| 摘要 |
This disclosure relates generally to multi-sensor data, and more particularly to summarizing multi-sensor data. In one embodiment, the method includes computing plurality of histograms from sensor data associated with a plurality of sensors. The respective histograms of each sensor are clustered into a first plurality of sensor-clusters, and a first set of rules is extracted therefrom. First set of rules defines patterns of histograms of a set of sensors occurring frequently over a time-period. Two or more sensor-clusters from amongst the first plurality of sensor-clusters are merged selectively to obtain a second plurality of sensor-clusters. Second set of rules are extracted from the second plurality of sensor-clusters, and a set of correlated sensors are identified therefrom based on the second set of rules. Third set of rules are extracted from the set of correlated sensors, the third set of rules summarizes the multi-sensor data to represent prominent co-occurring sensor behaviors. |
| 主权项 |
1. A processor-implemented method for summarizing multi-sensor data comprising:
computing, via one or more hardware processors, a plurality of histograms from sensor data associated with a plurality of sensors; clustering, via the one or more hardware processors and from the plurality of histograms, respective histograms of each of the plurality of sensors to obtain a first plurality of sensor-clusters based on shape of the respective histograms, each sensor-cluster of the first plurality of sensor-clusters comprising a centroid histogram representative of distinct sensor behavior for a distinct sensor of the plurality of sensors; performing, via the one or more hardware processors, frequent pattern mining on the first plurality of sensor-clusters to extract a first set of rules, a rule of the first set of rules being associated with a set of sensors of the plurality of sensors and comprising a set of sensor-clusters occurring frequently in the first plurality of sensor-clusters over a time period; merging, via the one or more hardware processors, selectively two or more sensor-clusters from amongst the first plurality of sensor-clusters to obtain a second plurality of sensor-clusters, the two or more sensor-clusters selected corresponding to a sensor of the set of sensors, the two or more sensor-clusters being merged based on two or more rules from amongst the first set of rules associated with the two or more sensor-clusters and a distance measure between the two or more sensor-clusters of the sensor; extracting, via the one or more hardware processors, a second set of rules from the second plurality of sensor-clusters, the second set of rules indicative of distinct sensor behaviors associated with the second plurality of sensor-clusters; identifying, via the one or more hardware processors, a plurality of sets of correlated sensors from the second plurality of sensor-clusters based on the second set of rules; and extracting, via the one or more hardware processors, a third set of rules from the one or more sets of correlated sensors, the third set of rules summarizing the multi-sensor data to represent prominent co-occurring sensor behaviors. |
