IND8137AE — Techno-entrepreneurship · Team of 4 · Polytechnique Montréal
Iris: Smart Glasses for the Visually Impaired
Iris is a concept for AI-powered smart glasses that help visually impaired people navigate the world more safely and confidently. Working in a team of four, I helped carry the idea through the full techno-entrepreneurship lifecycle: from spotting the opportunity and researching the technology, to building a business case and an operations plan for actually bringing it to market.
With teammates Jane A., Lorenzo C. & Roxana C. — Team 04, IND8137AE, Oct. 2024
FIG. 03 — Why this matters, by the numbers
0.0M
Canadians live with sight loss
CNIB
0.0M
more Canadians have an eye disease that could cause it
CNIB
0.0M
people are blind worldwide
Global Burden of Disease Study, 2020
0M
more live with moderate-to-severe visual impairment
Global Burden of Disease Study, 2020
From research to operations plan
Step 1 of 5 — click a milestone to explore it
Started from the scale of the problem — the WHO estimates 2.2 billion people live with some form of vision impairment — and framed the opportunity: smart glasses that combine echolocation sensing with AI-driven, conversational guidance.
How Iris turns sensing into guidance
Side-mounted sensors
Echolocation hardware that senses obstacles and surroundings in real time.
Computer vision + AI
Processes camera & sensor data to identify objects, hazards, and paths.
Natural language processing
Turns raw detections into clear, conversational guidance.
Built-in auditory feedback
Speaks verbal cues and directions through onboard speakers.
Inside the pitch deck: how we actually built the case
The numbers and takeaways above all came from a deck the four of us put together slide by slide — mission and values, structured analyses (PESTEL, SWOT), market segmentation, competitor benchmarking, the business model, and a 30-month action plan with a financial runway behind it. Here's the deck itself, the artifact that shows how the thinking actually came together.
Mission & values — what Iris is for, and who it's for.
Slide 1 of 9 — click the slide to zoom in
The idea
Iris is a pair of smart glasses fitted with side-mounted sensors and cameras that use echolocation to sense the wearer's surroundings in real time. An onboard AI system processes that sensory data and speaks it back through built-in speakers — describing nearby obstacles, identifying hazards, and offering navigation guidance — so the user can move through their environment with more confidence than a cane, guide dog, or GPS app can offer alone.
Key features at a glance
Integrated AI
Cameras and sensors stream data continuously; onboard AI turns it into real-time, actionable insight.
Auditory feedback
Natural-language processing converts what the glasses "see" into clear, conversational verbal cues.
Wearable, ergonomic design
Built to be worn all day — light, comfortable, and unobtrusive, like a regular pair of glasses.
Cameras & sensors
Side-mounted hardware detects obstacles and objects and feeds real-time visual input to the AI.
From idea to operations plan
- 1Technological intelligence. Researched the scale of the problem (the WHO estimates 2.2 billion people live with vision impairment), then mapped the core technologies — AI/computer vision, echolocation sensors, natural language processing, and auditory feedback — through patent and literature searches on Scopus, IEEE Xplore, and Google Patents.
- 2Opportunity & competitive analysis. Identified a gap: existing assistive devices (canes, guide dogs, GPS apps) each solve part of the problem, but nothing on the market fully integrates echolocation with AI-based object recognition and contextual, conversational guidance.
- 3Market & business model. Built out the business case — market sizing, business model canvas, and go-to-market thinking — to test whether the idea could survive contact with a real market.
- 4New-product-development & operations plan. Closed the loop with an NPD and operations plan: how the product would actually move from concept to a manufactured, supported device — covering logistics, human resources, and value-chain management.
Where the opportunity is
Our patent and literature research found that ultrasonic sensors, LiDAR, and camera-based systems each solve part of the navigation problem — but no existing solution combined echolocation, AI-based object recognition, and natural, conversational guidance into one device. That gap is exactly where Iris sits, and where we saw room to differentiate: more human-like communication via NLP, integration with smart-city infrastructure for transit data, and AI that adapts to each user's habits and preferences over time.
We benchmarked Iris against the closest direct competitors on the market — here's how the landscape looked:
| Product | Price | Feedback type | Audience |
|---|---|---|---|
| eSight | $5,950 | Bioptic tilt | Blind & visually impaired |
| BrainPort Vision Pro | $6,750 | Electrical | Blind |
| OrCam | $4,250 | Auditory | Blind & visually impaired |
| Ashirase | $350 | Mechanical | Visually impaired |
| BuzzClip | $250 | Haptic | Visually impaired |
Iris's case for standing out: combine the strengths of each category — echolocation, AI object recognition, conversational guidance — into one device, at a price point well below the premium end of this table.
The business model, in brief
- Value proposition. Affordable, easy-to-use smart glasses that help visually impaired people navigate independently — without the price tag of devices like eSight.
- Profit model. Direct hardware sales supported by partnerships with healthcare providers, insurers, and accessibility-focused NGOs to widen access and lower the cost barrier.
- Entry strategy. Launch within underserved communities first, build trust and word-of-mouth, then expand reach through partnerships and continuous, user-driven iteration.
Financial snapshot
- Pricing. $2,000 per device, plus a $150/year subscription for ongoing AI and feedback features.
- Path to break-even. No product revenue for the first ~2.5 years (R&D, prototyping, regulatory work); first sales arrive mid-Year 3, break-even projected in Year 4.
- Capital needed. About $2.5M to cover the runway: roughly $1.5M in equity financing, $700K in grants and accessibility-innovation funding, and $300K in low-interest debt repayable once profitable.
- Payback period. Projected at 5–6 years overall, including the initial development phase.
What this taught me
- How to validate a technology-driven idea against a real, well-documented human need before investing further in it
- Running a structured patent and literature search (Scopus, IEEE Xplore, Google Patents) to find genuine white space rather than assuming one exists
- Connecting a technical concept to a business model — market size, competition, and a credible path to revenue
- Thinking through what it actually takes to operationalize a hardware product: supply chain, people, and a realistic NPD timeline
Why it matters to me
Projects like Iris are where my engineering instincts and my interest in process and planning meet: a good idea is only as good as the plan to build, validate, and deliver it. That's the connective tissue across all of the work on this site — taking something messy and giving it a structure that can actually be executed.
Before committing to the idea, we ran it through a SWOT analysis — a reality check on where Iris would actually be strong, where it would struggle, and what could help or hurt it down the line.
Strengths
- AI-driven, real-time echolocation that goes beyond what a cane or guide dog can offer
- 360° awareness with hazard detection and object recognition
- Lower cost potential through open-source tooling and production partnerships
Weaknesses
- High development & production costs could push end-user prices up
- Affordability remains a real barrier in lower-income communities
- Users need time and support to adapt to a new way of navigating
Opportunities
- Ongoing AI and battery innovation can keep improving the product and lowering its cost
- Partnerships with healthcare providers and NGOs to build awareness and unlock funding
- Government grants, subsidies, and insurance coverage to soften the price barrier
Threats
- Well-established alternatives — guide dogs, smart canes — already dominate the market
- Regulatory approval (FDA, CE) could delay launch and add cost
- Cameras and sensors raise real privacy and data-ethics questions that need addressing head-on