Zebralocalizer: identification and localization of pedestrian crossings
Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services
Migrating operator placement for compositional stream graphs
Proceedings of the 15th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
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Context-awareness is a critical aspect of safe navigation especially for the blind and visually impaired in unfamiliar environments. Existing mobile devices for context-aware navigation fall short in many cases due to their dependence on specific infrastructure requirements as well as having limited access to resources that could provide a wealth of contextual clues. In this paper, we propose a mobile-cloud collaborative approach for context-aware navigation by exploiting the computational power of resources made available by Cloud Computing providers as well as the wealth of location-specific resources available on the Internet. We propose an extensible system architecture that minimizes reliance on infrastructure, thus allowing for wide usability. We present a traffic light detector that we developed as an initial application component of the proposed system. We present preliminary results of experiments performed to test the appropriateness for the real-time nature of the application.