Abstract: A method for monitoring an IoT network receives a first user input from a user, the first user input comprising a selection of a machine learning model associated with an activity, and a second user input from the user, the second user input comprising a selection of one or more attributes of a set of attributes associated with an asset. User created rules define an asset behavior. The rules are input by the user in a human-readable language. Information representing the asset type and asset behavior is associated with one or more physical devices associated with a node of the network. Data indicative of a current state of the asset, the current state of the asset indicative of at least one attribute of the asset, is received and processed in the machine learning model to determine whether a notification should be provided.

Abstract: A method is provided for performing dynamic inferencing at a node configured to communicate with other nodes of an IoT hierarchy. In the method, a schema for an asset object associated with one or more of at least one physical process and at least one physical device is received at the node. The schema is formatted according to an inferencing engine model format. An artificial intelligence model capable of being executed in an inferencing engine is received at the node. Data indicative of one or more of a current state of at least one physical process and a current state of at least one physical device is received at the node. The received data according to the schema and an inferencing engine are processed at the node. The inferencing engine generates a new predictive attribute based on the set of attributes, and the processing normalizes the received data according to the schema to generate normalized data, the normalized data includes the predictive attribute from the inferencing engine.

Abstract: A method is provided for performing dynamic inferencing at a node configured to communicate with other nodes of an IoT hierarchy. In the method, a schema for an asset object associated with one or more of at least one physical process and at least one physical device is received at the node. The schema is formatted according to an inferencing engine model format. An artificial intelligence model capable of being executed in an inferencing engine is received at the node. Data indicative of one or more of a current state of at least one physical process and a current state of at least one physical device is received at the node. The received data according to the schema and an inferencing engine are processed at the node. The inferencing engine generates a new predictive attribute based on the set of attributes, and the processing normalizes the received data according to the schema to generate normalized data, the normalized data includes the predictive attribute from the inferencing engine.

Abstract: The present invention relates to IoT devices existing in a deployed ecosystem. The various computers in the deployed ecosystem are able to respond to requests from a device directly associated with it in a particular hierarchy, or it may seek a response to the request from a high order logic/data source (parent). The logic/data source parent may then repeat the understanding process to either provide the necessary response to the logic/data source child who then replies to the device or it will again ask a parent logic/data sources for the appropriate response. This architecture allows for a single device to make one request to a single known source and potentially get a response back from the entire ecosystem of distributed servers.

Abstract: The present invention relates to IoT devices existing in a deployed ecosystem. The various computers in the deployed ecosystem are able to respond to requests from a device directly associated with it in a particular hierarchy, or it may seek a response to the request from a high order logic/data source (parent). The logic/data source parent may then repeat the understanding process to either provide the necessary response to the logic/data source child who then replies to the device or it will again ask a parent logic/data sources for the appropriate response. This architecture allows for a single device to make one request to a single known source and potentially get a response back from the entire ecosystem of distributed servers.

Abstract: The present invention relates to IoT devices existing in a deployed ecosystem. The various computers in the deployed ecosystem are able to respond to requests from a device directly associated with it in a particular hierarchy, or it may seek a response to the request from a high order logic/data source (parent). The logic/data source parent may then repeat the understanding process to either provide the necessary response to the logic/data source child who then replies to the device or it will again ask a parent logic/data sources for the appropriate response. This architecture allows for a single device to make one request to a single known source and potentially get a response back from the entire ecosystem of distributed servers.

Abstract: The present invention relates to IoT devices existing in a deployed ecosystem. The various computers in the deployed ecosystem are able to respond to requests from a device directly associated with it in a particular hierarchy, or it may seek a response to the request from a high order logic/data source (parent). The logic/data source parent may then repeat the understanding process to either provide the necessary response to the logic/data source child who then replies to the device or it will again ask a parent logic/data sources for the appropriate response. This architecture allows for a single device to make one request to a single known source and potentially get a response back from the entire ecosystem of distributed servers.

Abstract: The present invention relates to IoT devices existing in a deployed ecosystem. The various computers in the deployed ecosystem are able to respond to requests from a device directly associated with it in a particular hierarchy, or it may seek a response to the request from a high order logic/data source (parent). The logic/data source parent may then repeat the understanding process to either provide the necessary response to the logic/data source child who then replies to the device or it will again ask a parent logic/data sources for the appropriate response. This architecture allows for a single device to make one request to a single known source and potentially get a response back from the entire ecosystem of distributed servers.

Abstract: A method is provided for performing dynamic inferencing at a node configured to communicate with other nodes of an IoT hierarchy. In the method, a schema for an asset object associated with one or more of at least one physical process and at least one physical device is received at the node. The schema is formatted according to an inferencing engine model format. An artificial intelligence model capable of being executed in an inferencing engine is received at the node. Data indicative of one or more of a current state of at least one physical process and a current state of at least one physical device is received at the node. The received data according to the schema and an inferencing engine are processed at the node. The inferencing engine generates a new predictive attribute based on the set of attributes, and the processing normalizes the received data according to the schema to generate normalized data, the normalized data includes the predictive attribute from the inferencing engine.

Abstract: The present invention relates to IoT devices existing in a deployed ecosystem. The various computers in the deployed ecosystem are able to respond to requests from a device directly associated with it in a particular hierarchy, or it may seek a response to the request from a high order logic/data source (parent). The logic/data source parent may then repeat the understanding process to either provide the necessary response to the logic/data source child who then replies to the device or it will again ask a parent logic/data sources for the appropriate response. This architecture allows for a single device to make one request to a single known source and potentially get a response back from the entire ecosystem of distributed servers.

Abstract: The present invention relates to IoT devices existing in a deployed ecosystem. The various computers in the deployed ecosystem are able to respond to requests from a device directly associated with it in a particular hierarchy, or it may seek a response to the request from a high order logic/data source (parent). The logic/data source parent may then repeat the understanding process to either provide the necessary response to the logic/data source child who then replies to the device or it will again ask a parent logic/data sources for the appropriate response. This architecture allows for a single device to make one request to a single known source and potentially get a response back from the entire ecosystem of distributed servers.

Abstract: The present invention relates to IoT devices existing in a deployed ecosystem. The various computers in the deployed ecosystem are able to respond to requests from a device directly associated with it in a particular hierarchy, or it may seek a response to the request from a high order logic/data source (parent). The logic/data source parent may then repeat the understanding process to either provide the necessary response to the logic/data source child who then replies to the device or it will again ask a parent logic/data sources for the appropriate response. This architecture allows for a single device to make one request to a single known source and potentially get a response back from the entire ecosystem of distributed servers.

Abstract: A method for configuring output of information from an IoT network provides an interface for receiving user inputs from a user, the user inputs representing an asset type. User created rules define an asset behavior. The rules are input by the user in a human-readable language. Information representing the asset type and asset behavior is associated with one or more physical devices associated with a node of the network. The asset type is associated with a virtual area, which is associated with a physical area. The physical devices report raw state data of the asset, which is converted into user-defined state data and displayed to the user.

Abstract: The present invention relates to IoT devices existing in a deployed ecosystem. The various computers in the deployed ecosystem are able to respond to requests from a device directly associated with it in a particular hierarchy, or it may seek a response to the request from a high order logic/data source (parent). The logic/data source parent may then repeat the understanding process to either provide the necessary response to the logic/data source child who then replies to the device or it will again ask a parent logic/data sources for the appropriate response. This architecture allows for a single device to make one request to a single known source and potentially get a response back from the entire ecosystem of distributed servers.

Abstract: The present invention relates to IoT devices existing in a deployed ecosystem. The various computers in the deployed ecosystem are able to respond to requests from a device directly associated with it in a particular hierarchy, or it may seek a response to the request from a high order logic/data source (parent). The logic/data source parent may then repeat the understanding process to either provide the necessary response to the logic/data source child who then replies to the device or it will again ask a parent logic/data sources for the appropriate response. This architecture allows for a single device to make one request to a single known source and potentially get a response back from the entire ecosystem of distributed servers.

Abstract: The present invention relates to IoT devices existing in a deployed ecosystem. The various computers in the deployed ecosystem are able to respond to requests from a device directly associated with it in a particular hierarchy, or it may seek a response to the request from a high order logic/data source (parent). The logic/data source parent may then repeat the understanding process to either provide the necessary response to the logic/data source child who then replies to the device or it will again ask a parent logic/data sources for the appropriate response. This architecture allows for a single device to make one request to a single known source and potentially get a response back from the entire ecosystem of distributed servers.

Abstract: The present invention provides a system and method for constructing a complete definition of a backend requirements model that can be automatically accessed and interpreted, and generated into a mobile consumable API for creation of, and use with, mobile applications. The mobile consumable API can be provided and made available to mobile app developers on a separate, stand-alone platform, and may act as an intermediary between the mobile app and the primary mainframe/enterprise/back end system. The method may include identification and definition of one or more of information providers, integration providers, and system behaviors, and creating a domain model. The domain model may be automatically codified into an API based solution as the app/mainframe interface, and stored on a development and operational platform for use.

Abstract: The present invention provides a system and method for constructing a complete definition of a backend requirements model that can be automatically accessed and interpreted, and generated into a mobile consumable API for creation of, and use with, mobile applications. The mobile consumable API can be provided and made available to mobile app developers on a separate, stand-alone platform, and may act as an intermediary between the mobile app and the primary mainframe/enterprise/back end system. The method may include identification and definition of one or more of information providers, integration providers, and system behaviors, and creating a domain model. The domain model may be automatically codified into an API based solution as the app/mainframe interface, and stored on a development and operational platform for use.

Abstract: The present invention provides a system and method for constructing a complete definition of a backend requirements model that can be automatically accessed and interpreted, and generated into a mobile consumable API for creation of, and use with, mobile applications. The mobile consumable API can be provided and made available to mobile app developers on a separate, stand-alone platform, and may act as an intermediary between the mobile app and the primary mainframe/enterprise/back end system. The method may include identification and definition of one or more of information providers, integration providers, and system behaviors, and creating a domain model. The domain model may be automatically codified into an API based solution as the app/mainframe interface, and stored on a development and operational platform for use.

Abstract: The present invention provides a system and method for constructing a complete definition of a backend requirements model that can be automatically accessed and interpreted, and generated into a mobile consumable API for creation of, and use with, mobile applications. The mobile consumable API can be provided and made available to mobile app developers on a separate, stand-alone platform, and may act as an intermediary between the mobile app and the primary mainframe/enterprise/back end system. The method may include identification and definition of one or more of information providers, integration providers, and system behaviors, and creating a domain model. The domain model may be automatically codified into an API based solution as the app/mainframe interface, and stored on a development and operational platform for use.