The problem Wayfer solves

On any normal day, while we're out travelling in any city across the world, we often find ourselves dependent on various Map applications. We use it to find the most convenient path to our destination. It offers us the shortcuts and less traffic prone area to reduce our travel time. But, what it fails to inform us is, how safe is the journey, whether they are extremely deserted at that time, and other such matters. The situation has been well described in an article of Financial Times as follows:- "So why doesn’t the app provide safer walking directions to women, or indeed anybody else, at night? It knows where we are, it knows what time the sun sets. It knows the population density of the area, and crime statistics are geotagged and publicly available in most major cities. It can even see which areas people walk through with impunity during the day but avoid in the dark." What we are doing:-
We divided our country into head nodes, and made a graph of the city.Based on past data and current data of a road, we have hourly updatea on whether the road is safe or not. We also continously scrape twitter data to search for any incidents which may occur , and show them onto our map.
We have also built a user community, where people of the current node and neighboring nodes can chat. This allows users to ask queries only to nearby users,(implemented using graph ). As this is a community based App, users can mark their house as safe house. After proper Verification, it'll be included in the list of safehouses. If any woman is attacked, she can press the SOS button, alerts will be sent to nearby people, that is users of the current node and family members and our emergency contacts, simultaneously.
We are not only showing a road safe/unsafe based on our model(which takes into consideration jam factor confidence,Type of road,modes of communication on road and several other factors and past data).We collects them from heremaps and others Govt websites only.

Challenges we ran into

but also manual reporting of roads can be done, that is, data will be added by real users to avoid false positives and true negatives. Lastly family can track them as well, under certain conditions.

Apart from the App, we are building a human interaction detection system with Surveillance Cameras using IOT based equipment, and artificial intelligence. This will help detect any criminal activity against women on roads, and alarm the concerned authorities.

challenges:-----

Scrapping websites for safe roads, and other related data for our ML model was a really tough job.Also cleaning and processing data from here maps were challenging.
For IOT part data collection was also difficult .