Abstract: Various embodiments of the present technology relate to digital twins of devices and assemblies. More specifically, some embodiments relate to the orchestration of digital twin models for representing industrial systems based on characteristics of digital twins. In an embodiment, a method of operating an orchestration engine in an industrial automation environment comprises identifying a targeted outcome for modeling the industrial automation environment, configuring a digital twin environment corresponding to the industrial automation environment based at least on the targeted outcome, and executing a process associated with the industrial automation environment using the digital twin environment.

Abstract: The present invention provides a system and method which includes a machine learning module which analyzes data collected from one or more sources such as UAVs, satellites, span mounted crop sensors, direct soil sensors and climate sensors. According to a further preferred embodiment, the machine learning module preferably creates sets of field objects from within a given field and uses the received data to create a predictive model for each defined field object based on detected characteristics from each field object within the field.

Abstract: A device includes a housing with a reference electrode having a metal plug extending through the housing. One or more sensing surfaces are disposed on an exterior of the housing, where the one or more sensing surfaces are configured to perform a nutrient measurement of a soil. A moisture sensor is disposed on an exterior of the housing for detecting a moisture level of the soil.

Abstract: A method of delivering a consumable to an irrigation area may include determining application characteristics for applying the consumable to the irrigation area based on irrigation area characteristics of the irrigation area, generating an irrigation schedule for the irrigation area based on consumable characteristics of the consumable and the application characteristics, and transmitting the irrigation schedule to a local control to selectively activate one or more water outlets to the irrigation area based on the irrigation schedule.

Abstract: A cooking appliance may employ one or both of a post-preheat phase and a two stage preheat phase to both accelerate preheating of an oven cavity while minimizing temperature differentials therein. A post-preheat phase may be performed subsequent to a preheat phase, but prior to a cooking phase, to cycle a cooking element disposed in a cooler portion of an oven cavity to reduce a temperature differential between the top and bottom of the oven cavity. A two stage preheat phase may sequentially activate each of top and bottom cooking elements in an oven cavity a single time.

Abstract: According to one embodiment, a method to increase drought tolerance for grass is disclosed. The method includes estimating by a server a root depth of grass watered by an irrigation system based on one or more of historical watering data of the grass, grass type characteristics, or soil characteristics of soil in which the grass is growing; determining by the server a target water depletion threshold of the grass based on the root depth; generating by the server an irrigation schedule based on the target water depletion threshold and weather information; and transmitting by the server the irrigation schedule to an irrigation controller to selectively activate the irrigation system based on the irrigation schedule.

Abstract: A method includes receiving, for a first pipe, first pressure values corresponding to first valve positions of a first valve coupled to the first pipe. The method further includes receiving, for a second pipe routed in parallel with the first pipe, second pressure values corresponding to second valve positions of a second valve coupled to the second pipe. The method further includes generating a fluid conductance map based on the first valve positions, the first pressure values, the second valve positions, and the second pressure values. The method further includes causing, by a processing device based on a recipe and the fluid conductance map, the first valve to be in a first valve position and the second valve to be in a second valve position for a process of the recipe.

Abstract: Systems and methods are described herein for novel uses and/or improvements to artificial intelligence applications in an environment with limited or no available data. In particular, systems and methods are described herein for providing network arrangement recommendations based on power consumption predictions for selected applications within network arrangements featuring devices with non-homogenous or unknown specifications.

Abstract: An apparatus for controlling an operation of a system is provided. The apparatus comprises an input interface configured to receive a state trajectory of the system, and a memory configured to store a model of dynamics of the system including a combination of at least one differential equation and a closure model. The apparatus further comprises a processor configured to update the closure model using reinforcement learning (RL) having a value function reducing a difference between a shape of the received state trajectory and a shape of state trajectory estimated using the model with the updated closure model, and determine a control command based on the model with the updated closure model. Further, the apparatus comprises an output interface configured to transmit the control command to an actuator of the system to control the operation of the system.

Abstract: System for monitoring and regulating plant productivity comprising: a memory for storing instructions; a processor for executing the instructions to cause a method of monitoring and regulating plant productivity to be performed, the method comprising: receiving field data from monitoring sensors; computing, by the at least one processor executing a machine learning algorithm, a predicted value for a variable associated with the production environment condition of a crop field, the machine learning algorithm having been trained based on a training set comprising one or both of (a) the field data from the monitoring sensors, and (b) a generated feature derived from the field data; and determining, based on a threshold associated with the variable, that the predicted value for the variable indicates that an intervention in the crop field is to be initiated; and in response to the determining, causing a controllable device to vary the production environment condition.

Abstract: An irrigation management system is disclosed and positionable in-line with an irrigation pipe for monitoring and controlling a flow of fluid therethrough. In at least one embodiment, the system provides an inlet pipe and an opposing outlet pipe in serial fluid communication with the irrigation pipe. At least one fluid control valve is in serial fluid communication between the inlet pipe and outlet pipe for selectively controlling the flow of fluid therebetween. The fluid control valve provides a main valve and a hydraulic actuator for selectively moving the main valve between open and closed positions. The hydraulic actuator is also in serial fluid communication between a pair of actuator valves for moving the hydraulic actuator between open and closed positions. The system also provides at least one sample collection tank configured for temporarily storing a volume of fluid diverted from the irrigation pipe in order to be tested.

Abstract: Novel tools and techniques are provided for implementing Internet of Things (“IoT”)-based microwell solution for irrigation. In various embodiments, in response to receiving, from the plurality of sensors, first sensor data indicative of environmental conditions within an area, a computing system may analyze the first sensor data to determine parameters associated with water requirements within the area, may generate a water distribution plan based at least in part on the determined parameters, and may map the generated water distribution plan to a positional map of a plurality of microwells disposed at pre-installed locations within the area. The computing system may generate and send instructions to the microwells to pump water from an underground water source(s) (in some cases, surface water sources as well) and to irrigate plants or crops in the area using integrated irrigation systems, based on the mapping. The microwells and sensors may utilize IoT functionalities.

Abstract: A convenient, water-saving and labor-saving FROG irrigation controller and system are provided, which determine the appropriate water budget and schedule for the property's landscaping based on evapotranspiration data for the geographic area, any regulation data, and property-specific data, with consideration given to reduction in watering days, increase in soil watering depth, and day of year. Once set, the FROG controller provides incremental adjustments over the course of the year; the homeowner no longer needs to re-set the watering program seasonally to automatically comply with local mandated and voluntary watering restrictions. One aspect provides a web-based wizard that is used to determine a customized water budget/schedule which is input into the FROG controller. Another aspect provides an integration of a network of FROG controllers with a central command unit.

Abstract: There is disclosed a method and system for regulating plant irrigation at a crop field. The method comprises obtaining soil water tension (SWT) data and/or soil water content (SWC) data corresponding to a crop field. The SWT data and/or the SWC data is segmented into three segments. A respective line of best fit is determined for each of the three segments. The intercepts of the lines of best fit are used to determine an irrigation start threshold and an irrigation stop threshold. Devices that control irrigation for the crop field are caused to start or stop irrigation based on the irrigation start threshold and irrigation stop threshold.

Abstract: An alignment control system for controlling an alignment of a plurality of mobile towers, each mobile tower supporting a section of conduit in an irrigation system comprises a plurality of tower angle measurement devices and a control processing element. Each tower angle measurement device is associated with a successive one of the mobile towers and is configured to measure an angle value which varies according to a rotation angle of the associated mobile tower relative to one or more of the other mobile towers. The control processing element is configured or programmed to receive the angle value from each tower angle measurement device, compare the angle value to a threshold angle value, and generate and transmit control signals, data, or both that include an activation hysteresis value to a drive motor associated with each mobile tower that has an angle value greater than the threshold angle value.

Abstract: Disclosed are an energy service system of a multi-machine production line and a control method thereof, the method includes reorganizing respective machines in the production line into three types of controllable entities: a drive system, an energy supply bus and an execution device, equipping them with a control center, and selecting a sub-drive system that is idle and is capable of completing the work stage with high energy efficiency to supply energy service for the corresponding execution device through the energy supply bus. Further disclosed is a design method of a multi-machine shared drive system of a production line, which increases the number of basic flow units of each drive unit to a maximum value one by one, and coordinates action time to form a variety of scheduling schemes, and selects a configuration scheme whose total time and total energy consumption are less as the shared drive system.

Abstract: A method, computer program product, and system are disclosed. The method, when implemented in a computer system, includes obtaining product information, selecting a production node from a plurality of production nodes, and communicating production information to the production node. The product information is configured to facilitate production of a product. The selecting performed by the computer system comprises determining a physical location of a destination of the product and identifying the production node. The identifying is based, at least in part, on the physical location and one or more production criteria. The production information comprises information identifying the product. The computer system is configured to communicate with each production node of the plurality of production nodes. The communicating is configured to result in production of the product by the production node.

Abstract: A distributed building management system for controlling a building control device of a building includes a virtual controller that is hosted on a computing device and an edge controller that is associated with the building control device. The virtual controller includes a virtual container or a virtual machine that has control logic that generates control commands for controlling the building control device. The edge controller includes control logic that is configured to at least selectively provide closed loop control of one or more functions of the building control device. The edge controller is in operative communication with the virtual controller and is configured to receive and execute the control commands generated by the virtual controller.

Abstract: On a user interface presented on a display screen, an alteration point marker is rendered on a circular shape representing a center pivot irrigation system. The alteration point marker is aligned with an input point specified by user input. A fine position control may also be rendered on the display screen. The fine position control may comprise a first icon and a second icon, wherein the first icon is for repositioning the alteration point marker in a first circular direction, and wherein the second icon is for rotating the alteration point marker in the second circular direction.

Abstract: A method for initiating and automatically improving model-driven operations in a low-data scenario includes creating a regression model using pre-operation data prior to initiating the model-driven operations, using the regression model to initiate and perform the model-driven operations during an operational stage, collecting operational data during the operational stage, creating a first artificial neural network model using the operational data, transitioning from using the regression model to perform the model-driven operations to using the first artificial neural network model to perform the model-driven operations responsive to the operational data satisfying a first sufficiency threshold.