Abstract
The growth of the Blue Economy has been boosted by a set of traditional and new activities including maritime transportation, fisheries, environmental monitoring, deep sea mining, and inspection missions. These activities are urging for a cost-effective broadband communications solution capable of supporting both above and underwater missions at remote ocean areas, since many of them rely on an ever-increasing number of Autonomous Surface Vehicles (ASV), Autonomous Underwater Vehicles (AUV) and Remote Operated Vehicles (ROV), which need to transmit large amounts of data to shore. The BLUE-COM+ project has considered the usage of helium balloons to increase the antenna height, and overtake the earth curvature and achieve Fresnel zone clearance, combined with the use of sub-GHz frequency bands to enable long range communications. In this paper we present the results obtained in three sea trials. They show that the BLUECOM+ architecture is capable of supporting human and system activities at remote ocean areas by enabling Internet access beyond 50 km from shore, live video conference calls with the quality of experience available on land, and real-time data upload to the cloud by ASVs, AUVs and ROVs using standard access technologies with bitrates above 1 Mbit/s.

Abstract
It is well-known that information and communication technologies enable many tasks in the context of precision agriculture. In fact, more and more farmers and food and agriculture companies are using precision agriculture-based systems to enhance not only their products themselves, but also their means of production. Consequently, problems arising from large amounts of data management and processing are arising. It would be very useful to have an infrastructure that allows information and agricultural tasks to be efficiently shared and handled. The cloud computing paradigm offers a solution. In this study, a cloud-based software architecture is proposed with the aim of enabling a complete crop management system to be deployed and validated. Such architecture includes modules developed by using Google App Engine, which allows the information to be easily retrieved and processed and agricultural tasks to be properly defined and planned. Additionally, Google's Datastore (which ensures a high scalability degree), hosts both information that describes such agricultural tasks and agronomic data. The architecture has been validated in a system that comprises a wireless sensor network with fixed nodes and a mobile node on an unmanned aerial vehicle (UAV), deployed in an agricultural farm in the Region of Murcia (Spain). Such a network allows soil water and plant status to be monitored. The UAV (capable of executing missions defined by an administrator) is useful for acquiring visual information in an autonomous manner (under operator supervision, if needed). The system performance has been analysed and results that demonstrate the benefits of using the proposed architecture are detailed.

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Abstract

Abstract
The detection of dissolved carbon dioxide (dCO(2)) is made possible through a colorimetric effect that occurs in a sensitive membrane. The reaction with dCO(2) changes the pH of the membrane causing a small difference in its colour which results in a characteristic absorbance spectrum band near 435 nm. A sensing platform based on this effect was developed and tested in gaseous and in aqueous environments. It is a combination of a bundle of large core fibre optics (with diameters above 200 mu m) with light emission diodes (LEDs) in the visible range of the spectrum, a silicon photodetector and a polymer membrane sensitive to CO2. A variation in the absorption of 3 / %VV was obtained in the range from 0 to 1.6 % of gaseous CO2 with an estimated response time below 60 seconds.

Abstract
It is in the nature of chaotic atmospheric processes that weather forecasts will never be perfectly accurate. This natural fact poses challenges not only for private life, public safety, and traffic but also for electrical power systems with high shares of weather-dependent wind and solar power production. © 2012 IEEE.