A Crowd-Assisted Real-time Public Transport Information Service: No More Endless Wait

Many passengers have expressed frustration in waiting for public bus endlessly without knowing the estimated ar- rival time. In many developing countries, requiring bus operators to invest in the installation of a GPS unit on every bus in order to track the bus location and subsequently predicting the bus arrival time can be costly. This paper proposes passenger-assisted sharing of bus location to provide an estimation of bus arrival time. Our scheme aims to exploit the availability and capability of passenger mobile phones to share location information of the travelling buses in order to collect transportation data, at the same time provide an estimation of bus arrival time to the general public. A mobile app is developed to periodically report bus location to the cloud service, and it can detect location spoofing by malicious users. The preliminary results of the field tests suggest that the proposed system is viable and the predicated ETA falls within three minutes of the bus actual arrival time

Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

Today's mobile phones are far from mere communication devices they were ten years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.Comment: 29 pages, 5 figure