RLTS: Recommendation for local transportation system using Ambient Intelligence

With the proliferation of advanced telecommunication technologies and mobile computing, the transportation system is also getting smarter. There has been a good amount of research work done in the past decade to enhance the user experience in transportation facilities, however the existing systems are found to be less emphasizing on the traveler's requirements. In order to align the traveler's requirements with the transportation services, a novel framework, based on Ambient Intelligence(AmI) is proposed in this paper. The system evaluates context of users in the transportation system and based on the situation it provides unique recommendations to the travelers discretely. The proposed system is evaluated on a micro-platform to testify its supportability in real-time mobile computing environment. The outcome of evaluation/test is found to provide realistic recommendations with faster processing capability on trusted handheld devices.