  Calculating aggregation operators of moving point objects, using time as a
continuous variable, presents unique problems when querying for congestion in a
moving and changing (or dynamic) query space. We present a set of congestion
query operators, based on a threshold value, that estimate the following 5
aggregation operations in d-dimensions. 1) We call the count of point objects
that intersect the dynamic query space during the query time interval, the
CountRange. 2) We call the Maximum (or Minimum) congestion in the dynamic query
space at any time during the query time interval, the MaxCount (or MinCount).
3) We call the sum of time that the dynamic query space is congested, the
ThresholdSum. 4) We call the number of times that the dynamic query space is
congested, the ThresholdCount. And 5) we call the average length of time of all
the time intervals when the dynamic query space is congested, the
ThresholdAverage. These operators rely on a novel approach to transforming the
problem of selection based on position to a problem of selection based on a
threshold. These operators can be used to predict concentrations of migrating
birds that may carry disease such as Bird Flu and hence the information may be
used to predict high risk areas. On a smaller scale, those operators are also
applicable to maintaining safety in airplane operations. We present the theory
of our estimation operators and provide algorithms for exact operators. The
implementations of those operators, and experiments, which include data from
more than 7500 queries, indicate that our estimation operators produce fast,
efficient results with error under 5%.
