Sensor Network-Based Localization for Continuous Tracking Applications: Implementation and Performance Evaluation

The increasing interest in systems able to provide users with immersive services (e.g., domotics, context-aware applications, and immersive distance learning tools) has encouraged the development of cheap and effective platforms aimed at tracking objects and people within a certain space. In this context, wireless sensor networks (WSNs) can play a very important role, since specialized sensors can be fruitfully exploited in order to generate/receive signals by means of which the WSN can derive the position of nodes joined to the objects to be tracked. The paper presents an original localization platform that exploits a single-hop WSN, based on a Microchip MCU and a Cypress RF device, to track its moving nodes. Specifically, the nodes of the network are divided into three sets: the first set consists of anchor nodes that, according to the commands from the sink (the central node of the WSN), generate ultrasonic pulses. These pulses are received by the second set of (moving) nodes, which estimate the pulse time trip and communicate it to the sink. Finally, the last set is constituted by general purpose nodes that collect any kind of data from the surrounding field. The sink gathers all the data, computes the position of moving nodes, and transfers information to external users on the Internet. The algorithms adopted to manage the network and to localize moving nodes are discussed. A working prototype based upon the hardware platform, software, and protocol described in this paper has been deployed and tested, and some results are shown. Simulation results of the localization system are presented to show system scalability

remote laboratory experiments in a virtual immersive learning environment

TheVirtual Immersive Learning(VIL) test bench implements a virtual collaborative immersive environment, capable of integrating natural contexts and typical gestures, which may occur during traditional lectures, enhanced with advanced experimental sessions. The system architecture is described, along with the motivations, and the most significant choices, both hardware and software, adopted for its implementation. The novelty of the approach essentially relies on its capability of embedding functionalities that stem from various research results (mainly carried out within the VICOM national project), and "putting the pieces together" in a well-integrated framework. These features, along with its high portability, good flexibility, and, above all, low cost, make this approach appropriate for educational and training purposes, mainly concerning measurements on telecommunication systems, at universities and research centers, as well as enterprises. Moreover, the methodology can be employed for remote access to and sharing of costly measurement equipment in many different activities. The immersive characteristics of the framework are illustrated, along with performance measurements related to a specific application

Commissioning and improvements of the instrumentation and launch of the scientific exploitation of OARPAF, the Regional Astronomical Observatory of the Antola Park

The OARPAF telescope is an 80-cm-diameter optical telescope installed in the Antola Mount Regional Reserve, in Northern Italy. We present the results of the characterization of the site, as well as developments and interventions that have been implemented, with the goal of exploiting the facility for scientific and educational purposes. During the characterization of the site, an average background brightness of 22.40mAB (B filter) to 21.14mAB (I) per arcsecond squared, and a 1.5″ to 3.0″ seeing, have been measured. An estimate of the magnitude zero points for photometry is also reported. The material under commissioning includes three CCD detectors for which we provide the linearity range, gain, and dark current; a 31-orders échelle spectrograph with R ∼ 8500 to 15,000 and a dispersion of n = 1.39 × 10 − 6 px − 1λ + 1.45 × 10 − 4 nm / px, where λ is expressed in nm. The scientific and outreach potential of the facility is proven in different science cases, such as exoplanetary transits and active galactic nuclei variability. The determination of time delays of gravitationally lensed quasars, the microlensing phenomenon, and the tracking and the study of asteroids are also discussed as prospective science cases

Asset tracking architecture with Bluetooth Low Energy tags and ad hoc smartphone applications

The paper describes an original architecture aimed at tracking assets within construction sites or similar contexts. The main components are: i) RFID tags, ii) Bluetooth Low Energy (BLE) tags and iii) smartphones. The core functions of the architecture are performed by two Android applications: the Asset Proximity Locator (APL) and the Wandering Objects Location Finder (WOLF). The key feature of the asset tracking function is the ability to maximize smartphone battery lifetime by switching on and off the GPS unit, thus guaranteeing that the smartphone can be used for an entire working shift. A detailed energy consumption analysis is carried out for each component of the architecture. The results achieved by simulations, concerning BLE tag detection probability, are presented and discussed

Asset tracking solution with BLE and smartphones: An energy/position accuracy trade-off

This paper presents a new asset tracking system that integrates a classical tracking solution with the Bluetooth Low Energy (BLE) technology and the opportunities offered by smartphones. The proposed platform has been explicitly designed and implemented to be employed in construction sites and was tested in a real environment. The solution aims at guaranteeing a two-fold requirement: i) a good level of precision in terms of accuracy of the position of the asset location and completeness of the acquired information (i.e., detection of all the tagged assets) and, at the same time, ii) saving smartphones' resources such as CPU, memory and, in particular, energy

A new asset tracking architecture integrating RFID, Bluetooth Low Energy tags and ad hoc smartphone applications

The paper describes an original architecture aimed at tracking assets within construction sites. The main components are Radio Frequency IDentification (RFID), Bluetooth Low Energy (BLE) tags and smartphones. The core functions are performed by two Android applications, which implement asset tracking and searching. The main merits of the architecture are its ability to maximize smartphone battery lifetime, that can reach an entire working shift, very satisfactory accuracy of BLE tag-smartphone distance estimation (with a mean error around 2 [m]), high probability of detecting all the tags present in the construction site, as well as a suitably short Aging time

Support Vector Machine Meets Software Defined Networking in IDS Domain

Intrusion Detection Systems (IDS) are aimed at analyzing and detecting security problems. IDS based on anomaly detection and, in particular, on statistical analysis, inspect each traffic flow in order to get its statistical characterization, which represents the fingerprint of the flow. Software Defined Networking (SDN) is revolutionizing the networking industry by enabling programmability, easier management and faster innovation. These benefits are made possible by its centralized control plane architecture which allows the network to be programmed and controlled by one central entity. The fusion of these two technologies can lead to an innovative system of malware detection. This paper tries to join these two concepts in order to obtain the best from the two worlds. We use a well known machine learning scheme (Support Vector Machine) as core system for detecting malware by using only traffic features that can be extracted using an SDN controller

Trace and ultratrace elements in spinel subgroup minerals of ultramafic rocks from the Voltri Massif (NW Italy): the influence of microstructure and texture

An innovative multi-analytical approach comprising mineralogical, minero-chemical, and microstructural analyses as well as an indirect machine learning-based statistical method was applied to investigate the mineralogy and the mineral chemistry of spinel subgroup minerals (SSMs) of different ultramafic rocks from the high-pressure metaophiolites of the Voltri Massif (Central Liguria, NW Italy). The study was focused on the correlation between the compositional variations of SSMs and their texture, microstructure, and the degree of serpentinization of the host rock. The SSM occurs with three main textures and microstructures linked to the progressive serpentinization and deformation of ultramafic rocks during the Alpine orogenic events: (i) Cr-spinel porphyroclasts with various degrees of recrystallization (up to magnetite porphyroblasts) within partially serpentinized peridotite and massive serpentinite; (ii) magnetite crystals associated with pseudomorphic and non-pseudomorphic serpentine textures (e.g., mesh, hourglass, ribbon, and interpenetrating textures) in partially serpentinized peridotite and massive serpentinites; and (iii) magnetite crystals re-oriented along the foliations developed in serpentine schist. The chemical composition of SSMs varies systematically within the textures and microstructures. These processes also affected the chemical composition of SSMs, the availability of Mn, Zn, Ni, and Co in solution, and their consequent incorporation in the lattice of chromian spinel due to olivine breakdown, the major repository of these elements in ultramafic rocks. At a general scale, the trace and ultratrace variability is primarily related to the petrologic and tectonic evolution but, at a local scale, also the mineralogical, lithological, structural, and textural features correlated to the degree of serpentinization and/or deformation. These significantly influence the distribution and concentration of trace and ultratrace elements in SSMs. The results of the present work were also confirmed by an innovative indirect statistical method performed through the Weka Machine Learning Workbench