| 摘要 |
A method models movement of users in an environment including sensors connected in a network. Events due to movement of the users are detected at the sensors and each event is labeled according to a particular sensor and time of the event. The events for each sensor are summed into a corresponding histogram time interval bin. A plurality of co-occurrence matrices are generated from the histograms according to <maths id="MATH-US-00001" num="00001"> <MATH OVERFLOW="SCROLL"> <MROW> <MROW> <MSUB> <MI>C</MI> <MROW> <MI>i</MI> <MO>,</MO> <MI>j</MI> <MO>,</MO> <MI>delta</MI> </MROW> </MSUB> <MO>=</MO> <MROW> <MUNDEROVER> <MO>∑</MO> <MROW> <MI>t</MI> <MO>=</MO> <MN>0</MN> </MROW> <MI>T</MI> </MUNDEROVER> <MO></MO> <MSTYLE> <mspace width="0.3em" height="0.3ex"/> </MSTYLE> <MO></MO> <MROW> <MSUB> <MI>H</MI> <MROW> <MI>i</MI> <MO>,</MO> <MI>t</MI> </MROW> </MSUB> <MO></MO> <MSUB> <MI>H</MI> <MROW> <MI>j</MI> <MO>,</MO> <MROW> <MI>t</MI> <MO>+</MO> <MI>delta</MI> </MROW> </MROW> </MSUB> </MROW> </MROW> </MROW> <MO>,</MO> </MROW> </MATH> </MATHS> where i and j represent each possible pair of sensors, delta represent time-off-sets, T is a total time for the detecting, t represents a particular time, and H represents the histogram time interval bins. The co-occurrence matrices can be used to determine a geometry of the network, and for predicting future activities signaled by terminating events.
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