Systems, apparatuses, methods, and computer program products for efficiency predictions using artificial intelligence framework
Inventors
J, Kirupakar • Khan, Kalimulla • Rajendran, Ramkumar • KURUDI, Srilakshmi • Gaba, Sai Keshav
Assignees
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Publication Number
US-12752935-B2
Publication Date
2026-10-06
Expiration Date
Abstract
Embodiments of the present disclosure provide techniques for generating validated operational efficiency reports. The techniques may include receiving operational data associated with at least one vehicle operation; generating, based on the operational data and using a machine learning efficiency framework, one or more initial operational efficiency reports comprising one or more efficiency-based modification parameters configured for adjusting one or more operational parameters associated with a subsequent vehicle operation; generating one or more validated efficiency reports based on the one or more initial operational efficiency reports and using one or more simulation engines; and initiating performance of one or more prediction-based actions based on the validated efficiency reports.
Core Innovation
The invention describes a vehicle-efficiency advisory system that receives operational data and uses a machine learning efficiency framework to generate initial operational efficiency reports with modification parameters for a subsequent vehicle operation. Simulation engines validate the reports and produce refined modification parameters. The system initiates prediction-based actions, including programmatically adjusting operational parameters for the subsequent vehicle operation.
The disclosure further describes anomaly detection and a domain-trained, reinforcement-based generative model for identifying outliers and generating operational efficiency recommendations. Digital-twin validation engines simulate or corroborate the generated recommendations before implementation. Through this automated framework, the system provides improved operational efficiency while reducing manual effort and operational inaccuracies across subsequent vehicle operations.
Claims Coverage
The claim coverage includes two independent claims directed to two inventive features that utilize operational data to generate and validate efficiency reports and initiate actions for subsequent vehicle operations.
Computing system for vehicle-efficiency recommendations
The computing system receives operational data, uses a machine learning efficiency framework to generate initial operational efficiency reports with modification parameters, and uses simulation engines to generate validated reports with refined parameters. It initiates prediction-based actions based on the validated reports, including programmatically adjusting operational parameters associated with a subsequent vehicle operation.
Computer-implemented method for vehicle-efficiency recommendations
The method receives operational data and uses a machine learning efficiency framework to generate initial operational efficiency reports containing modification parameters for a subsequent vehicle operation. Simulation engines generate validated reports with refined parameters, after which prediction-based actions include programmatically adjusting operational parameters for the subsequent operation.
Both independent claims cover the generation and simulation-based validation of efficiency recommendations from vehicle operational data, followed by prediction-based actions that adjust parameters for a subsequent vehicle operation.
Stated Advantages
The disclosure highlights improved efficiency.
The disclosure highlights reduced manual effort and inaccuracies.
Documented Applications
The claims identify aircraft flight, using flight data, as a vehicle-operation application.
The partial content describes an avionics implementation using digital-twin engines.
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