GLOS OTT Prototype Increasing Operational Efficiency for HAB

GLOS OTT Prototype Increasing Operational Efficiency for HAB Detection May 2, 2019 IOOS DMAC Annual Meeting Silver Spring, MD

I am not a scientist.

OTT HABs EWS Goals • GLOS part of a multiyear project funded by IOOS with these goals: • Stabilize and Enhance: • In-lake monitoring capabilities, • Data Management and Communications (DMAC) support structure, and • Online HABs Data Portal for the Lake Erie HABs Early Warning System (LEHABS-EWS).

Drivers for a Prototype Wanted to look at how it’s done today How could it be improved How could it be faster and more transparent How could we drive access to information Can it support an EWS

HABs Detection Data Today Satellite Imagery Sample Data Generates HAB Prediction Models Grab Sample and ESP Collections Processed into: HABs Forecast Models Accessed Via: NOAA HABs Tracker Accessed Via: HABs Bulletin NOAA HABs Models are generated from satellite imagery and complex algorithms. Converted to motion GIFs and static PDF documents, results are emailed weekly or accessed via the NOAA HABS Tracker. Sondes Streaming Data & Data Loggers Processed into: Time Series Data Accessed Via: Spreadsheet Accessed Via: GLOS as Net. CDF Sample data is collected and processed in a lab. Results are compiled into spreadsheets and made available online or emailed. Sonde data can be collected in real-time. Data is sent to servers for processing. Results are available on GLOS on demand.

OTT HABS EWS Policy People / Partners EWS Technology Platform

Rapid Prototype System To develop a platform that demonstrates a flow of sensor data to actionable intelligence. Device Registratio n Authenticate d Security Sensor Data Raw Data Storage Processing & Visualization A demonstration of a specific use case that supports observation to human data flow in the context of OTT HABS EWS. Web Services Actionable Intelligence Web Resources

A Simple GLOS Vision 3 Core Principles EDGE CAPABLE CLOUD SCALABLE ACTION ENABLED

Data Driven Services OTT HABs EWS Prototype Data Processing Real time, Frequent Data Individual Streams Stream driven services

A Scalable Tech Stack on the Edge Real-time processing towards web consumable data streams An initial Io. T “Thing” is configured to ingest a Pandas Data. Frame (Python), AWS API Gateway endpoint will provide streaming client applications a Web. Socket API to receive real-time data Edge Capable Cloud Scalable Action Enabled Firehose collects data from the realtime stream to be acted upon on a time-based or volume-based trigger

OTT Prototype To develop a platform that demonstrates a flow of sensor data to actionable intelligence. Streaming data, Grab Sample Data HAB Model Data Cloud Streams Storage/Archival Processing/Serving Web Application API End points Authentication Mobile Alert Dashboard Reporting Alert Prototype Inputs 50 Percent Complete Backend Infrastructure 80 Percent Complete Frontend (Analysis, Viz, API) 30 Percent Complete Alerts & Action 10 Percent Complete

Prototype Roadmap Design Q 4 -2018 Design & Architecture Development Q 1/Q 2 -2019 Agile Development Test Q 2 -2019 Test Phase • Platform design • SDLC Roadmap • Infrastructure • Cloud services • Agile Dev • R&D • Data Streams • Scaling/Streaming • User Requirements • Scrum • UAT QA/QC hardening Release & Feedback Q 2/Q 3 -2019 Release & Feedback App/API/Future Dev Q 4+ Future Development App Dev • Engaging stakeholders • Scope Development • Developing additional use • App Design cases • Seeking efficiencies • Feature List development • Architecture Scaling • Manufacturer Engagement

QUESTIONS still not a scientist.

THANK YOU Sneha Bhadbhade Mgr. Data Services sneha@glos. us 864 -908 -8391 Tim Kearns Senior Advisor tim@glos. us 206 -495 -2242

This prototype is in support of the OTT Project to demonstrate end to end capability of sensor data. Manufacturer Relationships Use Case Development User Story Review/Development Data Streams Identification Telemetry Issues Messaging Workflow Feedback on potential applications beyond OTT Correlation with DMAC Suggestions with Blue Sky Stakeholder engagement Geographic reach

great lakes observing system You are all partners and a part of the GLOS ecosystem. Academia Government Water Facilities Research Organizations Consultants Subject Matter Experts Canada

A Disconnected Network Consisting of Partners, Providers, Projects, Data, Users, Collaborators & Technology Providers. Contributor s Grantees Collaborator s Public Products Science & Research A result of multi-nodal efforts spanning years of development and initiatives. Special Project s Support & Technolog y Providers

A Connected Ecosystem Transitioning GLOS DMAC to a technology platform focused on smart great lakes. Contributor s Grantees Collaborator s Public Products Science & Research An intuitive, single entry point for all users with potential for growth, flexibility and scale. Special Project s Support & Technolog y Providers

Application and Support Vendors LIMNOTECH Ad hoc Product and data support Infrastructure maintenance and support Knowledge Transfer Key Stakeholder engagement RPS Cloud Migration Implementation Ad hoc product and data support Infrastructure support and maintenance Key Stakeholder Engagement

Technology Platform for OTT Supporting OTT HABS EWS and GLOS future DMAC. Sensor Direct Raw Data Drag & Drop FTP/Mai l AP I Web Services Authenticate d Security Web Resources 3 rd Party Tools Mobile Apps Processing & Visualization Downloa d A flexible and scalable architecture that meets the needs of the data to information life cycle. Informatio n Services Revenue Sharing