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Introduction In Chapter 2 local clouds were discussed followed by a local cloud automation architecture in Chapter 3. The automation architecture supports the implementation of local automation clouds. Such implementation is supported by the Arrowhead Framework and its core systems and services. © 2017 by Taylor & Francis Group, LLC.

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The hospitalization of patients with Heart Failure represents an increasing burden for the healthcare system with more than 23 million worldwide suffering from this disease. In this paper we explore methods to detect fluid retention in the lungs by measuring the thoracic impedance, so that is possible to monitor Heart Failure patients, and physicians can early detect acute episodes. A small and portable device was developed to measure the thoracic impedance of the patient. From the measured thoracic impedance it can estimate the accumulation of fluid in the lungs. This device is a low cost, friendly to use equipment that can be operated by a big range of users: Moreover, it was designed for low power consumption with a rechargeable battery for portable use. The device empowers the patient to monitor his own body fluid at home, and a physician can follow him remotely. This procedure would help to drastically reduce the number of hospitalizations and, consequently, improve the quality of life of people diagnosed with Heart Failure.

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Embedded computers such as Raspberry Pi are gaining market as they offer considerable computation power on a flexible platform that can run different operating systems and user level libraries. There are a number of contributions on building middleware for connecting devices based on embedded computers in various ways; however, the temporal behavior of these systems has not been sufficiently covered, despite the fact that this is essential to validate the system design, operation, and timeliness that is needed in domains such as cyber-physical systems (CPS). This paper analyzes the temporal behavior of the connection among embedded computers and servers in the context of time sensitive deployments where some nodes can be virtualized offering mixed criticality execution platforms. We provide a scheme for using the Data Distribution Service standard to connect embedded computers based on Raspberry Pi and servers to analyze the temporal response stability.

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This study addresses long-term sea level variability in Macaronesia from a holistic perspective using all available instrumental records in the region, including a dense network of GPS continuous stations, tide gauges and satellite observations. A detailed assessment of vertical movement from GPS time series underlines the influence of the complex volcano-tectonic setting of the Macaronesian islands in local uplift/subsidence. Relative sea level for the region is spatially highly variable, ranging from -1.1 to 5.1 mm yr(-1). Absolute sea level from satellite altimetry exhibits consistent trends in the Macaronesia, with a mean value of 3.0 +/- 0.5 mm yr(-1). Typically, sea level trends from tide gauge records corrected for vertical movement using the estimates from GPS time series are lower than uncorrected estimates. The agreement between satellite altimetry and tide gauge trends corrected for vertical land varies substantially from island to island. Trends derived from the combination of GPS and tide gauge observations differ by less than 1 mm yr(-1) with respect to absolute sea level trends from satellite altimetry for 56 per cent of the stations, despite the heterogeneity in length of both GPS and tide gauge series, and the influence of volcanic-tectonic processes affecting the position of some GPS stations.

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In this paper we address the allocation of perception tasks among a set of multiple robots, for tasks such as inspection, surveillance, or search in structured environments. We consider a set of target regions of interest in a mapped environment that need to be sensed by any of the robots, and the problem is to find paths for the robots that cover all the target regions with minimal cost. We consider not only sensing range when determining paths for the robots to perceive the targets, but also a sensor cost function that can be adapted to each robot’s sensor. Thus the planning has to search for paths with minimal motion and perception cost, instead of the traditional approach where line-of-sight is the only requirement in a motion cost minimization problem. Our contribution is to use planning to determine possible perception positions for every robot, which we cluster and then use as possible waypoints that can be used to construct paths for all the robots. Given the combinatorial characteristics of path determination in this setting, we contribute a construction heuristic to find paths that guarantee full coverage of all the feasible perception target regions, while minimizing the overall cost. We assume robots are heterogeneous regarding their geometric properties, such as size and maximum perception range. We consider simulated scenarios where we show the benefits of our approach, enabling multi-robot path planning for perception of multiple regions of interest. © Springer International Publishing AG 2018.