backpack systems. The aim of this paper is two-fold: first, assessing the reconstruction accuracy of the proposed low-cost mobile mapping system, based on photogrammetry and ultra-wide band (UWB) for relative positioning (and a GNSS receiver if georeferencing is needed), with respect to a TLS survey in an indoor environment, where the global navigation satellite system (GNSS) signal is not available; second, comparing such performance with that obtained with the Leica backpack. Both mobile mapping systems are designed to work without any control point, to enable an easy and quick survey (e.g., few minutes) and to be easily portable (relatively low weight and small size). The case study deals with the 3D reconstruction of a medieval bastion in Padua, Italy. Reconstruction using the Leica Pegasus backpack allowed obtaining a smaller absolute error with respect to the UWB-based photogrammetric system. In georeferenced coordinates, the root mean square (RMS) error was respectively 16.1 cm and 50.3 cm; relative error in local coordinates was more similar, respectively 8.2 cm and 6.1 cm. Given the much lower cost (approximately $6k), the proposed photogrammetric-based system can be an interesting alternative when decimetric reconstruction accuracy in georeferenced coordinates is sufficient. \ua9 2018 by the authors

Breast Milk Hormones and Regulation of Glucose Homeostasis

Growing evidence suggests that a complex relationship exists between the central nervous system and peripheral organs involved in energy homeostasis. It consists in the balance between food intake and energy expenditure and includes the regulation of nutrient levels in storage organs, as well as in blood, in particular blood glucose. Therefore, food intake, energy expenditure, and glucose homeostasis are strictly connected to each other. Several hormones, such as leptin, adiponectin, resistin, and ghrelin, are involved in this complex regulation. These hormones play a role in the regulation of glucose metabolism and are involved in the development of obesity, diabetes, and metabolic syndrome. Recently, their presence in breast milk has been detected, suggesting that they may be involved in the regulation of growth in early infancy and could influence the programming of energy balance later in life. This paper focuses on hormones present in breast milk and their role in glucose homeostasis