SafetiPin is a technology tool that seeks to use big data to make cities safer and more inclusive for women and others. We have mobile applications that collect data about safety parameters in the city. Our apps provide data about the level of safety in different public spaces in the city. We use the methodology of the safety audit, which measures the following parameters: lighting, openness, visibility, walk path, availability of public transport, crowd, gender diversity, and security.
SafetiPin started in 2013 and initially collected all data through crowd sourcing. Through this method, we collected over 10,000 audit points in Delhi and another 7,000 audit points in eight other Indian cities. This data has two distinct audiences. First is the individual user who can use the data to make safer and informed decisions while using and moving around a city. All this data is made available to all users of the app - currently approximately 40,000 users. This data is visible on the app and on our online platform and the user can interact with the data. A user can share their feeling of safety in an area and that gets added onto the database of information that we have. We provide a Safety Score and our app gives an alert when a user is in an unsafe area. We have recently launched an app My SafetiPin, which has a feature that shows the safest route.
We share the data with urban stakeholders to help them work towards the improvement of safety in different parts of the city. For example, we shared the data with the Public Works Department in Delhi who used it to improve street lighting in the city. We also shared the data with the Delhi Police who correlated the data with their data on unsafe spots in the city. Similarly, the Municipal Corporation of Gurgaon used the data to work on improving streets in the city.
We also established formal MoUs with the City of Nairobi and Bogota to share the data collected. In addition, we are also sharing the data with Manila, Jakarta, and Mexico in partnership with UN Women and UN Habitat. We are supplementing crowdsourced data collection with nighttime pictures of the city through an app SafetiPin Nite, which is mounted on cars to generate pictures of the city at night. These pictures are coded on the same safety audit parameters mentioned above. Using this method, we have collected data in 27 cities across 8 countries.
The SafetiPin project began in April 2015. The two co-founders (one a gender and urban safety expert and the other a technology entrepreneur) came up with the idea to build an app that worked on crime prevention. Further, we wanted to make this data widely available to women and others in cities across the world. It took around six months to develop the app and conduct a pilot in Delhi before launching it in November 2015. We then forged partnerships with NGOs in other Indian cities and conducted pilots in eight other cities. We also began expanding to other countries and launched the Spanish version in Bogota and a Bahasa version in Jakarta. We built a Hindi and a Mandarin version and began sharing our data with urban stakeholders.