VISUAL CORRELATION TECHNIQUE OF DATA FROM THE BUILDING MANAGEMENT SYSTEM

Presents a visualization driven approach to analyzing the heating ventilation and air conditioning (HVAC) system logs, that can be used to investigate various security incidents and to monitor the state of the system used for real-time monitoring. A distinctive feature of the approach is the detection of the time periods during which the state of the state of the system remains almost unchanged, it allows one to scale the data volumes, detect periods with changes in HVAC parameters, and graphically display only meaningful changes in data. To demonstrate the applicability of the proposed technique, the authors developed a software prototype on JavaScript language using NodeJS platform and NW.js framework; the visualization models were implemented using d3.js library.

Authors: E. S. Novikova, M. P. Bestuzhev, D. Yu. Guryanov

Direction: Informatics, Computer Technologies And Control

Keywords: HVAC systems, functioning patterns, anomaly detection, visual correlation, heterogeneous data, stream data clustering, heat map

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