A chiller threshold management system for a building, including one or more memory devices and one or more processors. The one or more memory devices are configured to store instructions to be executed on the one or more processors. The one or more processors are configured to determine whether chiller fault data exists in chiller data used to generate a plurality of chiller prediction models. The one or more processors are further configured to generate a first threshold evaluation value for each of the plurality of chiller prediction models using a first evaluation technique in response to a determination that chiller fault data exists in the chiller data, and generate a second threshold evaluation value for each of the chiller prediction models using a second evaluation technique in response to a determination that chiller fault data does not exist in the chiller data. The one or more processors are configured to select a first threshold for each of the plurality of chiller prediction models based on the first threshold evaluation values in response to the determination that chiller fault data exists in the chiller data, and select a second threshold for each of the plurality of chiller prediction models based on the second threshold evaluation values in response to the determination that chiller fault data does not exist in the chiller data.

Wireless communication enabled circuit breakers are described. Methods associated with such wireless communication enabled circuit breakers are also described. The wireless communication enabled circuit breakers may controlled by a remote entity. The remote entity may wirelessly case the wireless communication enabled circuit breakers to trip.

A chiller fault prediction system for a building, including one or more memory devices and one or more processors. The one or more memory devices are configured to store instructions to be executed on the one or more processors. The one or more processors are configured to receive chiller data for a plurality of chillers, the chiller data indicating performance of the plurality of chillers. The one or more processors are configured to generate, based on the received chiller data, a plurality of single chiller prediction models and a plurality of cluster chiller prediction models, the plurality of single chiller prediction models generated for each the plurality of chillers and the plurality of cluster chiller prediction models generated for chiller clusters of the plurality of chillers. The one or more processors are configured to label each of the plurality of single chiller prediction models and the plurality of cluster chiller prediction models as an accurately predicting chiller model or an inaccurately predicting chiller model based on a performance of each of the plurality of single chiller prediction models and a performance of each of the plurality of cluster chiller prediction models. The one or more processors are configured to predict a chiller fault with each of the plurality of single chiller prediction models labeled as the accurately predicting chiller models. The one or more processors are configured to predict a chiller fault for each of a plurality of assigned chillers assigned to one of a plurality of clusters labeled as the accurately predicting chiller model.

A device is configured to operate a Heating, Ventilation, and Air Conditioning (HVAC) system. The device is further configured to determine that the amount of time to close a pressure switch exceeds a time threshold value. The device is further configured to receive an audio signal from a microphone while operating the HVAC system, to identify an audio signature for the combustion air inducer, and to determine the audio signature for the combustion air inducer is present within the audio signal. The device is further configured to determine a fault type based on the determination that the audio signature for the combustion air inducer is present within the audio signal, to identify a component identifier for a component of the HVAC system that is associated with fault type, and to output a recommendation identifying the component identifier.

A smart brake system for adjusting a brake clamping force to be applied to brake pads of a vehicle comprises: an interface for receiving vehicle operation data measured by vehicle sensors, a memory device for storing data about a previous brake event, a current brake event, and a temperature prediction model, and a controller connected to the interface and the memory device. The controller estimates the current temperature of the rotor and adjusts the brake clamping force applied to the brake pads to compensate for the estimated current temperature. The vehicle operation data include current ambient temperature, current brake clamping force and current vehicle speed. The controller is configured to estimate the current temperature of the rotor from the vehicle operation data, the data about a previous brake event, and the data about a current brake event using the temperature prediction model.

An apparatus, methods and systems for data collection in an industrial environment are disclosed. A monitoring system can include a data collector coupled to a plurality of sensors to collect data, a data storage structured to store a plurality of data collection management plans, a data acquisition circuit structured to interpret a plurality of detection values from the collected data, and a data analysis circuit structured to analyze the collected data and select one of the plurality of data collection management plans, wherein the selected one of the plurality of data collection management plans is selected is at least in part based on a data analysis of received data from the plurality of sensors.

Communication enabled circuit breakers are described. Methods associated with such communication enabled circuit breakers are also described. The communication enabled circuit breakers may include one or more current sensors. The one or more current sensors may be disposed in a clip. The clip may be coupled to a line side phase connection, and the clip may be shielded to attenuate signals.

A platform for facilitating development of intelligence in an Industrial Internet of Things (IIoT) system generally includes a plurality of distinct data-handling layers comprising an industrial monitoring systems layer that collects data from or about a plurality of industrial entities in the IIoT system; an industrial entity-oriented data storage systems layer that stores the data collected by the industrial monitoring systems layer; an adaptive intelligent systems layer that provisions available computing resources within the platform; and an industrial management application platform layer that manages the platform in a common application environment.

Techniques for providing improvements in agricultural science by optimizing irrigation treatment placements for testing are provided, including analyzing a plurality of digital images of a field to determine vegetation density changes in a sector of the field. The techniques proceed by comparing a distribution of pixel characteristics in the digital images for each field sector to determine sectors in which minimal density deviations are present. Instructions for irrigation placements and testing may be displayed or modified based on the results of the sector determinations.

Systems for self-organizing data collection and storage in a manufacturing environment are disclosed. A system may include a data collector for handling a plurality of sensor inputs from sensors in the manufacturing system, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of at least one target system. The system may also include a self-organizing system for self-organizing a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs. The self-organizing system may organize a swarm of mobile data collectors to collect data from a plurality of target systems.