ENVIROfying the Future Internet BRINGING MARINE DATA ASSETS TO THE FUTURE INTERNET Leveraging the Future Internet for the Marine Usage Area Dr.Conor Delaney
Galway Bay Smart Bay - Ireland
MARINE SCENARIOS
Background to MAST Marine Asset Management Decision Support Tool (MAST) is a web portal developed from the analysis of a number of uses cases developed by the marine work package of ENVIROFI The use case addresses a problem of how to access coastal marine waters in a safe way for the management of marine assets. Adaptable, scalable platform technology which can be translated to other marine stakeholders and support research and enterprise development. MAST delivers on the requirements for Ocean Energy Asset Management. (UC-ENV3.B-WAV-03-V03)
Scenario A: Wave Energy Asset Management Location: SmartBay, Galway Ireland (Location of ENVIROFI s 20 mw Virtual Wave Energy Farm) Operational issue: Wave farm manager needs to schedule preventative maintenance on wave energy array Challenge: Identify weather window for operational maintenance within maximum limits of constraints
The Weather Window This is the window of time when it is safe to put to sea. To identify a weather window requires: Intelligent integration of the real-time data coupled with model predictions. This is an essential tool in identifying weather windows of opportunity to schedule essential operational maintenance and repairs. Monitoring of the sea sate and marine traffic is also important. To make a decision the user needs data! This is a question that is applicable many different types of marine users.
Third Party Data Feed Automatic Ship Tracking (AIS) Aggregated by various 3 rd parties Served back via internet web services
Operational MI modelling Hydrodynamic model of northeast Atlantic 1.2-2.5 km horizontal resolution 40 vertical levels 36,000,000 grid cells T, S, Ssh, velocity Daily 3-day forecast Weekly 7-day hindcast Data published to Thredds/FTP and web Hindcast data archived (LTO4) 560-core High Performance Computer
Weather Stations of Ireland Weather Buoy Marine Institute Weather Station
ERDDAP @ Marine Institute
Real Time Conditions Part 1 Ship Tracking Data Web Cam Personal Weather Station
Real Time Conditions Part 2 Feeds from various Sensors in Galway Bay
The Ocean Weather Widget The Atlantic Ocean Buoy is a Platform for a number of sensors. You can select a sensor via the radio buttons.
Predicted Conditions Output from operational models (run once a day) Prediction of astronomical tide.
Wave Forecast Widget Clicking Next Advances Forecast By 3 hours
Galway Bay Dashboard
Acknowledgements Marine Institute JACINTA MC CREANOR EOIN O GRADY RAMONA CARR KEITH MANSON DAMIAN SMYTH Intune Networks Ltd. FERGAL WARD SmartBay Ireland Ltd. PAUL GAUGHAN Julia Falvey (MAST connection test, USA) Mike Kobernus (MAST connection test and IT support, NILU, Norway)
Thank you for your attention www.envirofi.eu The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement Number 284898
Galway Bay Dashboard ERRDAP is the core environmental enabler of WP3, to demonstrate the flexibility of the technology a dashboard demo was developed (next slide). The key features of the dashboard: MOST OF THE DATA LINKS ARE THE SAME AS THOSE USED IN MAST, ALL THAT HAS CHANGED IS FORMAT OF THE DATA THAT HAS BEEN REQUESTED. INSTEAD OF REQUESTING IMAGES OF GRAPHS THE DASHBOARD REQUESTS THE DATA AND COMPOSES THE GRAPHS IN THE BROWSER. THE DATA IS JSON FORMAT AND CROSS DOMAIN FUNCTIONALITY IS ACHIEVED BY USING JSONP. THE DASHBOARD HAS BEEN PUBLISHED ON THE WEB SERVERS OF THE MARINE INSTITUTE. ALL CODE IS CONTAINED WITH THE BROWSER. http://apps.marine.ie/galwaydashboard/
Introduction Driving Use Case Global challenge of need for energy generation and security of supply Future development of arrays of offshore wind, wave and tidal marine energy systems planned Leverage internet-enabled decision support solutions for adaptive control of deployed marine infrastructures and related assets Decision support to schedule system preventative maintenance Reduce costs by maximizing power take off Improved security through integrated monitoring approach