WebsensorsDoracle is a Dapp for Artificial Intelligence-based Oracles. Users can train a classifier using a sample of reference events (georeferenced texts with facts about some phenomena of interest). WebsensorsDoracle verifies that new events similar to the training set have occurred and the output is stored in Blockchain for Smart Contracts decision making.

We present an alternative way to build Oracles for Smart Contracts by using machine learning algorithms from event knowledge datasets. An event is defined as “a particular thing which happens at a specific time and place” and is represented by components, such as place of occurrence (where), date of publication (when), textual information (what), and related persons and organizations (who). Thus, given an event of interest, machine learning algorithms are used to verify the future occurrence of this event. While most existing Oracles solutions collect pre-structured information, machine learning allows the construction of more semantic indicators by analyzing event content.