I am currently working on an NHLBI K01 Career Development Award-funded project examining the use of a personalized, automated digital platform + web/mobile app to improve the healthfulness of grocery purchases in an online grocery setting (i.e., SmartCart 2.0). In the first phase of the project, I am looking for help building out the web/mobile app. I will be conducting focus groups in Fall 2023 with eligible participants (i.e., adults at higher cardiometabolic risk, defined as a BMI >30kg/m2 and/or high blood pressure), and I would like to have a good ‘mock up’ of the web/mobile app to understand people’s platform and food group (i.e., types of recipes, nutrition tips, etc) preferences they have so we can refine the platform based on user preferences before testing it in a randomized controlled trial.
Because the webapp must integrate with a classification algorithm and recommender algorithm that we have developed and are using to process grocery receipt data and make personalized healthy dietary recommendations (with coupons), familiarity with this technology would also be helpful. I have documentation from previous teams of CS students who have worked on earlier iterations of this project for reference.
Milestone Title: Milestone #1 Milestone Description: Beta app and figma mockups complete to share for participant feedback, Launch presentation, set up git repo. Completion Date Goal: 2023-11-30
Milestone Title: Milestone #2 Milestone Description: Continuous update of app based on participant-feedback, integration of new recipes, begin testing functionality of app.
Completion Date Goal: 2024-01-31
Milestone Title: Milestone #3 Milestone Description: App finalization; begin connecting classification algorithm, recommender, and web app.
Completion Date Goal: 2024-02-28
Milestone Title: Milestone #4 Milestone Description: Continue connecting classification algorithm, recommender, and webapp and begin connecting web app to gorilla shopbuilder
Completion Date Goal: 2024-03-31
Milestone Title: Milestone #5 Milestone Description: Connect web app to Gorilla shopbuilder and pilot test; if time allows, collaborate on enhancing recommender and classification algorithms. Wrap up development, update project git and documentation, wrap presentation, exit interview.
Completion Date Goal: 2024-04-30
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Final Report
The SmartCart project has advanced nutritional science by integrating machine learning with dietary management. It has refined the use of natural language processing and classification algorithms to personalize nutritional recommendations. Overall, this is a step in increasing the effectiveness of dietary interventions.
Besides health informatics, the project has implications for behavioral science. Smartcart is a testament to how technology can influence healthy eating habits.
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SmartCart has the potential to make a substantial societal impact by promoting healthy eating habits, leading to a reduction of lifestyle-related diseases. Its UI/UX and personalized recommendations make nutritional guidance accessible and appealing to the general public.
Key lessons include the importance of user-centered product design and the challenges of integrating advanced technologies and algorithms into user-friendly interfaces. The transition from AWS DynamoDB to MySQL and MariaDB also highlighted the need for scalable solutions in data-heavy apps.
The project successfully developed a scalable, user-friendly web application. It has set a foundation for future enhancements, including more sophisticated and accurate algorithms and expanded user engagement features.