Towards smart fare pricing: Predictive algorithms and blockchain for dynamic price optimization in passenger transport

• DOI: https://doi.org/10.22533/at.ed.8208312611031

• Palavras-chave: dynamic pricing, predictive algorithms, blockchain, transportation systems, smart contracts

• Keywords: dynamic pricing, predictive algorithms, blockchain, transportation systems, smart contracts

• Abstract: Dynamic pricing in passenger transport services is undergoing a profound transformation driven by big data, artificial intelligence, and blockchain technology. This article proposes an integrated framework that combines predictive algorithms with blockchain infrastructure to optimize real time pricing strategies, improving both operational efficiency and end-user satisfaction. Using machine learning techniques, specifically time-series models and demand elasticity estimation, a dynamic pricing engine is developed that adjusts fares according to demand fluctuations, user segmentation, and external variables (such as weather, events, and traffic conditions). In parallel, blockchain technology is implemented to ensure transparency, traceability, and automation of fare transactions through smart contracts, reducing fraud and guaranteeing data immutability.