The problem Diet_Hard solves

PROBLEM:-
People belonging to the Indian middle-aged urban demographic, are more often than not, unable to choose and maintain their diet plan resolutions to achieve personal fitness goals which leads them to stop making conscious effort on their diet altogether and relapsing back to their previous unhealthier diet.

One of the main reason why they are unable to formalize a meal plan is a lack of simple and relatable resource for forming their meal plans. Most of the online resources which aid the formation of personalized diet plans for its users , are framed to be only useful for foreign markets and not for India, as the meals in the daily routine barely contain ingredients that the regional market is familiar with.

There are other applications that do contain Indian foods however the scope of variety of food is very limited which, again leaves the above mentioned demographic back to square one.

SOLUTION:-
The solution we came up with is to make a website which provides a simple UI so that the users do not feel intimidated and to integrate food items which the Indian middle aged demographic is familiar with.

The key focus of thought for our website is that we understand the diversity of Indian cuisines and how intimately the cultural identity of each and every region is tied up with its cuisines and food .

Thus , we have categorized the Indian dishes into local, regional dishes . The user can choose from a wide variety of dishes of his/her own preferred locality (Maharastrian , Kashmiri, Goan etc) and the algorithm sets up their meal plan amongst the chosen category with caloric and macronutrient constraints .We have also added a food and exercise diary where user can manually input their desired food item or exercises and which will be analyzed ,from which the user can track their progress anytime , daily , weekly , monthly etc …like a diary.

Challenges we ran into

Finding resourses and data was't a easy task to do.
As this was an unsolved issue we couldn't find any data set which contained food divided into cuisines with their nutritional informations.
We made the whole data manually using various resourses.
We had to study long manusripts to find constraint data of macronutrients and calories.