TSML (Time Series Machine Learnng)

Paulito Palmes; Joern Ploennigs; Niall Brady

TSML (Time Series Machine Learnng)

Machine Learning 2020-05-28 v1 Machine Learning

Authors: Paulito Palmes , Joern Ploennigs , Niall Brady

Abstract

Over the past years, the industrial sector has seen many innovations brought about by automation. Inherent in this automation is the installation of sensor networks for status monitoring and data collection. One of the major challenges in these data-rich environments is how to extract and exploit information from these large volume of data to detect anomalies, discover patterns to reduce downtimes and manufacturing errors, reduce energy usage, predict faults/failures, effective maintenance schedules, etc. To address these issues, we developed TSML. Its technology is based on using the pipeline of lightweight filters as building blocks to process huge amount of industrial time series data in parallel.

Keywords

unified modeling language time series classification pipeline optimization

Cite

@article{arxiv.2005.13191,
  title  = {TSML (Time Series Machine Learnng)},
  author = {Paulito Palmes and Joern Ploennigs and Niall Brady},
  journal= {arXiv preprint arXiv:2005.13191},
  year   = {2020}
}

Related papers

View all related →