Abstract: Systems and methods for transaction platforms include various systems interacting with each other and transacting in various ways. A method for configuring and launching a marketplace includes: identifying, by a processing system having one or more processors, an opportunity to facilitate configuration of a new marketplace; receiving marketplace opportunity data, wherein the marketplace opportunity data includes information related to a set of assets of one or more types; determining configuration parameters to be implemented in the new marketplace; determining the feasibility of implementing the configuration parameters in the new marketplace; determining data resources to support the new marketplace; determining an architecture of the new marketplace; determining the configuration of the data resources in a data model for the marketplace; configuring a marketplace object; connecting selected data resources to populate the marketplace object; and launching the new marketplace.

Abstract: Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, a set of edge devices is configured to communicate with at least one energy generation facility, energy storage facility, and/or energy consumption system and automatically execute a set of preconfigured policies that govern energy generation, energy storage, or energy consumption of the respective energy generation facilities, energy storage facilities, or energy consumption systems. In some embodiments, the automatically executed policies are a set of contextual policies that adjust based on the current status of a set of energy generation entities in an energy grid.

Abstract: Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, a policy and governance engine is configured to deploy a set of rules and/or policies that govern a set of energy generation, storage, and/or consumption workloads, wherein the rules and/or policies are associated with a configuration of a set of edge devices operating in local data communication with a set of energy generation facilities, energy storage facilities, energy delivery facilities or energy consumption systems. In some embodiments, upon configuration in the policy and governance engine, a policy associated with an energy generation instruction is automatically applied by at least one of the edge devices to control energy generation by at least one energy generation system that is controlled via the edge device.

Abstract: Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, an artificial intelligence system us configured to analyze a data set of monitored local conditions and generate a recommended configuration of at least one distributed system of a set of distributed systems, each distributed system of the set of distributed systems being configurable both to produce energy and to consume energy, wherein the configuration causes the at least one distributed system to produce and/or consume energy based on the monitored local conditions. In some embodiments, the artificial intelligence system configures a plurality of the distributed systems in the set such that a set of aggregate performance requirements are satisfied across the plurality. In some embodiments, the aggregate performance requirements are a set of economic performance requirements and/or a set of regulatory performance requirements.

Abstract: Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, an artificial intelligence system that is trained on a set of energy generation, energy storage, energy delivery and/or energy consumption outcomes, wherein the artificial intelligence system is configured to analyze a data set of current energy generation, current energy storage, current energy delivery and/or current energy consumption information and provide a recommendation including at least one operating parameter that satisfies both of a mobile entity energy demand or a fixed location energy demand in a defined domain. In some embodiments, the operating parameter indicates a generation instruction for a set of energy generation resources, a storage instruction for a set of energy storage resources, a delivery instruction for a set of energy delivery resources, and/or a consumption instruction for a set of entities that consume energy.

Abstract: Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, an intelligent agent is trained on a data set of expert interactions with an energy provisioning system, wherein the intelligent agent is trained to generate at least one recommendation and/or instruction with respect to optimization of at least one energy objective and at least one other objective. In some embodiments, the other objective is an operational objective of an enterprise. In some embodiments, the intelligent agent operates on status data from a set of edge devices via which a set of energy generation resources are controlled.

Abstract: Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, the AI-based platform includes a set of adaptive, autonomous data handling systems for energy data collection and transmission from a set of edge networking devices via which a set of distributed energy entities are controlled, wherein the data handling systems are trained based on a training data set to recognize a set of events and/or signals that indicate the energy patterns of the set of distributed energy resources. In some embodiments, the distributed energy entities include at least one energy generation resource, energy consuming entities, and/or energy storage resources. In various embodiments, the training data set includes historical energy generation data and/or historical energy consumption data for a set of entities similar to the entities controlled via the edge networking devices.

Abstract: Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, a data processing system is configured to fuse at least one entity of an energy grid entity generation, storage, delivery or consumption grid data set with at least one entity of an off-grid energy entity generation, storage, delivery and/or consumption data set. In some embodiments, the data processing system is configured to automatically time align energy grid entity data with off-grid energy entity data. In some embodiments, the data processing system is configured to automatically collect off-grid energy entity sensor data from a set of edge devices via which a set of off-grid energy entities are controlled. In some embodiments, the data processing system automatically normalizes the energy grid entity data and the off-grid energy entity data such as to present the data according to a set of common units.

Abstract: Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, a set of autonomous orchestration systems for improving delivery of a heterogeneous set of energy types to a point of consumption based on a location of the point of consumption and a set of consumption attributes, the consumption attributes including at least one of a peak power requirement at the point of consumption a continuity of power requirement at the point of consumption and a type of energy that can be used at the point of consumption. In various embodiments, the autonomous orchestration systems orchestrate delivery of defined types of energy generation capacity to the point of consumption.

Abstract: Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, a set of edge devices includes a set of artificial intelligence systems that are configured to process data handled by the edge devices and determine, based on the data, a mix of energy generation, storage, delivery and/or consumption characteristics for a set of systems that are in local communication with the edge devices and to output a data set that represents the constituent proportions of the mix. In some embodiments, the output data set indicates a fraction of energy generated by an energy grid and a fraction of energy generated by a set of distributed energy resources that operate independently of the energy grid. In some embodiments, the output data set indicates a fraction of energy generated by renewable energy resources and a fraction of energy generated by nonrenewable resources.

Abstract: Disclosed herein are AI-based platforms for enabling intelligent orchestration and management of power and energy. In various embodiments, a machine learning system is trained on a set of energy intelligence data and deployed on an edge device, wherein the machine learning system is configured to receive additional training by the edge device to improve energy management. In some embodiments, the energy management includes management of generation of energy by a set of distributed energy generation resources, management of storage of energy by a set of distributed energy storage resources management of delivery of energy by a set of distributed energy delivery resources, management of delivery of energy by a set of distributed energy delivery resources, and/or management of consumption of energy by a set of distributed energy consumption resources.

Abstract: Systems and methods for transaction platforms include various systems interacting with each other and transacting in various ways. A method for configuring and launching a marketplace includes: identifying, by a processing system having one or more processors, an opportunity to facilitate configuration of a new marketplace; receiving marketplace opportunity data, wherein the marketplace opportunity data includes information related to a set of assets of one or more types; determining configuration parameters to be implemented in the new marketplace; determining the feasibility of implementing the configuration parameters in the new marketplace; determining data resources to support the new marketplace; determining an architecture of the new marketplace; determining the configuration of the data resources in a data model for the marketplace; configuring a marketplace object; connecting selected data resources to populate the marketplace object; and launching the new marketplace.

Abstract: Systems and methods for transaction platforms include various systems interacting with each other and transacting in various ways. A method for configuring and launching a marketplace includes: identifying, by a processing system having one or more processors, an opportunity to facilitate configuration of a new marketplace; receiving marketplace opportunity data, wherein the marketplace opportunity data includes information related to a set of assets of one or more types; determining configuration parameters to be implemented in the new marketplace; determining the feasibility of implementing the configuration parameters in the new marketplace; determining data resources to support the new marketplace; determining an architecture of the new marketplace; determining the configuration of the data resources in a data model for the marketplace; configuring a marketplace object; connecting selected data resources to populate the marketplace object; and launching the new marketplace.

Abstract: A computer-implemented method for optimizing a distributed database includes receiving, at an aggregator, one or more query logs comprising past queries received by the distributed database. The computer-implemented method includes determining, by the aggregator, common queries received by one or more edge devices. The computer-implemented method includes determining, by the aggregator, that at least one edge device was not able to respond to a common query received by the at least one edge device. The computer-implemented method includes causing, by the aggregator, data for responding to the common query to be transmitted to the at least one edge device.

Abstract: Systems and methods for integrating a gaming engine and a smart contract system in a platform are provided. The gaming engine is programmed with a software development environment and an architecture that provides a set of gaming engine services with predefined tools for digital content developers to create a set of game engine generated environments. The smart contract system programmed with smart contract services associated with transactions that are based on electronically verifiable conditions. The integration platform is programmed with an execution framework that is common to the gaming engine and to the smart contract system to integrate the smart contract services with at least one of the gaming engine and the set of game engine generated environments.

Abstract: User interfaces configured to provide a list of conditions of interest to at least one entity associated with a role type stored within a role taxonomy, and to select a condition of interest in response to a user selection from the list of conditions; and a controller configured to determine a reduced dimensionality view of the data in response to a determined structure in the data and further in response to the selected condition of interest. The reduced dimensionality view a plurality of graphical elements representing mechanical portions of a machine of the industrial environment associated with the condition of interest. The reduced dimensionality view further comprises a plurality of highlighted graphical elements representing sensors from the plurality of input sensors that provided data outside an acceptable range of data. The user interface is further configured to display the reduced dimensionality view.

Abstract: A method for prioritizing predictive model data streams includes receiving, by a device, a plurality of predictive model data streams. Each predictive model data stream includes a set of model parameters for a corresponding predictive model. Each predictive model is trained to predict future data values of a data source. The method includes prioritizing, by the device, each of the plurality of predictive model data streams. The method includes selecting at least one of the predictive model data streams based on a corresponding priority. The method includes parameterizing, by the device, a predictive model using the set of model parameters included in the selected at least one predictive model data stream. The method includes predicting, by the device, the future data values of the data source using the parameterized predictive model.

Abstract: An artificial-intelligence-based platform for enabling intelligent orchestration and management of power and energy includes a governance system and a smart contract system. The governance system is configured to record, in a distributed ledger and/or blockchain, a set of mining operation events associated with a mining operation. The mining operation events are detected by one or more of a set of sensors in a mine of the mining operation, a set of wearable devices of a set of miners associated with the mining operation, or a set of sensors deployed on a set of smart containers for mined materials associated with the mining operation. The smart contract system is configured to allocate proceeds of the mining operation events among a set of owners, a set of services providers, and/or a set of governmental entities.

Abstract: An AI-based platform for automated labor law compliance associated with mining operations is disclosed. The AI-based platform includes a governance system for a mining operation and a reporting system for conveying at least one parameter that is sensed by a sensor of a mine of the mining operation, wherein the at least one parameter is associated with a compliance of the mining operation with a set of labor standards. In some embodiments, the set of labor standards is associated with at least one activity performed by a laborer of the mine, and the AI-based platform conveys an indication of a performance of the activity by the laborer. In some embodiments, the set of labor standards is associated with at least one object associated with a laborer of the mine, and the AI-based platform conveys an indication of a detection of the at least one object.

Abstract: An AI-based platform for enabling intelligent orchestration and management of power and energy is disclosed. The AI-based platform includes an artificial intelligence system that is configured to perform an analysis of a pattern of energy associated with an operating process that involves a set of resources, the resources being at least partially independent of an electrical grid, and output a set of operating parameters to provision energy generation, storage, and/or consumption to enable the operating process, wherein the set of operating parameters is based on the analysis. In some embodiments, at least one operating parameter in the set of operating parameters is a generation output level for a distributed energy generation resource, a target storage level for a distributed energy storage resource, and/or a delivery timing for a distributed energy delivery resource.