Bonus Territory!
Maybe you’re a little bored of reading all about me and my projects at this point, but in case you aren’t, here are a couple more projects that I’d love to show off to help support some of my bigger projects.
MOBI: an IoT financial planning device
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Spring 2023 - EDSGN 467 (Prototyping to Launch) - Dr. Jessica Menold
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Skills: Market Research, Product Pitch for Target Audience, Hands-On Prototyping (Adduino + Arduino IoT), Team Skills
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OUTCOME: Second Place in class pitch competiton, final keychain and app prototypes based on both market data and user interviews
The big ideas
Only 41% of students review their monthly statement on a regular (monthly) basis
71% of students spent more than they estimated after being asked to check their statements
About 95% of students wanted to be more aware of their spending
Stage 1: Defining our problem
This class began with the task of creating an IoT (Internet of Things) - connected device that helped someone, somewhere. With as broad of a topic as this was, our team had some brainstorming to do. After narrowing in on the topic of college students and their spending mindset and habits, we conducted a large preliminary survey with some interviews. After finding out that lots of students were blissfully unaware of their spending, we did secondary research to confirm the market (turns out, there’s no physical device to help with spending habits).
As a team of college students ourselves, our team was able to develop even more empathy for the problem here. As a part of our secondary research, we found out a few key things about money. According to the Educational Data Initiative, college students spend an average of $547 on food and $42 on alcohol every month. In addition to this, 36% of college students are in food precarious situations and struggle more than the “average” student.
Stage 2: Prototyping!
Through a few different rounds of prototyping with both “looks like” and “works like” prototypes to gain insights into what our users might be looking for both visually and feature-wise. While working on the physical side of things, our team was also doing a deeper dive into the market we may have (total addressable, service available, and service obtainable). Besides the physical realm of prototypes, our team created a clickable prototype to determine ease of navigation and certain features users may want in a streamlined spending app.
Stage 3: Pitch preparations
Before presenting to a group of stakeholders, our team wanted to make sure we focused more on the final form of both the physical prototype and the app features based on user feedback; the final designs were products of each stage of the interviews. To hone in on what we wanted our pitch video to be, we researched successful Kickstarter campaigns.
Starring Oscar-Nominated actress, me!
Starring Oscar-Nominated actress, me!
Our pitch video (featuring me as the star) highlighted a typical college student’s financial mindset before getting our product and after using it! Enjoy my acting skills!
Optimal grocery store redesign based on shoulder flexion
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Fall 2023 - EDSGN 547 (Designing for Human Variability) - Dr. Matt Parkinson
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Skills: R Studio Coding, Anthropometric Data, Technical Documentation & Reporting, Team Skills
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OUTCOME: Design recommendation for shelf pushers in grocery stores in order to accommodate not only a range of statures, but a range of ages since older adults tend to have a more limited shoulder range of motion
The big ideas
*Josefina Bertoli, Ewertton de Souza Bezerra, Kerri M. Winters-Stone, Luis Alberto Gobbo & Ismael Forte Freitas$suffix/text()$suffix/text(). (2023) Mat Pilates improves lower and upper body strength and flexibility in breast cancer survivors undergoing hormone therapy: a randomized controlled trial (HAPiMat study). Disability and Rehabilitation 45:3, pages 494-503.
Stage 1: Defining our problem
This graduate-level class had an open-ended final assignment. After a team discussion, we became intrigued by the area of common spaces in which people might not be accommodated. We thought of grocery stores; of course, grocery stores have a main goal of profiting, but it comes at the cost of disaccommodating older adults, who have difficulty reaching higher shelves due to limited shoulder flexion. With some trigonometry calculations and existing human anthropometric databases, our team ran a regression with residual analysis between an Australian shoulder flexion study and U.S. NHANES (National Health and Nutrition Examination Survey) to create a new variable on shoulder flexion.
Stage 2: The Data
We did a few things with our data, starting by going to different large-scale food sale stores to gather some key information (see right). From there, we did a lot, including regression with residual analysis, a disproportionate disaccommodation scan, and breaking up demographics (all using R Studio) to determine key results. Using our data, we found that vertical range of motion disaccommodates elderly shoppers 28.3% more than their younger counterparts. After this, we ran an optimization analysis using Excel Solver to determine maximum accommodation while considering cost for potential shelf pusher options.
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Stage 3: Report & recommendations
Our data recommended the presence of shelf pushers for all shelves with an optimized track length of 136mm; this recommendation would change overall elderly accommodation from 7% to 69%. Our team chose shelf pushers to increase accommodation rather than an entire reconfiguration to not only consider the existing grocery store model, but their primary goal of profit.