Time-series anomaly detection using dynamic programming based longest common subsequence on sensor data

•Measure the similarity of two time-series based on the longest common subsequence (LCS).•Investigate a gap search constraint to limit the searching range to find the LCS.•Provide a threshold to define the matching of a pair of time-series.•Detect the anomalous time-series based on the similarity-based LCS.•Apply on a case study of big multisensory data.