  Pattern matching of streaming time series with lower latency under limited
computing resource comes to a critical problem, especially as the growth of
Industry 4.0 and Industry Internet of Things. However, against traditional
single pattern matching model, a pattern may contain multiple subpatterns
representing different physical meanings in the real world. Hence, we formulate
a new problem, called "consecutive subpatterns matching", which allows users to
specify a pattern containing several consecutive subpatterns with various
specified thresholds. We propose a novel representation Equal-Length Block
(ELB) together with two efficient implementations, which work very well under
all Lp-Norms without false dismissals. Extensive experiments are performed on
synthetic and real-world datasets to illustrate that our approach outperforms
the brute-force method and MSM, a multi-step filter mechanism over the
multi-scaled representation by orders of magnitude.
