A fault prediction system for building equipment includes one or more memory devices configured to store instructions that, when executed on one or more processors, cause the one or more processors to receive device data for a plurality of devices of the building equipment, the device data indicating performance of the plurality of devices; generate, based on the received device data, a plurality of prediction models comprising at least one of single device prediction models generated for each of the plurality of devices or cluster prediction models generated for device clusters of the plurality of devices; label each of the plurality of prediction models as an accurately predicting model or an inaccurately predicting model based on a performance of each of the plurality of prediction models; and predict a device fault with each of the plurality of prediction models labeled as an accurately predicting model.

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 differences are present. Instructions for irrigation placements and testing may then be displayed or modified based on the results of the sector determinations.

A system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions. One general aspect includes an intelligent irrigation system including one or more of a sprinkler and one or more processors configured to: obtain imagery data regarding a plant; determine a current life cycle stage of the plant based on the imagery data, determine a plant crop coefficient for the plant based on the current life cycle stage of the plant, determine irrigation water output for the plant based on the plant crop coefficient, potential evapotranspiration calculated using solar radiation, temperature, wind speed and/or any other factors, and control the sprinkler to irrigate the plant based on the irrigation water output determined for the plant.

The present disclosure relates to a task processing method and device based on defect detection, a computer readable storage medium, and a task processing apparatus . The method includes receiving a detection task; determining a task type of the detection task; storing the detection task in a task queue if the task type is a target task type; and executing the detection task in a preset order and generating a feedback signal when a processor is idle. The detection task of the target task type includes an inference task and a training task. Executing the training task includes modifying configuration information according to a preset rule based on product information in the detection task; acquiring training data and an initial model according to the product information; and using the training data to train the initial model according to the configuration information to obtain a target model and store it in memory.

An automated container fill line system comprises a container fill line configured to transport a plurality of containers at a fill line speed, and a filler configured to dispense a material into each of the containers individually and sequentially. An Expert System is configured to control the container fill line speed using a set of hierarchical rules and one or more machine learning models associated with equipment of the container fill line.

An electronic monitor can monitor experimental animals in a cage. The cage has one or more walls that enclose a living space for the experimental animals. The electronic monitor is coupled to the cage. The electronic monitor may include a housing adapted to be mechanically coupled to the cage in a predefined position relative to the cage. A substantially sterile barrier is provided between the living space and the external environment in this coupled state. The walls of the cage may include a signal-interface section. An electromagnetic detector may be coupled to the housing to have a line-of-sight through the signal-interface section and into the living space of the cage. The electromagnetic detector is adapted to detect electromagnetic radiation that is transmitted through the signal-interface section. A controller processes a signal received from the electromagnetic detector to determine a status of the experimental animals or the living space.

A method for the autonomous construction and/or design of at least one component part of a component includes the step of determining a state (s.sub.i) of the component part by a state module, wherein a state (s.sub.i) is defined by parameters (p.sub.i) such as data and/or measured values of at least one property (e.sub.i) of the component part. The state (s.sub.i) is transmitted to a reinforcement learning agent, which uses a reinforcement learning algorithm. A calculation function (ƒ.sub.i) and/or an action (a.sub.i) is selected on the basis of a policy for a state (s.sub.i) for the modification of at least one parameter (p.sub.i) by the reinforcement learning agent. A modeled value for the property (e.sub.i) is calculated using the modified parameter (p.sub.i). A new state (s.sub.i+1) is calculated by an environment module on the basis of the modeled value for the property (e.sub.i).

A platform for updating one or more properties of one or more digital twins including receiving a request for one or more digital twins; retrieving the one or more digital twins required to fulfill the request from a digital twin datastore; retrieving one or more dynamic models corresponding to one or more properties that are depicted in the one or more digital twins indicated by the request; selecting data sources from a set of available data sources based on the one or more inputs of the one or more dynamic models; obtaining data from selected data sources; determining one or more outputs using the retrieved data as one or more inputs to the one or more dynamic models; and updating the one or more properties of the one or more digital twins based on the one or more outputs of the one or more dynamic models.

Methods and systems for data collection in an environment including pumps and fans are disclosed. A monitoring system may include a data collector communicatively coupled to a plurality of input channels, wherein the input channels are communicatively coupled to sensors measuring operational parameters of a pump or fan. A data storage may store one or more frequencies related to an operation of the pump or fan, and a data acquisition circuit may interpret a plurality of detection values from the collected data. A frequency evaluation circuit may detect a signal on one of the input channels at a frequency higher than the one or more frequencies at which the pump or fan operates.

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.