The  Poten)al  of  Surrogate  Monitoring:    Turbidity  Fiona  Regan  

Marine  and  Environmental  Sensing  Technology  Hub  (MESTECH)    December  9th    

Outline  

Decision  support  using  turbidity  data  

Deployments  

MulB-­‐modal  PlaEorm  

Water  Quality  Monitoring  

Monitoring  Site  

Poolbeg  Marina  

 Data  AnalyBcs  

•  Machine  learning  objecBves:  automated  detecBon  and  trajectory  of  vessels  

•  Automated  Turbidity  event  detecBon  –  pixel-­‐based  adapBve  segmenter  method  

•  Salinity  predicBon  using  mulBple  data  sources  (Bde,  flow,  weather  data)  using  regression  tree  approach  

•  Shipping  acBvity  +  turbidity:  predicBon  of  sampling  Bmes  and  microbial  contaminaBon  –  separaBng  natural  events  from  anthropogenic  events  

•  Water  level  predicBon  

•  Security  Threats:  Unauthorized  shipping  

Poolbeg  –  Surrogate  measurements  for  water  quality  

Water  Management  

• Surrogate  measurements  using  low-­‐cost  sensors    

• Informed  sampling  • Early  warning  of  events  

Decision  support  

Occurrence  of  e-­‐coli  

Acknowledgments Tim Sullivan, James Chapman, Ciprian Briciu, Brendan Heery, Dian Zhang Prof. Noel O’Connor Poolbeg Marina, Malahide Marina Brendan O’Flynn, Tyndall, John Wallace IDS Ltd., Cork Co.Co. SmartBay Ireland, Marine Institute, Guy Westbrook Funding: Marine Institute Beaufort Marine Research Awards, 2007, QUESTOR, IRCSET EPS (ISGEI)