Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England.

We investigate the spatial and temporal englacial and subglacial processes associated with a temperate glacier resting on a deformable bed using the unique Glacsweb wireless in situ probes (embedded in the ice and the till) combined with other techniques [including ground penetrating radar (GPR) and borehole analysis]. During the melt season (spring, summer and autumn), high surface melt leads to high water pressures in the englacial and subglacial environment. Winter is characterized by no surface melting on most days (‘base’) apart from a series of positive degree days. Once winter begins, a diurnal water pressure cycle is established in the ice and at the ice/sediment interface, with direct meltwater inputs from the positive degree days and a secondary slower englacial pathway with a five day lag. This direct surface melt also drives water pressure changes in the till. Till deformation occurred throughout the year, with the winter rate approximately 60% that of the melt season. We were able to show the bed comprised patches of till with different strengths, and were able to estimate their size, relative percentage and temporal stability. We show that the melt season is characterized by a high pressure distributed system, and winter by a low pressure channelized system. We contrast this with studies from Greenland (overlying rigid bedrock), where the opposite was found. We argue our results are typical of soft bedded glaciers with low englacial water content, and suggest this type of glacier can rapidly respond to surface‐driven melt. Based on theoretical and field results we suggest that the subglacial hydrology comprises a melt season distributed system dominated by wide anastomosing broad flat channels and thin water sheets, which may become more channelized in winter, and more responsive to changes in meltwater inputs. © 2019 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.

Erica the Rhino is an interactive art exhibit created by the University of Southampton, UK. Erica was created as part of a city wide art trail in 2013 called “Go! Rhinos”, curated by Marwell Wildlife, to raise awareness of Rhino conservation. Erica arrived as a white fibreglass shell which was then painted and equipped with five Raspberry Pi Single Board Computers (SBC). These computers allowed the audience to interact with Erica through a range of sensors and actuators. In particular, the audience could feed and stroke her to prompt reactions, as well as send her Tweets to change her behaviour. Pi SBCs were chosen because of their ready availability and their educational pedigree. During the deployment, ‘coding clubs’ were run in the shopping centre where Erica was located, and these allowed children to experiment with and program the same components used in Erica. The experience gained through numerous deployments around the country has enabled Erica to be upgraded to increase reliability and ease of maintenance, whilst the release of the Pi 2 has allowed her responsiveness to be improved.

Libvips is an open source image processing library originally created for museum imaging projects through a range of EU-funded projects from 1989 onwards. The challenges of processing images which were much larger than available RAM as well as coping with multi-band multi-format pixels led to an extremely efficient software design. It also makes automatic use of multi-core CPUs. Today libvips is used by many websites due to its speed and low memory use (from Wikipedia to shopify and booking.com). It is OSS Fuzz tested by Google as it is classed as essential Internet software. It has been used in many museum imaging projects to stitch X-ray images and process massive scans (e.g. The battle of Murten 1.6 TerraPixel scan). Tiled pyramidal tiff images made for multi-resolution web-browsing are easily made and handled by libvips and its viewer vipsdisp. A spreadsheet-like GUI called nip is also useful for experimenting with image processing. These features make it a useful tool for processing images in the earth sciences, especially when sizes are larger than 32 GiB when most desktop or laptop computers struggle with typical software. Python can use the library (pyvips) which makes it easy to use with other tools but can also be used from C, C++, Ruby and Javascript.

Wireless sensor networks, like other computing platforms, require software updates from time to time due to software bugs, new functionality, better understanding of the surrounding environment or new applications. Physically connecting to and reprogramming each node is usually not feasible and often impossible. A number of wireless code distribution and reprogramming techniques have been presented. In this paper we present a novel technique to efficiently update any nodes that were lost during programming periods. Our experiments demonstrate a 57% decrease of bytes sent over the air when updating nodes that previously missed updates.