engleski

Changes in Usage of an Indoor Public Space: Analysis of One Year of Person Tracking

Knowledge about space usage from variables such as density and walking speed could support a variety of service applications. However there is not much knowledge on how the usage of space changes during extended periods of time and what affects the changes. We have installed a person tracking system in a large area of a shopping center, and collected pedestrian data over a year. In this paper we analyze the collected data to find the changes in pedestrian density and speed, percentage of children, and pedestrian trajectories. The changes from day to day, as well as during the day are examined and a number of factors that affect them are identified. This is in turn used in the prediction of the state of the space using a Gaussian process model.

distributed vision networks ; modeling ; predictive models ; ubiquitous computing

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