N

Nazakat

You care for them, We care for You.

N

Nazakat

You care for them, We care for You.

The problem Nazakat solves

The kind of ignorance we see in women regarding their health is absolutely frightening as the ignorance continues until the very end in most cases.

In India, especially rural women, have numerous reasons as to why seeing a doctor is the last thing on their minds. These reasons include the stigma around talking about women's health, for example, menstrual hygiene, unawareness, the huge medical costs and unavailability of resources.
Well, what is there to which technology can’t offer a solution?
We have come up with an amalgamation of services dedicated to women health in the form of our website- NAZAKAT, an Urdu word for delicate.
Our vision is to unite women together and give them a safe, cosy place to learn, discuss, make friends and heal themselves.

Features of Our Website:

  1. Period Tracker- To help regulate your menstrual cycle, and be aware of your dates

  2. Baby Size Tracker- A cute feature for the curiosities of new moms.

  3. Chatrooms- Chatrooms for all communities to interact with each other in a private environment.

  4. SheBot- An intelligent bot made using IBM Watson API to answer any queries related to women health.

  5. Cancer Diagnosis and Prognosis- To detect skin, cervical and breast cancer and/or predict the chances of cancer

  6. DoctorPoll- A polling API that selects the doctor who has received the highest polls for consultation by a group of women with similar issues.

  7. RazorPay- A payment gateway that has a PhonePe payment method to help divide the costs among women who want to consult a similar doctor.

  8. GoogleTranslate API- A feature that helps women to communicate and interact in any language of their choice.

  9. AlanAPI- Your friendly voice assistant that can open any webpages according to your voice commands.

Challenges we ran into

These are the challenges we ran into :
1.)Connecting the chatrooms through Socket.io.
2.)Training the ML Model.
3.)Integrating the Alan API.
4.)Connecting the ML Models and Front-end through Flask.

Discussion