Abstract: The present solution, approach or method, including an end-to-end automated data pipeline for data ingestion, storage, analysis, deployment, and a machine learning model maintenance. The present solution, approach or method, which computes a baseline using machine learning methods, may help in the following ways. Accurate real time estimation may help evaluate the deviation in the actual energy consumption, effectively identifying underlying root causes for an increase in actual consumption, as compared to the estimated energy. Triangulating the time of day and place of high energy consumption results in quicker resolution. Accurately quantifying energy savings may be helpful. Forecasting energy consumption in the future, may enable planning for future energy needs. Energy saving calculations may be done by comparing actual consumption versus baseline predicted consumption based for a specific baseline period.

Abstract: Devices, systems, and methods for fire system floor plan layout generation are described herein. In some examples, one or more embodiments include a computing device comprising a memory and a processor to execute instructions stored in the memory to receive a floor plan layout of a space, define, via an object placement model utilizing the floor plan layout, placement locations of fire system objects for the floor plan layout, and generate, using the object placement model, a fire system floor plan for a fire system for the space including the fire system objects, wherein the fire system objects are located in the defined placement locations on the fire system floor plan from the floor plan layout.