In recent years, the development of low-cost GNSS sensors allowed monitoring in a continuous way movement related to natural processes like landslides with increasing accuracy and limited efforts. In this work, we present the first results of an experimental low-cost GNSS continuous monitoring applied to an unstable slope affecting the Madonna del Sasso Sanctuary (NW Italy). The courtyard of Sanctuary is built on two unstable blocks delimited by a high cliff. Previous studies and non-continuous monitoring showed that blocks suffer a seasonal cycle of thermal expansion and a long-term trend to downslope a few millimeters (2/3) per year. The presence of a continuous monitoring solution could be an essential help to better understand the kinematics of unstable slope. Continuous monitoring could help to forecast a possible paroxysm phase that could end with a failure of the unstable area. The first year of experimental measurements shows a millimetric accuracy of low-cost GNSS, and the long-term trend is in agreement with other monitoring data. We also propose a methodological approach that considers the use of semi-automatized procedures for the identification of anomalous trends and a risk communication strategy. Pro and cons of the proposed methodology are also discussed.
The protection of the Ocean has become one of the most urgent points in the world environmental agenda. The ResponSEAble project, funded by the H2020 European program, aims to increase the awareness of European people about the impact of the Ocean, called Ocean Literacy. The focus is about the development of the applied game on Ocean Literacy.
Monitoring of extreme events requires accurate measurement of rainfall intensities and merging weather radar data with ground information is a very common technique used to obtain the required precision. In order to do this, several methods exist but very few open source implementations are available. CondMerg is the first open source software developed in R language implementing the conditional merging method and some other experimental variants based on it. It is a cross-platform software, easily adaptable to different needs, optimized for batch processing of multiple events but also usable in near real time applications. For its execution it requires two inputs: a CSV file with rain gauges measurements and a geo-referred TIF file with weather radar quantitative precipitation estimations; main outputs are TIF files with merged observations although the code also returns information about cross-validation, with scatter plots and indexes. All TIF files are ready to be managed by common GIS software for easy visualization and analysis. Use of the program is very simple: execution can be interactive or non-interactive and, in both cases, it just requires to set some parameters at the beginning of the program and run it. The code has been tested on different extreme rain events occurred in the Piedmont region (northwestern Italy) showing improved accuracy of reconstructed rainfall fields.
For the management of a (micro)-smart grid it is important to know the patters of the load profiles and of the generators. In this article the power consumption data obtained through a monitoring activity developed on a micro-smart grid in an agro-industrial test-site are presented. In particular, this reports the synthesis of the monitoring results of 5 loads (5 industrial machineries for crop micronization, corncob crashing and other similar processes). How these data were used within a monitoring and managing scheme of a micro-smart grid can be found in (E. Fabrizio, V. Branciforti, A. Costantino, M. Filippi, S. Barbero, G. Tecco, P. Mollo, A. Molino, 2017) . The data can be useful for other researchers in order to create benchmarks of energy use input appropriate energy demand values in optimization tools for the industrial sector.
Open Education strategies, and specifically MOOC (Massive Open Online Courses) and OER (Open Educational Resources), play a particularly important role in supporting policies for educational innovation, employability, lifelong learning, support the third mission strategies in higher education and, more generally, the enlargement of educational opportunities for all. While there is an increasing interest in Open Education, there is little awareness about the role of Digital Library for learning enhancement. The paper presents briefly the state of art of digital libraries in Italy in the light of the most recent initiatives of Open Education, towards an integrated model of digital libraries as " knowledge and learning open hubs " .
The development of smart grids is a strategic goal at both national and international levels and has been funded by many research programs. At the same time, an increasing interest is rising about local energy systems using renewable energy sources (RES). In this paper, the creation of a monitoring and managing procedure of an electricity micro-smart grid in a small agro-food enterprise is presented. Scopes of the procedure are both the minimization of the energy exchange between the local grid and the public utility grid and the optimization of the exploitation of renewable sources. To achieve that, it was necessary to match energy demand and supply in as short as possible time steps, trying to create a self-sufficient small district. The two objectives above can also generate financial savings due to the reduction of the electricity purchase from the grid. The agro-industrial test site is a prosumer (both a producer and a consumer of energy) and it was equipped with wireless networks of smart meters and devices, monitoring generators and loads, a data acquisition tool and a user interface that shows the monitoring results and suggests the optimization strategies of the smart grid to be undertaken.
Research on intelligent and reconfigurable wireless systems is in continuous evolution. Nevertheless, in order to fix some keystones, more and more researchers are entering the idea of research-oriented test beds. Unfortunately, it is very difficult for a wide number of research groups to start with their own set up, since the potential costs and efforts could not pay back in term of expected research results. Software Defined Radio solutions offer an easy way to communication researchers for the development of customized research test beds. While several hardware products are commercially available, the software is most of the times open source and ready to use for third party users. Even though the software solution developers claim complete easiness in the development of custom applications, in reality there are a number of practical hardware and software issues that research groups need to face, before they are up and running in generating results. With this chapter we would like to provide a tutorial guide, based on direct experience, on how to enter in the world of test bed-based research, providing both insight on the issues encountered in every day development, and practical solutions. Finally, an overview on common research-oriented software products for SDR development, namely GNU Radio, Iris, and ASGARD, will be provided, including how to practically start the software development of simple applications. Finally, best practices and examples of all the software platforms will be provided, giving inspiration to researchers on how to possibly build their own customized systems.
The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.
We present a procedure to use micro-UAV (Unmanned Aerial Vehicles) to perform photogrammetry survey and monitoring analysis in landslide scenarios. The employed methodology is mainly composed of two phases: the first one is the UAV mission planning and execution, while the latter is the picture elaboration and alignment. The UAV used during all tests here described has been developed for photographic applications. Thanks to its "V" shape, propellers do not fall within camera field during normal flight operation and the eight motors configuration ensures more reliability in urban areas uses than a classical quadcopter configuration. The processing of the acquired photos relies on both standard photogrammetry procedure as well as innovative methods for photo alignment derived from computer vision algorithms. Examples of application are also provided to show the results and the potential of this methodology in real landslide scenarios.
The last decade has seen the success of satellite based navigation applications in the ordinary people’s life. New services with demanding performance are boosting also the development of improved technologies for navigation receivers. Although the navigation technology also rapidly evolved towards more complex signal processing techniques, when compared to communication receivers, GNSS receivers are dealing with signals of smaller bandwidth and much lower data-rates, thus making them appealing for Software-based implementations, considering both Hardware/Software platforms and fully software implementations. This chapter will provide a discussion of the technological challenges for the implementation of software positioning receivers, also discussing as examples of general validity the implementation of acquisition and tracking stages in a fully software receiver.
This chapter describes a set of spectrum sensing algorithms to be employed for the detection of Ortogonal Frequency Division Multiplexing transmissions in the TV bands (470–790 MHz), like DVB-T signals. Spectrum sensing techniques take a crucial role to support geo-referenced TV White-Spaces (TVWS) databases and to maintain them up-to-date over time. When considering a single-antenna spectrum sensing unit, very effective methods for detecting OFDM signals are based on DVB-T cyclic prefix and pilot pattern feature detection. Starting from these, further improvements can be obtained using multi-antenna techniques. This chapter shows performance analysis of feature-based single-antenna and multi-antenna techniques in order to derive trade-offs and conclusions.
A Cognitive Radio (CR) system can be visualised in Fig. 15.1 as a complicated wireless communication system that involves a virtual engine (soul) and a platform (body). The engine is implemented based on a number of logical arguments in order to reason and negotiate with other wireless systems, aiming towards the optimum utilisation of the spectrum while ensuring minimum disruption to existing wireless systems.
Automatic network recognition and classification may prove to be an important concept in the framework of cognitive radio and networks. For practical implementations, these operations must be carried out in a simple way by using simple devices and algorithms that require low computational load. The AIR-AWARE approach proposes to use MAC sub-layer features for technology recognition purposes where a rudimentary device like an energy detector is used for technology-specific feature extraction. The aim of this work is automatic Bluetooth classification. To this purpose, two MAC features reflecting properties, related to the time-varying pattern of MAC packet exchanges, are proposed. Experimental data obtained by using the Universal Software Radio Peripheral as energy detector show that the two proposed features are capable of highlighting MAC sub-layer behavior peculiar to Bluetooth. These features may therefore lead to successful Bluetooth recognition and the results obtained provide support to the validity of the AIR-AWARE approach.
Cognitive radio networks operating in the digital television white spaces are of particular interest for their practical applications. In this paper, we review several parametric and non-parametric test statistics commonly used in spectrum sensing. Both single-antenna as well as multiple antenna techniques are considered. For a selected subset of these techniques, an accurate performance assessment is carried out in the presence of a DVB-T primary signal generated using a software-defined real-time transmitter. Sensing performance is assessed both through Monte Carlo simulation and using a real software-defined radio implementation. Different channel profiles are considered. The obtained results show the performance of each algorithm in terms of detection probability under fixed false alarm rate and of Receiver Operating Curve (ROC). Moreover, these results permit to establish clear relationships between the considered algorithms in case of DVB-T primary signals.
The development of ICT infrastructures has facilitated the emergence of new paradigms for looking at society and the environment over the last few years. Participatory environmental sensing, i.e. directly involving citizens in environmental monitoring, is one example, which is hoped to encourage learning and enhance awareness of environmental issues. In this paper, an analysis of the behaviour of individuals involved in noise sensing is presented. Citizens have been involved in noise measuring activities through the WideNoise smartphone application. This application has been designed to record both objective (noise samples) and subjective (opinions, feelings) data. The application has been open to be used freely by anyone and has been widely employed worldwide. In addition, several test cases have been organised in European countries. Based on the information submitted by users, an analysis of emerging awareness and learning is performed. The data show that changes in the way the environment is perceived after repeated usage of the application do appear. Specifically, users learn how to recognise different noise levels they are exposed to. Additionally, the subjective data collected indicate an increased user involvement in time and a categorisation effect between pleasant and less pleasant environments.
In cognitive radio networks, systems operating in digital television white spaces are particularly interesting for practical applications. In this paper, we consider single- antenna and multi-antenna spectrum sensing of real DVB-T signals under different channel conditions. Some of the most important algorithms are considered and compared, including energy detection, eigenvalue based techniques and methods exploiting OFDM signal knowledge. The obtained results show the algorithm performance and hierarchy in terms of ROC and detection probability under fixed false alarm rate, for different channel profiles in case of true DVB-T signals.
Invited Papers Digital culture and the remix culture it has generated have changed the way in which knowledge and learning are constructed. The last decade since the Massachusetts Institute of Technology (MIT) launched the Open Courseware initiative (OCW) in 2002 has seen a significant increase in the number of initiatives related to Open Educational Resources (OER) and open education in general. New institutions, with different objectives and business models, are emerging rapidly outside traditional universities: start-ups that offer free Massive Open Online Courses (MOOC), consortia of universities from four continents that share teaching materials and infrastructure, and universities where classes are taught by the students themselves. This paper seeks to provide a historical overview of developments in the world of open education 1 and a look at the key challenges that it faces. | It considers how technology has altered the way in which information is obtained and shared and the consequences this has for the organization of education, from online learning to the flipped classroom. It also shows how roles and the balance of power between producers and consumers of content have become blurred leading to new possibilities for learning in different ways such as MOOCs, from peers and networks, etc. The new learning opportunities on offer can reach new groups of learners, a challenge that universities cannot ignore.
Digital culture and the remix culture it has generated have changed the way in which knowledge and learning are constructed. The last decade since the Massachusetts Institute of Technology (MIT) launched the Open Courseware initiative (OCW) in 2002 has seen a significant increase in the number of initiatives related to Open Educational Resources (OER) and open education in general. New institutions, with different objectives and business models, are emerging rapidly outside traditional universities: start-ups that offer free Massive Open Online Courses (MOOC), consortia of universities from four continents that share teaching materials and infrastructure, and universities where classes are taught by the students themselves. This paper seeks to provide a historical overview of developments in the world of open education and a look at the key challenges that it faces. It considers how technology has altered the way in which information is obtained and shared and the consequences this has for the organization of education, from online learning to the flipped classroom. It also shows how roles and the balance of power between producers and consumers of content have become blurred leading to new possibilities for learning in different ways such as MOOCs, from peers and networks, etc. The new learning opportunities on offer can reach new groups of learners, a challenge that universities cannot ignore.
The implementation of a common control channel is one of the most challenging issues in cognitive radio networks, since a fully reliable control channel cannot be created without reserving bandwidth specifically for this purpose. In this paper, we investigate a promising solution that exploits the ultra wide band (UWB) technology to let cognitive radio nodes discover each other and exchange control information for establishing a communication link. The contribution of this paper is threefold: (i) We define the communication protocol needed to let cognitive radio nodes discover each other and exchange control information for link set up, (ii) we overcome the gap in coverage, which typically exists between UWB and long-medium range technologies, by using multi-hop communication, (iii) we evaluate the performance of our approach by adopting an accurate channel model and show its benefits with respect to an in-band signaling solution.
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