Literature DB >> 17968059

Visualizing the history of living spaces.

Yuri Ivanov1, Christopher Wren, Alexander Sorokin, Ishwinder Kaur.   

Abstract

The technology available to building designers now makes it possible to monitor buildings on a very large scale. Video cameras and motion sensors are commonplace in practically every office space, and are slowly making their way into living spaces. The application of such technologies, in particular video cameras, while improving security, also violates privacy. On the other hand, motion sensors, while being privacy-conscious, typically do not provide enough information for a human operator to maintain the same degree of awareness about the space that can be achieved by using video cameras. We propose a novel approach in which we use a large number of simple motion sensors and a small set of video cameras to monitor a large office space. In our system we deployed 215 motion sensors and six video cameras to monitor the 3,000-square-meter office space occupied by 80 people for a period of about one year. The main problem in operating such systems is finding a way to present this highly multidimensional data, which includes both spatial and temporal components, to a human operator to allow browsing and searching recorded data in an efficient and intuitive way. In this paper we present our experiences and the solutions that we have developed in the course of our work on the system. We consider this work to be the first step in helping designers and managers of building systems gain access to information about occupants' behavior in the context of an entire building in a way that is only minimally intrusive to the occupants' privacy.

Entities:  

Year:  2007        PMID: 17968059     DOI: 10.1109/tvcg.2007.70621

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  2 in total

1.  Simulation of Smart Home Activity Datasets.

Authors:  Jonathan Synnott; Chris Nugent; Paul Jeffers
Journal:  Sensors (Basel)       Date:  2015-06-16       Impact factor: 3.576

2.  Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach.

Authors:  Zhaoyuan Yu; Linwang Yuan; Wen Luo; Linyao Feng; Guonian Lv
Journal:  Sensors (Basel)       Date:  2015-12-30       Impact factor: 3.576

  2 in total

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