Feasibility of a photovoltaic-thermoelectric generator: performance analysis and simulation results

This paper describes a theoretical approach to evaluate the performance of a hybrid solar system made with photovoltaic cells and thermoelectric (TE) modules. After a brief treatment of the integrated system, energy conversion and performance parameters are evaluated through numerical simulations depending on the global radiation and temperature distribution obtained by the Joint Research Center of the European Commission and of the National Renewable Energy Laboratory. The contribution of TE module to total energy seems significant in southern European towns and less substantial when the locations considered are very distant from the equator and show the possibility of using TE devices for energy production

An Automatic Reader of Identity Documents

Identity documents automatic reading and verification is an appealing technology for nowadays service industry, since this task is still mostly performed manually, leading to waste of economic and time resources. In this paper the prototype of a novel automatic reading system of identity documents is presented. The system has been thought to extract data of the main Italian identity documents from photographs of acceptable quality, like those usually required to online subscribers of various services. The document is first localized inside the photo, and then classified; finally, text recognition is executed. A synthetic dataset has been used, both for neural networks training, and for performance evaluation of the system. The synthetic dataset avoided privacy issues linked to the use of real photos of real documents, which will be used, instead, for future developments of the system.Comment: 6 pages, 9 figure

Long-Term Monitoring of Photovoltaic Plants

This paper deals with a data-acquisition system that has been specifically developed for a long-term monitoring of ten different photovoltaic plants. The main goals of the system consist in estimating the drift of the plant components, mainly photovoltaic modules and power inverters, and comparing the performance of the ten plants, which are based on different technologies and architectures. Owing to these goals, the traceabilityassurance of the obtained measurements is mandatory, hence the data-acquisition system has been designed to be easily calibrated and, if necessary, adjusted to compensate for measuring-chain drifts. In addition, the measurement uncertainty, which has to be suitable to distinguish the behaviour of the different PV plants, has to be stated for each of the estimated parameters. A brief description of the data-acquisition system is provided and its measurement capabilities are highlighted in terms of measured quantities and expected uncertainty. Results that refer to a period of thirty months are also reported

A novel electromagnetic tracking system for surgery navigation

Objective: This paper proposes the development of a novel electromagnetic tracking system for navigation surgery. Main objective is to provide a system able to operate in a wide tracking volume to make easier and efficient the surgical procedures by assuring high measurement accuracy. Methods: A new field generator consisting in five transmitting coils excited with Frequency Division Multiplexing technique has been developed. Attention is devoted to designing and arrangement of the coils to assure high sensitivity, system scalability and a homogeneous magnetic field inside working volume. A suitable technique based on Look-Up-Table is applied for sensor position calculation and an anthropomorphic robot is used for table calibration. Results: Experimental tests highlight a good repeatability of the measurement data and a negligible noise influence for the proposed system. The obtained tracking volume is wider with respect to the commercial tracking device used in surgical applications and seem promising. Conclusion: The main characteristic of the developed system consists of: scalable and modular configuration of Field Generator, high measured sensitivity due to the increased number of transmitting coils with respect to the classical configuration and large tracking volume. The development of the proposed magnetic tracking systems with high accuracy and wide working volume allows to promote broader utilization of advantaged techniques in surgery procedures for both improving the effectiveness and decreasing the invasiveness of medical interventions

A virtual platform for real-time performance analysis of electromagnetic tracking systems for surgical navigation

Electromagnetic Tracking Systems (EMTSs) are widely used in surgical navigation, allowing to improve the outcome of diagnosis and surgical interventions, by providing the surgeon with real-time position of surgical instruments during medical procedures. However, particular effort was dedicated to the development of efficient and robust algorithms, to obtain an accurate estimation of the instrument position for distances from the magnetic field generator beyond 0.5 m. Indeed, the main goal is to improve the limited range of current commercial systems, which strongly affects the freedom of movement of the medical team. Studies are currently being conducted to optimize the magnetic field generator configuration (both geometrical arrangements and electrical properties) since it affects tracking accuracy. In this paper, we propose a virtual platform for assessing the performance of EMTSs for surgical navigation, providing real-time results and statistics, and allowing to track instruments both in real and simulated environments. Simulations and experimental tests are performed to validate the proposed virtual platform, by employing it to assess the performance of a real EMTS. The platform offers a real-time tool to analyze EMTS components and field generator configurations, for a deeper understanding of EMTS technology, thus supporting engineers during system design and characterization.</p

Fast Detection of Olive Trees Affected by Xylella Fastidiosa from UAVs Using Multispectral Imaging

Xylella fastidiosa (Xf) is a well-known bacterial plant pathogen mainly transmitted by vector insects and is associated with serious diseases affecting a wide variety of plants, both wild and cultivated; it is known that over 350 plant species are prone to Xf attack. In olive trees, it causes olive quick decline syndrome (OQDS), which is currently a serious threat to the survival of hundreds of thousands of olive trees in the south of Italy and in other countries in the European Union. Controls and countermeasures are in place to limit the further spreading of the bacterium, but it is a tough war to fight mainly due to the invasiveness of the actions that can be taken against it. The most effective weapons against the spread of Xf infection in olive trees are the detection of its presence as early as possible and attacks to the development of its vector insects. In this paper, image processing of high-resolution visible and multispectral images acquired by a purposely equipped multirotor unmanned aerial vehicle (UAV) is proposed for fast detection of Xf symptoms in olive trees. Acquired images were processed using a new segmentation algorithm to recognize trees which were subsequently classified using linear discriminant analysis. Preliminary experimental results obtained by flying over olive groves in selected sites in the south of Italy are presented, demonstrating a mean S&oslash;rensen&ndash;Dice similarity coefficient of about 70% for segmentation, and 98% sensitivity and 93% precision for the classification of affected trees. The high similarity coefficient indicated that the segmentation algorithm was successful at isolating the regions of interest containing trees, while the high sensitivity and precision showed that OQDS can be detected with a low relative number of both false positives and false negatives