BRTS Final Presentation · BRTS Final Presentation 11/29/18. 2 Johnson | Cornell SC Johnson College...

Neuromorphic Vision

BRTS Final Presentation

11/29/18

2 Johnson | Cornell SC Johnson College of Business

Agenda

• Recap midterm feedback

• Getting to target segment

• Culling process

• Developing/testing hypotheses

• Updated business model canvas

• Preliminary market sizing

• Next steps


Review of Neuromorphic Vision

“Event based” camera only captures movement

Unique to our neuromorphic algorithm?

• Simultaneous independent motion detection

and depth estimation

• Lighter computational weight allows real-time

processing


Midterm Course Correction

Evaluate potential targets based on assumptions

and preliminary findings along the following criteria:

• Customer Urgency

• Market Size

• Length of Sales Cycle

• Navigating Sales Hurdles

• Technical Difficulty


Goal: Identify Target Segment

Customer

Urgency

0.3

Market

Size

0.2

Length of

Cycle

0.2

Barriers

To Entry

0.15

Technological

Difficulty

0.15

TOTAL

Wind Farms 2 2 5 4 3 3.05

Ammunition Tracking 3 4 3 1 2 2.75

Incoming Hostile Fire 4 5 3 1 2 3.25

Sports Broadcasting 1 2 4 4 3 2.55

Sports Performance 3 1 4 4 3 2.95

Agricultural Technology 3 3 3 4 4 3.30

Warehouse Automation 2 4 4 4 3 3.25

AV Perception 5 3 3 2 1 3.15

Traffic Planning 1 4 2 2 5 2.55

Camera Technology 2 3 4 4 4 3.20


Customer Discovery Interviews

• 39 interviews total

• 20 since mid-term presentations

• Ag Tech

• Warehouse Automation

• Camera Tech

• Hostile Fire Detection

• Hypothesis Testing

• Value Seeking


Application 1 – Ag Tech

• Hypotheses

• Customer Segment: Tree fruit farmers, field crop farmers, high value crop food processors (eg

Heinz and its partners), pesticide companies, disease management analysts

• Value Proposition: 1) Neuromorphic cameras could more quickly, more accurately, and more

cost effectively identify pests, 2) Neuromorphic cameras could more accurately and more cost

effectively automate repetitive high value crop sorting or gathering

• Findings:

• Technologically Feasible– the problems that exist in AgTech are not technically challenging,

though more testing must be done in order to determine feasibility for camera to solve industry

problems

• Many Applications – bird tracking and control, pest identification, field crop AV driving and AV

nut gathering, high value crop sorting

• Identifying the hair on fire issues – bird tracking is seen as a nuisance but current solutions

are seen as sufficient, pest management is expensive and doing this more cheaply or

accurately is valuable though farmer budgets are limited, AV solutions depend on tech

feasibility, high value crop sorting is a hair on fire issue and the biggest potential ag tech market


Application 2 – Warehouse Automation

• Hypotheses

• Customer segment – e-commerce warehouses, logistics companies

• Value Proposition – for highly automated warehouses, neuromorphic cameras could

reduce lag time and free up computing power for more advanced features that increase

efficiency and decrease error (i.e. AR glasses for pickers, guidance for robotic processes,

2d barcode scanners, inventory movement tracking), creating labor savings

• Findings:

• Not underserved – most significant challenges are largely solved or are being addressed.

Most eager interviewees are product managers at ecommerce retailers, not materials

handling companies. Level of automation varies widely, but is increasing.

• Willing to pay, at scale – In the last few years, Amazon overhauled their picking and

putting system to save on human labor; Amazon has 125k full-time hourly associates

• Opportunities for savings –Even after Amazon’s picking overhaul, users still must hold a

barcode up to a scanner. Neuromorphic vision could shave off time. For sortation systems,

high-speed barcode scanners are expensive (~$100k each), offering additional

opportunities for savings.


Application 3 – Camera Tech

• Hypotheses

• Customer Segment – find a foothold with independent creatives, action sports gurus, then try to

prove the value to cinema production companies

• Value Proposition – real-time motion detection and depth estimates may create a

tracking/focus system capable of overcoming lack of faith in autofocusing for video

• Findings:

• Willingness to Pay – current cost of neuromorphic sensor is within reason

• Lack of Urgency – inherent distrust of automation in creative and broadcast

• Demands aligned with Tech Strengths – creators value two attributes above all:

• Performance in low light

• Responsiveness

• Few Intermediaries – end user could be primary target audience, direct adopters

• High Compatibility – example rig includes mix-match of 3 or more brands


Application 4 – Hostile Fire Detection

• Hypotheses

• Customer Segment – Special Forces under Joint Special Operations Command (JSOC)

• Value Proposition – Reduce false positives from existing systems by 95%

• Findings:

• SWAT as early adopters, not JSOC – JSOC required a white paper for discussions. SWAT

frequently uses and tests new weapon technology – adoption timeline would be MUCH faster

than JSOC

• Saving lives – Increase officer safety by determining shooter location, increase civilian safety by

preventing misidentification of the shooter, provide courtroom evidence

• Testbed for ongoing product development – Niagara falls SWAT was willing to provide

shooting range for testing, were very interested in the technology

• Starting with SWAT before approaching Department of Defense is best approach


• Increase officer

safety by

determining shooter

location

• Increase civilian

safety by preventing

misidentification of

the shooter

• Provide courtroom

evidence

• iniVation

(neuromorphic

camera company)

• Cornell University

• Get: trade show

booths (NYTOA and

NTOA), police

magazines, trials &

demonstrations for

equipment reviewers

• Keep: training

programs

• Software

development

• Hardware integration

• End User Training

• Cameras

• IP

• Access to shooting

range for testing

• Compatibility with

existing equipment

Primary

• Domestic SWAT:

end user – officer,

decision maker –

commander,

purchaser –

purchasing officer

Secondary

• International SWAT

(see above)

• Department of

Defense: end user

–front line military,

decision maker &

purchaser – DOD

CEO or Chiefs of

Staff

• Direct sales to

SWAT

• Direct sales to

Dept. of Defense

• Development & R&D costs (compatibility, upkeep, etc)

• Sales costs

• Camera (if vertical integration to reduce dependency)

• Potential licensing costs if move towards military

• Unit sales

• Maintenance

• Data management or application to process and interpret

information

Hostile Fire Detection

BRTS NMV Team 11/29 2.1Taylor Clawson

https://inivation.com/




Estimated Opportunity – Near Term (24-48 months)

Total SWAT units = 10,000*

Value Range = $10,000-$30,000

Estimated penetration = 5% in 4 years

Size of Initial Opportunity = $10 million

*Based on survey of International

Association of Chiefs of Police 2013

national SWAT study.

– 17,000 total police units

– 60% surveyed also have SWAT teams


Total Potential Market

• Best-guess US military market-sizing: $650M

– UAE contract for acoustic detection technology: $52.27M (2015,

DefenseNews)

– UAE total military spend: $23,400M (2017)

– US total military spend: $610,000M (2017)

– Implied US market size: $1,300M

– 50% adjustment for US military buyer power: $650M


Next Steps

• Test Speeding Bullet Recording/Tracking

• Distribute results in white paper to targeted early adopters

• Secure letters of intent from potential customers

• Additional Customer Discovery

• Develop a pricing model

• Understand the purchase roadmap

• Create a Financial Model

• Threshold for operational profitability

• Estimate acquisition costs

Questions?

BRTS Final Presentation · BRTS Final Presentation 11/29/18. 2 Johnson | Cornell SC Johnson College...

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