We were inspired by the Head Starter's vision to develop the products for the betterment for children, which are going to be our next generation. We couldn't find any app regarding the recipe's recommendation for children. Also, in developing countries, there are so many children that are having multiple deficiencies of various nutrients. We kept them in the mind and made this project.
What it does
Our web app has 2 parts. Initially, the app will make a profile for the child containing the age of child, sex, weight, height, activity level of a child and allergic to any items. As per profile, our app will suggest the recipes suitable for the kids, targetting to cover all the nutritional values required for the children as per the data from the USDA nutrient calculator(approximately hardcoded).
Secondly, our app has also a feature to take input the recipes which parents are currently feeding to their children. As per the input of recipes and approximate quantity of them, we will recommend the other dishes if the nutritional requirements(calculated in part 1) of the child are not fulfilled.
How we built it
Challenges I ran into
We didn't find any direct data or APIs to get the nutritional requirements for children. We tried to build web-scrawler for " https://www.nal.usda.gov/fnic/dri-calculator/ ", but as there were no IDs in this Html page, it was difficult to feed the data and get the nutritional data as per child profile. We had to crawl the web for information about nutrient details once any user submits their profile. Since this request had to be processed by the backend server, the asynchronous process of web scraping was handled by a Python script. The main issue here was that, there were not many python packages or proper documentation for the ones that we found, that could directly alter the HTML elements. Had it been a frontend scripting language, it would've been, much simpler and easier to work with HTML DOM.
Accomplishments that we're proud of
Building something for children, which is not properly implemented yet, is something we are proud of. Also, developing front-end using ReactJs was challenging and we are proud that we learned and implemented for our product.
What we learned
We learned more about ReactJs front end framework, learned about the MongoDB and its integration with java driver to run with spring boot. Learned about how to divide the work and build the product efficiently and quickly. Got the taste of few technologies at the time of deciding the technology stack for development.
What's next for NutrionoKid
Suggestion for the recipes or eatables as per the location of the user. Also, integrating the amazon or other online delivery services available for online shopping of those recipes.
Suggestion to reduce or avoid the recipes(entered by Parents) which are not good for the health of children.
Integrating clustering or other machine learning algorithms to suggest the recipes. Also, to add the feature to filter the recipes by "total time to prepare".