Frequent sensor calibration is essential in sensor networks with low-cost sensors. We exploit the fact that temporally and spatially close measurements of different sensors measuring the …
Scalable training of Bayesian nonparametric models is a notoriously difficult challenge. We explore the use of coresets-a data summarization technique originating from computational …
Z Xu, S Zhu - Proceedings of the 5th ACM Conference on Data and …, 2015 - dl.acm.org
While mobile sensing applications are booming, the sensor management mechanisms in current smartphone operating systems are left behind--they are incomprehensive and …
Spatial computing Page 1 72 COMMUNICATIONS OF THE ACM | JANUARY 2016 | VOL. 59 | NO. 1 DOI:10.1145/2756547 Knowing where you are in space and time promises a …
This paper analyzes the benefits of big data for smart cities and the potential of the knowledge discovery from sensed data. Big data enables real-time systems monitoring …
O Masutani - 2015 IEEE International Conference on Pervasive …, 2015 - ieeexplore.ieee.org
General vehicles have much potential to contribute to city surveillance in a context of Smart City. Vehicular crowd sensing is essential for reasonable and sustainable city surveillance …
P Yang, Q Li, Y Yan, XY Li, Y Xiong… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
In this paper, we investigate the task offloading issue in mobile social networks. Although the “d-choice” paradigm in “ball and bin” theory had shown the power of random choice in load …
Awareness of our surrounding environment is very important. Traditional stationary air quality and pollution monitoring systems which installed in dedicated locations are usually …
Spatial computing is a set of ideas, solutions, tools, technologies, and systems that transform our lives with a new prospect of understanding, navigating, visualizing and using locations …