A wireless sensor network system deployment for detecting stick slip motion in glaciers

The behaviour of glaciers is an area in which only limited research has been carried out due to the difficulties of monitoring sub-glacial movements. The authors believe that this can be addressed by the deployment of a wireless sensor network, consisting of heterogeneous sensors to instrument this activity. By deploying a sensor network measurements can be taken for a longer period than would otherwise be possible. The initial designs for this sensor network are presented along with details of some of the challenges posed by the project

Poster Abstract:Deploying a 6LoWPAN, CoAP, low power, wireless sensor network

In order to integrate equipment from different vendors, wireless sensor networks need to become more standardized. Using IP as the basis of low power radio networks, together with application layer standards designed for this purpose is one way forward. This research focuses on implementing and deploying a system using Contiki, 6LoWPAN over an 868 MHz radio network, together with CoAP as a standard application layer protocol. A system was deployed in the Cairngorm mountains in Scotland as an environmental sensor network, measuring streams, temperature profiles in peat and periglacial features. It was found that RPL provided an effective routing algorithm, and that the use of UDP packets with CoAP proved to be an energy efficient application layer. This combination of technologies can be very effective in large area sensor networks

Britain’s highest bog: can we unlock its secrets?

The Glenfeshie Mòine Mhór (Great Moss) is Britain’s highest bog, the largest bog in the Cairngorm Mountains (Scotland) and a water source area for the River Spey. The area was managed primarily for sport hunting for about two centuries, but deer numbers have been heavily reduced in the last decade to allow regeneration of natural woodland and the return to more natural condition of all ecosystems including peatland. However, it may not be realistic to expect spontaneous improvement in peatland condition and ecosystem services provision in the harsh environment of the Mòine Mhór, which retains snow cover for more than half the year and differs floristically from lower-altitude bogs. To understand whether and where management intervention may be required, we need first to understand how the system works at scales ranging from microform to macrotope, and from sub-catchment to whole-system level. Multi-disciplinary condition and process studies (involving various collaborators) are in progress, with a current emphasis on streamflow generation and fluvial carbon loads. This presentation develops two sub-themes. First, ground survey and GIS analysis are used to address the questions: what are the special features of this bog; what is the nature and extent of degradation; and what are the implications for water delivered to the outflow streams? Secondly, a striking feature is the bare peat patches which were favourite resting places for deer on warm, dry summer days. The occurrence of seasonally extreme surface conditions seems a likely factor in preventing their recolonisation by bog plants now. Information about these conditions that cannot readily be accessed through direct observation, originating from temperature sensors and delivered at 60-minute intervals via a low power internet link, is explored in this context. Finally, we discuss aspects of the suitability of our investigation methods for remote and intermittently accessible field sites such as the Mòine Mhór

Erica the Rhino: a case study in using Raspberry Pi Single Board Computers for interactive art

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 5 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, 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

Author Correction: Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment

Correction to: Scientific Reports https://doi.org/10.1038/s41598-019-43716-3, published online 16 May 2019. This Article contains a typographical error in the Acknowledgements section. “Natural Environmental Research Council grant number [NE/L002531/1]” should read: “Natural Environment Research Council: NE/N012070/1”

Laboratory comparison of low-cost particulate matter sensors to measure transient events of pollution

Airborne particulate matter (PM) exposure has been identified as a key environmental risk factor, associated especially with diseases of the respiratory and cardiovascular system and with almost 9 million premature deaths per year. Low-cost optical sensors for PM measurement are desirable for monitoring exposure closer to the personal level and particularly suited for developing spatiotemporally dense city sensor networks. However, questions remain over the accuracy and reliability of the data they produce, particularly regarding the influence of environmental parameters such as humidity and temperature, and with varying PM sources and concentration profiles. In this study, eight units each of five different models of commercially available low-cost optical PM sensors (40 individual sensors in total) were tested under controlled laboratory conditions, against higher-grade instruments for: lower limit of detection, response time, responses to sharp pollution spikes lasting <1 min , and the impact of differing humidity and PM source. All sensors detected the spikes generated with a varied range of performances depending on the model and presenting different sensitivity mainly to sources of pollution and to size distributions with a lesser impact of humidity. The sensitivity to particle size distribution indicates that the sensors may provide additional information to PM mass concentrations. It is concluded that improved performance in field monitoring campaigns, including tracking sources of pollution, could be achieved by using a combination of some of the different models to take advantage of the additional information made available by their differential response

Commodity single board computer clusters and their applications

© 2018 Current commodity Single Board Computers (SBCs) are sufficiently powerful to run mainstream operating systems and workloads. Many of these boards may be linked together, to create small, low-cost clusters that replicate some features of large data center clusters. The Raspberry Pi Foundation produces a series of SBCs with a price/performance ratio that makes SBC clusters viable, perhaps even expendable. These clusters are an enabler for Edge/Fog Compute, where processing is pushed out towards data sources, reducing bandwidth requirements and decentralizing the architecture. In this paper we investigate use cases driving the growth of SBC clusters, we examine the trends in future hardware developments, and discuss the potential of SBC clusters as a disruptive technology. Compared to traditional clusters, SBC clusters have a reduced footprint, are low-cost, and have low power requirements. This enables different models of deployment—particularly outside traditional data center environments. We discuss the applicability of existing software and management infrastructure to support exotic deployment scenarios and anticipate the next generation of SBC. We conclude that the SBC cluster is a new and distinct computational deployment paradigm, which is applicable to a wider range of scenarios than current clusters. It facilitates Internet of Things and Smart City systems and is potentially a game changer in pushing application logic out towards the network edge

Next generation single board clusters

Until recently, cluster computing was too expensive and too complex for commodity users. However the phenomenal popularity of single board computers like the Raspberry Pi has caused the emergence of the single board computer cluster. This demonstration will present a cheap, practical and portable Raspberry Pi cluster called Pi Stack. We will show pragmatic custom solutions to hardware issues, such as power distribution, and software issues, such as remote updating. We also sketch potential use cases for Pi Stack and other commodity single board computer cluster architectures

Characterisation and calibration of low-cost PM sensors at high temporal resolution to reference-grade performance

Particulate Matter (PM) low-cost sensors (LCS) present a cost-effective opportunity to improve the spatiotemporal resolution of airborne PM data. Previous studies focused on PM-LCS-reported hourly data and identified, without fully addressing, their limitations. However, PM-LCS provide measurements at finer temporal resolutions. Furthermore, government bodies have developed certifications to accompany new uses of these sensors, but these certifications have shortcomings. To address these knowledge gaps, PM-LCS of two models, 8 Sensirion SPS30 and 8 Plantower PMS5003, were collocated for one year with a Fidas 200S, MCERTS-certified PM monitor and were characterised at 2 min resolution, enabling replication of certification processes, and highlighting their limitations and improvements. Robust linear models using sensor-reported particle number concentrations and relative humidity, coupled with 2-week biannual calibration campaigns, achieved reference-grade performance, at median PM2.5 background concentration of 5.5 μg/m3, demonstrating that, with careful calibration, PM-LCS may cost-effectively supplement reference equipment in multi-nodes networks with fine spatiotemporality