An Android-based personalized public transportation advisor

This work presents the development of a mobile application which allows the user to access real time data related with public transportation information. This application combines the geographic user context and preferences with the data provided by a public transportation information system, fulfilling the necessities of today’s passengers and providing an incentive for the population to use the public transportation infrastructure. The proposed application, still in prototype stage, allows the user to benefit from real time access to public transportation data in a simple and intuitive form. Results from use cases and real world tests using data from a Brazilian bus fleet operator were employed to validate the operability and features of the developed prototype.info:eu-repo/semantics/acceptedVersio

Context aware advisor for public transportation

This paper presents an Android-based mobile app designed to provide real time context aware public transportation information and advice to its users through the combination of the user's preferences and geographic context with data retrieved from a public transportation information system called XTraN Passenger. Thus, this mobile app contributes to fulfill the necessities of the passengers, and also provides an incentive for people to use the public transportation infrastructure more frequently. The proposed mobile app allows the users to benefit from the access to real time public transportation data in a simple and intuitive way. The validation of the features and operation of the developed app was assessed with results from use cases and real-world experimental tests using public transportation data from a Brazilian bus fleet operator.This work is supported by FCT with the reference project UID/EEA/04436/2013, by FEDER funds through the COMPETE 2020 –Programa Operacional Competitividade e Internacionalização (POCI) with the reference project POCI-01-0145-FEDER-006941

Automatically Generating Personalized User Interfaces with SUPPLE

Today's computer–human interfaces are typically designed with the assumption that they are going to be used by an able-bodied person, who is using a typical set of input and output devices, who has typical perceptual and cognitive abilities, and who is sitting in a stable, warm environment. Any deviation from these assumptions may drastically hamper the person's effectiveness—not because of any inherent barrier to interaction, but because of a mismatch between the person's effective abilities and the assumptions underlying the interface design. We argue that automatic personalized interface generation is a feasible and scalable solution to this challenge. We present our Supple system, which can automatically generate interfaces adapted to a person's devices, tasks, preferences, and abilities. In this paper we formally define interface generation as an optimization problem and demonstrate that, despite a large solution space (of up to 1017 possible interfaces), the problem is computationally feasible. In fact, for a particular class of cost functions, Supple produces exact solutions in under a second for most cases, and in a little over a minute in the worst case encountered, thus enabling run-time generation of user interfaces. We further show how several different design criteria can be expressed in the cost function, enabling different kinds of personalization. We also demonstrate how this approach enables extensive user- and system-initiated run-time adaptations to the interfaces after they have been generated. Supple is not intended to replace human user interface designers—instead, it offers alternative user interfaces for those people whose devices, tasks, preferences, and abilities are not sufficiently addressed by the hand-crafted designs. Indeed, the results of our study show that, compared to manufacturers' defaults, interfaces automatically generated by Supple significantly improve speed, accuracy and satisfaction of people with motor impairments.Engineering and Applied Science