Intoxiwatch
Case Study: Engineering
Engineering 21: Introduction to Engineering
WHEN
Fall 2021 - 6 week timeframe
Tags
Wearable Technology
Product Design
Market Research
Overview
In this Engineering 21 group project, we had 6 weeks to find a need and develop a product to solve the problem. Our group chose to focus on over intoxication. Specifically, we focused on students not knowing how much they have consumed. College students, who are often drinking in party settings from premade "punch" cocktails or playing drinking games, often struggle to keep a mental tally of how much they have consumed as proven by our survey results.
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Our product, the Intoxiwatch, allows the user to conveniently and discretely check their blood alcohol content (BAC) in order to know how much they have consumed. Further, optional sharing features allow people to keep track of their friends' consumptions in the event that someone has consumed a dangerous amount of alcohol.
Team
Leo Fuchs - Led SolidWorks and manufacturing engineering process
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Lexi Dewire – Project management, managed deliverables, led market research and business plan
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Veronica Yarovinsky – Software development and chemical research
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Josh Vorbrich – Led prototyping, circuit design, and mechanical engineering process
Skills
Tools
Circuit Design, Business Plan, 3D Printing, Data Analysis
User Research, Market Research, Patent Research
Design Review Presentations, Rapid Prototyping, Strength Tests
3D CAD (Computer Aided Design)
SolidWorks
Arduino
Problem
Teens and young adults struggle to keep track of their own and their friends’ alcohol consumption, which is necessary in order to use alcohol safely and avoid the risks of overconsumption.
Users
18-24 year olds (high school and college age)
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Purchasers
Purchasers: Users and their concerned friends
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Test Group
Dartmouth students
User Research
Our survey data not only confirmed that keeping track of BAC was a problem, but that there was a desire for the product as >75% of students surveyed stated they would be interested in a device that monitored their BAC
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Further, user Input during initial surveys emphasized the desire for a product that was discrete, paired with their phone, and was easy to use (even when intoxicated).
The Challenges
Developing a product that:
Was small and discrete enough that people would feel comfortable wearing it
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Maintained user privacy and safety
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Could not be "gamified" or otherwise used to effectively increasing consumption
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Durability sufficient to be it "drunk person proof"
The Process
We began by researching existing and state of the art technology, patent searching etc. Next, we determined performance criteria and ranked solutions in matrix (below) before evaluating in depth our top solutions
Solutions and Alternatives Matrix
Promising Idea 1: NIR Spectroscopy
Patent: US 20200323486
Problems
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Lack of information
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Complicated light spectroscopy physics and biochemistry
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Difficult to determine correct wavelength for detecting alcohol
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Challenging sensor algorithm
Barriers
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Cost
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Acquiring specialized materials
Conclusion
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Not feasible with the given budget and timeframe
Promising Idea 2: Chemically reactive tattoo that changes colors detection via infrared technology
Patent: US20170325724A1
Non-invasive and wearable chemical sensors and biosensors
Problems
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Requires user to keep their phone nearby
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Delicate and not discrete/ unaesthetic
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Sweat will cause sensor to unstick
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A prototype sketch of a scrunchy that would use the same sticky with BAC sensing technology
Promising Idea 3: Apple Watch BAC attachment
This idea was abandoned because Apple technology (specifically the Apple Watch) makes it incredibly difficult to add third party features as the system is actively built to reject them
For the reasons listed above, we ended up ruling out all three of our initial ideas and pivoting. We kept the concept of a wearable BAC device, but decided to adapt existing technology in a miniaturized wearable breathalyzer.
Development
SolidWorks Iterations
Prototype 1
User Feedback on Prototype 1
Additional Considerations for Prototype 2 Based on Feedback
Prototype 2
Limitations in sourcing and producing a model on this scale caused us to split up to develop a works like and a looks like prototype
Prototype #2 Looks Like
Testing
Drop Testing
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Accuracy Tests
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Approximately 0.004 difference in values
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Benchmark gives only slightly higher values
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All values are within one standard deviation of mean in Brand Altman plot, indicating statistical insignificance of the error
Feedback from Prototype 2
We used this feedback when designing our future model
Future Plans
Here are some of my technical sketches for future developmetn
