Aleksandar Antonic

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In this paper we focus on mobile crowdsensing applications for community sensing where sensors and mobile devices jointly collect and share data of interest to observe and measure phenomena over a larger geographic area. Such applications, e.g., environmental monitoring or crowdsourced traffic monitoring, involve numerous individuals that on the one hand(More)
—We are witnessing the rise of a novel class of wearable devices equipped with various sensing capabilities as well as further miniaturization of sensing components that are nowadays being integrated into mobile devices. The inherent mobility of such devices has the capacity to produce dense and rich spatiotemporal information about our environment creating(More)
The ACM DEBS Grand Challenge 2015 focuses on real-time analytics over a high volume geospatial data stream composed of taxi trip reports from New York City. The goal of the challenge is to provide a solution which continuously identifies the most frequent routes (query 1) and most profitable areas (query 2) for taxis in New York City. The solution needs to(More)
—We demonstrate an urban crowd sensing application for monitoring air quality by use of specially-designed wearable sensors and mobile phones. The application is built upon the OpenIoT platform 1 with the goal to support context-aware and energy-efficient acquisition and filtering of sensor data in mobile environments while ensuring adequate sensing(More)