We propose the development and pilot implementation of a mobile application that improves the safety of women in urban public spaces. The solution leverages real-time data analytics, geolocation and risk mapping to identify unsafe areas and warn users when they are approaching locations with an increased likelihood of violence or harassment. The application integrates multiple safety parameters — such as lighting conditions, time of day, pedestrian and traffic activity, proximity to police services and crime statistics — to generate predictive risk assessments. In case of a perceived threat, users can instantly notify trusted contacts or security services and share their location. The app enables safer route choices for users and provides city
authorities with analytics and dashboards to guide urban safety policies, planning and investments. In the long term, the solution is intended to be commercialized as FinEst-managed SaaS and consulting service for cities based on annual license and implementation projects. Additionally, the application provides city authorities with analytical insights and dashboards
to improve urban safety policies, spatial planning, and infrastructure investments.
