Rodalinets is a mobile application providing real-time information on train schedules, occupancy levels, and potential incidents for Rodalies Catalunya, a commuter rail service. By using machine learning algorithms, the app delivers accurate, up-to-date data, enabling users to efficiently plan their journeys and promoting more effective use of public transport.
Funding
Funding not disclosed
Founders
Product
Problem
Commuters using the Rodalies Catalunya rail service often lack real-time information regarding train schedules, occupancy, and potential disruptions, making यात्रा planning difficult. Reliance on static schedules and lack of immediate updates can lead to delays, overcrowding, and inefficient use of public transportation.
Solution
Rodalinets is a mobile application that provides real-time, user-sourced data on the Rodalies Catalunya commuter rail service. The app leverages machine learning algorithms to predict train arrival times, estimate occupancy levels, and report incidents based on anonymized user data and historical trends. By crowdsourcing information and cross-referencing it with official schedules, Rodalinets delivers up-to-date insights directly to commuters' smartphones. This enables users to make informed decisions about their journeys, avoid crowded trains, and stay informed about delays or disruptions, ultimately improving their commuting experience.
Target Audience
The primary users are daily commuters of the Rodalies Catalunya rail service who seek real-time information to optimize their travel plans and avoid potential disruptions.
Features
- Real-time train arrival predictions based on machine learning algorithms and user-submitted data.
- Crowd-sourced occupancy reports allowing users to see how full trains are in real-time.
- Incident reporting feature enabling users to alert others about delays, disruptions, or other issues.
- Automatic shut-off after the user boards the train to conserve battery life.
- Anonymized data collection to protect user privacy.
- Integration of weather forecasts to improve prediction accuracy.
- Digital twin application (TwinNets) for railway network management, offering predictive analysis, real-time monitoring, and incident simulation.