Networks of Sensors Research Themes

 

The NERC Networks of Sensors programme comprises of six research themes being led by six institutions. 

The objective of this £5M NERC-funded programme is to deliver collaborative demonstration projects exploiting the potential of distributed high density networks of sensors, with the objective of discovering new insights into the environment. The successful projects cover a broad section of the NERC remit, and involve over 30 different partners including major public and private sector stakeholders

Please see below further details on these six funded projects. 

 

1. A United Kingdom Lake Ecological Observatory Network
Principal Investigator - Prof. Stephen Maberley, Centre for Ecology and Hydrology

This NERC-funded project will develop a national demonstration-network of automatic lake monitoring stations that will exploit state-of-the-art sensor technology and provide linked, concurrent, high-temporal resolution data at a globally-unique density. The scientific and operational advantages of data at this unprecedented spatial and temporal scale will be illustrated in three science demonstration topics.

Freshwaters are extremely vulnerable to a wide range of stressors including climate change, eutrophication, invasion of alien species and acidification. At the same time, they provide essential provisioning, regulating, cultural and supporting ecosystem services including a major, but under-recognised, role in the global carbon cycle. Because of their importance to society, most lakes are subject to numerous legally-binding European directives that set stringent targets for water quality and biodiversity. Meeting these targets requires a detailed understanding of lake processes which in turn requires measurements at an appropriate temporal scale. Traditional monitoring, of at best weekly or fortnightly intervals, is sufficient to record seasonal change but cannot resolve the processes driving many aspects of lake function. This is because lake properties can be completely altered by short-term, meteorologically-driven physical disturbance such as a strong wind event that causes de-stratification in summer, and because the organisms that control lake function are often microbial with division times of the order of days.

The primary technological objective of this project is to establish the UK’s first coordinated, high-intensity lake monitoring network. Eleven Automatic Water Quality Monitoring Stations (AWQMS) are included in the network, and each comprises a meteorological station, depth temperature profiles and newly developed self-cleaning sondes at the surface to measure temperature, oxygen (optical technology), conductivity, pH, phytoplankton chlorophyll a and phycocyanin (cyanobacteria) and concentration of CO2. The AWQMS will be fitted with solar panels to improve power-supply and battery life. The high frequency (4-minute) and large number of sensors (~30 per site) will result in a large amount of data being produced. An information system has been developed to collect the data automatically via GPRS, subject them to quality-control procedures and load them into a central database where they can be used by the project partners and also provide summary data on a project web site for the general public.

Potential Impacts and Applications:

Smart Monitoring Networks have the potential to provide information reliably and efficiently to environmental regulators, agencies, water companies and planners of aquatic events. The three science projects will demonstrate the value of such an approach:

  • Using medium-range weather forecasts, near real-time lake models will forecast water quality for a 5-10 day period, helping to inform decisions about whether or not mitigating actions may be needed, such as treatments of algal blooms etc.
  • Providing information on storage and release of carbon by lakes for comparison to national carbon balance calculations
  • Assessing the extent of short-term coherence in response across lakes to inform regulators of the reliability of extrapolating from one measured lake to another nearby unmeasured lake.

More information is available at the project website: http://www.ceh.ac.uk/sci_programmes/water/UK-Lake-Ecological-Observatory-Network.html


2. FUSE: Floodplain Underground Sensors - A high density, wireless underground Sensor Network to quantify floodplain hydro-ecological interactions
Principal Investigator - Dr. Anne Verhoef, University of Reading

Beastie Wireless Sensing NodesThe FUSE project aims to advance the knowledge on the interaction between the hydrological regime and the functioning of plant communities in floodplain meadows, at a variety of scales. A better understanding of these vulnerable ecosystems will ultimately allow improved environmental management, under current and future conditions.

Floodplain meadows are a valuable resource; not only can they support some of the most diverse vegetation in the UK (up to 40 species m-2), but they also perform key ecosystem services, such as flood storage and sediment retention. However, the UK now has less than 1500 ha of this unique habitat remaining and the habitat has been given protection under the European Habitats Directive (92/43/EEC). However, in order to conserve and better exploit the services provided by this grassland, an improved understanding of its functioning is essential. Species composition for instance, is known to be tightly correlated to the hydrological regime and related temperature and nutrient regime, but the mechanisms controlling these relationships are not established. Nitrogen mineralisation rate has been suggested as such a mechanism which is regulated by both soil temperature and soil oxygen availability.

This NERC project therefore aims to investigate the spatiotemporal variability (sub-metre to tens of metres; half-hourly to seasonally) in plant community composition and vegetation functioning (e.g. photosynthesis and transpiration) in floodplain meadows, and their relationship to key soil physical variables and nutrient levels, by using an intensity of monitoring not previously attempted in this environment. Such detailed observations are required because plant processes are responsive to fine-scale changes in the environmental setting (e.g. microtopography, water-table depth and soil temperature) and short-term seasonal effects. Seasonality is important because the phenology of competing species varies, meaning that some species (e.g. fibrous-rooted grasses) rely on high nitrogen mineralisation rates early in the season, whilst others (e.g. rhizomatous sedges) do not, as they have stored reserves to support spring growth.

A key aim of this project will be the deployment of sophisticated high-resolution model-data fusion involving: underground wireless measurement technologies; high-resolution hierarchical observational data; as well as state-of-the-art modelling tools. The use of wireless Underground Sensor Networks (WUSNs) are relatively rare and these systems haven’t been tested long-term in challenging environments, such as the Oxford Floodplain where there is frequent flooding and all components need to be underground (this is a site of specific scientific interest, due to its rare plant species; furthermore, sheep or cattle will be grazing the site during autumn and winter). A dense meshed network of up to 75 wireless nodes will be deployed over the field.

An Integrated Development Environment  will be produced to program, test, simulate and configure the WUSN, as well as a web portal for data manipulation, model parameter estimation and real-time model output.  Additionally, development of a middleware framework for the nodes, will facilitate WUSN plug-ins to ease programming, upgrading and maintenance (given the expected long-term deployment). This can include modules to carry out calibration, statistics and clock synchronisation.

The provision of these software environments, tools and utilities will reduce the reliance of environmental scientists on WUSN developers and environmental modelling experts. The precise form of the WUSN will be designed by a numerical optimisation procedure, subject to existing subsurface data, to minimise likely interpolation error, according to a geostatistical model.

The project will also undertake distributed biophysical modelling, combining Earth Observation (EO) data with Soil Vegetation Atmosphere Transfer (SVAT) models. The SVAT will be specifically designed in order to support direct interpretation of the EO data. This will allow for a coherent integration of underground and above-ground key biophysical and chemical processes; it will be extended with a multi-layer below-ground component, in order to account for nutrients, soil temperature and groundwater depth/soil moisture content on plant physiology and connected species composition. This modelling tool, implemented via the web portal, will be used for combined spatial interpolation of model predictions and in-situ as well as EO data.

The resulting powerful data-model fusion system will enhance scientists’ process understanding through sensitivity studies. FUSE will allow researchers to assess underground spatial variability at hitherto unachievable resolutions (sub-metre).

Potential Impacts and Applications

WUSNs have the potential to revolutionise our understanding of how plant community composition and vegetation functioning are affected by physical variables and nutrient levels. The outputs of this project have the following benefits:

  • Providing a variety of measurement scales for interactions between the hydrological regime and functioning of plant communities in floodplain meadows
  • Improved environmental management of vulnerable ecosystems
  • Improved WUSN technologies which could be used in multiple applications such as monitoring floods and land slippage, pipelines, roads, embankments, train lines, etc. Those that could benefit could include government agencies, energy companies, water industry, transportation companies – road and rail
  • Cutting edge geospatial data and modelling tools - useful in a number of applications across various industries including insurance, transport, utilities, agriculture and horticulture, natural resource management
  • Data-model fusion system developments could benefit users of data in areas such as hydrometeorology, climatology, marine sciences, agriculture, utilities etc., to gain more accurate information to improve planning, risk analysis, and mitigation activities.


3. Networks of Sensors in Extreme Environments: High-Resolution Glacier Dynamic Monitoring
Principal Investigator - Professor Tavi Murray, Swansea University

The overall aim of this NERC-funded project is to derive new insights into the dynamics of tidewater glaciers by deploying a novel, self-healing wireless sensor network consisting of GPS receivers and wireless nodes on the ice surface to obtain real-time, in situ measurements of high spatial and temporal resolution which would have been impractical hitherto. A first generation sensor network was deployed successfully and field tested on Helheim Glacier during July 2012.

The monitoring of glacial activity in Greenland is of vital global importance. Some 80% of Greenland’s land surface is covered by ice and the ice sheet is the largest in the Northern Hemisphere and second only in size to the Antarctic ice sheets. Approximately 50% of the ice loss in Greenland occurs through a process known as “calving”, which is the sudden release and breaking away of ice from a glacier to form an iceberg. Calving is believed to have increased because of rising oceanic and atmospheric temperatures. To complicate matters, modelling of calving events is made difficult by the challenge of instrumenting heavily crevassed glaciers as they reach coastal waters. The extreme environment also complicates instrument design.

A key aim of this project is to accurately measuring glacier dynamics during and immediately after glacier calving events. To address this, a novel, wireless sensor network has been deployed consisting of GPS ice-nodes placed on the glacier surface providing high rate (2-5 second), real-time, in situ measurements. The network includes features such as robust form-factor, low energy consumption, and operating longevity in extreme environments, with the ability to remain operational without data loss as network segments are lost via calving events. The wireless network also provides an opportunity to monitor the characteristics of radio propagation in a unique environment. A prototype network was successfully deployed in 2012, and in 2013 the full network of around 20 ice-node sensors will be used to measure variations in horizontal flow speed and direction, vertical uplift and the associated strain field. The GPS measurements will be used in conjunction with remotely sensed velocity fields from satellite, airborne, and ground-based photogrammetry measurements to cross-validate techniques and generate a synthesised dataset of high temporal and spatial resolution. Numerical modelling will be used subsequently to relate changes in ice geometry and velocity to tidal forcing in the fjord, crevasse spacing and location, as well as iceberg calving events. For example we will gain new insights on how the glacier flow field responds to a calving event in the short and longer term. A new web-based interface is being designed to provide a public presentation of project data in real-time, embedded in a web site that incorporates other project datasets, field and laboratory diaries and photographs, thus providing NERC with a portal that demonstrates the power of these technologies and their potential for environmental monitoring in a wide variety of environments.

In combination with auxiliary data, such as LIDAR measurements of surface topography, crevasse spacing and calving rates, the network will provide velocity and elevation data of unprecedented temporal and spatial resolution. This will form a unique dataset for testing calving models and to improve understanding of the controls on the contribution to these tidewater glaciers to sea-level rise.

Potential Impacts and Applications:

Smart Monitoring Networks have the potential to inform governments, environmental scientists, the maritime industry, offshore oil and gas exploration:

  • Providing accurate velocity and elevation data of unprecedented temporal and spatial resolution in environments that are otherwise too hostile to access (volcanic areas or earthquake zones and landslide or rockslide prone slopes might be other suitable application areas).
  • Information could be useful for maritime and offshore oil and gas installation monitoring activities.
  • Concepts and performance of the wireless network are relevant to principles of self-organising networks and distributed radio access architectures.

4. High density sensor network system for air quality studies at Heathrow Airport
Principal Investigator - Professor R L Jones, University of Cambridge.

A Networked Sensor Node at Heathrow Airport (Inset shows close-up of module)The overall scientific objective for this NERC funded project is to demonstrate the potential of low cost sensor network systems for characterising air quality in the urban environment at an appropriate granularity in order to understand the factors which influence pollutant concentrations on local scales. The ultimate aim is to develop and demonstrate the sensor network system methodology which, when appropriately deployed, can contribute to scientific, economic, public policy and regulatory issues, human (health) responses, as well as air quality on local and regional scales. The project is led by the University of Cambridge, in collaboration with the Universities of Hertfordshire and Manchester, CERC and NPL, with support from Alphasense.

The aim is to demonstrate the generic capabilities of high density networks in this project. This will enable a better understanding of sensor network deployment strategies, with, importantly, a number of specific scientific issues and ultimately legislative issues relevant to London Heathrow Airport being addressed. However, the aim is to develop a more widely applicable strategy which allows sensor deployments in a wide range of environments and meteorological conditions. The resulting high-density air quality sensor network system in and around London Heathrow Airport is being deployed for an extended period (~ 1 year). It is using state of the art low cost sensors for selected gases and for size speciated aerosols, creating an unprecedented data-set for a range of studies. There is wide-ranging stakeholder support for this project, including the Heathrow Airport Limited and British Airways, with interest from DfT, and the London Boroughs adjacent to Heathrow Airport.

The sensor network developed within the project utilises close-to-market, inexpensive field-based sensors and instruments, coupled to existing infrastructures such as GPS and GPRS. Some of the key project outputs include development of novel software tools for network calibration, analysis and data-mining, visualisation and interpretation. The network will create a calibrated, high spatial and temporal resolution data set including NO, NO2, CO, CO2, SO2, O3, VOCs and size-speciated PM (from 0.4 – 15 mm) for further scientific and policy studies. For gases, techniques include electrochemical (e.g. NO, NO2, CO, O3, SO2), optical absorption (CO2), photo-ionization (VOCs - hydrocarbons), and optical scattering (for aerosols). Standard meteorological variables (T, RH, wind speed/direction) are measured, and the network also incorporates existing infrastructures for positioning (GPS) and communication (GPRS/3G).

Novel instruments and techniques being developed in this project include a custom miniature optical particle counter (aerosol sensor) developed from the novel detection technology used in the University of Hertfordshire’s SID (Small Ice Detector) aircraft cloud microphysics probes. There will also be enhancements to the sensor package design, based on an autonomous integrated GPS/GPRS gas sensor unit, with improved power management to allow extended low maintenance deployment. An innovative feature of this project is to exploit the fact that information from one node of the network can be used to make inferences about nearby nodes. For example, the non-ideal behaviour of one sensor node (in terms of calibration drift) can be constrained by the behaviour of nearby sensor nodes along with model predictions derived from ADMS, particularly during stable environmental conditions and quiet source behaviour (e.g., at night).

Potential Impacts and Applications:

The High Density Sensor Network System could have the potential to help regulators, agencies and other key stakeholders interested in prediction of pollution by:

  • Characterising air quality in a low cost, flexible and highly scalable approach, complementing existing fixed site networks, identifying hotspots, quantifying traffic control measures etc.
  • Personal exposure, health impacts of air quality (epidemiological, respiratory/COPD)
  • Modelling of air and ground traffic increases over time to help those involved in planning potential expansions of airports, motorways, etc,.
  • Informing government policies where source data can assist in building a more complete picture


5. High density temperature measurements within the urban environment (HiTemp)
Principal Investigator - Dr. Lee Chapman, University of Birmingham

Mounted Aginova WiFi temperature sensorThis project aims to provide a demonstration sensor network designed to measure air temperature across the Birmingham conurbation. Data from this project will be instrumental in answering key scientific research questions currently under investigation such as what is the impact of the current and future climate on the people and infrastructure of a major city.

Research conducted for the Greater London Authority has identified urban heat as amongst the most pressing priorities of impacts of climate change1. The Urban Heat Island effect (UHI) is a direct consequence of anthropogenic influences on the local climate. Many studies have been devoted to the investigation of UHI extent and magnitude, as well as the impacts increased urban temperatures have on meteorology, climatology, human health and society. Although the UHI phenomena is well documented and studies have generally led to better understanding of them, the basic measurement of temperatures across urban areas remains very limited.

Climate change scenarios all suggest increases in mean temperatures: these will exacerbate the incidence of heat waves which will be most noticeable in urban areas. The 2003 heat wave was considered to be responsible for 14802 and 2045 excess deaths in France and the UK, respectively. Most of these deaths were in urban areas and were a direct result of the increased temperatures experienced in towns and cities.  Increases in heat waves will consequently impact upon human health (e.g. heat stress), society (e.g. law and order) as well as the infrastructure of the urban areas themselves, such as transportation (e.g. roads melting, rail buckling) and power supplies (e.g. transformer overloading due to increased heat and need for air conditioning). However, UHI intensity can be mitigated by improved planning, for example, passive cooling, green roofs and trees.

Such adaptations are essential to prevent a repeat of the devastating effects of the 2003 heat wave. The long-term aim of the NERC-funded HiTemp project is to identify, model and promote adaptation to the impacts of urban heat and climate change on the people and infrastructure of major conurbations. To this effect, in order to identify and mitigate the impacts of UHI, large scale measurement campaigns of current temperatures are required. Although this can be easily achieved for surface temperatures using remote sensing techniques, these techniques cannot be used to measure air temperatures near the surface. Indeed, due to a paucity of high resolution air temperature measurements in cities, studies are often limited to the measurement of surface temperatures and hence the surface or ‘skin’. Instead, traditional measurements of UHI are made instead using pairs or urban/rural weather stations or temperature transects. However, in all but a few applications, it is near surface air temperature that is the important parameter to measure, not surface temperature. This project aims to tackle this problem by implementing high resolution sensor networks primarily focussed on measuring air temperatures across the Birmingham conurbation so that the UHI can be mapped at a scale previously not possible.

The demonstration sensor network for this project is designed to measure air temperature across Birmingham includes a coarse array of 29 weather stations located in secure primary (i.e.main) electrical substations, a wide area array consisting of 131 Wi-Fi air temperature sensors located schools and a fine scale Wi-Fi array in the central business district consisting of 50 sensors per square kilometre. A full suite of weather parameters will be measured at each site (air temperature, humidity, windspeed, direction, rainfall, radiation).

The proposed sensor network will provide an unparalleled data set that would benefit many users. Most importantly, it will be used to inform the decision-makers current temperatures variations, and consequently help then formulate future mitigation development strategies.

Potential Impacts and Applications:

This large scale measurement campaign has the potential to inform governments and agencies, environmental scientists, public health, industries such as transportation, utilities and infrastructure with essential information on UHI intensity, to help facilitate mitigating actions and appropriate planning:

  • Providing leading edge accurate temperature measurements across urban areas.
  • Real-time forecasting capabilities for winter road maintenance, railway buckling, passenger thermal comfort and energy demand (and associated interdependencies)
  • Inform health care authorities on potential implications to human health in urban areas
  • Long-term transportation and utilities infrastructure planning, construction and asset replacement.
  • Strategic targeting of mitigation measures to urban heat across the built environment

6. An Aircraft Deployable GPS Stake Network for Antarctic Glaciers
Principal Investigator -Dr. Hilmar Gudmundsson, British Antarctic Survey.

The main objective of this NERC-funded project is to design and build low-cost pole-based GPS sensors, called "Javelins" that can be installed on the surface of a glacier by airdropping them from an aircraft to form a network. The positions would be data compressed locally and stored by a low-cost field microcontroller on the pole. They would then be sent to an existing data repository in the British Antarctic Survey's (BAS) UK headquarters, via the Iridium satellite data network in short cost-effective bursts.

There is an urgent scientific need to better monitor the contribution of glaciers and ice sheets to worldwide sea level change. Currently sea-level is changing at a rate of 2.5 to 3 mm per year, which is considerably higher than projected in the last IPCC report (Scientific Committee on Antarctic Research, 2007-8). It has become increasingly evident that most of the contribution of ice sheets and glaciers to sea level change originates from a few highly dynamic areas, such as the remote Pine Island Glacier. Such regions are difficult or impossible to reach by ground via overland treks or through aircraft landing. Remote sensing can provide some motion and flow data in these areas, but such techniques are restricted by poor temporal resolution and lack of stable tracking features. Thus, terrestrial sensor equipment that can be deployed by air in this environmentally sensitive area is the only option for monitoring these critical regions.

A trial for the practical implementation of this network is being undertaken in one of the most rapidly changing regions of the Antarctic ice sheet, the Pine Island Glacier in West Antarctica, with a network of these sensors providing a key data set to study the current contribution of the cryosphere to sea level change. The design of a "disposable" sensor for an environmentally sensitive area will require individual sensors made of inexpensive material with low environmental impact. The project will focus upon the aerodynamics of the Javelin, to maximize the number of successful airborne deployments. The end result will be design and manufacturing plans for a product that will be of use to BAS in several glacier regions beyond grounding lines. The primary long-term benefit of this project is the acquisition of high-resolution temporal data on the flow of critical glaciers. These glaciers have been otherwise inaccessible other than through remote sensing, which cannot provide the level of temporal resolution required to identify flow changes on a seasonal, monthly, or daily level. Data from the project will be used to reduce uncertainties in the direct estimates of the current rates of glacier change thinning and their contribution to world-wide sea level change.

The GPS sensor Javelins have been designed to provide new data on the seasonal variability of flow in glaciers of critical climate importance. In order to meet the challenges of deployment, a major focus in the design has been upon the aerodynamics of the Javelin, to maximize the number of successful airborne deployments. As well as a novel aerodynamic design, a novel damping system to reduce the impact force seen by the payload has also been developed. 

The Javelin sensor could be manufactured and used in a number of other scientific or industrial applications where there is a need for data collection from remote or hazardous areas. The primary beneficiaries of this technology development will be governments, agencies and environmental scientists. The defence industry could also be a potential user.

Potential Impacts and Applications:

This project addresses the need to monitor critical Antarctic regions, providing critical data on changes of ice sheets and glaciers and the impacts of these on sea levels. This information will help inform governments and agencies, environmental scientists and industries such as maritime and defence. Examples of potential applications include:

  • Glacier motion data of critical regions – specifically, high resolution temporal data on the flow of critical glaciers that cannot be reached over ground . Direct beneficiaries would be the IPCC and glacier modellers.
  • A set of proven electronic and aerodynamic designs for the Javelin sensor, and corresponding deployment procedures. These could be translated into a number of technology transfer opportunities for environmental and defence applications.
  • Technical Data for Aircraft-to-Ice Deployment. A major component of the design process will be the measurement of impact forces and ballistic data that results from deploying items from aircraft to ice surface at various altitudes. This data in itself will be of value in the design of similar devices in the future.
  • Environmental surveying in glaciated areas worldwide, where accessibility is limited, using GPS sensors and any other sensors with similar power requirements.