Abstract: Devices, systems, and methods for maintenance prediction for devices of a fire system 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 fire system device data of a fire device in a fire system and generate a fire device analysis based on the fire system device data, where the fire device analysis includes a predicted behavior of the fire device and a predicted timeline for the predicted behavior of the fire device.

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 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: A system receives an energy demand response schedule, one or more user preferences, and one or more predicted environmental variables into a computer processor. The system generates an optimized energy schedule as a function of the demand response schedule, the user preferences, and the predicted environmental variables. The optimized energy schedule includes one or more of a set point temperature variation in one or more zones, an air handling unit set point temperature variation, a chilled water set point temperature variation, a carbon dioxide level set point variation, a pre-cooling time shift, a pre-cooling duration variation, and a load based optimized chiller schedule. The system transmits the optimized energy schedule to a building management server.

Abstract: A system receives an energy demand response schedule, one or more user preferences, and one or more predicted environmental variables into a computer processor. The system generates an optimized energy schedule as a function of the demand response schedule, the user preferences, and the predicted environmental variables. The optimized energy schedule includes one or more of a set point temperature variation in one or more zones, an air handling unit set point temperature variation, a chilled water set point temperature variation, a carbon dioxide level set point variation, a pre-cooling time shift, a pre-cooling duration variation, and a load based optimized chiller schedule. The system transmits the optimized energy schedule to a building management server.