175 results about "Supervisory control" patented technology

The present invention relates to a method for constructing a digital twin system for an additive manufacturing process with lifecycle data management. The digital twin system for an additive manufacturing process constructed by the method includes a data acquisition and supervisory control system, a data management and storage system, a manufacturing executing system, a configuration model, a simulation system, and a multi-physics simulation system. The present invention can fully and accurately characterize the molding quality of parts, thereby saving a lot of time required for offline data processing, and achieving real-time acquisition and updating of data.

The invention relates to the technical field of industrial park intelligent monitoring, and particularly discloses a data acquisition and monitoring control method based on an intelligent industrial park, which comprises the following steps: acquiring key state data of equipment in real time, including operation time, operation temperature and operation power; an advanced signal processing algorithm is used for calculating an operation temperature abnormal index and an operation power abnormal index, the system can comprehensively evaluate the state of equipment and accurately judge whether slight or serious abnormal conditions exist or not based on detailed data analysis results, and the system can not only give out instant early warning notifications but also give out alarm information according to the serious abnormal conditions. According to the method, a machine learning model is adopted to predict the future operation state of the equipment, the equipment state abnormal coefficient in each future monitoring period is predicted based on the equipment state data in the current period, and classification and dynamic regulation and control of the equipment state are carried out according to a preset threshold value.

The invention relates to the technical field of supervision control and data acquisition, in particular to an intelligent monitoring system based on a multi-sensor fusion technology, comprising a multi-sensor acquisition and preprocessing module which acquires and self-calibrates at least two kinds of physical quantity data in real time and fuses the physical quantity data into a unified monitoring feature vector; and the fault diagnosis and prediction module is used for integrating interpretable semantic analysis in combination with a production plan and a maintenance record. And performing equipment state diagnosis, operation trend analysis and fault prediction in real time by utilizing electric inspection type monitoring, generating health assessment and early warning, and guiding optimization and adjustment of a control strategy. And the data storage module is used for storing semantic data model evaluation results, diagnosis reports and early warning information, and supporting fault root analysis and control effect evaluation based on processing batches and time sequences. And the remote man-machine interaction interface is used for displaying the equipment running state, the control parameters and the automatic process in real time, supporting voice instruction interaction and facilitating remote monitoring and intervention of an operator.

The invention provides a controllable SCADA (supervisory control and data acquisition) industrial production control platform based on an industrial internet architecture. The controllable SCADA industrial production control platform comprises a field layer, an edge layer, a communication layer, a cloud / fog computing layer and a data management layer, wherein the field layer is composed of a sensor array, an execution mechanism, a PLC controller and an RTU terminal; the sensor array comprises a temperature sensor, a pressure sensor, a flow sensor and a position sensor, and adopts 4-20mA current loop signal output; the execution mechanism comprises an electric valve, a servo motor and a variable frequency driver, and communicates with the PLC through a Modbus RTU protocol; the PLC controller is provided with a dual-core processor and is provided with 16 digital quantity input / output channels and 8 analog quantity input channels; the RTU terminal is internally provided with a LoRa wireless communication module; the edge layer comprises an edge computing node and a protocol conversion gateway; the edge computing node is provided with an FPGA coprocessor and supports an edge reasoning framework; and multi-protocol conversion is realized through the protocol conversion gateway.

The invention relates to the technical field of vacuum induction heating temperature control, and discloses a vacuum induction heating temperature closed-loop control system integrated with SCADA (supervisory control and data acquisition), which is characterized in that a functional material layer with preset Curie temperature is compounded on the surface of an induction coil, and the absolute value of phase difference is analyzed by collecting voltage and current signals of the coil in real time; according to the invention, through the synergistic effect of the electromagnetic impedance sudden change characteristic of the functional material layer and the phase difference detection mechanism, non-contact accurate control of the phase change critical temperature of the workpiece is realized; and meanwhile, due to the coupling application of the asymmetric micro-pulse waveform design and the dynamic adjustment strategy, the contradiction between thermodynamic response and electromagnetic interference in a vacuum environment is effectively balanced, and the control precision and stability of the system are remarkably improved.

Disclosed is an explainable method for monitoring a state of a generator of a wind turbine generator system on the basis of a spatio-temporal graph. The method includes: S1: acquiring data collected by a supervisory control and data acquisition (SCADA) system; S2: carrying out data understanding on the SCADA data, selecting features associated with the generator, and carrying out data preparation on the selected feature data, and obtaining valid data; S3: embedding the SCADA data, and forming a directed spatio-temporal graph data sequence; and S4: carrying out modeling of a normal behavior model of the generator on the constructed directed spatio-temporal graph data sequence, computing a full-graph-level residual and a node-level residual, computing a residual through an exponentially weighted moving average (EWMA) control chart method, carrying out full-graph-level state monitoring on the generator, forming a fault information transmission chain relation, and enhancing explainability and robustness of a monitoring result.

The invention relates to the technical field of monitoring and data acquisition systems, and discloses an SCADA (supervisory control and data acquisition) system based on a large language model, an implementation method and equipment, and the system comprises a user interaction terminal which receives a natural language instruction input by a user and displays a dynamic user interface; the natural language processing module is used for preliminarily analyzing the natural language instruction to obtain a user intention and key information; the large language model is used for deeply analyzing the user intention and the key information and generating a task description or a task execution plan; the MCP arrangement engine is used for mapping the task description or the task execution plan to a predefined function to obtain executable structured data; and the dynamic UI generator is used for generating a dynamic user interface based on the executable structured data and a preset UI instruction. According to the method, the usability and the data analysis capability of the SCADA system are improved through natural language interaction, and meanwhile, the reliability and the safety of the system are ensured by utilizing an MCP and a predefined function mechanism.

The invention relates to the technical field of supervision control, in particular to a new energy storage optimization control method and system, and the method comprises the following steps: collecting a grid-connected point voltage amplitude deviation, a frequency deviation and a voltage total harmonic distortion rate, and generating a power grid stress index; according to the method, the multi-dimensional state vector is constructed by collecting the grid-connected point voltage amplitude deviation, the frequency deviation and the total harmonic distortion rate to generate the stress index reflecting the power grid operation pressure, accurate quantitative sensing of the power grid state is achieved, the power grid supporting gain coefficient is dynamically generated according to comparison of the index and the preset threshold value, and the power grid supporting effect is improved. And the total required power to be responded by the energy storage system is adjusted and determined, so that the power support strength is matched with the actual demand of the power grid, and insufficient response or excessive response is avoided.

The invention relates to the technical field of supervision and control, in particular to a polyethylene chlorination reaction control system which comprises a hot-pressing time difference extraction module, a viscosity variable-speed recognition module, a chlorine pressure collaborative trend division module, a response centralized recombination module and a stirring amplitude management and control module. According to the method, a multi-source variable data structure is unified through period numbers, cooperative sections with consistent trend directions are constructed, response feature fragments in a continuous period are recognized by combining fluctuation frequency and adjustment amplitude feature extraction, the behavior boundary of each variable in the time dimension is unified, and the recognition precision of multi-variable abnormal evolution is improved; a regulation and control reference is established through trend classification and strength grading, structured expression and controllability analysis of periodic behaviors are realized, the matching between the regulation rhythm and the variable trend is enhanced, and a regulation and control strategy is enabled to have clear boundary recognition, period tracking and behavior intervention capabilities.

A system for AI-supported cybersecurity and regulatory compliance in energy distribution networks, consisting of: a hardware-embedded data acquisition module configured to intercept, capture, and time-stamp operational data streams and to control data traffic from SCADA (Supervisory Control and Data Acquisition) systems, AMI (Advanced Metering Infrastructure) systems, and energy management systems (EMS) via multiple communication protocols without operational latency; an FPGA-based deep packet inspection unit coupled with the data acquisition module, wherein the FPGA firmware is configured to perform line rate filtering, protocol decomposition and metadata extraction of the acquired data and forwards preprocessed packet data to an AI processing unit; an AI processing unit consisting of a multi-core central processing unit (CPU), a dedicated AI accelerator selected from a graphics processing unit (GPU) or a tensor processing unit (TPU), and a volatile memory buffer; a response orchestration module that is communicatively coupled with network management devices and operations controllers, wherein the response orchestration module is configured to perform automated security and compliance remediation measures, including network isolation of compromised segments, enforcement of protocol encryption, and privilege revocation; and an immutable audit logging subsystem configured to record all detected events, compliance assessments, and corrective actions in a blockchain-based distributed ledger, with each log entry cryptographically anchored with a secure hash value and digitally signed with keys stored in a secure hardware enclave.

The invention relates to the technical field of control systems, and provides a supervision control system, method and equipment in an industrial weaving process and a storage medium. The method comprises the following steps: acquiring engineering data and environment data in a weaving process through an intelligent sensor, and standardizing an original spatio-temporal data matrix formed by the engineering data and the environment data to generate an engineering matrix; attribute information including elasticity, fluid and heat conduction is generated based on the engineering matrix, and a space model representing the weaving process state is constructed based on the attribute information; generating a dynamic control parameter based on the deviation between the model parameter of the spatial model and the target trajectory; generating a tension signal for the dynamic control parameter and a preset target tension, and generating an execution instruction through the tension signal to control the weaving equipment to operate. A multi-physics field coupling space model is constructed, dynamic control parameters are generated according to the deviation between model parameters and a target track, and an accurate closed-loop supervision control process from data perception to equipment control is formed.

The invention discloses a robot and an intelligent interaction method thereof, and relates to the technical field of robots, and the robot comprises an instruction obtaining module which is used for converting external instruction information into text information; the artificial intelligence module is used for performing vectorization processing and similarity comparison on the text information and keywords in a preset task list through a large model to obtain a conventional target task and an unconventional target task; the task decomposition module is used for decomposing the conventional target task or the unconventional target task into a plurality of sub-tasks and determining solutions matched with the sub-tasks according to the types of the sub-tasks; the task execution module is used for supervising and controlling execution of each subtask; the memory module is used for storing key data and a knowledge graph database in the execution process of each subtask; and the planning decision module is used for controlling the operation of the modules. According to the invention, man-machine interaction and autonomous planning and intelligent control of the robot body can be realized.

A unification method based on data acquisition interfaces of different SCADA (supervisory control and data acquisition) production monitoring systems of a sewage plant comprises the following steps: analyzing private protocols such as Modbus through protocol conversion middleware, and standardizing data streams; establishing association between the unique identifier and the data stream by using an equipment mapping mechanism to form a data mapping table; a data normalization algorithm is adopted to unify a field format, and missing values are filled through linear interpolation. And an increment adaptation module is designed to realize compatibility of new and old system interfaces, and AES-256 encryption is combined to guarantee transmission security. The transmission rate is dynamically adjusted based on the network state, and video and production data are fused. A multi-protocol environment is adapted through an adaptive protocol adjustment module, and finally data integrity is ensured by using a CRC check and retransmission mechanism. According to the scheme, a technical closed loop from protocol conversion to multi-source fusion is constructed, the problems of data island and compatibility of the SCADA system of the sewage plant are solved, and the data management efficiency and reliability are improved.

The invention discloses an electric power inspection operation robot anti-misoperation system and method based on video analysis, and relates to the technical field of electric power equipment, and the system comprises an inspection robot which is used for collecting first real-time state data of to-be-operated equipment, and executing an operation instruction issued by a user; the video acquisition module is used for acquiring second real-time state data of the equipment to be operated; the data acquisition and monitoring control module is used for acquiring third real-time state data of the equipment to be operated; and the main control module is used for judging whether equipment state data fed back by the first real-time state data, the second real-time state data and the third real-time state data are consistent or not, and controlling the inspection robot to execute a corresponding operation instruction when the equipment state data are consistent. The situation of misoperation of the inspection robot is avoided, and therefore stable operation of a power system is guaranteed.

The invention discloses a closed-loop control method for a hydraulic control butterfly valve of a PCCP (prestressed concrete cylinder pipe) long-distance high-pressure water conveying pipeline, and belongs to the technical field of long-distance high-pressure water conveying pipeline control. The problems that in the prior art, due to manual scheduling or single-point PID control, a long-distance PCCP water conveying system has response lag and lacks global cooperation, the water attack risk is difficult to effectively deal with, and the optimal overall energy consumption of the system cannot be considered are solved. According to the invention, by constructing a hierarchical control architecture in which a distributed measurement and control network is coordinated with a central supervision control and data acquisition system platform, a variable-parameter PID control algorithm is built in an equipment PLC, so that millisecond-level identification and active suppression of a sudden water attack working condition are realized; a hydraulic simulation model and a multi-objective optimization algorithm are deployed in a central supervision control and data acquisition system master station, and a whole-line optimal pressure set value is solved through iterative calculation and is issued to each PLC for execution, so that the system energy consumption minimization is realized on the premise of ensuring the pipeline safety.

The invention provides a chopped chilli fermentation jar temperature remote regulation and control system and method based on supervision and control, and relates to the technical field of temperature remote regulation and control. The abnormal confidence coefficient of the temperature of the chopped chilli fermentation jar in the current chopped chilli fermentation period is determined; calibrating the temperature value of each temperature sensor; further generating temperature regulation and control instructions of a heating rate control section and a constant temperature maintaining section in the current chopped chilli fermentation period; when the abnormal confidence exceeds a set threshold value, a semiconductor temperature control module on the outer wall of the chopped hot pepper fermentation jar body is remotely controlled to execute a temperature regulation and control instruction, temperature gradient distribution in the chopped hot pepper fermentation jar is continuously monitored in the instruction execution process, and then the distribution proportion of the heating power and the refrigerating power of the semiconductor temperature control module is adjusted. According to the application, the internal temperature of the chopped chilli fermentation jar can be remotely and accurately regulated and controlled in a high-acid, high-salt and high-humidity chopped chilli fermentation environment, so that the uniform distribution of the internal temperature of the fermentation jar is improved.

The invention discloses a wind-solar hydrogen storage and charging multi-energy complementary integrated system and a cooperative control method thereof, and belongs to the technical field of supervision control and data acquisition, and the method comprises the following steps: firstly detecting the fluctuation index of the output power of a power generation side, and starting the absorption of a super capacitor and the PID adjustment buffering of a lithium battery; and evaluating the state of the electrolytic cell, and determining whether or not and how to accurately adjust the feed water flow according to the water content and humidity distribution variance. And finally responding to the load change rate. According to the wind and light hydrogen storage and charging multi-energy complementary cooperative control method provided by the invention, accurate management of all working conditions of the electrolytic cell is realized through a three-step cooperative closed-loop control logic. A complete chain of'prevention-response-optimization 'is formed from source protection of power fluctuation on a power generation side, dynamic correction of the state of the electrolytic cell and graded adjustment of load change. The core value of the method lies in that through multi-parameter linkage, the damage risk of the proton exchange membrane is reduced to the maximum extent, and efficient and stable operation of the electrolytic cell is guaranteed.

The invention discloses a supervision and control-based punctual scheduling method and system for wafer combination equipment, and mainly solves the problems of high probability of blockage, path conflict and low scheduling efficiency during multi-resource parallel operation of the existing wafer combination equipment. According to the implementation scheme, the method comprises the following steps: respectively constructing corresponding automaton models for process units in equipment, and carrying out synchronous splicing according to a real process flow to form an overall model capable of reflecting dynamic behaviors of a system; a corresponding constraint model is established by combining factors such as process sequence constraint, equipment capacity limitation, carrying time constraint and residence time limitation; and the supervision controller continuously judges whether the event to be executed can cause blockage or not, gradually eliminates the blockage by disabling the controllable event, triggers the optimal event according to the priority of the event, and guides the scheduling path to propel and output the optimal scheduling scheme along the optimal direction. According to the method, the overall model capable of being dynamically adjusted is constructed, the event priority and multi-class constraint collaborative optimization scheduling is utilized, the wafer residence time can be remarkably shortened, the overall scheduling efficiency is improved, and the method can be used for operation inspection, evaluation and optimization of an equipment system.

The invention discloses a wind driven generator fault diagnosis method based on missing SCADA data and a self-adaptive time-sensitive multi-head attention mechanism, and relates to the technical field of wind driven generator fault diagnosis and prediction. In order to solve the technical defects in the prior art that errors and error accumulation are caused by data missing, only data interpolation is concerned, and time sequence dependence modeling is insufficient in the existing fan fault diagnosis work, the technical scheme provided by the invention comprises the following steps: collecting monitoring data in a wind turbine generator SCADA system to form an SCADA data matrix; carrying out numerical value standardization processing on the SCADA data; performing segmentation extraction on the time sequence data, constructing a missing indication matrix, and generating a missing value mapping matrix; extracting time sequence dependence characteristics of the SCADA data, and generating a dynamic time sequence dependence mapping matrix; and generating a fan fault prediction result according to the dynamic time sequence dependence mapping matrix. The method is suitable for intelligent operation and maintenance of a wind power plant, SCADA data analysis, equipment health management, predictive maintenance and the like.

The invention discloses an SCADA (supervisory control and data acquisition) system interface point rerouting method, system, equipment, medium and product, and relates to the field of SCADA systems, the method comprises the following steps: in each HMI (human machine interface) of an SCADA system, respectively receiving a pre-configured variable redirection script for binding two preset logic point identifiers, the picture logic point identifier is directly associated with the picture element in the current HMI interface and is not directly associated with the physical equipment monitored by the SCADA system, and the equipment logic point identifier is opposite; when a trigger instruction for the variable redirection script of any HMI interface is received, after it is detected that the logic point identifier of the current picture is bound with the logic point identifiers of other devices, the binding relation is unbound; and binding the unbound current picture logic point identifier and the unbound current equipment logic point identifier so as to complete redirection of the picture elements and the physical equipment in the HMI interface. The expansibility of the system is improved.

The application provides a Petri net supervisory control method and a controller applied to a complex manufacturing system, and the method comprises the following steps: obtaining system information of the complex manufacturing system, and constructing a Petri net model of the complex manufacturing system according to the system information; constructing a reachable graph of the Petri net model according to the Petri net model; taking the current state and resources of each device as input, and predicting transition enabling values of each device in all reachable states through a trained neural network model; and performing supervisory control on the complex manufacturing system according to the transition enabling values of each device in all reachable states. For the complex manufacturing system, the application can avoid the state explosion problem caused by the calculation of the reachable graph of the complex manufacturing system, greatly reduce the time complexity and calculation complexity caused by the calculation of the reachable graph, and directly realize the deadlock control of the complex Petri net and has high behavior permissibility.

A method and system that include receiving sensor data that is indicative of an operational status of a well construction equipment that is being utilized to construct a planned well that include receiving a well construction plan that includes information that is indicative of the planned well and the well construction equipment. The method and system additionally include accessing a database of operational sequences that are executable to be performed by the well construction equipment to construct a plurality of wells and selecting from the database an operational sequence to construct the planned well. The method and system further include electronically controlling the well construction equipment to autonomously perform the plurality of physical or mechanical operations of the selected operational sequence to drill at least one of: a selected portion of the planned well and a path along the selected portion of the planned well through a subterranean formation.

The invention provides a poultry house intelligent adjustment control method and system based on temperature and humidity double control, and relates to the technical field of supervision control, and the method comprises the steps: collecting a temperature data set and a humidity data set in a poultry house in real time through a temperature sensor and a humidity sensor; temperature and humidity double-control calculation is carried out based on the environment parameter set, a control instruction set is generated, an MOS tube switching circuit is activated according to the control instruction set to drive adjusting equipment, the poultry house environment is intelligently adjusted, and an adjusting result is obtained; and performing adjustment error analysis based on an adjustment result, and generating a switching control mode to formulate a control strategy to continuously optimize the poultry house environment. The technical problems that in the prior art, due to the fact that the control mode is single, poultry house environment adjustment is extensive and response is lagged when environment fluctuation is large are solved, through temperature and humidity coupling analysis and in combination with error analysis, the control modes are dynamically switched, an MOS tube is driven to conduct accurate adjustment, stability of the poultry house environment is achieved, and the poultry house environment is stable. And the optimal comfortable area is maintained.

1. The name of the design product: supervisory management graphical user interface for computer. 2. The use of the design product: the design product is used for running programs and displaying information, and is suitable for computer screens. 3. The design points of the design product: the graphical user interface content in the screen. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: the graphical user interface of the design product is used for users to perform market supervision administration daily supervision and management tasks and view related information. 6. The human-computer interaction mode of the graphical user interface: the interface uses the state reference diagram as the "home page" page when logging in, and enters the main view interface through the login account and password to perform task operations. 7. Other circumstances that need to be explained: the computer part in the design product is a conventional design.

A hybrid electric vehicle includes: a dual clutch transmission having first and second sub-transmissions having respective first and second clutches and first and second synchronizers, and an electric motor rotationally coupled to the second sub-transmission for common rotation therewith; and a control system including a hybrid controller and a transmission controller with the HCP being a supervisory controller, wherein the control system is configured to execute an engine clutch start procedure using the electric motor, and wherein the procedure eliminates hard vehicle speed limits, provides smooth wheel torque during the procedure, and increases a number of transmission gears available for the procedure.

Various embodiments described herein relate to automated asset strategy selection for assets via cloud-based supervisory control. In this regard, one or more baselines for asset strategy data related to an asset is estimated based on a regression analysis process associated with the asset. Additionally, a maximum uncertainty level for the one or more baselines is determined, one or more conditions related to energy optimization for an environment associated with the asset is estimated for a future period of time, and a predicted uncertainty level for the one or more conditions related to the energy optimization is determined. Based on a comparison between the maximum uncertainty level and the predicted uncertainty level, a predetermined asset strategy or an energy optimization asset strategy for the future period of time is then selected.

The application discloses a kind of supervision control strategy generation methods based on counterexample guide deep reinforcement learning, comprising: one, definition model;Two, supervision control strategy generation, the method with deep Q network as reinforcement learning subject, introduce online counterexample guide verification mechanism, using counterexample search dynamic correction control permission dictionary and optimizing reinforcement learning strategy, finally coupling convergent deep network parameters and whole state space dynamic permission dictionary, generate with global non-blocking characteristics coordinated supervision control strategy.This method can meet non-blocking and approach maximum allowable supervision strategy without explicitly constructing the global state space of controlled discrete event system, balance between computational complexity and strategy allowance, provide a new technical approach for non-blocking control of super large scale discrete event system.

The invention relates to the technical field of operation and inspection of wind turbine generator equipment, and discloses a knowledge graph and deep learning-based fan anomaly monitoring and operation and inspection optimization method, which comprises the following steps of: acquiring operation data of a wind turbine generator through an SCADA (Supervisory Control and Data Acquisition) system, and acquiring state data of the wind turbine generator through a CMS (Content Management System) system; obtaining operation and maintenance data of the wind turbine generator; constructing a TCN-BiGRU-Attention network model to analyze the multi-dimensional data, and outputting an anomaly type and confidence coefficient predicted by the model; constructing a double-layer knowledge graph; taking the exception type as input, extracting a feasible scheme according to a graph reasoning algorithm, and outputting an operation inspection strategy triple; and inputting the operation and maintenance strategy triple and the multi-dimensional data into the large language model, performing multi-round semantic reasoning and strategy optimization, and outputting an optimal operation and maintenance strategy. The method has the advantages that the high precision of anomaly identification and the high reliability of operation and maintenance decision are realized, the expandability and the practical value are good, and the method is suitable for various scenes such as intelligent wind power plant operation and maintenance, remote state monitoring and intelligent scheduling.

The utility model relates to the related technical field of gas pipelines, in particular to a pipeline leakage detection device for an SCADA (supervisory control and data acquisition) system, which comprises an upper arc clamping block and a lower arc clamping block which are combined on a pipeline, and further comprises a connecting mechanism, a detection mechanism and a control mechanism, the upper arc clamping block and the lower arc clamping block are fixedly mounted outside a to-be-detected pipeline; and the gas collection mechanism is used for gathering and collecting gas leaked from the to-be-detected pipeline and conveying the gas to the detection end of the leakage probe. According to the utility model, through the leakage probe connected with the gas collection mechanism, gas at a certain leakage point of the to-be-detected pipeline can be gathered and collected and conveyed to the leakage probe, so that an operator can conveniently detect the SCADA system pipeline, and the effect of detecting the SCADA system pipeline is achieved; and through the arrangement of the connecting mechanism, the device can be fixedly installed outside the to-be-detected pipeline conveniently, and the device is suitable for multi-pipe-diameter installation and is convenient to operate.

A control system configured to control operation of reverse osmosis (RO) array(s), nanofiltration (NF) array(s) and / or a blending system including a control panel (CP), regulatory controllers (RCs), and a supervisory controller (SC), wherein the SC is in signal communication with the CP, and with the RCs, wherein the SC is configured to: receive user inputs from the CP, and receive inputs from RCs regarding data from sensors, wherein the RCs are in signal communication with the plurality of sensors, wherein the RCs are configured to: receive data from the sensors, provide outputs to and receive permissions from the SC, and instruct devices in response to the received permissions from the SC, and wherein the SC is configured to: monitor trends in the inputs regarding and / or predict outcomes from data received from the RCs and determine the permissions for RCs based on the monitored trends and / or user inputs from the CP.