An IoT enabled point system for end-to-end multi-modal transportation optimization

Transportation is one of the areas that could highly benefit from the use of Internet of Things (IoT) innovative aspects not only in terms of information aggregation, but also for pattern identification and policy enforcement. In this paper we present a novel system for a transportation optimization, which exploits information streams from individuals, transportation means and external environment in order to provide dynamically end-to-end mobility recommendations. The proposed solution incorporates also incentivization features to motivate end-users by introducing a unique point-system that covers all transportation modes and is adaptive to the mobility behavior of all user types including pedestrians, car drivers, taxi customers, cyclists and public transportation users.