M@TE - Monitoring at TeV Energies

Blazars are extremely variable objects emitting radiation across the electromagnetic spectrum and showing variability on time scales from minutes to years. For the understanding of the emission mechanisms, simultaneous multi-wavelength observations are crucial. Various models for flares predict simultaneous flux increases in the X-ray and gamma-ray band or more complex variability patterns, depending on the dominant process responsible for the gamma-ray emission. Monitoring at TeV energies is providing important information to distinguish between different models. To study duty cycle and variability time scales of an object, an unbiased data sample is essential, and good sensitivity and continuous monitoring are needed to resolve smaller time scales. A dedicated long-term monitoring program at TeV energies has been started by the FACT project. Its success clearly illustrated that the usage of silicon based photo sensors (SIPMs) is ideal for long-term monitoring. They provide not only an excellent and stable detector performance, but also allow for observations during bright ambient light minimizing observational gaps and increasing the instrument's duty cycle. The observation time in a single longitude is limited to 6 hours. To study typical variability time scales of few hours to one day, the ultimate goal is 24/7 monitoring with a network of small telescopes around the globe (DWARF project). The installation of an Imaging Air Cherenkov Telescope is planned in San Pedro Martir, Mexico. For the M@TE (Monitoring at TeV energies) telescope, a mount from a previous experiment is being refurbished to be equipped with a camera using the new generation of SiPMs. In the presentation, the status of the M@TE project will be reported outlining the scientific potential, including the possibility to extend monitoring campaigns to 12 hours by coordinated observations together with FACT.Comment: 5 pages, 1 figure. Contribution to the 6th International Symposium on High Energy Gamma-Ray Astronomy (Gamma2016), Heidelberg, Germany. To be published in the AIP Conference Proceeding

Close Approaches of Debris to LARES Satellite During Its First Four Years of Operation

Since its launch in February 2012, the LAser RElativity Satellite (LARES) of the Italian Space Agency experienced four close approaches with space debris. LARES orbits at an altitude of 1450 km, in a region where the density of space debris has a peak. However, the probability of an impact with a debris during the operational life of the satellite was reasonably low. The analysis of the close approaches identified three of the objects, that are from two peculiar population of objects. This paper discusses the problem of space debris in low orbit, the approaches occurred with LARES, and some possible scenarios related to space regulations and space law in case of an impact

Smart environment monitoring through micro unmanned aerial vehicles

In recent years, the improvements of small-scale Unmanned Aerial Vehicles (UAVs) in terms of flight time, automatic control, and remote transmission are promoting the development of a wide range of practical applications. In aerial video surveillance, the monitoring of broad areas still has many challenges due to the achievement of different tasks in real-time, including mosaicking, change detection, and object detection. In this thesis work, a small-scale UAV based vision system to maintain regular surveillance over target areas is proposed. The system works in two modes. The first mode allows to monitor an area of interest by performing several flights. During the first flight, it creates an incremental geo-referenced mosaic of an area of interest and classifies all the known elements (e.g., persons) found on the ground by an improved Faster R-CNN architecture previously trained. In subsequent reconnaissance flights, the system searches for any changes (e.g., disappearance of persons) that may occur in the mosaic by a histogram equalization and RGB-Local Binary Pattern (RGB-LBP) based algorithm. If present, the mosaic is updated. The second mode, allows to perform a real-time classification by using, again, our improved Faster R-CNN model, useful for time-critical operations. Thanks to different design features, the system works in real-time and performs mosaicking and change detection tasks at low-altitude, thus allowing the classification even of small objects. The proposed system was tested by using the whole set of challenging video sequences contained in the UAV Mosaicking and Change Detection (UMCD) dataset and other public datasets. The evaluation of the system by well-known performance metrics has shown remarkable results in terms of mosaic creation and updating, as well as in terms of change detection and object detection