EnergyWeb - EWAI

EWAI - EnergyWeb A.I. Clean Energy Data Subsystem, is a conceptual prototype for a clean energy/renewables energy marketplace which enables the collection, storage and subsequent analysis of time-series Power Telemetry Data (PTD) message streams sent in by millions (or billions) of EW-DOS enabled IOT Distributed Energy Resource Devices (DERs). The EW-DOS devices send Power Telemetry Data (PDT) messages about their energy and power generation and consumption metrics to EWAI.

EWAI aggregates and stores that data for subsequent presentation to a data marketplace or A.I. analysis application layer with the ultimate goal of improving the energy efficiency of IOT devices and networks through the study of and learning from patterns visible in their real-world consumption data. The PTD data packets/messages are role-authenticated by EW-Switchboard and use EW-Messaging as transport.

Imagine being able to do analysis and learning across clean energy and renewables devices, networks and industries, for example, by analyzing and learning from energy generation and consumption patterns across wind, solar, EV, hydro and geothermal IOT devices and networks by being able to apply AI learning to energy generation and consumption patterns. The application of AI techniques can potentially expose heretofore unknown energy consumption patterns across clean energy and renewables markets and result in specific system, device and network efficiency recommendations and improvements back to the manufacturers and network operators.

The PTD data is organized into "datasets" (data assets) and surfaced via REST and GraphQL APIs to allow analysis and consumption by both Web3 dApp marketplaces and Web2 analysis layer applications.