In March of 2018, Kochi Metro Rail Limited (KMRL) became the first metro agency in the country to open its data in a machine-readable format for easy processing and analysis. In the pursuit to make mobility services more accessible to commuters, KMRL and WRI India Sustainable Cities organized a Data Innovation Challenge in January 2019 to encourage the use of data-driven interventions to improve access and the experience of moving in the city.

The Data Innovation Challenge had two tracks:

The Technology Challenge: Participants were asked to develop data-driven technology interventions to

(a) improve accessibility to transport services for all demographics of the city or

(b) support the agency in increasing ridership or efficiency

The Visualization Challenge: Participants were asked to use data points to develop innovative design-based approaches to visualize urban transport in Kochi. These visualizations would help city stakeholders identify gaps in the transportation network.

The Challenge received over 502 registrations. A total of 16 teams were shortlisted to be a part of the STAMP in-premise Tech Submission Bootcamp at Kochi. The winners were: 

• Team Hyperpro: Their analytic solution addressed a major aspect of KMRL’s operations. KMRL collects valuable data from ticketing and Automatic Fare Collection (AFC)/gate operations that the team’s solution can ingest and provide valuable information on commuters’ travel patterns and activity at station. The team used Google Cloud Platform (GCP) as their technology base and created data pipelines for a variety of visualizations and insights, customized to almost real-time analytics.
• Team Sukriti: The solution provided an overall view of passenger boarding and alighting patterns, with a focus on identifying the type of commuters based on the economic zoning of the city. The solution gave an in-depth view on how feeder services should be designed for each metro station given the type and frequency of commuters. Team Sukriti’s combination of urban planning expertise and data crunching tool displayed the ability to go beyond mobility data sets.