OPEN SOURCE WEB TOOL FOR TRACKING IN A LOWCOST MOBILE MAPPING SYSTEM

During the last decade several Mobile Mapping Systems (MMSs), i.e. systems able to acquire efficiently three dimensional data using moving sensors (Guarnieri et al., 2008, Schwarz and El-Sheimy, 2004), have been developed. Research and commercial products have been implemented on terrestrial, aerial and marine platforms, and even on human-carried equipment, e.g. backpack (Lo et al., 2015, Nex and Remondino, 2014, Ellum and El-Sheimy, 2002, Leica Pegasus backpack, 2016, Masiero et al., 2017, Fissore et al., 2018).<br><br> Such systems are composed of an integrated array of time-synchronised navigation sensors and imaging sensors mounted on a mobile platform (Puente et al., 2013, Tao and Li, 2007). Usually the MMS implies integration of different types of sensors, such as GNSS, IMU, video camera and/or laser scanners that allow accurate and quick mapping (Li, 1997, Petrie, 2010, Tao, 2000). The typical requirement of high-accuracy 3D georeferenced reconstruction often makes such systems quite expensive. Indeed, at time of writing most of the terrestrial MMSs on the market have a cost usually greater than 50000, which might be expensive for certain applications (Ellum and El-Sheimy, 2002, Piras et al., 2008). In order to allow best performance sensors have to be properly calibrated (Dong et al., 2007, Ellum and El-Sheimy, 2002).<br><br> Sensors in MMSs are usually integrated and managed through a dedicated software, which is developed ad hoc for the devices mounted on the mobile platform and hence tailored for the specific used sensors. Despite the fact that commercial solutions are complete, very specific and particularly related to the typology of survey, their price is a factor that restricts the number of users and the possible interested sectors.<br><br> This paper describes a (relatively low cost) terrestrial Mobile Mapping System developed at the University of Padua (TESAF, Department of Land Environment Agriculture and Forestry) by the research team in CIRGEO, in order to test an alternative solution to other more expensive MMSs. The first objective of this paper is to report on the development of a prototype of MMS for the collection of geospatial data based on the assembly of low cost sensors managed through a web interface developed using open source libraries. The main goal is to provide a system accessible by any type of user, and flexible to any type of upgrade or introduction of new models of sensors or versions thereof. After a presentation of the hardware components used in our system, a more detailed description of the software developed for the management of the MMS will be provided, which is the part of the innovation of the project. According to the worldwide request for having big data available through the web from everywhere in the world (Pirotti et al., 2011), the proposed solution allows to retrieve data from a web interface Figure 4. Actually, this is part of a project for the development of a new web infrastructure in the University of Padua (but it will be available for external users as well), in order to ease collaboration between researchers from different areas.<br><br> Finally, strengths, weaknesses and future developments of the low cost MMS are discussed

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

Freeze-drying modeling and monitoring using a new neuro-evolutive technique

This paper is focused on the design of a black-box model for the process of freeze-drying of pharmaceuticals. A new methodology based on a self-adaptive differential evolution scheme is combined with a back-propagation algorithm, as local search method, for the simultaneous structural and parametric optimization of the model represented by a neural network. Using the model of the freeze-drying process, both the temperature and the residual ice content in the product vs. time can be determine off-line, given the values of the operating conditions (the temperature of the heating shelf and the pressure in the drying chamber). This makes possible to understand if the maximum temperature allowed by the product is trespassed and when the sublimation drying is complete, thus providing a valuable tool for recipe design and optimization. Besides, the black box model can be applied to monitor the freeze-drying process: in this case, the measurement of product temperature is used as input variable of the neural network in order to provide in-line estimation of the state of the product (temperature and residual amount of ice). Various examples are presented and discussed, thus pointing out the strength of the too

From TLS survey to 3d solid modeling for documentation of built heritage: The case study of porta savonarola in Padua

It is a matter of fact that 3D visualisation and proper documentation of cultural objects helps to preserve the history and memories of historic buildings, archaeological sites and cultural landscapes, and supports economic growth by stimulating cultural tourism. Preservation, visualisation and recreation of valuable historical and architectural objects and places has always been a serious challenge for specialists in the field. Today, the rapid developments in the fields of close-range photogrammetry, terrestrial laser scanning (TLS) and computer vision (CV) enable to carry out highly accurate 3D models so as to be extremely effective and intuitive for users who have stringent requirements and high expectations. In this note we present the results of the survey and 3D modeling of an ancient gate, Porta Savonarola, located within the remains of the medieval town walls surrounding the historical city center of Padua, Italy. The work has been undertaken within the framework of the project \u201cWalls Multimedia Museum\u201d (WMM) promoted by the local private association \u201cPadua Walls Committee\u201d. The goal of the project was to develop a prototype of an \u201cextended\u201d virtual museum, spreaded along most interesting locations of the town walls. The survey of the ancient gate was performed with a Leica C10 and P20 terrestrial laser scanners. Once the acquired scans were properly merged together, a solid model was generated from the global point cloud, and plans and elevations were extracted from it for restoration purposes. A short multimedia video was also created for the \u201cWalls Multimedia Museum\u201d, showing both the outer and inner part of the gate. In the paper we will discuss all the steps and challenges addressed to provide the 3D solid model of Porta Savonarola from the TLS data

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

DYNAMICS AND CONTROL OF FORCED UNSTEADY-STATE CATALYTIC REACTORS

This research deals with the dynamics and control of forced unsteady-state catalytic reactors and it is focused on two topics: 1. auto-thermal after-treatment of lean VOC mixtures. Two reactor configurations have been taken into consideration: the reverse-flow reactor (RFR), where the flow direction is periodically changed, and the network of two or three reactors (RN), where the flow direction remains the same, but the feeding position is periodically changed, thus simulating a moving bed. This study (§3) has been organised as follows: - modelling of the two reactor configurations and study of the influence of the main operating parameters (§3.1 and §3.2). As the RFR shows higher stability with respect to disturbances in the feed a deeper investigation has been carried out on this device; - optimisation of the RFR. A simplified model has been used for this analysis in order to strongly reduce the computational effort which is required by detailed models. It has been pointed out that both heat capacity and thermal conductivity of the catalyst play a role, not less important than kinetic activity, strongly influencing the minimum inlet VOC concentration required for autothermal operation (§3.3); - experimental validation of the modelling results in a bench-scale RFR with reduced influence of the wall effects. This activity has been carried at the Departamento de Ingeniería Química y Tecnología del Medio Ambiente-Universidad de Oviedo (Spain) in the framework of the Research Project "Azioni Integrate Italia-Spagna", granted by the Italian Ministry of Research (MIUR). In addition to the intrinsecally dynamic behaviour of the RFR, one must deal with unexpected external perturbations (feed concentration, composition and temperature) which may lead to reactor extinction or catalyst overheating. In order to avoid these problems it is necessary to implement some closed-loop control strategy based on the measurement of the inlet concentration (and composition) and the outlet conversion. This study has been organised as follows: - a model-based soft-sensor (observer) has been developed, in order to quickly and reliably estimate the feed composition from some temperature measurements in the reactor, thus avoiding expensive hardware sensors and time consuming on-line measurements. As deriving an observer from a detailed model is an overwhelming task, a simplified model has been developed and validated in a medium size RFR. This research has been carried out in cooperation with prof. H. Hammoury and D. Schweich of the CPE-Lyon, France (§4.1); - a Model Based control strategy has been proposed and tested to prevent reaction extinction and catalyst overheating (§4.2); 2. enhancement of conversion and selectivity in exothermic, equilibriumlimited reactions. Methanol synthesis and syngas prouction by partial oxidation of methane have been considered as test reactions. This section has been organised as follows: - modelling of the two processes in the two reactor configurations previously described. The influence of the main operating conditions has been addressed with the aim to optimise the two processes. As the RN has shown higher conversion and selectivity with respect to the RFR, in the following the research will be focused on this device (§5); - a simple open loop control policy, which can be useful for a safe startup, has been also tested to study the response of the RN to disturbances on the input parameters, showing that a more robust control strategy is needed for this application; - if a tight control on the outlet product conversion is needed, a Model Predictive Control scheme (MPC) should be used, varying the switching time to maximise the conversion and the selectivity of the reactor. The on-line optimisation requires a simplified model and a Neural Network based model has been developed (§6

Model-based optimization of the primary drying step during freeze-drying

Since large molecules are considered the key driver for growth of the pharmaceutical industry, the focus of the pharmaceutical industry is shifting from small molecules to biopharmaceuticals: around 50% of the approved biopharmaceuticals are freeze-dried products. Therefore, freeze-drying is an important technology to stabilise biopharmaceutical drug products which are unstable in an aqueous solution. However, the freeze-drying process is an energy and time-consuming process. The use of mechanistic modelling to gather process knowledge can assist in optimisation of the process parameters during the operation of the freeze-drying process. By applying a dynamic shelf temperature and chamber pressure, which are the only controllable process variables, the processing time can be decreased by a factor 2 to 3