International Journal of Science, Engineering and TechnologyAuthors: Ishita Shetty, Desmond Ferrao, Dr. Jasbir Kaur, Ifrah Kampoo, Suraj Kanal
Abstract: Urban ride-hailing platforms constitute a significant and rapidly growing source of transportation-related carbon emissions in emerging economies, yet existing commercial ap-plications provide no trip-level carbon transparency and no reward mechanism calibrated to quantified emission reduction. This paper presents MugenRider, a carbon-aware ride-hailing system in which an adaptive Eco-Coin reward currency is awarded in direct proportion to the per-ride carbon saving, computed using fuel-type-specific emission factors sourced from the GHG Protocol and the Handbook Emission Factors for Road Transport (HBEFA) standards, benchmarked against an internal combustion engine (ICE) reference of 180 g CO2/km. The system is implemented as a cross-platform Flutter mobile application backed by Firebase Cloud Firestore, with route distances resolved via the Google Directions API and EV emissions computed using the Indian grid well-to-wheel factor of 0.708 kg CO2/kWh. A fixed monetary redemption equivalence of R5 per 100 Eco-Coins establishes a financially legible incentive instrument, distinguishing the system from prior non-redeemable gamification approaches. A multi-horizon EcoZone Dashboard delivers environmental feedback at immediate, periodic, and longitudinal temporal scales, complemented by a peer-comparison leaderboard. A mixed-methods empirical evaluation comprising (i) a structured functional validation suite of 33 test cases across seven system modules, all achieving 100% pass rates, and (ii) a user survey administered to 62 respondents via Google Forms, demonstrating system correctness, negligible emission computation deviation, and strong user preference for reward-linked sustainable ride selection. EV rides yielded a computed 41.0% carbon reduction relative to the ICE baseline. Five UI/UX design guidelines for reward-integrated sustainability applications are derived from the results.
DOI: http://doi.org/10.5281/zenodo.20829278
