This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...
The current sensor networks are assumed to be designed for specific applications, having strongly coupled data communication protocols. The future sensor networks are envisioned a...
This work investigates the use of semantic information to link ground level occupancy maps and aerial images. A ground level semantic map, which shows open ground and indicates th...
This paper presents the framework of a mobile air quality monitoring network, with an in-depth discussion of several new innovative techniques for web-based visualization. These t...
— This paper proposes an approach allowing indoor environment supervised learning to recognize relevant features for environment understanding. Stochastic preprocessing methods i...