Abstract: Devices, systems, and methods for providing predictive analytics of fire systems are described herein. One fire system maintenance system, includes fire system detectors, a fire system control panel, and a gateway device positioned within the facility and in communication with at least one of the fire system control panel or fire system detectors, the gateway having instructions to: collect fire system device health data associated with one or more fire or smoke detector devices and to send this fire system device health data to a remote device; the remote device having instructions to: analyze the collected fire system device health data to predict if the data contains any anomalies or deviations from an expected behavior; and a fire system maintenance solution application that identifies a nearest scheduled maintenance visit and associates a service item with the scheduled maintenance visit.

Abstract: A Building Management System (BMS) may be controlled in accordance with predicted occupancy using a trained model. A model is trained by providing the model with time stamped environmental data and corresponding time stamped occupancy data pertaining to a training building, wherein the time stamped environmental data is derived from one or more environmental sensors of the training building and the corresponding time stamped occupancy data is derived from one or more occupancy sensors of the training building. Once trained, the trained model is provided with time stamped environmental data for a use building that is derived from one or more environmental sensors of the use building. Occupancy data for the use building is not required. The trained model outputs a predicted occupancy value that represents a predicted occupancy count in the use building, and the BMS of the use building is controlled based at least in part on the predicted occupancy value.

Abstract: Devices, systems, and methods for filter life prediction for an aspirating smoke detector 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 log operational data of the aspirating smoke detector for a first time period to generate an initial data set, fit a machine learning model to the initial data set, and determine, based on the machine learning model, a remaining useful life of the filter.

Abstract: Methods and systems for operating a Heating, Ventilating and Air Conditioning (HVAC) system in accordance with one of a plurality of operating modes. The plurality of operating modes include one or more of a health mode, an energy savings mode and a balanced mode. In some cases, the operating modes include two or more energy saving modes. The currently operating mode is selected based on the current operating conditions of the building and the desired goals of the building operator. The goals can include, for example, reducing energy usage, reducing pathogen risks, increasing air quality and/or a combination of these goals. In some cases, the operating modes are autonomously controlled. In some cases, the operating modes are manually controlled.

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 providing fire events pattern analysis and cross-building data analytics are described herein. One fire system maintenance system, includes a number of fire system detectors, a fire system control panel, and a gateway device all positioned within the facility, the gateway device having instructions to: collect fire system device health data associated with one or more fire or smoke detector devices and to send this fire system device health data to a remote device, the remote device having instructions to: analyze the collected fire system device health data to determine an event type for each device health event recorded in the collected data, predict future device health events, categorize the device health events based on their determined event type, and prioritize the categorized device health events based on the quantity of events categorized in each event type.

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.

Abstract: Devices, systems, and methods for providing fire events pattern analysis and cross-building data analytics are described herein. One fire system maintenance system, includes a number of fire system detectors, a fire system control panel, and a gateway device all positioned within the facility, the gateway device having instructions to: collect fire system device health data associated with one or more fire or smoke detector devices and to send this fire system device health data to a remote device, the remote device having instructions to: analyze the collected fire system device health data to determine an event type for each device health event recorded in the collected data, predict future device health events, categorize the device health events based on their determined event type, and prioritize the categorized device health events based on the quantity of events categorized in each event type.

Abstract: Devices, systems, and methods for providing predictive analytics of fire systems are described herein. One fire system maintenance system, includes fire system detectors, a fire system control panel, and a gateway device positioned within the facility and in communication with at least one of the fire system control panel or fire system detectors, the gateway having instructions to: collect fire system device health data associated with one or more fire or smoke detector devices and to send this fire system device health data to a remote device; the remote device having instructions to: analyze the collected fire system device health data to predict if the data contains any anomalies or deviations from an expected behavior; and a fire system maintenance solution application that identifies a nearest scheduled maintenance visit and associates a service item with the scheduled maintenance visit.

Abstract: Devices, systems, and methods for providing fire events pattern analysis and cross-building data analytics are described herein. One fire system maintenance system, includes a number of fire system detectors, a fire system control panel, and a gateway device all positioned within the facility, the gateway device having instructions to: collect fire system device health data associated with one or more fire or smoke detector devices and to send this fire system device health data to a remote device, the remote device having instructions to: analyze the collected fire system device health data to determine an event type for each device health event recorded in the collected data, predict future device health events, categorize the device health events based on their determined event type, and prioritize the categorized device health events based on the quantity of events categorized in each event type.

Abstract: Appropriate ventilation for a building space while maintaining building comfort includes tracking one or more interior environmental conditions within the building space and one or more exterior environmental conditions outside of the building space during operation of the HVAC system. An environmental model for the building space is learned over time based at least in part on these tracked environmental conditions, where the environmental model predicts an environmental response of the building space to operation of the HVAC system under various interior and exterior environmental conditions. An appropriate ventilation rate that maintains adherence to one or more comfort parameters of the building space is determined by using the environmental model of the building space. The outdoor air ventilation damper of the HVAC system is controlled to provide appropriate ventilation.