Computer-implemented systems and methods of analyzing spatial, temporal and contextual elements of data for predictive decision-making

This invention describes a computer system that makes predictions by analyzing different types of information. It takes a set of rules and incoming data that includes details about location, time, and context. The system then figures out which rules apply to this data and organizes the relevant data in its memory according to those rules. This structured data is then used to identify specific events that match a rule, allowing the system to make a predictive decision.

Why it matters: Filed before the widespread availability of cost-effective big data processing and real-time data streams from IoT devices. The ability to efficiently gather, process, and index vast amounts of spatial, temporal, and contextual data has significantly matured, making such a rule-based predictive system more practical to implement and scale.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedComplex software logic, data structures, rule engine.

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