Smart Abnormal Trend Analysis System (SATAS)

Industrial partner:  DSP Construction & Engineering Works Pte.Ltd

  • The operational process of SATAS

  • Data Filtering Module (DFM)

    • It is found that some dates have NULL entries or data corresponding to certain time slots are missing. Initially such instances are identified by DFM and filtered out on daily basis.

  • Feature Extraction Module (FEM)


    • The FEM is used to extract significant features for abnormal event detection.

      A typical feature trajectory on the 3D-feature space during a day with an abnormality
      Detail view of the abnormality

  • Abnormal Trajectory Detection Module (ATDM)

    • The trajectories of the principle components extracted in the FEM are used as features to detect the dates with abnormal events.

  • Detailed Abnormal Event Detection Module (DAEDM)

    • The raw data corresponding to the suspected abnormal trajectories are analyzed to extract more details of the


Smart Abnormal Trend Analysis System (SATAS)

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