Merck / Vence / SenseHubACorporate & U.S. Market ProfileBPublicly Disclosed Technology ArchitectureCPatent Element MappingDAreas of Technical CorrespondenceEPatent Architecture Elements Not Identif…FEvidence SourcesGAnalytical Summary and Implementation Ev…HCorporate Technology EcosystemIVence — Publicly Disclosed FunctionalityJSenseHub Feedlot — AI Evidence CardKScale and U.S. RelevanceLCombined Ecosystem Question
Merck Animal Health — Vence & SenseHub — Page J
SenseHub Feedlot — AI Evidence Card
Merck expressly states that collected data is used by machine-learning algorithms to identify cattle varying from baseline norms. A current app description describes advanced AI algorithms analysing outlier behaviour for individuals and groups.
Section
Disclosed U.S. functionality
- Electronic livestock ear tags
- Temperature monitoring
- Activity monitoring
- Continuous monitoring
- Accelerometers
- Data gateway / platform
- Machine-learning algorithms
- Baseline / outlier identification
- Automatically generated animal lists requiring assessment
- Customizable alerts
- Mobile / computer interface
- Identifying potentially sick animals before obvious clinical signs
Section
Limitations of this evidence
The disclosed machine learning operates on animal-derived baselines. Reviewed material does not establish AI selection of a most-likely emergency category across heterogeneous property hazards, nor severity determination using property context.