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.

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.

In recent years, Unmanned Aerial Vehicles (UAVs) are attracting more and more attention in both the research and industrial communities: indeed, the possibility to use them in a wide range of remote sensing applications makes them a very flexible and attractive solution in both civil and commercial cases (e.g. precision agriculture, security and control, monitoring of sites, exploration of areas difficult to reach). Most of the existing UAV positioning systems rely on the use of the GPS signal. Despite this can be a satisfactory solution in open environments where the GPS signal is available, there are several operating conditions of interest where it is unavailable or unreliable (e.g. close to high buildings, or mountains, in indoor environments). Consequently, a different approach has to be adopted in these cases. This paper considers the use ofWiFi measurements in order to obtain position estimations of the device of interest. More specifically, to limit the costs for the devices involved in the positioning operations, an approach based on radio signal strengths (RSS) measurements is considered. Thanks to the use of a Kalman filter, the proposed approach takes advantage of the temporal dynamic of the device of interest in order to improve the positioning results initially provided by means of maximum likelihood estimations. The considered UAVs are assumed to be provided with communication devices, which can allow them to communicate with each other in order to improve their cooperation abilities. In particular, the collision avoidance problem is examined in this work.

In this work we present preliminary results regarding a proof-of-concept project which aims to provide tools for mapping the amount of solar radiation reaching surfaces of objects, accounting for obstructions between objects themselves. The implementation uses the NASA World Wind development platform (NASA WW) to model the different physical phenomena that participate in the process, from the calculation of the Sun’s position relative to the area that is being considered, to the interaction between atmosphere and solid obstructions, e.g., terrain or buildings. A more complete understanding of the distribution of energy from the Sun illuminating elements on the Earth’s surface adds value to applications ranging from planning the renewable energy potential of an area to ecological analyses.

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’s equation is offered as a packaging decision support system.