Health dhaba

A healthy way to eat.

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Inspiration

Eating out in restaurants has become both,  a fashion and a genuine necessity  for the masses nowadays.  With health suffering from this generic inclination towards eating out, everybody looks for a healthy eating alternative option . How many restaurants are you going to test and try to find that perfect dish that satisfies your palette without punishing your health?

What it does

This android application helps you find out the best dishes of the nearby restaurants which are suitable for you and helps you monitor your diet on the basis of your calculated BMR and gives you suggestions to compensate your dietary indulgences

How we built it

We worked on the basic yet custom pre-requisites for a healthy diet of a person. A healthy diet takes accounts of the nutrients required for a person on the basis of the certain indexes such as age, weight, BMR ( basal Metabolic rate ) and the particular health condition pertaining to that individual i.e. deficiency or excess of particular nutrients etc. we analyzed the menu of the restaurants and calculated the nutrient quotient of all the popular dishes. We took health indexes of the users e.g. Height , Weight, Age and calculated the BMR using “ Harris-Benedict equation” in our code. We abstracted data out of ZOMATO API combined with scraping to get the menu of the restaurants nearby. We used NutreintsIX to get the nutritional value of the popular dishes in the nearby restaurants ( rounding of to about 600 dishes In our database).

Challenges we ran into

The concept was so rare that a complete pack was not avalable, so we found different solutions, combined our algorithms with the previously developed API's.

Accomplishments that we're proud of

We are proud to recieve such an accuracy in our calculations and data that we scraped from other sources.

What we learned

We learned to work with new Open source libraries. Scraping data from other sources.

What's next for Health dhaba

Implement machine learning to suggest food items to the user according to his previous choices. Add feature to connect our app with smart watches, to find better results.

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