Team Sentinel

112 Interviews

Jared Dunnmon Darren Hau Atsu Kobashi Rachel Moore

Problem: Intelligence, surveillance, reconnaissance is difficult for 7th Fleet in contested areas

Solution: Navy needs cheap, distributed sensors

Problem: Navy is hindered by outdated, cumbersome maritime domain awareness tools

Solution: Navy actually needs enhanced data fusion, analytics, and sharing

4 Site Visits

Week 0 Week 9

Jared Dunnmon Darren Hau Atsu Kobashi Rachel Moore

Degree Program & Department

PhDMechanical Engineering

BSElectrical Engineering

MSElectrical

Engineering

Joint Degree MBA and E-IPER

MSGSB

Expertise Experience in mechanical design, distributed energy harvesting, computational modeling, machine learning, and data analytics, MBA and previous work experience at energy startup Offgrid Electric.

Co-founder of Dragonfly Systems, a solar company acquired by SunPower. Experience in renewable energy, power electronics, reliability, and manufacturing. Inventor of multiple U.S. patents. Record of translating market needs into viable product.

Industry experience as a software engineer for Nissan's Autonomous Vehicle team and experience in the defense sector working for Lockheed Martin. Academic experience with machine learning and data analytics.

Rachel (Caltech ‘13) worked extensively with hardware as an engineer and project manager at a defense contractor prior to the GSB.

Team Sentinel

Interview Breakdown Over 10 Weeks

Emotional Journey

So many problems, so little time...

Classified.

Illegal Fishing Analog

Research- Interviews to assess needs, organizational dynamics, procurement strategy- Site visits to see current practices- Identify key geographic areas of interest

Prototype- Evaluate existing sensor platforms with commercial partners- Integrate sensor(s) of interest into partner product- Compile existing data resources- Evaluate ML algorithms

Scaling- Develop fabrication / procurement strategy

- Primary: 7th Fleet decision makers, ONI intelligence officers, and operators- Secondary: Dual-use entities such as Coast Guard, environmental monitoring, research

- Tertiary: State Department

Lower cost sensor solutionImproved coverage- Persistent presence over enlarged area- Design reliability & robustness via distributed architecture

Actionable intelligence- Cross-domain analysis techniques to integrate multiple data sources- Improved UI increases decision quality and speed- Provide insights to identify potential hot spots

Flexible platform- open architecture- plug-and-play- disposable/low-maintenance- back/forward compatibility

Reduce manpower burden: - Remove tedious/manual tasks through automation- More efficiently use existing analysts

- Good UI for operators, decision-makers

- Decreased time to ID & differentiate threats

- Increased area coverage + persistence

- Cost savings with respect to existing solutions

- Prototype operability + demonstrated scalability

- Prototype initial sensor platform with single desired capability

- Build multiple units pursuing the same threat group (network effects) and derive useful insights from analysis tools

- Deploy pilot in operational environment

- Develop fabrication/procurement pipeline + cost models for scaling

Fixed- Buying proprietary data- Software tools- Hardware evaluation + prototyping equipment- Evaluation of commercial products

Prototyping- Existing sensor platforms- Academic research

Scaling- Available commercial + military data- Existing analysis software tools- AWS

- Need demand from operators and deployment personnel in 7th Fleet

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if want to leverage their platforms

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key PartnersMilitary- 7th Fleet + designated sponsor- Naval Postgraduate School (NPS)- Office of Naval Research (ONR)

Commercial- Distributed sensor platform companies (i.e. Saildrone, AMS)- Data analytics (i.e. Palantir, Google)- Advanced manufacturing

Academic- Universities (i.e. University of Hawaii)- National Labs (Lincoln Labs, Sandia)

Other- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)

Week 0 Mission: Provide Cost-Effective, Actionable Intelligence at All Times

Testing- 7th Fleet assets for pilot- Research barge

Variable- Travel for site visits, pilots- R&D personnel- Manufacturing

- Lower cost sensor solution

- Actionable intelligence

- Flexible platform

- Primary: 7th Fleet decision makers, ONI intelligence officers, and operators

- Secondary: Dual-use entities such as Coast Guard

Research- Interviews to assess needs, organizational dynamics, procurement strategy- Site visits to see current practices- Identify key geographic areas of interest

Prototype- Evaluate existing sensor platforms with commercial partners- Integrate sensor(s) of interest into partner product- Compile existing data resources- Evaluate ML algorithms

Scaling- Develop fabrication / procurement strategy

- Primary: 7th Fleet decision makers, ONI intelligence officers, and operators- Secondary: Dual-use entities such as Coast Guard, environmental monitoring, research

- Tertiary: State Department

Lower cost sensor solutionImproved coverage- Persistent presence over enlarged area- Design reliability & robustness via distributed architecture

Actionable intelligence- Cross-domain analysis techniques to integrate multiple data sources- Improved UI increases decision quality and speed- Provide insights to identify potential hot spots

Flexible platform- open architecture- plug-and-play- disposable/low-maintenance- back/forward compatibility

Reduce manpower burden: - Remove tedious/manual tasks through automation- More efficiently use existing analysts

- Good UI for operators, decision-makers

- Decreased time to ID & differentiate threats

- Increased area coverage + persistence

- Cost savings with respect to existing solutions

- Prototype operability + demonstrated scalability

- Prototype initial sensor platform with single desired capability

- Build multiple units pursuing the same threat group (network effects) and derive useful insights from analysis tools

- Deploy pilot in operational environment

- Develop fabrication/procurement pipeline + cost models for scaling

Fixed- Buying proprietary data- Software tools- Hardware evaluation + prototyping equipment- Evaluation of commercial products

Prototyping- Existing sensor platforms- Academic research

Scaling- Available commercial + military data- Existing analysis software tools- AWS

- Need demand from operators and deployment personnel in 7th Fleet

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if want to leverage their platforms

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Key Activities

Key Resources

Key PartnersMilitary- 7th Fleet + designated sponsor- Naval Postgraduate School (NPS)- Office of Naval Research (ONR)

Commercial- Distributed sensor platform companies (i.e. Saildrone, AMS)- Data analytics (i.e. Palantir, Google)- Advanced manufacturing

Academic- Universities (i.e. University of Hawaii)- National Labs (Lincoln Labs, Sandia)

Other- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)

Week 0 Mission: Provide Cost-Effective, Actionable Intelligence at All Times

Testing- 7th Fleet assets for pilot- Research barge

Variable- Travel for site visits, pilots- R&D personnel- Manufacturing

- Lower cost sensor solution

- Actionable intelligence

- Flexible platform

- Primary: 7th Fleet decision makers, ONI intelligence officers, and operators

- Secondary: Dual-use entities such as Coast Guard

Value Proposition

- Lower cost sensor solution

- Actionable intelligence

- Flexible platform

Beneficiaries

- Primary: 7th Fleet decision makers, ONI intelligence officers, and operators

- Secondary: Dual-use entities such as Coast Guard

Value Proposition

Boiling the ocean?

Learning Progression: Week 1

● Week 1

○ Hypotheses

■ This is a problem with insufficient sensing

○ Experiments:

■ Conversations with mentors/stakeholders/contacts

○ Learning:

■ Sensors largely exist, but price point can be too high

■ Government struggles with sheer volume of open-source data

■ Internal information sharing is a big problem

■ Episodic persistence is acceptable--24/7 is not required

○ Proposed solution (MVP)

■ Diagram of entire ISR infrastructure with an emphasis on data aggregation

○ Key Takeaways:

■ Sensors aren’t the problem--data aggregation is--we pivoted before week 1!

■ Needed to talk to more end-users--had identified operators, analysts, and acquisition as beneficiaries, but had only talked to analysts

○ Diagrams to Include

■ MVP

■ MMC

■ Team /Mentor Composition

Number of Interviews: 14

Hypothesis:- Insufficient sensing

capabilities

Learning Progression: Week 1

● Week 1

○ Hypotheses

■ This is a problem with insufficient sensing

○ Experiments:

■ Conversations with mentors/stakeholders/contacts

○ Learning:

■ Sensors largely exist, but price point can be too high

■ Government struggles with sheer volume of open-source data

■ Internal information sharing is a big problem

■ Episodic persistence is acceptable--24/7 is not required

○ Proposed solution (MVP)

■ Diagram of entire ISR infrastructure with an emphasis on data aggregation

○ Key Takeaways:

■ Sensors aren’t the problem--data aggregation is--we pivoted before week 1!

■ Needed to talk to more end-users--had identified operators, analysts, and acquisition as beneficiaries, but had only talked to analysts

○ Diagrams to Include

■ MVP

■ MMC

■ Team /Mentor Composition

Number of Interviews: 14

Experiments:- Interviews, site

visits...

Learning Progression: Week 1

● Week 1

○ Hypotheses

■ This is a problem with insufficient sensing

○ Experiments:

■ Conversations with mentors/stakeholders/contacts

○ Learning:

■ Sensors largely exist, but price point can be too high

■ Government struggles with sheer volume of open-source data

■ Internal information sharing is a big problem

■ Episodic persistence is acceptable--24/7 is not required

○ Proposed solution (MVP)

■ Diagram of entire ISR infrastructure with an emphasis on data aggregation

○ Key Takeaways:

■ Sensors aren’t the problem--data aggregation is--we pivoted before week 1!

■ Needed to talk to more end-users--had identified operators, analysts, and acquisition as beneficiaries, but had only talked to analysts

○ Diagrams to Include

■ MVP

■ MMC

■ Team /Mentor Composition

Number of Interviews: 14

Learnings:- Sensors largely exist- Information sharing is a big

problem- Gov overwhelmed by sheer bulk

of data

Learning Progression: Week 1

● Week 1

○ Hypotheses

■ This is a problem with insufficient sensing

○ Experiments:

■ Conversations with mentors/stakeholders/contacts

○ Learning:

■ Sensors largely exist, but price point can be too high

■ Government struggles with sheer volume of open-source data

■ Internal information sharing is a big problem

■ Episodic persistence is acceptable--24/7 is not required

○ Proposed solution (MVP)

■ Diagram of entire ISR infrastructure with an emphasis on data aggregation

○ Key Takeaways:

■ Sensors aren’t the problem--data aggregation is--we pivoted before week 1!

■ Needed to talk to more end-users--had identified operators, analysts, and acquisition as beneficiaries, but had only talked to analysts

○ Diagrams to Include

■ MVP

■ MMC

■ Team /Mentor Composition

Number of Interviews: 14

We pivoted in Week 1!

Weeks 1 - 3: What’s the problem?

High-level ThinkersDefense Contractors

Week 1Information sharing, data

aggregation

Weeks 1 - 3: What’s the problem?

INTELLIGENCE (N2)

High-level ThinkersDefense Contractors

Week 1Information sharing, data

aggregation

Week 2Sensors and deployment?

Weeks 1 - 3: What’s the problem?

INTELLIGENCE (N2)

OPERATIONS (N3)

High-level ThinkersDefense Contractors

Week 1Information sharing, data

aggregation

Week 2Sensors and deployment?

Week 3Nope, it really is a data

problem

Weeks 1 - 3: Cognitive Dissonance

INTELLIGENCE (N2)

OPERATIONS (N3)

High-level ThinkersDefense Contractors

Week 1Information sharing, data

aggregation

Week 2Sensor deployment?

Week 3Nope, it really is a data

problem

BIG IDEAS:

1. Everyone is right, but priorities are influenced by their roles.

2. Sensors are great but Navy wouldn’t know what to do with it.

Weeks 1 - 3: Cognitive Dissonance

INTELLIGENCE (N2)

OPERATIONS (N3)

High-level ThinkersDefense Contractors

Week 1Information sharing, data

aggregation

Week 2Sensor deployment?

Week 3Nope, it really is a data

problem

BIG IDEAS:

1. Everyone is right, but priorities are influenced by their roles.

2. Sensors are great but Navy wouldn’t be able to effectively use the data.

Getting out of the building!

Research- Interviews to assess needs, organizational dynamics, procurement strategy- Site visits to see current practices

Prototype- Integrate sensor(s) of interest into partner product- Compile existing data resources- Evaluate relevant ML algorithms- Iterate on human-machine interaction

Strategic Decision MakersE.g. CPT, VADM, ADM (PACFLT), ADM (PACOM)

Analysts (N2)E.g. Jason Knudson, John Chu, Jed Raskie, Joseph Baba Operators (N3)Scheduled this week

Planners (N5)Need to find these people

- Decreased time to predict hot spots, ID & differentiate threats

- Good UI for operators, decision-makers

- Timely, episodic persistent coverage with easily-deployed system

- Cost savings with respect to existing solutions

- Prototype operability + demonstrated scalability

Hardware- Acquire initial sensor platform with single desired capability- Design deployment strategy + platform- Deploy pilot in operational environment- Develop fabrication/procurement pipeline + cost models for scaling

Software- Determine most useful data interface for analysts- Determine optimal information flow to strategic decision makers- Develop ML and visualization algorithms- Build, Test, and Deploy Product

Fixed- Buying proprietary data- Software tools- Evaluation of commercial products

Prototyping- Existing sensor platforms- Academic research

Scaling- Available commercial + military data- Existing database tools (Palantir, AWS)

- Need demand from operators and deployment personnel in 7th Fleet

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if want to leverage their platforms

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key Partners

Military- 7th Fleet + designated sponsor- Naval Postgraduate School (NPS)- Office of Naval Research (ONR)- Acquisition Personnel

Commercial- Distributed sensor platform companies (i.e. Saildrone, AMS)- Data analytics (i.e. Palantir, Google)

Academic- Universities (i.e. University of Hawaii)- National Labs (Lincoln Labs, Sandia)

Other- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)

Week 3 Mission: Provide Cost-Effective, Actionable Intelligence at All Times

Testing- Research barge- Access to model analyst data interface

Variable- Travel for site visits, pilots- R&D personnel- Manufacturing/Development

IMPROVE TACTICAL AND STRATEGIC DECISION MAKING VIA BETTER

DATA HANDLING

(1) Rapid Strategic Decisionmaking via Improved Reporting

(2) Improved Tactical Decision Making via Enhanced Information Sharing

(3) More Effective Analysis via Searchable, Visualizable Data Integration

ENHANCE INCOMING DATA STREAMS

(1) Improved Collection of Existing Data Streams (e.g. Fishing Broadcasts)

(2) Predictive Intel through Machine Learning

Additional Sensing Capability

BETTER DECISION MAKING:

(1) Improved Reporting

(2) Enhanced Information Sharing

(3) Searchable, Visualizable Data Integration

BETTER UTILIZATION OF

DATA:

(1) Improved Collection of Existing Data Streams

(2) Predictive Intel through Machine Learning

- Strategic Decision Makers (e.g. Admirals)

- Intel Analysts - Operators

- Planners

Research- Interviews to assess needs, organizational dynamics, procurement strategy- Site visits to see current practices

Prototype- Integrate sensor(s) of interest into partner product- Compile existing data resources- Evaluate relevant ML algorithms- Iterate on human-machine interaction

Strategic Decision MakersE.g. CPT, VADM, ADM (PACFLT), ADM (PACOM)

Analysts (N2)E.g. Jason Knudson, John Chu, Jed Raskie, Joseph Baba Operators (N3)Scheduled this week

Planners (N5)Need to find these people

- Decreased time to predict hot spots, ID & differentiate threats

- Good UI for operators, decision-makers

- Timely, episodic persistent coverage with easily-deployed system

- Cost savings with respect to existing solutions

- Prototype operability + demonstrated scalability

Hardware- Acquire initial sensor platform with single desired capability- Design deployment strategy + platform- Deploy pilot in operational environment- Develop fabrication/procurement pipeline + cost models for scaling

Software- Determine most useful data interface for analysts- Determine optimal information flow to strategic decision makers- Develop ML and visualization algorithms- Build, Test, and Deploy Product

Fixed- Buying proprietary data- Software tools- Evaluation of commercial products

Prototyping- Existing sensor platforms- Academic research

Scaling- Available commercial + military data- Existing database tools (Palantir, AWS)

- Need demand from operators and deployment personnel in 7th Fleet

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if want to leverage their platforms

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key Partners

Military- 7th Fleet + designated sponsor- Naval Postgraduate School (NPS)- Office of Naval Research (ONR)- Acquisition Personnel

Commercial- Distributed sensor platform companies (i.e. Saildrone, AMS)- Data analytics (i.e. Palantir, Google)

Academic- Universities (i.e. University of Hawaii)- National Labs (Lincoln Labs, Sandia)

Other- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)

Week 3 Mission: Provide Cost-Effective, Actionable Intelligence at All Times

Testing- Research barge- Access to model analyst data interface

Variable- Travel for site visits, pilots- R&D personnel- Manufacturing/Development

IMPROVE TACTICAL AND STRATEGIC DECISION MAKING VIA BETTER

DATA HANDLING

(1) Rapid Strategic Decisionmaking via Improved Reporting

(2) Improved Tactical Decision Making via Enhanced Information Sharing

(3) More Effective Analysis via Searchable, Visualizable Data Integration

ENHANCE INCOMING DATA STREAMS

(1) Improved Collection of Existing Data Streams (e.g. Fishing Broadcasts)

(2) Predictive Intel through Machine Learning

Additional Sensing Capability

BETTER DECISION MAKING:

(1) Improved Reporting

(2) Enhanced Information Sharing

(3) Searchable, Visualizable Data Integration

BETTER UTILIZATION OF

DATA:

(1) Improved Collection of Existing Data Streams

(2) Predictive Intel through Machine Learning

- Strategic Decision Makers (e.g. Admirals)

- Intel Analysts - Operators

- Planners

Value Proposition

- More Educated Decision-Making (improved reporting, info sharing, and visualization)

- Better Utilization of Data (fusing disparate data sources and predictive models)

Beneficiaries

- Strategic Decision Makers (e.g. Admirals)

- Intel Analysts (monitor enemy ships) - Operators (control US Navy ships; decisions based on intel reports)

Weeks 4 - 5: This is a REALLY BIG problem

“I’ve been using GCCS for 7 years and I still don’t know how to filter with it.”

- Surface Warfare Officer

Week 4:There isn’t really a

Common Operational Picture...

“Pacific Command, Pacific Fleet, and 7th Fleet see the same ship in different places.”

- PACOM officer

Weeks 4 - 5: This is a REALLY BIG problem

“I’ve been using GCCS for 7 years and I still don’t know how to filter with it.”

- Surface Warfare Officer

Week 4:There isn’t really a

Common Operational Picture...

“PACOM, Pac Fleet, and 7th Fleet see the same ship in different places.”

- PACOM officer

Week 5:Outdated technology due to procurement

processes

“Navy acquisition: using yesterday’s technology... tomorrow.”

- 7th Fleet N2

Customer Discovery - Operations Center Workflow

Hey Max, why is the ship still in port? This info isn’t up-to-date.

Can you ask them to update this?

Customer Discovery - Operations Center Workflow

Yeah, hold on...

Customer Discovery - Operations Center Workflow

Customer Discovery - Operations Center Workflow

PacFleet unit manager

Hey Lauren, can you tell them to update this ship’s location?

Customer Discovery - Operations Center Workflow

7th Fleet

Hey Phil, can you get the new position for these guys?

Customer Discovery - Operations Center Workflow

Sure!

Customer Discovery - Operations Center Workflow

*Brrring*

Customer Discovery - Operations Center Workflow

Okay, the OS put in a new latitude and longitude.

Ah, there it is.

Customer Discovery - Operations Center Workflow

Weeks 6-7: Other Programs Trying to Address Gaps

● DARPA Insight● SRI International Cooperative Situational Information Integration● Maritime Tactical Command and Control (MTC2)● Global Command and Control System (GCCS-M)● Command and Control Personal Computer (C2PC)● Distributed Common Ground System - Navy (DCGS-N)● ONI Sealink Advanced Analysis● Resilient Command and Control

Weeks 6-7: Other Programs Trying to Address Gaps

● DARPA Insight● SRI International Cooperative Situational Information Integration● Maritime Tactical Command and Control (MTC2)● Global Command and Control System (GCCS-M)● Command and Control Personal Computer (C2PC)● Distributed Common Ground System - Navy (DCGS-N)● ONI Sealink Advanced Analysis● Resilient Command and ControlLots of existing programs...

Week 7: Classification Wall

You should talk with the program manager! I’ll send an intro email.

Great, thanks!

Week 7: Classification Wall

Hi, can you share anything about this tool?

Actually...no... Sorry.

Week 7: Found an Analogous Problem

Illegal Fishing

All the same problems and needs…

But without the classification issues!

Data & Analytics- Compile existing data resources/scope out future ones- Develop flexible data fusion/analytics algorithms

Defining C2-F- Brainstorming what “Command and Control of the Future” (C2-F or “MTC2-F”) would be- Interviewing (customer discovery) for younger sailors

Software Development

Prototype Testing/Acquisitions

Pursue Information Assurance Certification

USN Strategic Decision Makers

USN Analysts (N/J2)

USN Operators (N/J3)

Anti-IUU Fishing Enforcers (USCG, Partner Nations, etc.)

Anti-IUU Fishing Stakeholders (NGOs, Legal Fishing)

(Commercial entities that use/would benefit from enhanced C2-type systems)

USN- Timely, accurate operational decisions- Decreased time to predict hot spots, ID & differentiate threats- Increased engagement and effectiveness of younger sailors - Up-to-date, reliable info in frontline environment

Anti-IUU Fishing- Reduction in IUU fishing worldwide due to better deterrence- Better allocation of scarce / expensive interdiction resources- Widespread engagement of operators, governments, and the public

USN- Work with fleet sponsor to get C2-F system on fleet needs list- Ensure C2-F makes it into FIMES database, engage S&T bridge personnel to talk with key decision makers- Work with NWDC, ONR S&T, PACFLT LOEs to test solution- Engage PACFLT N8/N9 shops to implement modular operational deployment & update pathways

Anti IUU Fishing- Work with NGOs, gov’t departments, USCG, operators, etc. to find key influencers/stakeholders- Deploy solution where possible,

Fixed- Existing Software tools/APIs- Evaluation of commercial products- Information assurance process steps

Data & Analytics- APIs for accessing data (e.g. API for Global Fishing Watch, AIS), $$$ needed to access this

Defining C2-F-Ideas/feedback from young sailors

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 and operators from N3 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if we want to leverage their platforms

-Need support of existing PMOs/S&T personnel to make sure we’re not duplicating work

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key PartnersMilitary- PACFLT (7th/3rd Fleet, young E- and O- who use current C2 tools)- Program Office for MCT2 (PMW 150)- Information Assurance Personnel- NWDC, ONR S&T Advisors, C7F N2, C7F CIG, C3F N8/9, PACOM CSIG, OPNAV N2/N6 (Acquisition/Testing)

Anti-IUU Fishing Stakeholders- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)

Data/Software/Algorithms- Data: Skytruth, Pew, Global Fishing Watch, Capella, TerraSAR-Software: Palantir Skytruth, USCG, NPS/ONR, SeaVision, Sea Scout-Algorithms: Universities (e.g. Vanderbilt), NPS/ONR, NGOs

Software Development-AWS, programmers, $$$ for both, subject matter expertise on phenomenology of ships, activities

Prototype Testing/Acquisition- Military Sealift Command ships, 7th Fleet experimentation ships and personnel

Information Assurance Certification-Access to personnel to provide certification / approval

Variable- Travel for site visits, pilots, interviews with sailors- R&D personnel- Development- Data and APIs- AWS & Distributed Computing

IMPROVE USN DECISIONS & OPS VIA C2-F WITH

IMPROVED DATA HANDLING, UI/UX,

COMMS, AND HARDWARE

(1) Rapid Strategic Decisionmaking via Improved Reporting, Coordination, Visibility

(2) Improved Tactical Decision Making via Timely, Accurate Information Sharing

(3) More Effective Analysis via Searchable, Visualizable, Source-Flexible Data Integration (Layering & Filtering)

(4) Increased Analyst Bandwidth via Predictive Intel and Alerts (e.g. Machine Learning) Flexibly Applied to Available Data

(5) Improved Collection of Existing Data Streams

(6) Increasing Morale & Engagement for Millenial Sailors

ENHANCE ANTI-IUU FISHING CAPABILITIES

(1) Improved Detection Using Data Fusion/Analytics

(2) Enhanced Enforcement via Improved Communication

(3) Lower Barriers to Engaging Civilians in Reporting IUU Fishing Activities

Week 7 Mission: Enabling Rapid Decisions from Heterogeneous Data - Pivot to Proxy

Data & Analytics- Compile existing data resources/scope out future ones- Develop flexible data fusion/analytics algorithms

Defining C2-F- Brainstorming what “Command and Control of the Future” (C2-F or “MTC2-F”) would be- Interviewing (customer discovery) for younger sailors

Software Development

Prototype Testing/Acquisitions

Pursue Information Assurance Certification

USN Strategic Decision Makers

USN Analysts (N/J2)

USN Operators (N/J3)

Anti-IUU Fishing Enforcers (USCG, Partner Nations, etc.)

Anti-IUU Fishing Stakeholders (NGOs, Legal Fishing)

(Commercial entities that use/would benefit from enhanced C2-type systems)

USN- Timely, accurate operational decisions- Decreased time to predict hot spots, ID & differentiate threats- Increased engagement and effectiveness of younger sailors - Up-to-date, reliable info in frontline environment

Anti-IUU Fishing- Reduction in IUU fishing worldwide due to better deterrence- Better allocation of scarce / expensive interdiction resources- Widespread engagement of operators, governments, and the public

USN- Work with fleet sponsor to get C2-F system on fleet needs list- Ensure C2-F makes it into FIMES database, engage S&T bridge personnel to talk with key decision makers- Work with NWDC, ONR S&T, PACFLT LOEs to test solution- Engage PACFLT N8/N9 shops to implement modular operational deployment & update pathways

Anti IUU Fishing- Work with NGOs, gov’t departments, USCG, operators, etc. to find key influencers/stakeholders- Deploy solution where possible,

Fixed- Existing Software tools/APIs- Evaluation of commercial products- Information assurance process steps

Data & Analytics- APIs for accessing data (e.g. API for Global Fishing Watch, AIS), $$$ needed to access this

Defining C2-F-Ideas/feedback from young sailors

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 and operators from N3 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if we want to leverage their platforms

-Need support of existing PMOs/S&T personnel to make sure we’re not duplicating work

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key PartnersMilitary- PACFLT (7th/3rd Fleet, young E- and O- who use current C2 tools)- Program Office for MCT2 (PMW 150)- Information Assurance Personnel- NWDC, ONR S&T Advisors, C7F N2, C7F CIG, C3F N8/9, PACOM CSIG, OPNAV N2/N6 (Acquisition/Testing)

Anti-IUU Fishing Stakeholders- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)

Data/Software/Algorithms- Data: Skytruth, Pew, Global Fishing Watch, Capella, TerraSAR-Software: Palantir Skytruth, USCG, NPS/ONR, SeaVision, Sea Scout-Algorithms: Universities (e.g. Vanderbilt), NPS/ONR, NGOs

Week 7 Mission: Enabling Rapid Decisions from Heterogeneous Data - Pivot to Proxy

Software Development-AWS, programmers, $$$ for both, subject matter expertise on phenomenology of ships, activities

Prototype Testing/Acquisition- Military Sealift Command ships, 7th Fleet experimentation ships and personnel

Information Assurance Certification-Access to personnel to provide certification / approval

Variable- Travel for site visits, pilots, interviews with sailors- R&D personnel- Development- Data and APIs- AWS & Distributed Computing

IMPROVE USN DECISIONS & OPS VIA C2-F WITH

IMPROVED DATA HANDLING, UI/UX,

COMMS, AND HARDWARE

(1) Rapid Strategic Decisionmaking via Improved Reporting, Coordination, Visibility

(2) Improved Tactical Decision Making via Timely, Accurate Information Sharing

(3) More Effective Analysis via Searchable, Visualizable, Source-Flexible Data Integration (Layering & Filtering)

(4) Increased Analyst Bandwidth via Predictive Intel and Alerts (e.g. Machine Learning) Flexibly Applied to Available Data

(5) Improved Collection of Existing Data Streams

(6) Increasing Morale & Engagement for Millenial Sailors

ENHANCE ANTI-IUU FISHING CAPABILITIES

(1) Improved Detection Using Data Fusion/Analytics

(2) Enhanced Enforcement via Improved Communication

(3) Lower Barriers to Engaging Civilians in Reporting IUU Fishing Activities

Value Proposition

- Data fusion & analytics with multiple sensor feeds

- Intuitive, easy-to-use UI

Beneficiaries

- …

- anti-IUU fishing enforcers & stakeholders (i.e. Coast Guard, NGOs, legal fishers)

Week 8: Redefined our Approach/Visit to San Diego

- Procurement + deployment tricks

- How to fit with existing tools?

Access to tools, datasets

IUU Fishing

Navy 7th Fleet, 3rd Fleet

Visit to San Diego!

Weeks 8: Visit to San Diego

Weeks 8 - 9: Towards the Future

Week 8:Command & Control of the Future (C2-F)

“If I had you four working for me, I’d have you work

on C2 for your generation.”- 3rd Fleet

Weeks 8 - 9: Towards the Future

Week 8:Command & Control of the Future (C2-F)

“If I had you four working for me, I’d have you work

on C2 for your generation.”- 3rd Fleet

Week 9:Sponsor is excited

about C2-F

“You guys have grasped what very few people understand.”

- Sponsor, 7th Fleet

“I’d like to stay involved in what you are doing moving forward!”

- Sponsor, 7th Fleet

Final MVP - Command & Control of the Future

CIC PACOM

Surface radar contact but no AIS… This is odd. Let me ALERT others.

Final MVP - Command & Control of the Future

CIC PACOM

Surface radar contact but no AIS… This is odd. Let me ALERT others.

I see an ALERT from DDG102. Lets share the C2 screen and take a look

Final MVP - Command & Control of the Future

CIC PACOM

Final MVP - Command & Control of the Future

CIC PACOM

Data & Analytics- Compile existing data resources/scope out future ones- Develop flexible data fusion/analytics algorithms

Defining C2-F- Brainstorming what “Command and Control of the Future” (C2-F or “MTC2-F”) would be- Interviewing (customer discovery) for younger sailors

Software Development

Prototype Testing/Acquisitions

Pursue Information Assurance Certification

USN Strategic Decision Makers

USN Analysts (N/J2)

USN Operators (N/J3)

Anti-IUU Fishing Enforcers (USCG, Partner Nations, etc.)

Anti-IUU Fishing Stakeholders (NGOs, Legal Fishing)

(Commercial entities that use/would benefit from enhanced C2-type systems)

USN- Timely, accurate operational decisions- Decreased time to predict hot spots, ID & differentiate threats- Increased engagement and effectiveness of younger sailors - Up-to-date, reliable info in frontline environment

Anti-IUU Fishing- Reduction in IUU fishing worldwide due to better deterrence- Better allocation of scarce / expensive interdiction resources- Widespread engagement of operators, governments, and the public

USN- Work with fleet sponsor to get C2-F system on fleet needs list- Ensure C2-F makes it into FIMES database, engage S&T bridge personnel to talk with key decision makers- Work with NWDC, ONR S&T, PACFLT LOEs to test solution- Engage PACFLT N8/N9 shops to implement modular operational deployment & update pathways

Anti IUU Fishing- Work with NGOs, gov’t departments, USCG, operators, etc. to find key influencers/stakeholders- Deploy solution where possible,

Fixed- Existing Software tools/APIs- Evaluation of commercial products- Information assurance process steps

Data & Analytics- APIs for accessing data (e.g. API for Global Fishing Watch, AIS), $$$ needed to access this

Defining C2-F-Ideas/feedback from young sailors

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 and operators from N3 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if we want to leverage their platforms

-Need support of existing PMOs/S&T personnel to make sure we’re not duplicating work

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key PartnersMilitary- PACFLT (7th/3rd Fleet, young E- and O- who use current C2 tools)- Program Office for MCT2 (PMW 150)- Information Assurance Personnel- NWDC, ONR S&T Advisors, C7F N2, C7F CIG, C3F N8/9, PACOM CSIG, OPNAV N2/N6 (Acquisition/Testing)

Anti-IUU Fishing Stakeholders- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)

Data/Software/Algorithms- Data: Skytruth, Pew, Global Fishing Watch, Capella, TerraSAR-Software: Palantir Skytruth, USCG, NPS/ONR, SeaVision, Sea Scout-Algorithms: Universities (e.g. Vanderbilt), NPS/ONR, NGOs

Week 9 Mission: Creating C2-F - Enabling Rapid Decisions from Heterogeneous Data

Software Development-AWS, programmers, $$$ for both, subject matter expertise on phenomenology of ships, activities

Prototype Testing/Acquisition- Military Sealift Command ships, 7th Fleet experimentation ships and personnel

Information Assurance Certification-Access to personnel to provide certification / approval

Variable- Travel for site visits, pilots, interviews with sailors- R&D personnel- Development- Data and APIs- AWS & Distributed Computing

IMPROVE USN DECISIONS & OPS VIA C2-F WITH

IMPROVED DATA HANDLING, UI/UX,

COMMS, AND HARDWARE

(1) Rapid Strategic Decisionmaking via Improved Reporting, Coordination, Visibility

(2) Improved Tactical Decision Making via Timely, Accurate Information Sharing

(3) More Effective Analysis via Searchable, Visualizable, Source-Flexible Data Integration (Layering & Filtering)

(4) Increased Analyst Bandwidth via Predictive Intel and Alerts (e.g. Machine Learning) Flexibly Applied to Available Data

(5) Improved Collection of Existing Data Streams

(6) Increasing Morale & Engagement for Millenial Sailors

ENHANCE ANTI-IUU FISHING CAPABILITIES

(1) Improved Detection Using Data Fusion/Analytics

(2) Enhanced Enforcement via Improved Communication

(3) Lower Barriers to Engaging Civilians in Reporting IUU Fishing Activities

Next Steps

Goal: Develop dual-use “Command & Control Tool of the Future” based on collaborative data aggregation tool for the IUU fishing use case

We’re going to continue working on this

Navy and sponsor interested

IUU Fishing folks are interested

IRL 1

IRL 4

IRL 3

IRL 2

IRL 7

IRL 6

IRL 5

IRL 8

IRL 9

First pass on MMC w/Problem Sponsor

Complete ecosystem analysis petal diagram

Validate mission achievement (Right side of canvas)

Problem validated through initial interviews

Prototype low-fidelity Minimum Viable Product

Value proposition/mission fit (Value Proposition Canvas)

Validate resource strategy (Left side of canvas)

Prototype high-fidelity Minimum Viable Product

Establish mission achievement metrics that matterTeam Assessment :IRL 5

Post H4D Course Actions

Team Sentinel intends to pursue funding to create a dual use solution for IUU fishing, with the eventual goal of getting a variant adopted by the Navy.

Investment Readiness Level

Thank You!

We could not have survived this journey without the support from these outstanding individuals (and many more!):

Sponsor● LT Jason Knudson

Military Liaisons● COL John Chu● CDR Todd “Chimi” Cimicata

PACOM/Pac Fleet/7th Fleet/3rd Fleet● CAPTs Andy Hertel, Greg

Hussman, ...● CDR Rich LeBron, ...● CAPT Yvette Davids, ...● LT Kevin Walter, LTJG Vince

Fontana

Coast Guard● CAPT Chris Conley● LCDR Jed Raskie

NPS● CDR Pablo Breuer● CAPT Scot Miller

Others● Dean Moon● Rick Rikoski● Chuck Wolf● Richard D'Alessandro

(OGSystems)● Graham Gilmer (BAH)

DIUx● Steve Butow, Lauren

Schmidt

Thanks for listening!

Questions?

Appendix

Mission Model Canvii

Research- Interviews to assess needs, organizational dynamics, procurement strategy- Site visits to see current practices- Identify key geographic areas of interest

Prototype- Evaluate existing sensor platforms with commercial partners- Integrate sensor(s) of interest into partner product- Compile existing data resources- Evaluate ML algorithms

Scaling- Develop fabrication / procurement strategy- Develop tactical deployment strategy

Strategic Decision MakersE.g. CPT Greg Hussman, VADM Joseph AucoinAcquisition PersonnelWe need to find + talk with these peopleAnalystsE.g. Jason Knudson, John Chu, Jed RaskieDeployersWe need to find + talk with these peoplePrimary: 7th Fleet decision makers, ONI intelligence officers, and operatorsSecondary: Dual-use entities such as Coast Guard, environmental monitoring, researchTertiary: State Department

Actionable intelligence- Predictive vs reactionary intel through machine learning - identify potential hot spots- Simplifying to reduce data overload- Improved UI increases decision quality and speed

Information Sharing- Open architecture- Improved information sharing with differential permissions- Cross-domain analysis techniques to integrate multiple data sources- Plug-and-play data sources- Back/forward compatibility

Deployment strategy- i.e. deploy disposable sensors off of waveglider- modularity + distributed architecture- deployable from multiple platforms

Lower cost sensor solution- disposable/low-maintenance

Improved coverage- Persistent presence over enlarged area- Design reliability & robustness via distributed architecture

Episodic persistence- Persistent coverage of a chokepoint area for a limited time

Reduce manpower burden: - Remove tedious/manual tasks through automation- More efficiently use existing analysts

- Decreased time to predict hot spots, ID & differentiate threats- Good UI for operators, decision-makers- Increased area coverage + persistence- Episodic persistent coverage with easily-deployed system- Cost savings with respect to existing solutions- Prototype operability + demonstrated scalability

Hardware- Acquire initial sensor platform with single desired capability- Build multiple units pursuing the same threat group (network effects) and derive useful insights from analysis tools- Deploy pilot in operational environment- Develop fabrication/procurement pipeline + cost models for scaling

Software- Build data aggregation backend + analytic engine + user-friendly UI

Fixed- Buying proprietary data- Software tools- Hardware evaluation + prototyping equipment- Evaluation of commercial products

Prototyping- Existing sensor platforms- Academic research

Scaling- Available commercial + military data- Existing analysis software tools- AWS

- Need demand from operators and deployment personnel in 7th Fleet

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if want to leverage their platforms

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key Partners

Military- 7th Fleet + designated sponsor- Naval Postgraduate School (NPS)- Office of Naval Research (ONR)

Commercial- Distributed sensor platform companies (i.e. Saildrone, AMS)- Data analytics (i.e. Palantir, Google)- Advanced manufacturing

Academic- Universities (i.e. University of Hawaii)- National Labs (Lincoln Labs, Sandia)

Other- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)

Mission: Provide Cost-Effective, Actionable Intelligence at All Times

Testing- 7th Fleet assets for pilot- Research barge

Variable- Travel for site visits, pilots- R&D personnel- Manufacturing

Research- Interviews to assess needs, organizational dynamics, procurement strategy- Site visits to see current practices- Identify key geographic areas of interest

Prototype- Evaluate existing sensor platforms with commercial partners- Integrate sensor(s) of interest into partner product- Compile existing data resources- Evaluate ML algorithms

Scaling- Develop fabrication / procurement strategy- Develop tactical deployment strategy

Strategic Decision MakersE.g. CPT Greg Hussman, VADM Joseph Aucoin

Analysts (N2)E.g. Jason Knudson, John Chu, Jed Raskie, Joseph Baba Deployers (N3)We need to find + talk with these people

ACQUIRING READY-TO-USE DATA

Episodic persistence- Persistent coverage of a chokepoint area for a limited time (days - 1 mo)

Timely deployment strategy- i.e. deploy disposable sensors off of waveglider- sub-2 hr latency (TBD)- deployable from multiple platforms

Lower cost sensor solution- disposable/low-maintenance- modularity + distributed architecture

Open Architecture- Improved information sharing with differential permissions- Object-oriented database that is easily searchable- Cross-domain analysis techniques to integrate multiple data sources- Compatible data format (.kmz)

Actionable intelligence- Predictive vs reactionary intel through machine learning - identify potential hot spots- Simplifying to reduce data overload- Improved UI increases decision quality and speed

Reduce manpower burden: - Remove tedious/manual tasks through automation- More efficiently use existing analysts

- Decreased time to predict hot spots, ID & differentiate threats

- Good UI for operators, decision-makers

- Timely, episodic persistent coverage with easily-deployed system

- Cost savings with respect to existing solutions

- Prototype operability + demonstrated scalability

Hardware- Acquire initial sensor platform with single desired capability- Build multiple units pursuing the same threat group (network effects) and derive useful insights from analysis tools- Design deployment strategy + platform- Deploy pilot in operational environment- Develop fabrication/procurement pipeline + cost models for scaling

Software- Determine most useful data interface for analysts

Fixed- Buying proprietary data- Software tools- Hardware evaluation + prototyping equipment- Evaluation of commercial products

Prototyping- Existing sensor platforms- Existing deployment platforms- Academic research

Scaling- Available commercial + military data- Existing database tools (Palantir, AWS)

- Need demand from operators and deployment personnel in 7th Fleet

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if want to leverage their platforms

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key Partners

Military- 7th Fleet + designated sponsor- Naval Postgraduate School (NPS)- Office of Naval Research (ONR)- Acquisition Personnel

Commercial- Distributed sensor platform companies (i.e. Saildrone, AMS)- Data analytics (i.e. Palantir, Google)- Advanced manufacturing

Academic- Universities (i.e. University of Hawaii)- National Labs (Lincoln Labs, Sandia)

Other- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)

Mission: Provide Cost-Effective, Actionable Intelligence at All Times

Testing- 7th Fleet assets for pilot- Research barge

Variable- Travel for site visits, pilots- R&D personnel- Manufacturing

Research- Interviews to assess needs, organizational dynamics, procurement strategy- Site visits to see current practices- Identify key geographic areas of interest

Prototype- Evaluate existing sensor platforms with commercial partners- Integrate sensor(s) of interest into partner product- Compile existing data resources- Evaluate relevant ML algorithms- Iterate on human-machine interaction

Strategic Decision MakersE.g. CPT Greg Hussman, VADM Joseph AucoinADM Scott Swift (PacFleet)ADM Harry Harris (PACOM)

Analysts (N2)E.g. Jason Knudson, John Chu, Jed Raskie, Joseph Baba Deployers (N3)Scheduled this week

Planners (N5)Need to find these people

- Decreased time to predict hot spots, ID & differentiate threats

- Good UI for operators, decision-makers

- Timely, episodic persistent coverage with easily-deployed system

- Cost savings with respect to existing solutions

- Prototype operability + demonstrated scalability

Hardware- Acquire initial sensor platform with single desired capability- Design deployment strategy + platform- Deploy pilot in operational environment- Develop fabrication/procurement pipeline + cost models for scaling

Software- Determine most useful data interface for analysts- Determine optimal information flow to strategic decision makers- Develop ML and visualization algorithms- Build, Test, and Deploy Product

Fixed- Buying proprietary data- Software tools- Hardware evaluation + prototyping equipment- Evaluation of commercial products

Prototyping- Existing sensor platforms- Existing deployment platforms- Academic research

Scaling- Available commercial + military data- Existing database tools (Palantir, AWS)

- Need demand from operators and deployment personnel in 7th Fleet

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if want to leverage their platforms

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key Partners

Military- 7th Fleet + designated sponsor- Naval Postgraduate School (NPS)- Office of Naval Research (ONR)- Acquisition Personnel

Commercial- Distributed sensor platform companies (i.e. Saildrone, AMS)- Data analytics (i.e. Palantir, Google)- Advanced manufacturing

Academic- Universities (i.e. University of Hawaii)- National Labs (Lincoln Labs, Sandia)

Other- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)

Mission: Provide Cost-Effective, Actionable Intelligence at All Times

Testing- 7th Fleet assets for pilot- Research barge- Access to model analyst data interface

Variable- Travel for site visits, pilots- R&D personnel- Manufacturing/Development

IMPROVE TACTICAL AND STRATEGIC DECISION

MAKING VIA BETTER DATA HANDLING

(1) Rapid Strategic Decisionmaking via Improved Reporting

(2) Improved Tactical Decision Making via Enhanced Information Sharing

(3) More Effective Analysis via Searchable, Visualizable Data Integration

ENHANCE INCOMING DATA STREAMS

(1) Improved Collection of Existing Data Streams (e.g. Fishing Broadcasts)

(2) Predictive Intel through Machine Learning

Additional Sensing Capability

Research- Interviews to assess needs, organizational dynamics, procurement strategy- Site visits to see current practices-Understanding current workflow

Prototype- Evaluate existing sensor platforms with commercial partners- Integrate sensor feeds of interest into prototype platform- Compile existing data resources- Create representative “fake” datasets- Evaluate relevant ML algorithms for prediction and rules for push alerts- Iterate on human-machine interaction

Strategic Decision MakersVADM Joseph AucoinADM Scott Swift (PacFleet)ADM Harry Harris (PACOM)

Analysts (N/J2)E.g. Jason Knudson, John Chu, Jed Raskie, Joseph Baba Operators (N/J3)CDR Chris Adams (7th Fleet)

Planners (N/J5)Need to find these people

- Common and consistent view of the Area of Responsibility (AOR)

- Timely operational decisions

- Decreased time to predict hot spots, ID & differentiate threats

- Reduced time for analysts to find information and draw conclusions

- Prototype operability + demonstrated scalability

Data Fusion/Sensor Integration Software (THIS SECTION IS A WORK IN PROGRESS!)

- Build solution that integrates with current systems (e.g. GCCS)

- Work with PMs and key influencers to determine optimal funding/dissemination avenues

- Deploy prototype, confirm buy-in and update features

- Scale deployment, improve product as necessary

Fixed- Buying proprietary data- Software tools- Hardware evaluation + prototyping equipment- Evaluation of commercial products

Prototyping- Existing sensor platforms and feeds- Existing deployment platforms- Academic research- Existing data fusion platforms

Scaling- Available commercial + military data- Existing database tools (Palantir, AWS)

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 and operators from N3 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if want to leverage their platforms

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key Partners

Military- 7th Fleet + designated sponsor- Naval Postgraduate School (NPS)- Office of Naval Research (ONR)- Acquisition Personnel

Commercial- Distributed sensor platform companies (i.e. Saildrone, AMS)- Data analytics (i.e. Palantir, Google)

Academic- Universities (i.e. University of Hawaii)- National Labs (Lincoln Labs, Sandia)

Other- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)- Disaster relief agencies

Mission: Enabling Rapid, Well-Informed Decisions from Heterogeneous Data

Testing- 7th Fleet assets for pilot- Research barge- Access to model analyst data interface- Access to sample incoming sensor feeds

Variable- Travel for site visits, pilots- R&D personnel- Manufacturing/Development

IMPROVE TACTICAL AND STRATEGIC DECISION

MAKING VIA BETTER DATA HANDLING

(1) Rapid Strategic Decisionmaking via Improved Reporting

(2) Improved Tactical Decision Making via Enhanced Information Sharing

(3) More Effective Analysis via Searchable, Visualizable Data Integration

(4) Predictive Intel and Alerts (e.g. Machine Learning)

ENHANCE INCOMING DATA STREAMS

(1) Improved Collection of Existing Data Streams (e.g. Fishing Broadcasts)

(2) Painless Incorporation of Multiple New Sensing Modalities

Research- Interviews to assess needs, organizational dynamics, procurement strategy- Site visits to see current practices-Understanding current workflow

Prototype- Integrate sensor feeds of interest into prototype platform- Compile existing data resources- Create representative “fake” datasets- Evaluate relevant ML algorithms for prediction and rules for push alerts- Iterate on human-machine interaction

Strategic Decision MakersVADM Joseph AucoinADM Scott Swift (PacFleet)ADM Harry Harris (PACOM)

Analysts (N/J2)E.g. Jason Knudson, John Chu, Jed Raskie, Joseph Baba Operators (N/J3)CDR Chris Adams (7th Fleet)

Planners (N/J5)Jose Lepesuastegui (N25)

- Common and consistent view of the Area of Responsibility (AOR)

- Timely operational decisions

- Decreased time to predict hot spots, ID & differentiate threats

- Reduced time for analysts to find information and draw conclusions

- Prototype operability + demonstrated scalability

Data Fusion/Sensor Integration Software (THIS SECTION IS A WORK IN PROGRESS!)

- Build solution that integrates with current systems (e.g. GCCS, QUELLFIRE, FOBM)

- Work with PMs and key influencers to determine optimal funding/dissemination avenues

- Deploy prototype, confirm buy-in and update features

- Scale deployment, improve product as necessary

Fixed- Buying proprietary data- Software tools- Evaluation of commercial products

Prototyping- Existing sensor platforms and feeds- Academic research- Existing data fusion platforms

Scaling- Available commercial + military data- Existing database tools (Palantir, AWS)

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 and operators from N3 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if want to leverage their platforms

-Need support of existing PMOs to make sure we’re not duplicating work

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key PartnersMilitary- 7th Fleet + designated sponsor- NPS/ONR- Acquisition Personnel- Existing PORs (Insight, PMW-150, Quellfire, SeaVision, FOBM)

Commercial- Distributed sensor platform companies (i.e. Saildrone, AMS)- Data analytics (i.e. Palantir, Google)

Academic- Universities (i.e. University of Hawaii)- National Labs (Lincoln Labs, Sandia)

Other- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)- Disaster relief agencies

Mission: Enabling Rapid, Well-Informed Decisions from Heterogeneous Data

Testing- 7th Fleet assets for pilot- Research barge- Access to model analyst data interface- Access to sample incoming sensor feeds

Variable- Travel for site visits, pilots- R&D personnel-Development

IMPROVE TACTICAL AND STRATEGIC DECISION

MAKING VIA BETTER DATA HANDLING

(1) Rapid Strategic Decisionmaking via Improved Reporting and Coordination

(2) Improved Tactical Decision Making via Timely, Accurate Information Sharing

(3) More Effective Analysis via Searchable, Visualizable Data Integration (Layering & Filtering)

(4) Predictive Intel and Alerts (e.g. Machine Learning)

ENHANCE INCOMING DATA STREAMS

(1) Improved Collection of Existing Data Streams (e.g. Fishing Broadcasts)

(2) Painless Incorporation of Multiple New Sensing Modalities

(3 Integration of Incoming Data Streams with Existing Object-Oriented Database

Research- Interviews to assess needs, organizational dynamics, procurement strategy- Site visits to see current practices-Understanding current workflow

Connecting People and Programs- Ensuring tool developers and users are aware of one another- Finding functional gaps to fill

Prototype- Compile existing data resources- Create representative “fake” datasets- Evaluate relevant ML algorithms for prediction/rules for push alerts- Iterate on human-machine interaction

Strategic Decision MakersVADM Joseph AucoinADM Scott Swift (PacFleet)ADM Harry Harris (PACOM)

Analysts (N/J2)E.g. Jason Knudson, John Chu, Jed Raskie, Joseph Baba Operators (N/J3)CDR Chris Adams (7th Fleet)

Planners (N/J5)Jose Lepesuastegui (N25)

- Common and consistent view of the Area of Responsibility (AOR)

- Timely operational decisions

- Decreased time to predict hot spots, ID & differentiate threats

- Reduced time for analysts to find information and draw conclusions

- Prototype operability + demonstrated scalability

Data Fusion/Sensor Integration Software

- Build solution that integrates with current systems (e.g. GCCS, QUELLFIRE, FOBM, EWBM, INSIGHT)

- Work with PMs and key influencers to determine optimal funding/dissemination avenues and integration with current tool pipeline

- Deploy prototype, confirm buy-in and update features

- Scale deployment, improve product as necessary

Fixed- Buying proprietary data- Software tools- Evaluation of commercial products

Prototyping- Existing sensor platforms and feeds- Academic research- Existing data fusion platforms

Scaling- Available commercial + military data- Existing database tools (Palantir, AWS)

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 and operators from N3 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if we want to leverage their platforms

-Need support of existing PMOs/S&T personnel to make sure we’re not duplicating work

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key PartnersMilitary- 7th Fleet + designated sponsor- NPS/ONR- Acquisition Personnel- Existing PMOs/PORs- Other Fleets

Commercial- Distributed sensor platform companies (i.e. Saildrone, AMS)- Data analytics (i.e. Palantir, Google)

Academic- Universities (i.e. University of Hawaii)- National Labs (Lincoln Labs, Sandia)

Other- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)- Disaster relief agencies

Mission: Enabling Rapid, Well-Informed Decisions from Heterogeneous Data

Testing- 7th Fleet assets for pilot- Research barge- Access to model analyst data interface and in-development tools- Access to sample incoming sensor feeds

Variable- Travel for site visits, pilots- R&D personnel-Development

IMPROVE TACTICAL AND STRATEGIC DECISION

MAKING VIA BETTER DATA HANDLING

(1) Rapid Strategic Decisionmaking via Improved Reporting and Coordination

(2) Improved Tactical Decision Making via Timely, Accurate Information Sharing

(3) More Effective Analysis via Searchable, Visualizable Data Integration (Layering & Filtering)

(4) Predictive Intel and Alerts (e.g. Machine Learning)

ENHANCE INCOMING DATA STREAMS

(1) Improved Collection of Existing Data Streams (e.g. Fishing Broadcasts)

(2) Painless Incorporation of Multiple New Sensing Modalities

(3 Integration of Incoming Data Streams with Existing Object-Oriented Database

Research- Interviews to assess needs, organizational dynamics, procurement strategy- Site visits to see current practices-Understanding current workflow

Connecting People and Programs- Ensuring tool developers and users are aware of one another- Finding functional gaps to fill

Prototype- Compile existing data resources- Create representative “fake” datasets- Evaluate relevant ML algorithms for prediction/rules for push alerts-Create demo of flexible data fusion/analytics for IUU fishing

Strategic Decision Makers

Analysts (N/J2)

Operators (N/J3)

Planners (N/J5)

- Timely operational decisions

-Common and consistent view of the Area of Responsibility (AOR)

=Flexible integration of new feeds into COP and analytics

- Decreased time to predict hot spots, ID & differentiate threats

- Reduced time for analysts to find information and draw conclusions

- Prototype operability + demonstrated scalability

Data Fusion/Sensor Integration Software

- Build solution that integrates with current systems (e.g. GCCS, QUELLFIRE, FOBM, EWBM, INSIGHT)

- Work with PMs and key influencers to determine optimal funding/dissemination avenues and integration with current tool pipeline

- Deploy prototype, confirm buy-in and update features

- Scale deployment, improve product as necessary

Fixed- Buying proprietary data- Software tools- Evaluation of commercial products

Prototyping- Existing sensor platforms and feeds- Academic research- Existing data fusion platforms

Scaling- Available commercial + military data- Existing database tools (Palantir, AWS)

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 and operators from N3 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if we want to leverage their platforms

-Need support of existing PMOs/S&T personnel to make sure we’re not duplicating work

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key PartnersMilitary- 7th Fleet + designated sponsor- NPS/ONR- Acquisition Personnel- Existing PMOs/PORs- Other Fleets

Commercial- Distributed sensor platform companies (i.e. Saildrone, AMS)- Data analytics (i.e. Palantir, Google)

Academic- Universities (i.e. University of Hawaii)- National Labs (Lincoln Labs, Sandia)

Other- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)- Disaster relief agencies

Mission: Enabling Rapid, Well-Informed Decisions from Heterogeneous Data

Testing- 7th Fleet assets for pilot- Research barge- Access to model analyst data interface and in-development tools- Access to sample incoming sensor feeds

Variable- Travel for site visits, pilots- R&D personnel-Development

IMPROVE TACTICAL AND STRATEGIC DECISION

MAKING VIA BETTER DATA HANDLING

(1) Rapid Strategic Decisionmaking via Improved Reporting and Coordination

(2) Improved Tactical Decision Making via Timely, Accurate, Information Sharing

(3) More Effective Analysis via Searchable, Visualizable, Source-Flexible Data Integration (Layering & Filtering)

(4) Predictive Intel and Alerts (e.g. Machine Learning) Flexibly Applied to Available Data and Rapidly Updateable to Account for New Sources

ENHANCE INCOMING DATA STREAMS

(1) Improved Collection of Existing Data Streams (e.g. Fishing Broadcasts)

(2) Painless Incorporation of Multiple New Sensing Modalities

(3 Integration of Incoming Data Streams with Existing Object-Oriented Database

Data & Analytics- Compile existing data resources/scope out future ones- Develop flexible data fusion/analytics algorithms

Defining C2-F- Brainstorming what “Command and Control of the Future” (C2-F or “MTC2-F”) would be- Interviewing (customer discovery) for younger sailors

Software Development

Prototype Testing/Acquisitions

Pursue Information Assurance Certification

USN Strategic Decision Makers

USN Analysts (N/J2)

USN Operators (N/J3)

Anti-IUU Fishing Enforcers (USCG, Partner Nations, etc.)

Anti-IUU Fishing Stakeholders (NGOs, Legal Fishing)

(Commercial entities that use/would benefit from enhanced C2-type systems)

USN- Timely, accurate operational decisions- Decreased time to predict hot spots, ID & differentiate threats- Increased engagement and effectiveness of younger sailors - Up-to-date, reliable info in frontline environment

Anti-IUU Fishing- Reduction in IUU fishing worldwide due to better deterrence- Better allocation of scarce / expensive interdiction resources- Widespread engagement of operators, governments, and the public

USN- Work with fleet sponsor to get C2-F system on fleet needs list- Ensure C2-F makes it into FIMES database, engage S&T bridge personnel to talk with key decision makers- Work with NWDC, ONR S&T, PACFLT LOEs to test solution- Engage PACFLT N8/N9 shops to implement modular operational deployment & update pathways

Anti IUU Fishing- Work with NGOs, gov’t departments, USCG, operators, etc. to find key influencers/stakeholders- Deploy solution where possible,

Fixed- Existing Software tools/APIs- Evaluation of commercial products- Information assurance process steps

Data & Analytics- APIs for accessing data (e.g. API for Global Fishing Watch, AIS), $$$ needed to access this

Defining C2-F-Ideas/feedback from young sailors

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 and operators from N3 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if we want to leverage their platforms

-Need support of existing PMOs/S&T personnel to make sure we’re not duplicating work

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key PartnersMilitary- PACFLT (7th/3rd Fleet, young E- and O- who use current C2 tools)- Program Office for MCT2 (PMW 150)- Information Assurance Personnel- NWDC, ONR S&T Advisors, C7F N2, C7F CIG, C3F N8/9, PACOM CSIG, OPNAV N2/N6 (Acquisition/Testing)

Anti-IUU Fishing Stakeholders- IUU fishing + anti-smuggling stakeholders (i.e. Coast Guard, PNA)

Data/Software/Algorithms- Data: Skytruth, Pew, Global Fishing Watch, Capella, TerraSAR-Software: Palantir Skytruth, USCG, NPS/ONR, SeaVision, Sea Scout-Algorithms: Universities (e.g. Vanderbilt), NPS/ONR, NGOs

Mission: Creating C2-F--Enabling Rapid Decisions from Heterogeneous Data

Software Development-AWS, programmers, $$$ for both, subject matter expertise on phenomenology of ships, activities

Prototype Testing/Acquisition- Military Sealift Command ships, 7th Fleet experimentation ships and personnel

Information Assurance Certification-Access to personnel to provide certification / approval

Variable- Travel for site visits, pilots, interviews with sailors- R&D personnel- Development- Data and APIs- AWS & Distributed Computing

IMPROVE USN DECISIONS & OPS VIA C2-F WITH

IMPROVED DATA HANDLING, UI/UX,

COMMS, AND HARDWARE

(1) Rapid Strategic Decisionmaking via Improved Reporting, Coordination, Visibility

(2) Improved Tactical Decision Making via Timely, Accurate Information Sharing

(3) More Effective Analysis via Searchable, Visualizable, Source-Flexible Data Integration (Layering & Filtering)

(4) Increased Analyst Bandwidth via Predictive Intel and Alerts (e.g. Machine Learning) Flexibly Applied to Available Data

(5) Improved Collection of Existing Data Streams

(6) Increasing Morale & Engagement for Millenial Sailors

ENHANCE ANTI-IUU FISHING CAPABILITIES

(1) Improved Detection Using Data Fusion/Analytics

(2) Enhanced Enforcement via Improved Communication

(3) Lower Barriers to Engaging Civilians in Reporting IUU Fishing Activities

Data- Compile existing data resources/scope out future ones

Defining C2-F- Brainstorming what “Command and Control of the Future” would be by interviewing younger sailors

Software Development- Develop flexible data fusion/analytics algorithms, and an intuitive UI for millennials

Information Assurance

Prototype Testing/Procurement

Contracting, Acquisitions

Maintenance and Support

USN Strategic Decision Makers

USN Analysts (N/J2)

USN Operators (N/J3)

Anti-IUU Fishing Enforcers (USCG, Partner Nations, etc.)

Anti-IUU Fishing Stakeholders (NGOs, Legal Fishing)

(Commercial entities that use/would benefit from enhanced C2-type systems)

USN- Timely, accurate operational decisions- Decreased time to predict hot spots, ID & differentiate threats- Increased engagement and effectiveness of younger sailors - Up-to-date, reliable info in frontline environment

Anti-IUU Fishing- Reduction in IUU fishing worldwide due to better deterrence- Better allocation of scarce / expensive interdiction resources- Widespread engagement of operators, governments, and the public

USN- Work with fleet sponsor to get C2-F system on fleet needs list- Ensure C2-F makes it into FIMS database, engage S&T bridge personnel to talk with key decision makers- Work with NWDC, ONR S&T, PACFLT LOEs to test solution - Engage PACFLT N8/N9 shops to implement modular operational deployment & update pathways

Anti IUU Fishing- Work with NGOs, gov’t departments, USCG, operators, etc. to find key influencers/stakeholders- Deploy solution where possible,

Fixed- Existing Software tools/APIs, Data- IA process steps- Travel for site visits, pilots, interviews with sailors- R&D personnel- AWS & Distributed Computing- Overhead

Data & AnalyticsAPIs for accessing data (e.g. API for Global Fishing Watch, AIS), $$$ needed to access this

Defining C2-FIdeas/feedback from young sailorsHackathon w/ Navy and DIUx support

Software DevelopmentAWS, programmers, $$$ for both, SME on phenomenology of ships, activities

- Need commanding officer to confirm decision-making benefits

- Need intelligence officers from ONI / N2 and operators from N3 to confirm effectiveness of insights

- Need IT approvals to integrate into systems

- Need support of commercial partners if we want to leverage their platforms

-Need support of existing PMOs/S&T personnel to make sure we’re not duplicating work

Beneficiaries

Mission Achievement

Mission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key PartnersDataSkytruth, Pew, GFW, TerraSAR

Defining C2-F7th,3rd Fleet junior officers, sailors

Software developmentPalantir Skytruth, NPS/ONR, SeaVision, Sea Scout, Universities (e.g. Vanderbilt), NGOs

Information AssuranceGSA, NWDC

Prototype Testing/ProcurementUSFF (NWDC), NAVSEA, SPAWAR, C7F CIG, PACFLT CSIG, IA contact

Contracting, Acquisitions-IP Lawyer, subs with gov experience-DIUx, C3F N8/9, PACFLT N8/N9

Mission: Creating C2-F--Enabling Rapid Decisions from Heterogeneous Data

Information Assurance Access to personnel to provide certification / approval

Prototype Testing/AcquisitionNavy testing venue and exercise (e.g. Trident Warrior), Military Sealift Command ships, 7th Fleet experimentation ships and personnel

Contracting, AcquisitionsDomain knowledge of software contracting and IP from lawyers, subsVariable- Maintenance and Support- Integration with existing systems and processes

IMPROVE USN DECISIONS & OPS VIA C2-F WITH

IMPROVED DATA HANDLING, UI/UX,

COMMS, AND HARDWARE

(1) Rapid Strategic Decisionmaking via Improved Reporting, Coordination, Visibility

(2) Improved Tactical Decision Making via Timely, Accurate Information Sharing

(3) More Effective Analysis via Searchable, Visualizable, Source-Flexible Data Integration (Layering & Filtering)

(4) Increased Analyst Bandwidth via Predictive Intel and Alerts (e.g. Machine Learning) Flexibly Applied to Available Data

(5) Improved Collection of Existing Data Streams

(6) Increasing Morale & Engagement for Millenial Sailors

ENHANCE ANTI-IUU FISHING CAPABILITIES

(1) Improved Detection Using Data Fusion/Analytics

(2) Enhanced Enforcement via Improved Communication

(3) Lower Barriers to Engaging Civilians in Reporting IUU Fishing Activities

Learning Progression

Learning Progression: Week 1

● Week 1

○ Hypotheses

■ This is a problem with insufficient sensing

○ Experiments:

■ Conversations with mentors/stakeholders/contacts

○ Learning:

■ Sensors largely exist, but price point can be too high

■ Government struggles with sheer volume of open-source data

■ Internal information sharing is a big problem

■ Episodic persistence is acceptable--24/7 is not required

○ Proposed solution (MVP)

■ Diagram of entire ISR infrastructure with an emphasis on data aggregation

○ Key Takeaways:

■ Sensors aren’t the problem--data aggregation is--we pivoted before week 1!

■ Needed to talk to more end-users--had identified operators, analysts, and acquisition as benficiaries, but had only talked to analysts

○ Diagrams to Include

■ MVP

■ MMC

■ Team /Mentor Composition

Learning Progression: Week 2

● Week 2

○ Hypotheses

■ Information sharing is a core problem

■ Predictive analytics for hotspots will add value

■ Sensor platforms for our needs exist

○ Experiments:

■ Conversations with C7F N2: MOC description (reservist), data fusion skepticism/deployment emphasis (N2 Chief C7F), maybe use partner nation radar (IUU fishing operator)

○ Learning:

■ 7th Fleet wants details about surface ships--A2/AD is a problem because they can’t deploy normal sensor packages

■ Predicting hotspots is not useful--they know where these are!

■ Information sharing within the Maritime Operations Center (MOC) is not optimal

■ Sensors exist, but cannot be deployed in timely fashion!

○ Proposed solution (MVP)

■ System of low-cost sensors rapidly deployable by UUV along with backend common database

○ Key Takeaways:

■ We thought that the key problems were identifying a low cost sensor solution, enabling timely deployment, putting data into an open-source, commonly formatted database

■ N2 director said he’d seen lots of data fusion products, but was never impressed

■ We pivoted again!

○ Diagrams to Include

■ MVP, Customer Workflow

Learning Progression: Week 3

● Week 3

○ Hypotheses

■ Sensor deployment is the major issue

○ Experiments:

■ Visit to NPS

○ Learning:

■ N3 (Ops) owns N2 and N6--we had only been speaking to N2

■ Pete: what decisions are people actually trying to make?

■ Ship-based radar is all that’s automated--data fusion is very manual!

■ Our problem came from PACOM->PACFLT->7th Fleet...affects how we think about it

■ Lots of single-purpose data fusion tools exist--don’t fall into that trap--how do you do modular updates without creating single-use tools?

■ There are specific systems (GCCS) that we should be thinking about learning more about

○ Proposed solution (MVP)

■ Data fusion (AIS+METOC)

○ Key Takeaways:

■ Data fusion is an enormous problem, both in importance and in scope

■ Needed to talk to N3

■ Got good sense of high-level system workflow and organizational charts

■ MMC starts to take form--focus on enhancing incoming data streams and data sharing

○ Diagrams to Include

■ MVP, org chart, MMC. workflow

Learning Progression: Week 4

● Week 4

○ Hypotheses

■ Data fusion/aggregation is the problem--need to find out more about specific needs

○ Experiments:

■ Conversations with variety of stakeholders (N0, N2, N3, N6, J5, J8, etc.)

○ Learning:

■ PACOM, PACFLT, 7th Flt see different things--COP is not really a COP

■ Analysts do data layering manualy on GCCS, and there’s usually too much there to be useful

■ Automation would be helpful (and our own algorithms could be useful)

■ Common, easily searchable database would be desirable

■ Don’t actually care that much about A2/AD! Subset of a bigger problem!

○ Proposed solution (MVP)

■ Updated previous MVP--now we include automated push alerts and clickable vessel-specific information

○ Key Takeaways:

■ Found out that UI/UX is a big problem for users of COP/C2 systems

■ Data overload is a common problem

○ Diagrams to Include

■ MVP

Learning Progression: Week 5

● Week 5

○ Hypotheses

■ We have identified a clear problem with data fusion, interaction--need to understand exactly where the biggest pain points are, map customer workflow precisely, think about acquisiton paths

○ Experiments:

■ Visit to USCG ops center

■ Acquisition discussions with C7F sponsor

■ Interviews with GCS users/operators and GCCS support contractors

○ Learning:

■ Customer workflow nailed down (JIOC SWO)

■ Functional org chart nailed down

■ Navy POR acquisition path laid out

■ POR-POR interaction within C2 system mapped Proposed solution (MVP)

○ MVP

■ A hard drive containing historical data locally--alleviates bandwidth, allows better pattern recognition/alerts

○ Key Takeaways:

■ Storage and bandwidth are major issues, hardware tied to POR

■ Many programs coming down the pipe to fix various parts of C2, also many problems!

■ Application-style updates are not currently done...it’s all OS style updates

○ Diagrams to Include

■ Customer Discovery, Systemfunctions and needs, acqusition path, MMC, functional org chart

Learning Progression: Week 6

● Week 6

○ Hypotheses

■ The overall C2 system needs to be modernized--there are programs in existence to do this

○ Experiments:

■ Send out spreadsheet to contact list, get understanding of awareness of current programs

■ Speak with ONR research staff about existing programs

○ Learning:

■ Intel is not the same as COP

■ Most users do not have a good sense of which programs already exist for modernizing various parts of the C2 system (Quellfire, EWBM, ADAPT, etc.)

■ Very difficult to get UNCLASS-level details on C2 programs

■ anti-IUU Fishing (Illegal, Unregulated, Unreported) is a great analog use case for desirable Navy C2 functionality

○ Proposed solution (MVP)

■ Spreadsheet with list of C2 programs and info

○ Key Takeaways:

■ For actual product development, illegal fishing use case is a better place to start than Navy C2/COP

○ Diagrams to Include

■ Get/Keep/Grow

■ MVP

Learning Progression: Week 7

● Week 7

○ Hypotheses

■ Flexible integration of heterogeneous new sensor feeds into COP would be useful

■ IUU problem is a good analog for Navy COP

○ Experiments:

■ Interviews with PACOM COP/GCCS experts, IUU fishing stakeholders

○ Learning:

■ Wide variety of sensor feeds (drones, social media, etc.) exist that cannot be effectively integrated into GCCS/COP

○ Proposed solution (MVP)

■ MarineTraffic.com/Global Fishing Watch--would capabilities like this be of use to the Navy?

○ Key Takeaways:

■ Developing a COP-type system for IUU Fishing would be a good dual-use case

○ Diagrams to Include

Learning Progression: Week 8

● Week 8

○ Hypotheses

■ New COP product is a worthwhile direction to go--acquisition and testing will be best done through 3rd Fleet

○ Experiments:

■ Conversations with C3F

○ Learning:

■ Trident Warrior/NWDC are the best organizations to engage for testing/evaluation

■ Information assurance is an important step in the deployment process

■ Requirements are sourced from the fleets, acquisition occurs via SecDef budget

■ Substantial demand for IUU fishing-type technology in CIC--clickable order of battle for different ships

■ They want our week 4 MVP!

○ Proposed solution (MVP)

■ Future C2--integrating social media feeds, etc, into COP

○ Key Takeaways:

■ Need to create future C2 for millenial users

○ Diagrams to Include

■ MVP

■ Pictures

■ MMC

Learning Progression: Week 9

● Week 1

○ Hypotheses

■ This is a problem with insufficient sensing

○ Experiments:

■ Conversations with mentors/stakeholders/contacts

○ Learning:

■ Sensors largely exist, but price point can be too high

■ Government struggles with sheer volume of open-source data

■ Internal information sharing is a big problem

■ Episodic persistence is acceptable--24/7 is not required

○ Proposed solution (MVP)

■ Diagram of entire ISR infrastructure with an emphasis on data aggregation

○ Key Takeaways:

■ Sensors aren’t the problem--data aggregation is--we pivoted before week 1!

■ Needed to talk to more end-users--had identified operators, analysts, and acquisition as benficiaries, but had only talked to analysts

○ Diagrams to Include

■ MVP

■ MMC

■ Team /Mentor Composition

MVPs

Analytics Engine Improved UI/UXBroadly-Accessible Database

Week 1 MVP: Distributed Sensing Architecture

Data Acquisition

ContextualizedDatabase

Week 2 MVP: Sensor Deployment System

Deployment

Last Month

Today

Object-orientedDatabase

Query

- What data is most useful to capture?- What sensor modalities can capture?- What products exist?

- What deployment options exist?- What is easiest to deploy?- What is “good-enough” time to data acquisition?- What is the deployment process?

- Is .kmz format all that is necessary for compatibility?- What do companies like Palantir do today?

Week 3 MVP

AIS Weather

Week 4 MVP: Layering

Week 4 MVP: Push Alerts

Week 4 MVP: Vessel-Level Info & Predictive Analytics

Week 5 MVP

Modular Device● Local storage of historical data→less bandwidth usage + ability to do better

pattern recognition, alerts

GCCS /ADS

Week 6 - MVP: “Software Domain Awareness”

Program POC OrganizationFunction & Goals

To be used by whom?

Security Level Status Contract History Inputs

Technical Details

CSII

Insight

MTC2

Quellfire

DCGS-N Increment 2

C2PC

HAMDD

SeaVision

GCCS

EWBMRC2 (Resilient C2)

Week 7 MVP: Modular Intake, Algorithm, and Display

Week 7 MVP: Modular Intake, Algorithm, and Display

Week 7 MVP: Modular Intake, Algorithm, and Display

Week 7 MVP: Modular Intake, Algorithm, and Display

Week 8 MVP: Shareable Data & Analytics

CIC PACOM

Surface radar contact but no AIS… This is odd. Let me ALERT others.

Week 8 MVP: Shareable Data & Analytics

CIC PACOM

Surface radar contact but no AIS… This is odd. Let me ALERT others.

I see an ALERT from DDG102. Lets share the C2 screen and take a look

Week 8 MVP: Shareable Data & Analytics

CIC PACOM

Week 8 MVP: Shareable Data & Analytics

CIC PACOM

Key Diagrams

Customer Workflow

N2

N3

N2(“owns”

the intel)

N3(“owns”

the assets)

Contextualized DataDeployment

Data Acquisition

Data Analysis

Data

Order/Decision

MVP

JIOC

J1 J2 J3

J4 J5

J7

J6

J8 J9

N1 N4 N7N6 N8 N9

VADM Joe Aucoin

ADM Scott Swift

ADM Harry Harris Jr

N2/N39Intel and Info Ops

N3Operations

N5 Planning

N22Op/Intel Overwatch

N23Collection Operations

N391Fleet Cryptology &

Information Operations

N31Current Operations

N32Fleet Oceanographer

N33Future Operations

N34AT/CIP/NWS

N52Fleet Doctrine Strategy

N53Deliberate Plans

Division

N54Maritime Assessments

N55Functional Plans

Division

Director (CPT Greg Husmann)

Deputy Director(CDR Silas Ahn)

Director (CPT Wes Bannister)

Deputy Director(CDR Chris Adams)

Director

Deputy Director

LT Jason Knudson

Directorate (N/J/A/G)

Description

1 Manpower and Personnel

2 Intelligence

3 Operations

4 Logistics, Engineering, Security & Cooperation

5 Planning

6 C4: Command, Control, Communication, Cyber

7 Training & Exercises

8 Resources & Assessments

9 Civil, Military Cooperation

Customer Workflow

N2

Analysis

Strategic Decisions

CUB

Task Forces

Data Acquisition (among other things)N3

Operational Decisions

Information aggregation + analysis platform

Core Navy Procurement Process

PACOMTo win a war, we need to have awareness of potential adversary's disposition of forces within the area we intend to operate and be able to maintain that through all phases of the conflict (Joint Intelligence Preparation of the Environment)

PACFLT Use the Navy in 3rd and 7th Fleet to conduct JIPOE

7th Fleet Direct ships, aircraft, submarines, marines, and other sensors to conduct JIPOE

7th Fleet N2

Task, Collect, Process, Exploit, and Disseminate and maintain JIPOE for C7F

7th Fleet N2, LT

Knudson

Identify potential operational gaps and determine possible ways to fill those gaps

1. Operational Requirements flow down from PACOM and is interpreted at each level:

Operational Requirements

USFF

PACFLT

7th Fleet Do I have the tools to accomplish my Operational Requirement?

Yes No

YAY, Done

Does PACFLT have the money and/or resources to fund it?

Send Acquisitions Requirement to PACFLT

Yes No

YAY. Validated and resourced. Done.

PACFLT “endorses” requirement, sends to US Fleet Forces Command

Is USFF able to fund or resource this requirement?

Yes No

YAY. Validated and resourced. Done.

Send to OPNAV

OPNAVIs there an existing Program of Record?

No

YAY. DoneMake new POR and include in Navy’s budget via

SECNAV, SECDEF.. Send to Congress.

Congress Budget approved?

Yes

Acquisition Requirements

Congress Budget approved?

Yes

OPNAV

PMO

USFF

Force Commands

PACFLT

7th FLEET

Money flows from SECDEF to SECNAV to CNO/OPNAV

Primes/ NAC

Program Management Office decides who to tap for production/development

A government contractor (Boeing, Lockheed, etc.) or Naval Acquisition Command (SPAWAR, NAVSEA, etc.) builds this system

Product made available to US Fleet Forces Command to issue to Navy units

SURFFOR, SUBFOR, and IFOR man, train, and equip using 2-year money

No GG

PACFLT receives resources from the appropriate force command

7th FLEET GETS SOMETHING!!!! …. Many YEARS later…. YAY!!!!

Program Execution

Customer Discovery - Get/Keep/Grow Diagram

Awareness Interest Consideration Purchase Keep Unbundling Up-sell Cross-sell Referral

Activity & People

- Evangelist & advocate from originator Flt- ???

Corey Hesselberg, CDR Jason Schwarzkopf, MIOC watch standers

- Buy-in from flag officers- ADM Swift, VADM Aucoin, RADM Piersey

- N8/9- Dave Yoshihara (PacFlt N9)- 7th Fleet ???

- Maintainers (N6)- Bob Stevenson (PacFlt N6)- 7th Fleet ???

N/A Expanding COP & intel extensions / functionality within 7th Fleet

Expanding user base within 7th Fleet

Expanding tool set to other fleets

Metrics % people who have heard of program before vs after *how to reassess?

# people who say “we want this”

Seems binary… any recommendations?

# Systems outfitted

?? ?? ?? # users within 7th Fleet using tool

# fleets using tool

Map of System Functions and Needs

QUELLFIRE

GCCS (1)

FOBM

STORAGE/COMMS

CST

GCCS (3)GCCS (2)

STORAGE/COMMS

STORAGE/COMMS

Sensors Sensors Sensors

.oth-.json Translator

Visualization

Analytics

Ship-to-Ship Sharing

Long-Term Storage

KEY NEEDSFUNCTIONS

& PROGRAMS

SHIP 2 SHIP 3SHIP 1

Week 8 - MVP?

Modular Device● Local storage of historical data→less bandwidth usage + ability to do better

pattern recognition, alerts

GCCS /ADS

Week 8 - MVP? Deployment Method!

Modular Device● Local storage of historical data→less bandwidth usage + ability to do better

pattern recognition, alerts

“C2-F”

Cost Flows

Database ($80k)

Analytics Engine ($120k)

Translation (ETLs) ($100k)

AIS VMS Radar SAR Sat

UI ($80k)

Information Assurance

($240k)

Testing ($480k)

Maintenance and Support

(VC)

Assume 10 data streams, need cost validation on streams

$380K $240K $480K $???

Total: $1.1 MM + Var Costs

Customer Discovery DeploymentProduct Development Navy Testing

Initial Testing

Information Assurance

Maintenance & Support

Key Activities, Resources, and Partners

TRL 1 TRL 2 TRL 3 TRL 4 TRL 5 TRL 6 TRL 7 TRL 8 TRL 9

3 Year Financial/Ops/Funding Timeline

2016 2017 2018 2019

Q3 Q4 Q1 Q2

Cas

h R

eser

ves

Phase

Prod

uct

Gov

’tC

om’l

Mile

ston

es

Q1 Q2Q3 Q4 Q1 Q2Q3 Q4

TRL 1

TRL 2

TRL 3

TRL 4

TRL 5

TRL 6

TRL 7

TRL 8

TRL 9

POC

Wireframe

Prototype BetaPrototype

Marketable Product

BetaPrototype

Released to first customers (<3)

Commercial Product Launch;

2 contracts

Test in Navy env Navy-wide Deployment Maintenance and Support

V2.0 Commercial Product Launch;

5 contracts signed

Initialize System Development/Customer Relationship Development Launch at scale

Hea

dco

unt

410

20 50

15 customers; V2.5 launch

CONTRACT SIGNED CONTRACT

RENEWED

SBIR/DIUx

Series A (In-Q-Tel, Impact Investor(s))

2 com’l contracts

$250k$0

$1.25M DoD Contract

$2M

$5M

3 Year Financial/Ops/Funding Timeline

2016 2017 2018 2019

Q3 Q4 Q1 Q2

Cas

h R

eser

ves

Phase

Prod

uct

Gov

’tC

om’l

Mile

ston

es

Q1 Q2Q3 Q4 Q1 Q2Q3 Q4

TRL 1

TRL 2

TRL 3

TRL 4

TRL 5

TRL 6

TRL 7

TRL 8

TRL 9

POC

Wireframe

Prototype BetaPrototype

Marketable Product

BetaPrototype

Released to first customers (<3)

Commercial Product Launch;

2 contracts

Test in Navy env Navy-wide Deployment Maintenance and Support

V2.0 Commercial Product Launch;

5 contracts signed

Initialize System Development/Customer Relationship Development Launch at scale

Hea

dco

unt

410

20 50

15 customers; V2.5 launch

CONTRACT SIGNED CONTRACT

RENEWED

SBIR/DIUx

Series A (In-Q-Tel, Impact Investor(s))

2 com’l contracts

$250k$0

$1.25M DoD Contract

$2M

$5M

CAVEAT:This is what the timeline would look like if we

worked on the project full time.