Abstract: An Industrial Virtual Assistant (IVA) platform with Robotic Process Automation that operates like a Digital Knowledge Companion and allows operational staff at industrial facilities to have natural language conversations with the IVA to obtain information about, and to control operations of, industrial facilities, and which automates certain processes based in part on those natural language conversations. In an embodiment, the platform uses a Robotic Process Automater (RPA) to ingest information from documentation, human inputs, and operational data from the facility, organize that information into a knowledge graph containing comprehensive facility information, and apply machine learning algorithms to the knowledge graph to provide natural language responses to human queries and to automate certain processes of the facility.

Abstract: An Industrial Virtual Assistant (IVA) platform with Robotic Process Automation that operates like a Digital Knowledge Companion and allows operational staff at industrial facilities to have natural language conversations with the IVA to obtain information about, and to control operations of, industrial facilities, and which automates certain processes based in part on those natural language conversations. In an embodiment, the platform uses a Robotic Process Automater (RPA) to ingest information from documentation, human inputs, and operational data from the facility, organize that information into a knowledge graph containing comprehensive facility information, and apply machine learning algorithms to the knowledge graph to provide natural language responses to human queries and to automate certain processes of the facility.

Abstract: A distributed Industrial Virtual Assistant (IVA) platform and method that that allows operational staff at industrial facilities to have natural language conversations with an IVA to obtain information about, and to control operations of, industrial facilities. For each facility, the IVA platform contains a facilities asset database, one or more domain-specific knowledge databases, a natural language processing engine, and machine learning algorithms for both knowledge domains and context which update the domain-specific knowledge databases based on continuing interactions with operational staff over time. The IVA platform is capable of generating user-specific and device-specific IVA instances that can be queried by voice or text independently of the platform but can connect to the platform to update the databases based on new knowledge, exceptions, and incidents.

Abstract: A method of modelling a water distribution system, the method comprising steps of: identifying a plurality of demand zones within said water distribution network; estimating water consumption data for said demand zones; simulating the hydraulic characteristics of the water distribution system using said estimated water consumption data and so; providing simulated pressure and flow rates within said demand zones; receiving output from sensors within said water distribution network in the form of pressure and flow rate data; correcting the simulated pressure and flow rate data within said demand zones based upon the sensor output and so; calibrating a model of the water distribution system.

Abstract: A method for the determination of demand zones for use with a water distribution model of a water distribution network, the method comprising the steps of: constructing polygons about clusters of consumption nodes; calculating base load consumption of the nodes within each polygon; assigning a consumption type to each polygon, and; aggregating connected polygons of the same consumption type into demand zones.