The inspiration for RaahSakhi stemmed from the increasing need for safety solutions for women traveling alone. Recognizing the challenges women face in navigating unfamiliar or high-risk areas, we aimed to create a platform that combines real-time crime data, community feedback, and personalized preferences to ensure safer travel. The goal was to empower women by providing a reliable navigation app that promotes confidence and peace of mind.
RaahSakhi is a navigation app that suggests safer routes for women traveling alone. It allows users to input their destination and personal preferences, such as avoiding poorly lit areas or high-crime neighborhoods. The app uses real-time data on crime rates and integrates community-generated safety ratings for routes and locations, enabling women to make informed decisions about their travel.
We built RaahSakhi using a combination of APIs for real-time crime data and mapping services. The app’s core functionality includes user-generated safety ratings, allowing users to contribute feedback on their routes. We also incorporated machine learning models to analyze crime data and predict safer routes based on historical patterns. The front-end was designed to be user-friendly, with an emphasis on accessibility and simplicity.
One of the biggest challenges was integrating real-time crime data into the app. There were several limitations around the availability of up-to-date and accurate crime data, which required significant effort to ensure the information was reliable. Additionally, building a seamless user interface that balanced functionality with simplicity posed another challenge, especially when trying to include real-time data without overwhelming the user.
We are proud of creating a functional prototype that combines essential features like real-time crime data and community-generated ratings in a way that feels intuitive and user-friendly. The integration of personalized preferences such as avoiding specific neighborhoods or poorly lit areas adds a unique layer of customization. Seeing the idea transform into an app that could potentially have a positive impact on women's safety is a huge accomplishment.
Throughout this project, we learned how to handle complex data integration, particularly when working with live data sources. We also gained insight into the nuances of developing apps that deal with sensitive topics like personal safety, which requires a careful balance of accuracy, empathy, and user trust. Additionally, the importance of creating a simple yet functional user interface was a key takeaway from this project.
Looking forward, we plan to refine the app by expanding the range of data sources for even more accurate crime and safety insights. We aim to incorporate more community-driven features like live reporting of incidents and real-time alerts. Future updates will also focus on enhancing the app's accessibility features and expanding its availability to more regions to provide safer journeys to as many women as possible.
