SANY Sensors Anywhere

SP5 prototype can be explored at SP5 application web page. In case the demonstration is currently offline, please contact BMT.

Marine risks arise from a number of sources including natural events, anthropogenic causes and a combination of both. In almost all cases, marine risks have an economic, human and environmental impact. In SANY, short term microbial contamination of both Bathing Waters and Shellfish Waters has been targeted. These designated water areas are subject to extensive regulatory standards, established via EU Directives.

In the case of Bathing Waters, failure to meet regulatory standards can have significant impacts on public health and tourism revenue. Similarly, short term microbial pollution events in Shellfish Waters can have serious consequences for consumer health and cause a reduction in revenue for the local aquaculture industry. Presently, microbial levels in the selected water areas are assessed using laboratory testing. These tests often have a turnaround time of more than 24
hours and, as such, can only determine whether a contamination event has occurred. Improvement in the ability to forecast the risk of short term microbial pollution in designated waters could reduce both the human and economic
impact of such events. The SANY marine risk applications use a number of services developed within the SANY project to access data from sensor networks and assess the likelihood of a contamination event occurring. The use of SANY
Sensor Service Architecture enables:

• Access to third-party sensor networks and phenomenological models, to create cost-effective access to measured or modelled data streams and equally to allow operators of such networks/models to valorise their investments;
  
• The use of web-based services to provide high-value data processing (eg for spatial fusion, temporal fusion and modelling) that will enable users to get enhanced information about parameters of interest;
  
• Rapid deployment of additional in-situ sensors on both fixed and mobile platforms. These will acquire data on key water quality parameters, to fill gaps in spatial and temporal data coverage, and thereby permit improved quality of risk now-casting and forecasting;
  
• Provision of alerts and alarm systems to raise the awareness on a possible hazard and support preventative measures;
  
• Remote configuration of smart sensors and, if possible, adaptive tuning of stochastic models to allow ‘on the fly’ enhancement of risk forecasting through incorporation of recent data within the forecasting algorithm.