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IoT Platform Replaces 10,000 Rules With 252-Entity Ontology, Cuts False Alarms by 79%

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Industrial IoT platform DGIOT replaced its traditional rules-based alarm system with a 252-entity OWL ontology engine that understands equipment structure and context, not just raw sensor values. The shift was driven by problems at China's Daqing Oil Field, where false alarm rates exceeded 20% under the old system, causing operators to routinely ignore alerts. Instead of comparing readings against static thresholds, the ontology engine identifies equipment type, known failure modes, and multi-sensor patterns to recommend specific actions such as scheduling maintenance. The result was a drop in false alarms from 22% to 4.7%, a reduction in maintainable rules from over 10,000 to 252 entities, and an estimated $2.3 million in savings in the first year at Daqing. The platform, built on Erlang with OWL axioms compiled to native pattern matches, is open source under the Apache 2.0 license.

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IoT Platform Replaces 10,000 Rules With 252-Entity Ontology, Cuts False Alarms by 79% · ShortSingh