The problem Confidænt solves

Women's safety has become a rising global concern, with women being assaulted and abused in all aspects of their daily life.
Taking this into account, we devised the concept for, our web application Confidaent.
We hope that our web app Confidaent will provide women a sense of security so that they can pursue any horizon in life while being linked to their safety network. We regularly use our phone's Google Maps to find the quickest route.
However, the path that we are directed upon may turn out to be a dangerous one.
This is why we decided to take on the task of creating a map that not only provides the quickest but also the safest path based on the area's recent crime statistics.

Challenges we ran into

Unsupervised Machine learning algorithm: We had to understand and apply an Unsupervised Machine Learning Algorithm to find the danger index of multiple routes between two places. In our project, we have used the K-means Clustering algorithm to rate the criminal activities on the map of Delhi on a scale of 0 to 4.

API integration: Since most of our team members were working with APIs for the first time, it was quite challenging to integrate them in the span of 24 hours.

Dataset availability: Since no public datasets are available except for Delhi, we had to currently restrict the scope of our application.